How to Calculate Risk Reward Ratio in Forex - Forex Education

Former investment bank FX trader: some thoughts

Former investment bank FX trader: some thoughts
Hi guys,
I have been using reddit for years in my personal life (not trading!) and wanted to give something back in an area where i am an expert.
I worked at an investment bank for seven years and joined them as a graduate FX trader so have lots of professional experience, by which i mean I was trained and paid by a big institution to trade on their behalf. This is very different to being a full-time home trader, although that is not to discredit those guys, who can accumulate a good amount of experience/wisdom through self learning.
When I get time I'm going to write a mid-length posts on each topic for you guys along the lines of how i was trained. I guess there would be 15-20 topics in total so about 50-60 posts. Feel free to comment or ask questions.
The first topic is Risk Management and we'll cover it in three parts
Part I
  • Why it matters
  • Position sizing
  • Kelly
  • Using stops sensibly
  • Picking a clear level

Why it matters

The first rule of making money through trading is to ensure you do not lose money. Look at any serious hedge fund’s website and they’ll talk about their first priority being “preservation of investor capital.”
You have to keep it before you grow it.
Strangely, if you look at retail trading websites, for every one article on risk management there are probably fifty on trade selection. This is completely the wrong way around.
The great news is that this stuff is pretty simple and process-driven. Anyone can learn and follow best practices.
Seriously, avoiding mistakes is one of the most important things: there's not some holy grail system for finding winning trades, rather a routine and fairly boring set of processes that ensure that you are profitable, despite having plenty of losing trades alongside the winners.

Capital and position sizing

The first thing you have to know is how much capital you are working with. Let’s say you have $100,000 deposited. This is your maximum trading capital. Your trading capital is not the leveraged amount. It is the amount of money you have deposited and can withdraw or lose.
Position sizing is what ensures that a losing streak does not take you out of the market.
A rule of thumb is that one should risk no more than 2% of one’s account balance on an individual trade and no more than 8% of one’s account balance on a specific theme. We’ll look at why that’s a rule of thumb later. For now let’s just accept those numbers and look at examples.
So we have $100,000 in our account. And we wish to buy EURUSD. We should therefore not be risking more than 2% which $2,000.
We look at a technical chart and decide to leave a stop below the monthly low, which is 55 pips below market. We’ll come back to this in a bit. So what should our position size be?
We go to the calculator page, select Position Size and enter our details. There are many such calculators online - just google "Pip calculator".

https://preview.redd.it/y38zb666e5h51.jpg?width=1200&format=pjpg&auto=webp&s=26e4fe569dc5c1f43ce4c746230c49b138691d14
So the appropriate size is a buy position of 363,636 EURUSD. If it reaches our stop level we know we’ll lose precisely $2,000 or 2% of our capital.
You should be using this calculator (or something similar) on every single trade so that you know your risk.
Now imagine that we have similar bets on EURJPY and EURGBP, which have also broken above moving averages. Clearly this EUR-momentum is a theme. If it works all three bets are likely to pay off. But if it goes wrong we are likely to lose on all three at once. We are going to look at this concept of correlation in more detail later.
The total amount of risk in our portfolio - if all of the trades on this EUR-momentum theme were to hit their stops - should not exceed $8,000 or 8% of total capital. This allows us to go big on themes we like without going bust when the theme does not work.
As we’ll see later, many traders only win on 40-60% of trades. So you have to accept losing trades will be common and ensure you size trades so they cannot ruin you.
Similarly, like poker players, we should risk more on trades we feel confident about and less on trades that seem less compelling. However, this should always be subject to overall position sizing constraints.
For example before you put on each trade you might rate the strength of your conviction in the trade and allocate a position size accordingly:

https://preview.redd.it/q2ea6rgae5h51.png?width=1200&format=png&auto=webp&s=4332cb8d0bbbc3d8db972c1f28e8189105393e5b
To keep yourself disciplined you should try to ensure that no more than one in twenty trades are graded exceptional and allocated 5% of account balance risk. It really should be a rare moment when all the stars align for you.
Notice that the nice thing about dealing in percentages is that it scales. Say you start out with $100,000 but end the year up 50% at $150,000. Now a 1% bet will risk $1,500 rather than $1,000. That makes sense as your capital has grown.
It is extremely common for retail accounts to blow-up by making only 4-5 losing trades because they are leveraged at 50:1 and have taken on far too large a position, relative to their account balance.
Consider that GBPUSD tends to move 1% each day. If you have an account balance of $10k then it would be crazy to take a position of $500k (50:1 leveraged). A 1% move on $500k is $5k.
Two perfectly regular down days in a row — or a single day’s move of 2% — and you will receive a margin call from the broker, have the account closed out, and have lost all your money.
Do not let this happen to you. Use position sizing discipline to protect yourself.

Kelly Criterion

If you’re wondering - why “about 2%” per trade? - that’s a fair question. Why not 0.5% or 10% or any other number?
The Kelly Criterion is a formula that was adapted for use in casinos. If you know the odds of winning and the expected pay-off, it tells you how much you should bet in each round.
This is harder than it sounds. Let’s say you could bet on a weighted coin flip, where it lands on heads 60% of the time and tails 40% of the time. The payout is $2 per $1 bet.
Well, absolutely you should bet. The odds are in your favour. But if you have, say, $100 it is less obvious how much you should bet to avoid ruin.
Say you bet $50, the odds that it could land on tails twice in a row are 16%. You could easily be out after the first two flips.
Equally, betting $1 is not going to maximise your advantage. The odds are 60/40 in your favour so only betting $1 is likely too conservative. The Kelly Criterion is a formula that produces the long-run optimal bet size, given the odds.
Applying the formula to forex trading looks like this:
Position size % = Winning trade % - ( (1- Winning trade %) / Risk-reward ratio
If you have recorded hundreds of trades in your journal - see next chapter - you can calculate what this outputs for you specifically.
If you don't have hundreds of trades then let’s assume some realistic defaults of Winning trade % being 30% and Risk-reward ratio being 3. The 3 implies your TP is 3x the distance of your stop from entry e.g. 300 pips take profit and 100 pips stop loss.
So that’s 0.3 - (1 - 0.3) / 3 = 6.6%.
Hold on a second. 6.6% of your account probably feels like a LOT to risk per trade.This is the main observation people have on Kelly: whilst it may optimise the long-run results it doesn’t take into account the pain of drawdowns. It is better thought of as the rational maximum limit. You needn’t go right up to the limit!
With a 30% winning trade ratio, the odds of you losing on four trades in a row is nearly one in four. That would result in a drawdown of nearly a quarter of your starting account balance. Could you really stomach that and put on the fifth trade, cool as ice? Most of us could not.
Accordingly people tend to reduce the bet size. For example, let’s say you know you would feel emotionally affected by losing 25% of your account.
Well, the simplest way is to divide the Kelly output by four. You have effectively hidden 75% of your account balance from Kelly and it is now optimised to avoid a total wipeout of just the 25% it can see.
This gives 6.6% / 4 = 1.65%. Of course different trading approaches and different risk appetites will provide different optimal bet sizes but as a rule of thumb something between 1-2% is appropriate for the style and risk appetite of most retail traders.
Incidentally be very wary of systems or traders who claim high winning trade % like 80%. Invariably these don’t pass a basic sense-check:
  • How many live trades have you done? Often they’ll have done only a handful of real trades and the rest are simulated backtests, which are overfitted. The model will soon die.
  • What is your risk-reward ratio on each trade? If you have a take profit $3 away and a stop loss $100 away, of course most trades will be winners. You will not be making money, however! In general most traders should trade smaller position sizes and less frequently than they do. If you are going to bias one way or the other, far better to start off too small.

How to use stop losses sensibly

Stop losses have a bad reputation amongst the retail community but are absolutely essential to risk management. No serious discretionary trader can operate without them.
A stop loss is a resting order, left with the broker, to automatically close your position if it reaches a certain price. For a recap on the various order types visit this chapter.
The valid concern with stop losses is that disreputable brokers look for a concentration of stops and then, when the market is close, whipsaw the price through the stop levels so that the clients ‘stop out’ and sell to the broker at a low rate before the market naturally comes back higher. This is referred to as ‘stop hunting’.
This would be extremely immoral behaviour and the way to guard against it is to use a highly reputable top-tier broker in a well regulated region such as the UK.
Why are stop losses so important? Well, there is no other way to manage risk with certainty.
You should always have a pre-determined stop loss before you put on a trade. Not having one is a recipe for disaster: you will find yourself emotionally attached to the trade as it goes against you and it will be extremely hard to cut the loss. This is a well known behavioural bias that we’ll explore in a later chapter.
Learning to take a loss and move on rationally is a key lesson for new traders.
A common mistake is to think of the market as a personal nemesis. The market, of course, is totally impersonal; it doesn’t care whether you make money or not.
Bruce Kovner, founder of the hedge fund Caxton Associates
There is an old saying amongst bank traders which is “losers average losers”.
It is tempting, having bought EURUSD and seeing it go lower, to buy more. Your average price will improve if you keep buying as it goes lower. If it was cheap before it must be a bargain now, right? Wrong.
Where does that end? Always have a pre-determined cut-off point which limits your risk. A level where you know the reason for the trade was proved ‘wrong’ ... and stick to it strictly. If you trade using discretion, use stops.

Picking a clear level

Where you leave your stop loss is key.
Typically traders will leave them at big technical levels such as recent highs or lows. For example if EURUSD is trading at 1.1250 and the recent month’s low is 1.1205 then leaving it just below at 1.1200 seems sensible.

If you were going long, just below the double bottom support zone seems like a sensible area to leave a stop
You want to give it a bit of breathing room as we know support zones often get challenged before the price rallies. This is because lots of traders identify the same zones. You won’t be the only one selling around 1.1200.
The “weak hands” who leave their sell stop order at exactly the level are likely to get taken out as the market tests the support. Those who leave it ten or fifteen pips below the level have more breathing room and will survive a quick test of the level before a resumed run-up.
Your timeframe and trading style clearly play a part. Here’s a candlestick chart (one candle is one day) for GBPUSD.

https://preview.redd.it/moyngdy4f5h51.png?width=1200&format=png&auto=webp&s=91af88da00dd3a09e202880d8029b0ddf04fb802
If you are putting on a trend-following trade you expect to hold for weeks then you need to have a stop loss that can withstand the daily noise. Look at the downtrend on the chart. There were plenty of days in which the price rallied 60 pips or more during the wider downtrend.
So having a really tight stop of, say, 25 pips that gets chopped up in noisy short-term moves is not going to work for this kind of trade. You need to use a wider stop and take a smaller position size, determined by the stop level.
There are several tools you can use to help you estimate what is a safe distance and we’ll look at those in the next section.
There are of course exceptions. For example, if you are doing range-break style trading you might have a really tight stop, set just below the previous range high.

https://preview.redd.it/ygy0tko7f5h51.png?width=1200&format=png&auto=webp&s=34af49da61c911befdc0db26af66f6c313556c81
Clearly then where you set stops will depend on your trading style as well as your holding horizons and the volatility of each instrument.
Here are some guidelines that can help:
  1. Use technical analysis to pick important levels (support, resistance, previous high/lows, moving averages etc.) as these provide clear exit and entry points on a trade.
  2. Ensure that the stop gives your trade enough room to breathe and reflects your timeframe and typical volatility of each pair. See next section.
  3. Always pick your stop level first. Then use a calculator to determine the appropriate lot size for the position, based on the % of your account balance you wish to risk on the trade.
So far we have talked about price-based stops. There is another sort which is more of a fundamental stop, used alongside - not instead of - price stops. If either breaks you’re out.
For example if you stop understanding why a product is going up or down and your fundamental thesis has been confirmed wrong, get out. For example, if you are long because you think the central bank is turning hawkish and AUDUSD is going to play catch up with rates … then you hear dovish noises from the central bank and the bond yields retrace lower and back in line with the currency - close your AUDUSD position. You already know your thesis was wrong. No need to give away more money to the market.

Coming up in part II

EDIT: part II here
Letting stops breathe
When to change a stop
Entering and exiting winning positions
Risk:reward ratios
Risk-adjusted returns

Coming up in part III

Squeezes and other risks
Market positioning
Bet correlation
Crap trades, timeouts and monthly limits

***
Disclaimer:This content is not investment advice and you should not place any reliance on it. The views expressed are the author's own and should not be attributed to any other person, including their employer.
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Former investment bank FX trader: Risk management part II

Former investment bank FX trader: Risk management part II
Firstly, thanks for the overwhelming comments and feedback. Genuinely really appreciated. I am pleased 500+ of you find it useful.
If you didn't read the first post you can do so here: risk management part I. You'll need to do so in order to make sense of the topic.
As ever please comment/reply below with questions or feedback and I'll do my best to get back to you.
Part II
  • Letting stops breathe
  • When to change a stop
  • Entering and exiting winning positions
  • Risk:reward ratios
  • Risk-adjusted returns

Letting stops breathe

We talked earlier about giving a position enough room to breathe so it is not stopped out in day-to-day noise.
Let’s consider the chart below and imagine you had a trailing stop. It would be super painful to miss out on the wider move just because you left a stop that was too tight.

Imagine being long and stopped out on a meaningless retracement ... ouch!
One simple technique is simply to look at your chosen chart - let’s say daily bars. And then look at previous trends and use the measuring tool. Those generally look something like this and then you just click and drag to measure.
For example if we wanted to bet on a downtrend on the chart above we might look at the biggest retracement on the previous uptrend. That max drawdown was about 100 pips or just under 1%. So you’d want your stop to be able to withstand at least that.
If market conditions have changed - for example if CVIX has risen - and daily ranges are now higher you should incorporate that. If you know a big event is coming up you might think about that, too. The human brain is a remarkable tool and the power of the eye-ball method is not to be dismissed. This is how most discretionary traders do it.
There are also more analytical approaches.
Some look at the Average True Range (ATR). This attempts to capture the volatility of a pair, typically averaged over a number of sessions. It looks at three separate measures and takes the largest reading. Think of this as a moving average of how much a pair moves.
For example, below shows the daily move in EURUSD was around 60 pips before spiking to 140 pips in March. Conditions were clearly far more volatile in March. Accordingly, you would need to leave your stop further away in March and take a correspondingly smaller position size.

ATR is available on pretty much all charting systems
Professional traders tend to use standard deviation as a measure of volatility instead of ATR. There are advantages and disadvantages to both. Averages are useful but can be misleading when regimes switch (see above chart).
Once you have chosen a measure of volatility, stop distance can then be back-tested and optimised. For example does 2x ATR work best or 5x ATR for a given style and time horizon?
Discretionary traders may still eye-ball the ATR or standard deviation to get a feeling for how it has changed over time and what ‘normal’ feels like for a chosen study period - daily, weekly, monthly etc.

Reasons to change a stop

As a general rule you should be disciplined and not change your stops. Remember - losers average losers. This is really hard at first and we’re going to look at that in more detail later.
There are some good reasons to modify stops but they are rare.
One reason is if another risk management process demands you stop trading and close positions. We’ll look at this later. In that case just close out your positions at market and take the loss/gains as they are.
Another is event risk. If you have some big upcoming data like Non Farm Payrolls that you know can move the market +/- 150 pips and you have no edge going into the release then many traders will take off or scale down their positions. They’ll go back into the positions when the data is out and the market has quietened down after fifteen minutes or so. This is a matter of some debate - many traders consider it a coin toss and argue you win some and lose some and it all averages out.
Trailing stops can also be used to ‘lock in’ profits. We looked at those before. As the trade moves in your favour (say up if you are long) the stop loss ratchets with it. This means you may well end up ‘stopping out’ at a profit - as per the below example.

The mighty trailing stop loss order
It is perfectly reasonable to have your stop loss move in the direction of PNL. This is not exposing you to more risk than you originally were comfortable with. It is taking less and less risk as the trade moves in your favour. Trend-followers in particular love trailing stops.
One final question traders ask is what they should do if they get stopped out but still like the trade. Should they try the same trade again a day later for the same reasons? Nope. Look for a different trade rather than getting emotionally wed to the original idea.
Let’s say a particular stock looked cheap based on valuation metrics yesterday, you bought, it went down and you got stopped out. Well, it is going to look even better on those same metrics today. Maybe the market just doesn’t respect value at the moment and is driven by momentum. Wait it out.
Otherwise, why even have a stop in the first place?

Entering and exiting winning positions

Take profits are the opposite of stop losses. They are also resting orders, left with the broker, to automatically close your position if it reaches a certain price.
Imagine I’m long EURUSD at 1.1250. If it hits a previous high of 1.1400 (150 pips higher) I will leave a sell order to take profit and close the position.
The rookie mistake on take profits is to take profit too early. One should start from the assumption that you will win on no more than half of your trades. Therefore you will need to ensure that you win more on the ones that work than you lose on those that don’t.

Sad to say but incredibly common: retail traders often take profits way too early
This is going to be the exact opposite of what your emotions want you to do. We are going to look at that in the Psychology of Trading chapter.
Remember: let winners run. Just like stops you need to know in advance the level where you will close out at a profit. Then let the trade happen. Don’t override yourself and let emotions force you to take a small profit. A classic mistake to avoid.
The trader puts on a trade and it almost stops out before rebounding. As soon as it is slightly in the money they spook and cut out, instead of letting it run to their original take profit. Do not do this.

Entering positions with limit orders

That covers exiting a position but how about getting into one?
Take profits can also be left speculatively to enter a position. Sometimes referred to as “bids” (buy orders) or “offers” (sell orders). Imagine the price is 1.1250 and the recent low is 1.1205.
You might wish to leave a bid around 1.2010 to enter a long position, if the market reaches that price. This way you don’t need to sit at the computer and wait.
Again, typically traders will use tech analysis to identify attractive levels. Again - other traders will cluster with your orders. Just like the stop loss we need to bake that in.
So this time if we know everyone is going to buy around the recent low of 1.1205 we might leave the take profit bit a little bit above there at 1.1210 to ensure it gets done. Sure it costs 5 more pips but how mad would you be if the low was 1.1207 and then it rallied a hundred points and you didn’t have the trade on?!
There are two more methods that traders often use for entering a position.
Scaling in is one such technique. Let’s imagine that you think we are in a long-term bulltrend for AUDUSD but experiencing a brief retracement. You want to take a total position of 500,000 AUD and don’t have a strong view on the current price action.
You might therefore leave a series of five bids of 100,000. As the price moves lower each one gets hit. The nice thing about scaling in is it reduces pressure on you to pick the perfect level. Of course the risk is that not all your orders get hit before the price moves higher and you have to trade at-market.
Pyramiding is the second technique. Pyramiding is for take profits what a trailing stop loss is to regular stops. It is especially common for momentum traders.

Pyramiding into a position means buying more as it goes in your favour
Again let’s imagine we’re bullish AUDUSD and want to take a position of 500,000 AUD.
Here we add 100,000 when our first signal is reached. Then we add subsequent clips of 100,000 when the trade moves in our favour. We are waiting for confirmation that the move is correct.
Obviously this is quite nice as we humans love trading when it goes in our direction. However, the drawback is obvious: we haven’t had the full amount of risk on from the start of the trend.
You can see the attractions and drawbacks of both approaches. It is best to experiment and choose techniques that work for your own personal psychology as these will be the easiest for you to stick with and build a disciplined process around.

Risk:reward and win ratios

Be extremely skeptical of people who claim to win on 80% of trades. Most traders will win on roughly 50% of trades and lose on 50% of trades. This is why risk management is so important!
Once you start keeping a trading journal you’ll be able to see how the win/loss ratio looks for you. Until then, assume you’re typical and that every other trade will lose money.
If that is the case then you need to be sure you make more on the wins than you lose on the losses. You can see the effect of this below.

A combination of win % and risk:reward ratio determine if you are profitable
A typical rule of thumb is that a ratio of 1:3 works well for most traders.
That is, if you are prepared to risk 100 pips on your stop you should be setting a take profit at a level that would return you 300 pips.
One needn’t be religious about these numbers - 11 pips and 28 pips would be perfectly fine - but they are a guideline.
Again - you should still use technical analysis to find meaningful chart levels for both the stop and take profit. Don’t just blindly take your stop distance and do 3x the pips on the other side as your take profit. Use the ratio to set approximate targets and then look for a relevant resistance or support level in that kind of region.

Risk-adjusted returns

Not all returns are equal. Suppose you are examining the track record of two traders. Now, both have produced a return of 14% over the year. Not bad!
The first trader, however, made hundreds of small bets throughout the year and his cumulative PNL looked like the left image below.
The second trader made just one bet — he sold CADJPY at the start of the year — and his PNL looked like the right image below with lots of large drawdowns and volatility.
Would you rather have the first trading record or the second?
If you were investing money and betting on who would do well next year which would you choose? Of course all sensible people would choose the first trader. Yet if you look only at returns one cannot distinguish between the two. Both are up 14% at that point in time. This is where the Sharpe ratio helps .
A high Sharpe ratio indicates that a portfolio has better risk-adjusted performance. One cannot sensibly compare returns without considering the risk taken to earn that return.
If I can earn 80% of the return of another investor at only 50% of the risk then a rational investor should simply leverage me at 2x and enjoy 160% of the return at the same level of risk.
This is very important in the context of Execution Advisor algorithms (EAs) that are popular in the retail community. You must evaluate historic performance by its risk-adjusted return — not just the nominal return. Incidentally look at the Sharpe ratio of ones that have been live for a year or more ...
Otherwise an EA developer could produce two EAs: the first simply buys at 1000:1 leverage on January 1st ; and the second sells in the same manner. At the end of the year, one of them will be discarded and the other will look incredible. Its risk-adjusted return, however, would be abysmal and the odds of repeated success are similarly poor.

Sharpe ratio

The Sharpe ratio works like this:
  • It takes the average returns of your strategy;
  • It deducts from these the risk-free rate of return i.e. the rate anyone could have got by investing in US government bonds with very little risk;
  • It then divides this total return by its own volatility - the more smooth the return the higher and better the Sharpe, the more volatile the lower and worse the Sharpe.
For example, say the return last year was 15% with a volatility of 10% and US bonds are trading at 2%. That gives (15-2)/10 or a Sharpe ratio of 1.3. As a rule of thumb a Sharpe ratio of above 0.5 would be considered decent for a discretionary retail trader. Above 1 is excellent.
You don’t really need to know how to calculate Sharpe ratios. Good trading software will do this for you. It will either be available in the system by default or you can add a plug-in.

VAR

VAR is another useful measure to help with drawdowns. It stands for Value at Risk. Normally people will use 99% VAR (conservative) or 95% VAR (aggressive). Let’s say you’re long EURUSD and using 95% VAR. The system will look at the historic movement of EURUSD. It might spit out a number of -1.2%.

A 5% VAR of -1.2% tells you you should expect to lose 1.2% on 5% of days, whilst 95% of days should be better than that
This means it is expected that on 5 days out of 100 (hence the 95%) the portfolio will lose 1.2% or more. This can help you manage your capital by taking appropriately sized positions. Typically you would look at VAR across your portfolio of trades rather than trade by trade.
Sharpe ratios and VAR don’t give you the whole picture, though. Legendary fund manager, Howard Marks of Oaktree, notes that, while tools like VAR and Sharpe ratios are helpful and absolutely necessary, the best investors will also overlay their own judgment.
Investors can calculate risk metrics like VaR and Sharpe ratios (we use them at Oaktree; they’re the best tools we have), but they shouldn’t put too much faith in them. The bottom line for me is that risk management should be the responsibility of every participant in the investment process, applying experience, judgment and knowledge of the underlying investments.Howard Marks of Oaktree Capital
What he’s saying is don’t misplace your common sense. Do use these tools as they are helpful. However, you cannot fully rely on them. Both assume a normal distribution of returns. Whereas in real life you get “black swans” - events that should supposedly happen only once every thousand years but which actually seem to happen fairly often.
These outlier events are often referred to as “tail risk”. Don’t make the mistake of saying “well, the model said…” - overlay what the model is telling you with your own common sense and good judgment.

Coming up in part III

Available here
Squeezes and other risks
Market positioning
Bet correlation
Crap trades, timeouts and monthly limits

***
Disclaimer:This content is not investment advice and you should not place any reliance on it. The views expressed are the author's own and should not be attributed to any other person, including their employer.
submitted by getmrmarket to Forex [link] [comments]

Where is Bitcoin Going and When?

Where is Bitcoin Going and When?

The Federal Reserve and the United States government are pumping extreme amounts of money into the economy, already totaling over $484 billion. They are doing so because it already had a goal to inflate the United States Dollar (USD) so that the market can continue to all-time highs. It has always had this goal. They do not care how much inflation goes up by now as we are going into a depression with the potential to totally crash the US economy forever. They believe the only way to save the market from going to zero or negative values is to inflate it so much that it cannot possibly crash that low. Even if the market does not dip that low, inflation serves the interest of powerful people.
The impending crash of the stock market has ramifications for Bitcoin, as, though there is no direct ongoing-correlation between the two, major movements in traditional markets will necessarily affect Bitcoin. According to the Blockchain Center’s Cryptocurrency Correlation Tool, Bitcoin is not correlated with the stock market. However, when major market movements occur, they send ripples throughout the financial ecosystem which necessary affect even ordinarily uncorrelated assets.
Therefore, Bitcoin will reach X price on X date after crashing to a price of X by X date.

Stock Market Crash

The Federal Reserve has caused some serious consternation with their release of ridiculous amounts of money in an attempt to buoy the economy. At face value, it does not seem to have any rationale or logic behind it other than keeping the economy afloat long enough for individuals to profit financially and politically. However, there is an underlying basis to what is going on which is important to understand in order to profit financially.
All markets are functionally price probing systems. They constantly undergo a price-discovery process. In a fiat system, money is an illusory and a fundamentally synthetic instrument with no intrinsic value – similar to Bitcoin. The primary difference between Bitcoin is the underlying technology which provides a slew of benefits that fiat does not. Fiat, however, has an advantage in being able to have the support of powerful nation-states which can use their might to insure the currency’s prosperity.
Traditional stock markets are composed of indices (pl. of index). Indices are non-trading market instruments which are essentially summaries of business values which comprise them. They are continuously recalculated throughout a trading day, and sometimes reflected through tradable instruments such as Exchange Traded Funds or Futures. Indices are weighted by market capitalizations of various businesses.
Price theory essentially states that when a market fails to take out a new low in a given range, it will have an objective to take out the high. When a market fails to take out a new high, it has an objective to make a new low. This is why price-time charts go up and down, as it does this on a second-by-second, minute-by-minute, day-by-day, and even century-by-century basis. Therefore, market indices will always return to some type of bull market as, once a true low is formed, the market will have a price objective to take out a new high outside of its’ given range – which is an all-time high. Instruments can only functionally fall to zero, whereas they can grow infinitely.
So, why inflate the economy so much?
Deflation is disastrous for central banks and markets as it raises the possibility of producing an overall price objective of zero or negative values. Therefore, under a fractional reserve system with a fiat currency managed by a central bank – the goal of the central bank is to depreciate the currency. The dollar is manipulated constantly with the intention of depreciating its’ value.
Central banks have a goal of continued inflated fiat values. They tend to ordinarily contain it at less than ten percent (10%) per annum in order for the psyche of the general populace to slowly adjust price increases. As such, the markets are divorced from any other logic. Economic policy is the maintenance of human egos, not catering to fundamental analysis. Gross Domestic Product (GDP) growth is well-known not to be a measure of actual growth or output. It is a measure of increase in dollars processed. Banks seek to produce raising numbers which make society feel like it is growing economically, making people optimistic. To do so, the currency is inflated, though inflation itself does not actually increase growth. When society is optimistic, it spends and engages in business – resulting in actual growth. It also encourages people to take on credit and debts, creating more fictional fiat.
Inflation is necessary for markets to continue to reach new heights, generating positive emotional responses from the populace, encouraging spending, encouraging debt intake, further inflating the currency, and increasing the sale of government bonds. The fiat system only survives by generating more imaginary money on a regular basis.
Bitcoin investors may profit from this by realizing that stock investors as a whole always stand to profit from the market so long as it is managed by a central bank and does not collapse entirely. If those elements are filled, it has an unending price objective to raise to new heights. It also allows us to realize that this response indicates that the higher-ups believe that the economy could crash in entirety, and it may be wise for investors to have multiple well-thought-out exit strategies.

Economic Analysis of Bitcoin

The reason why the Fed is so aggressively inflating the economy is due to fears that it will collapse forever or never rebound. As such, coupled with a global depression, a huge demand will appear for a reserve currency which is fundamentally different than the previous system. Bitcoin, though a currency or asset, is also a market. It also undergoes a constant price-probing process. Unlike traditional markets, Bitcoin has the exact opposite goal. Bitcoin seeks to appreciate in value and not depreciate. This has a quite different affect in that Bitcoin could potentially become worthless and have a price objective of zero.
Bitcoin was created in 2008 by a now famous mysterious figure known as Satoshi Nakamoto and its’ open source code was released in 2009. It was the first decentralized cryptocurrency to utilize a novel protocol known as the blockchain. Up to one megabyte of data may be sent with each transaction. It is decentralized, anonymous, transparent, easy to set-up, and provides myriad other benefits. Bitcoin is not backed up by anything other than its’ own technology.
Bitcoin is can never be expected to collapse as a framework, even were it to become worthless. The stock market has the potential to collapse in entirety, whereas, as long as the internet exists, Bitcoin will be a functional system with a self-authenticating framework. That capacity to persist regardless of the actual price of Bitcoin and the deflationary nature of Bitcoin means that it has something which fiat does not – inherent value.
Bitcoin is based on a distributed database known as the “blockchain.” Blockchains are essentially decentralized virtual ledger books, replete with pages known as “blocks.” Each page in a ledger is composed of paragraph entries, which are the actual transactions in the block.
Blockchains store information in the form of numerical transactions, which are just numbers. We can consider these numbers digital assets, such as Bitcoin. The data in a blockchain is immutable and recorded only by consensus-based algorithms. Bitcoin is cryptographic and all transactions are direct, without intermediary, peer-to-peer.
Bitcoin does not require trust in a central bank. It requires trust on the technology behind it, which is open-source and may be evaluated by anyone at any time. Furthermore, it is impossible to manipulate as doing so would require all of the nodes in the network to be hacked at once – unlike the stock market which is manipulated by the government and “Market Makers”. Bitcoin is also private in that, though the ledge is openly distributed, it is encrypted. Bitcoin’s blockchain has one of the greatest redundancy and information disaster recovery systems ever developed.
Bitcoin has a distributed governance model in that it is controlled by its’ users. There is no need to trust a payment processor or bank, or even to pay fees to such entities. There are also no third-party fees for transaction processing. As the ledge is immutable and transparent it is never possible to change it – the data on the blockchain is permanent. The system is not easily susceptible to attacks as it is widely distributed. Furthermore, as users of Bitcoin have their private keys assigned to their transactions, they are virtually impossible to fake. No lengthy verification, reconciliation, nor clearing process exists with Bitcoin.
Bitcoin is based on a proof-of-work algorithm. Every transaction on the network has an associated mathetical “puzzle”. Computers known as miners compete to solve the complex cryptographic hash algorithm that comprises that puzzle. The solution is proof that the miner engaged in sufficient work. The puzzle is known as a nonce, a number used only once. There is only one major nonce at a time and it issues 12.5 Bitcoin. Once it is solved, the fact that the nonce has been solved is made public.
A block is mined on average of once every ten minutes. However, the blockchain checks every 2,016,000 minutes (approximately four years) if 201,600 blocks were mined. If it was faster, it increases difficulty by half, thereby deflating Bitcoin. If it was slower, it decreases, thereby inflating Bitcoin. It will continue to do this until zero Bitcoin are issued, projected at the year 2140. On the twelfth of May, 2020, the blockchain will halve the amount of Bitcoin issued when each nonce is guessed. When Bitcoin was first created, fifty were issued per block as a reward to miners. 6.25 BTC will be issued from that point on once each nonce is solved.
Unlike fiat, Bitcoin is a deflationary currency. As BTC becomes scarcer, demand for it will increase, also raising the price. In this, BTC is similar to gold. It is predictable in its’ output, unlike the USD, as it is based on a programmed supply. We can predict BTC’s deflation and inflation almost exactly, if not exactly. Only 21 million BTC will ever be produced, unless the entire network concedes to change the protocol – which is highly unlikely.
Some of the drawbacks to BTC include congestion. At peak congestion, it may take an entire day to process a Bitcoin transaction as only three to five transactions may be processed per second. Receiving priority on a payment may cost up to the equivalent of twenty dollars ($20). Bitcoin mining consumes enough energy in one day to power a single-family home for an entire week.

Trading or Investing?

The fundamental divide in trading revolves around the question of market structure. Many feel that the market operates totally randomly and its’ behavior cannot be predicted. For the purposes of this article, we will assume that the market has a structure, but that that structure is not perfect. That market structure naturally generates chart patterns as the market records prices in time. In order to determine when the stock market will crash, causing a major decline in BTC price, we will analyze an instrument, an exchange traded fund, which represents an index, as opposed to a particular stock. The price patterns of the various stocks in an index are effectively smoothed out. In doing so, a more technical picture arises. Perhaps the most popular of these is the SPDR S&P Standard and Poor 500 Exchange Traded Fund ($SPY).
In trading, little to no concern is given about value of underlying asset. We are concerned primarily about liquidity and trading ranges, which are the amount of value fluctuating on a short-term basis, as measured by volatility-implied trading ranges. Fundamental analysis plays a role, however markets often do not react to real-world factors in a logical fashion. Therefore, fundamental analysis is more appropriate for long-term investing.
The fundamental derivatives of a chart are time (x-axis) and price (y-axis). The primary technical indicator is price, as everything else is lagging in the past. Price represents current asking price and incorrectly implementing positions based on price is one of the biggest trading errors.
Markets and currencies ordinarily have noise, their tendency to back-and-fill, which must be filtered out for true pattern recognition. That noise does have a utility, however, in allowing traders second chances to enter favorable positions at slightly less favorable entry points. When you have any market with enough liquidity for historical data to record a pattern, then a structure can be divined. The market probes prices as part of an ongoing price-discovery process. Market technicians must sometimes look outside of the technical realm and use visual inspection to ascertain the relevance of certain patterns, using a qualitative eye that recognizes the underlying quantitative nature
Markets and instruments rise slower than they correct, however they rise much more than they fall. In the same vein, instruments can only fall to having no worth, whereas they could theoretically grow infinitely and have continued to grow over time. Money in a fiat system is illusory. It is a fundamentally synthetic instrument which has no intrinsic value. Hence, the recent seemingly illogical fluctuations in the market.
According to trade theory, the unending purpose of a market or instrument is to create and break price ranges according to the laws of supply and demand. We must determine when to trade based on each market inflection point as defined in price and in time as opposed to abandoning the trend (as the contrarian trading in this sub often does). Time and Price symmetry must be used to be in accordance with the trend. When coupled with a favorable risk to reward ratio, the ability to stay in the market for most of the defined time period, and adherence to risk management rules; the trader has a solid methodology for achieving considerable gains.
We will engage in a longer term market-oriented analysis to avoid any time-focused pressure. The Bitcoin market is open twenty-four-hours a day, so trading may be done when the individual is ready, without any pressing need to be constantly alert. Let alone, we can safely project months in advance with relatively high accuracy. Bitcoin is an asset which an individual can both trade and invest, however this article will be focused on trading due to the wide volatility in BTC prices over the short-term.

Technical Indicator Analysis of Bitcoin

Technical indicators are often considered self-fulfilling prophecies due to mass-market psychology gravitating towards certain common numbers yielded from them. They are also often discounted when it comes to BTC. That means a trader must be especially aware of these numbers as they can prognosticate market movements. Often, they are meaningless in the larger picture of things.
  • Volume – derived from the market itself, it is mostly irrelevant. The major problem with volume for stocks is that the US market open causes tremendous volume surges eradicating any intrinsic volume analysis. This does not occur with BTC, as it is open twenty-four-seven. At major highs and lows, the market is typically anemic. Most traders are not active at terminal discretes (peaks and troughs) because of levels of fear. Volume allows us confidence in time and price symmetry market inflection points, if we observe low volume at a foretold range of values. We can rationalize that an absolute discrete is usually only discovered and anticipated by very few traders. As the general market realizes it, a herd mentality will push the market in the direction favorable to defending it. Volume is also useful for swing trading, as chances for swing’s validity increases if an increase in volume is seen on and after the swing’s activation. Volume is steadily decreasing. Lows and highs are reached when volume is lower.
Therefore, due to the relatively high volume on the 12th of March, we can safely determine that a low for BTC was not reached.
  • VIX – Volatility Index, this technical indicator indicates level of fear by the amount of options-based “insurance” in portfolios. A low VIX environment, less than 20 for the S&P index, indicates a stable market with a possible uptrend. A high VIX, over 20, indicates a possible downtrend. VIX is essentially useless for BTC as BTC-based options do not exist. It allows us to predict the market low for $SPY, which will have an indirect impact on BTC in the short term, likely leading to the yearly low. However, it is equally important to see how VIX is changing over time, if it is decreasing or increasing, as that indicates increasing or decreasing fear. Low volatility allows high leverage without risk or rest. Occasionally, markets do rise with high VIX.
As VIX is unusually high, in the forties, we can be confident that a downtrend for the S&P 500 is imminent.
  • RSI (Relative Strength Index): The most important technical indicator, useful for determining highs and lows when time symmetry is not availing itself. Sometimes analysis of RSI can conflict in different time frames, easiest way to use it is when it is at extremes – either under 30 or over 70. Extremes can be used for filtering highs or lows based on time-and-price window calculations. Highly instructive as to major corrective clues and indicative of continued directional movement. Must determine if longer-term RSI values find support at same values as before. It is currently at 73.56.
  • Secondly, RSI may be used as a high or low filter, to observe the level that short-term RSI reaches in counter-trend corrections. Repetitions based on market movements based on RSI determine how long a trade should be held onto. Once a short term RSI reaches an extreme and stay there, the other RSI’s should gradually reach the same extremes. Once all RSI’s are at extreme highs, a trend confirmation should occur and RSI’s should drop to their midpoint.

Trend Definition Analysis of Bitcoin

Trend definition is highly powerful, cannot be understated. Knowledge of trend logic is enough to be a profitable trader, yet defining a trend is an arduous process. Multiple trends coexist across multiple time frames and across multiple market sectors. Like time structure, it makes the underlying price of the instrument irrelevant. Trend definitions cannot determine the validity of newly formed discretes. Trend becomes apparent when trades based in counter-trend inflection points continue to fail.
Downtrends are defined as an instrument making lower lows and lower highs that are recurrent, additive, qualified swing setups. Downtrends for all instruments are similar, except forex. They are fast and complete much quicker than uptrends. An average downtrend is 18 months, something which we will return to. An uptrend inception occurs when an instrument reaches a point where it fails to make a new low, then that low will be tested. After that, the instrument will either have a deep range retracement or it may take out the low slightly, resulting in a double-bottom. A swing must eventually form.
A simple way to roughly determine trend is to attempt to draw a line from three tops going upwards (uptrend) or a line from three bottoms going downwards (downtrend). It is not possible to correctly draw a downtrend line on the BTC chart, but it is possible to correctly draw an uptrend – indicating that the overall trend is downwards. The only mitigating factor is the impending stock market crash.

Time Symmetry Analysis of Bitcoin

Time is the movement from the past through the present into the future. It is a measurement in quantified intervals. In many ways, our perception of it is a human construct. It is more powerful than price as time may be utilized for a trade regardless of the market inflection point’s price. Were it possible to perfectly understand time, price would be totally irrelevant due to the predictive certainty time affords. Time structure is easier to learn than price, but much more difficult to apply with any accuracy. It is the hardest aspect of trading to learn, but also the most rewarding.
Humans do not have the ability to recognize every time window, however the ability to define market inflection points in terms of time is the single most powerful trading edge. Regardless, price should not be abandoned for time alone. Time structure analysis It is inherently flawed, as such the markets have a fail-safe, which is Price Structure. Even though Time is much more powerful, Price Structure should never be completely ignored. Time is the qualifier for Price and vice versa. Time can fail by tricking traders into counter-trend trading.
Time is a predestined trade quantifier, a filter to slow trades down, as it allows a trader to specifically focus on specific time windows and rest at others. It allows for quantitative measurements to reach deterministic values and is the primary qualifier for trends. Time structure should be utilized before price structure, and it is the primary trade criterion which requires support from price. We can see price structure on a chart, as areas of mathematical support or resistance, but we cannot see time structure.
Time may be used to tell us an exact point in the future where the market will inflect, after Price Theory has been fulfilled. In the present, price objectives based on price theory added to possible future times for market inflection points give us the exact time of market inflection points and price.
Time Structure is repetitions of time or inherent cycles of time, occurring in a methodical way to provide time windows which may be utilized for inflection points. They are not easily recognized and not easily defined by a price chart as measuring and observing time is very exact. Time structure is not a science, yet it does require precise measurements. Nothing is certain or definite. The critical question must be if a particular approach to time structure is currently lucrative or not.
We will measure it in intervals of 180 bars. Our goal is to determine time windows, when the market will react and when we should pay the most attention. By using time repetitions, the fact that market inflection points occurred at some point in the past and should, therefore, reoccur at some point in the future, we should obtain confidence as to when SPY will reach a market inflection point. Time repetitions are essentially the market’s memory. However, simply measuring the time between two points then trying to extrapolate into the future does not work. Measuring time is not the same as defining time repetitions. We will evaluate past sessions for market inflection points, whether discretes, qualified swings, or intra-range. Then records the times that the market has made highs or lows in a comparable time period to the future one seeks to trade in.
What follows is a time Histogram – A grouping of times which appear close together, then segregated based on that closeness. Time is aligned into combined histogram of repetitions and cycles, however cycles are irrelevant on a daily basis. If trading on an hourly basis, do not use hours.
  • Yearly Lows (last seven years): 1/1/13, 4/10/14, 1/15/15, 1/17/16, 1/1/17, 12/15/18, 2/6/19
  • Monthly Mode: 1, 1, 1, 1, 2, 4, 12
  • Daily Mode: 1, 1, 6, 10, 15, 15, 17
  • Monthly Lows (for the last year): 3/12/20 (10:00pm), 2/28/20 (7:09am), 1/2/20 (8:09pm), 12/18/19 (8:00am), 11/25/19 (1:00am), 10/24/19 (2:59am), 9/30/19 (2:59am), 8/29,19 (4:00am), 7/17/19 (7:59am), 6/4/19 (5:59pm), 5/1/19 (12:00am), 4/1/19 (12:00am)
  • Daily Lows Mode for those Months: 1, 1, 2, 4, 12, 17, 18, 24, 25, 28, 29, 30
  • Hourly Lows Mode for those Months (Military time): 0100, 0200, 0200, 0400, 0700, 0700, 0800, 1200, 1200, 1700, 2000, 2200
  • Minute Lows Mode for those Months: 00, 00, 00, 00, 00, 00, 09, 09, 59, 59, 59, 59
  • Day of the Week Lows (last twenty-six weeks):
Weighted Times are repetitions which appears multiple times within the same list, observed and accentuated once divided into relevant sections of the histogram. They are important in the presently defined trading time period and are similar to a mathematical mode with respect to a series. Phased times are essentially periodical patterns in histograms, though they do not guarantee inflection points
Evaluating the yearly lows, we see that BTC tends to have its lows primarily at the beginning of every year, with a possibility of it being at the end of the year. Following the same methodology, we get the middle of the month as the likeliest day. However, evaluating the monthly lows for the past year, the beginning and end of the month are more likely for lows.
Therefore, we have two primary dates from our histogram.
1/1/21, 1/15/21, and 1/29/21
2:00am, 8:00am, 12:00pm, or 10:00pm
In fact, the high for this year was February the 14th, only thirty days off from our histogram calculations.
The 8.6-Year Armstrong-Princeton Global Economic Confidence model states that 2.15 year intervals occur between corrections, relevant highs and lows. 2.15 years from the all-time peak discrete is February 9, 2020 – a reasonably accurate depiction of the low for this year (which was on 3/12/20). (Taking only the Armstrong model into account, the next high should be Saturday, April 23, 2022). Therefore, the Armstrong model indicates that we have actually bottomed out for the year!
Bear markets cannot exist in perpetuity whereas bull markets can. Bear markets will eventually have price objectives of zero, whereas bull markets can increase to infinity. It can occur for individual market instruments, but not markets as a whole. Since bull markets are defined by low volatility, they also last longer. Once a bull market is indicated, the trader can remain in a long position until a new high is reached, then switch to shorts. The average bear market is eighteen months long, giving us a date of August 19th, 2021 for the end of this bear market – roughly speaking. They cannot be shorter than fifteen months for a central-bank controlled market, which does not apply to Bitcoin. (Otherwise, it would continue until Sunday, September 12, 2021.) However, we should expect Bitcoin to experience its’ exponential growth after the stock market re-enters a bull market.
Terry Laundy’s T-Theory implemented by measuring the time of an indicator from peak to trough, then using that to define a future time window. It is similar to an head-and-shoulders pattern in that it is the process of forming the right side from a synthetic technical indicator. If the indicator is making continued lows, then time is recalculated for defining the right side of the T. The date of the market inflection point may be a price or indicator inflection date, so it is not always exactly useful. It is better to make us aware of possible market inflection points, clustered with other data. It gives us an RSI low of May, 9th 2020.
The Bradley Cycle is coupled with volatility allows start dates for campaigns or put options as insurance in portfolios for stocks. However, it is also useful for predicting market moves instead of terminal dates for discretes. Using dates which correspond to discretes, we can see how those dates correspond with changes in VIX.
Therefore, our timeline looks like:
  • 2/14/20 – yearly high ($10372 USD)
  • 3/12/20 – yearly low thus far ($3858 USD)
  • 5/9/20 – T-Theory true yearly low (BTC between 4863 and 3569)
  • 5/26/20 – hashrate difficulty halvening
  • 11/14/20 – stock market low
  • 1/15/21 – yearly low for BTC, around $8528
  • 8/19/21 – end of stock bear market
  • 11/26/21 – eighteen months from halvening, average peak from halvenings (BTC begins rising from $3000 area to above $23,312)
  • 4/23/22 – all-time high
Taken from my blog: http://aliamin.info/2020/
submitted by aibnsamin1 to Bitcoin [link] [comments]

Need some legitimate risk management advice

Brand new to forex, after messing around with stocks and ETFs for a year on robinhood.
In trying to learn about this strange new world, seemingly every article warns me that trading forex is the fastest route to poverty, that I'll lose every dime I have and that I'm better off buying lottery tickets, UNLESS I have a risk management plan.
That's all good and well, but it seems hard to find suggestions on how to actually manage my risk. So far what I have found is either unconvincing, or I just flat don't understand what is being explained. So I've landed here.
Reading the Forex FAQ, in this sub, the advice is to use a very small amount of capital when starting off, and practice live trading from there. If then recommends a formula to use in order to calculate risk, which seems like quite a bit of running calculations for every single trade that I make. Is it really the case that every Forex Trader that manages risk runs a series of calculations for each and every trade in order to figure out pip value and leverage amount, such matter and what have you?
Second problem, before even getting to the risk management section of this Subs FAQ, I'm told to read The Beginner's Guide on baby Pips. Babypips says that when you first start off trading you should not start small because then you will never be able to weather times of drawdown. They recommend something like an initial deposit of $20,000 or 50,000, and saying that if you don't have that much then build up your savings and come back the Forex when you have that to drop into the market. Are you kidding me?
My original plan before reading either of those guides was to deposit $300 and use something like a 10 to 1 or 20 to 1 Leverage.
The part that I'm hung up on which really baffles me and I need some help understanding is everywhere seems to say that I should only risk one or 2% of my account. I don't really understand what that means.
My trading app, OandA allows me to set default trade settings. One of them is trade size, which I can select an option "%Lev NAV" In all of my general Trading I have kept this number at 100, assuming that it is simply using 100% of my account for each trade.
I am also using a system in order to Define very specific entry points with a one-to-one risk reward ratio, setting a stop loss and take profit Target, usually between 9 and 60 Pips in size, depending on the instrument. Thus far, each trade that I have won usually amounts to a 3 to 8% change in the demo account value, which seems comprable to what I was experiencing with stocks and ETFs back on Robinhood. For the last 4 trades I've made, I'm up 15%.
Do I need to adjust this % Lev NAV down to 1% instead of 100? Or do I really need to download a pip value calculator app and make a determination after solving some arithmetic? I just can't seem to figure this out, and different sources use the same words interchangeably yet differently. When risking 1% of my account, does that include leverage, or not, in the trade? And if the most anyone recommends to risk in a trade is 1-2% then why use leverage at all? Won't the returns on 1% be so small as to be negligible? I don't seem to understand how it could possibly be Worth while to spend all that time trading... 1℅ of $300 is three bucks. As I understand it, that would allow me to buy 2 units of the EUUSD... there's no way that could be right, right?
Thanks for your patience and for reading this whole, chapter-length, question of a post.
I look forward to some clarity. I don't know how to switch to live trading, and the demo account does nothing to simulate leverage.
submitted by rm-rf_iniquity to Forex [link] [comments]

Risk Management

The investors or the traders should know what is Risk for knowing about details Risk Management.
Risk is the probability of a bad outcome
Risk is the probability of underachieving
Risk is the probability of failing investment or trading goals
Risk is the probability of losing money
Risk management is knowing exactly how much money you can lose at any particular time because you have pre-calculated this number. It is an attempt to assess the potential loss in any trade and then take the right measures based on your risk tolerance. In trading, you can lose a higher number of trades than you win and still have a profitable account, just as long as your risk to reward ratio is greater than 1:2. Risk management should be the cornerstone of every investment strategy. Get risk management correct in trading, you have to think of yourself as a risk manager first and a trader second as your risk tolerance will determine your success or failure as a trader.
Finally, the investors or the traders maintain their Risk Management:
Using perfect Stop Loss and Take Profit
Proper calculation of Position Size
Perfect measurement of Reward and Risk ratios
Following trading psychology
FX Magician
#TechnicalAnalysis #ForexTrade #OptionTrade #BestBroker #ForexSignal
submitted by SahinRasel6472 to u/SahinRasel6472 [link] [comments]

Risk Management

Risk Management
The investors or the traders should know what is Risk for knowing about details Risk Management.
Risk is the probability of a bad outcome
Risk is the probability of underachieving
Risk is the probability of failing investment or trading goals
Risk is the probability of losing money
Risk management is knowing exactly how much money you can lose at any particular time because you have pre-calculated this number. It is an attempt to assess the potential loss in any trade and then take the right measures based on your risk tolerance. In trading, you can lose a higher number of trades than you win and still have a profitable account, just as long as your risk to reward ratio is greater than 1:2. Risk management should be the cornerstone of every investment strategy. Get risk management correct in trading, you have to think of yourself as a risk manager first and a trader second as your risk tolerance will determine your success or failure as a trader.
Finally, the investors or the traders maintain their Risk Management:
Using perfect Stop Loss and Take Profit
Proper calculation of Position Size
Perfect measurement of Reward and Risk ratios
Following trading psychology
FX Magician
#TechnicalAnalysis #ForexTrade #OptionTrade #BestBroker #ForexSignal
http://fxmagician.com
#technical analysis #forex trade #option trade #best broker #forex signal
submitted by shofikul_islam to u/shofikul_islam [link] [comments]

Risk Management

Risk Management
The investors or the traders should know what is Risk for knowing about details Risk Management.
Risk is the probability of a bad outcome
Risk is the probability of underachieving
Risk is the probability of failing investment or trading goals
Risk is the probability of losing money
Risk management is knowing exactly how much money you can lose at any particular time because you have pre-calculated this number. It is an attempt to assess the potential loss in any trade and then take the right measures based on your risk tolerance. In trading, you can lose a higher number of trades than you win and still have a profitable account, just as long as your risk to reward ratio is greater than 1:2. Risk management should be the cornerstone of every investment strategy. Get risk management correct in trading, you have to think of yourself as a risk manager first and a trader second as your risk tolerance will determine your success or failure as a trader.
Finally, the investors or the traders maintain their Risk Management:
Using perfect Stop Loss and Take Profit
Proper calculation of Position Size
Perfect measurement of Reward and Risk ratios
Following trading psychology
FX Magician
#TechnicalAnalysis #ForexTrade #OptionTrade #BestBroker #ForexSignal
http://fxmagician.com
#technical analysis #forex trade #option trade #best broker #forex signal
submitted by shofikul_islam to u/shofikul_islam [link] [comments]

Risk Management


The investors or the traders should know what is Risk for knowing about details Risk Management.
Risk is the probability of a bad outcome
Risk is the probability of underachieving
Risk is the probability of failing investment or trading goals
Risk is the probability of losing money
Risk management is knowing exactly how much money you can lose at any particular time because you have pre-calculated this number. It is an attempt to assess the potential loss in any trade and then take the right measures based on your risk tolerance. In trading, you can lose a higher number of trades than you win and still have a profitable account, just as long as your risk to reward ratio is greater than 1:2. Risk management should be the cornerstone of every investment strategy. Get risk management correct in trading, you have to think of yourself as a risk manager first and a trader second as your risk tolerance will determine your success or failure as a trader.
Finally, the investors or the traders maintain their Risk Management:
Using perfect Stop Loss and Take Profit
Proper calculation of Position Size
Perfect measurement of Reward and Risk ratios
Following trading psychology
FX Magician
#TechnicalAnalysis #ForexTrade #OptionTrade #BestBroker #ForexSignal
submitted by SahinRasel6472 to u/SahinRasel6472 [link] [comments]

My experience with forex signals!


Hi my name is D and I have used multiple forex signal providers in the past and I would like to share my experience with the community in the hopes of warning others to wisely pick a signal provider and not burn their hard earned money like I did. ( I know this post is long but please give it a read before you start trading with any signal providers.)
So what made me start following signal providers? I had friends who were trading the forex market by themselves and making profits. I wanted to be like them however I was too impatient. I did not have the confidence to enter trades based on my own analysts as I was still in the learning stages but I still wanted to make some money from forex.
I started my search on instagram to find my first forex signal provider. It was then that I started my year long journey of subscribing to a signal provider and then switching to another one when the previous one was not profitable. (No. I did not switch provider right after a month as I believe every trader has bad months. I had multiple accounts to enter different signals from multiple providers.) After about a year, most of my accounts were down and I told myself I had to put a stop to this senseless burning of money.
I risk 2% for every trade no matter the size of my SL and TP. SL of 20 pips with TP of 40 pips? 2%. SL of 50 pips with TP of 100 pips? 2%. My lot size will just be smaller. Every profitable trader will agree that risk management is everything and is what keeps you in the game in the long run.
Over the many months I have collated the data and managed to pinpoint the exact reasons why my accounts were in a deficit even when the signal provider will show that it was a profitable month. There will be 5 reasons that I will be covering and I hope you take note of each one because if you see a signal provider doing one or more of these, it is a huge red flag that you will not be profitable if you follow it.
  1. Every post is showing off their lavish lifestyle and saying you should quit your 9-5 job
This is a huge huge red flag that the provider is not genuine. Real traders know that forex is not some get rich quick scheme and it takes months, even years of hardwork to start seeing results. They are trying to sell you a dream that you can get rich right away just by purchasing their signal package lol. Looking back, I realise that their analysts was total crap probably because they spent most of their time flexing on their gram. Genuine traders do not have to be such a douche about things as they know the value they offer and do not have to resort to such means to get attention.
  1. Bad risk reward ratio
Risk and reward ratio is everything. If your RR is 1:2. You only need to hit take profit 33% of the time to break even. 1:3? 25%, even better. Any percentage higher and you would be making money. Some signal providers only send trades with RR of maybe 1:1, some even lower than that. This means you have to hit take profit 50% of the time to break even. That is honestly pretty hard to do. So not only do you not make money, you end up losing.
  1. Setting multiple take profits
This is the biggest scam ever and how I was so stupid to not notice it sooner annoys me. Firstly, there is nothing wrong setting multiple take profits to secure some $$ first. However these providers do it in a way that makes it seem their week was profitable while in reality it was not. So let me show you how the maths works. I found an example of one of these trades from a provider I was once subscribed to. ( I have added in the number of pips from entry to save you from the calculations)
BUY XXXXXX NOW @ 1.59650 Sl: 1.59300 (35 pips) Tp1: 1.59822 (17.2 pips) Tp2: 1.60000 (35 pips) Tp3: 1.60200 (55 pips) Tp4: 1.60600 (95 pips) Tp5: 1.61000 (135 pips)
Wow! Looks good doesn't it. Nope it is actually not. Lets break it down. For calculation purposes assume that I risked 5% of my account for the entire trade. I would have to open 5 different positions, each risking 1% of my account. No now lets assume best case scenario and all the trades hit take profit, this is how much account growth I would have in total.
Tp1: 0.49% Tp2: 1% Tp3: 1.57% Tp4: 2.71% Tp5: 3.85%
Total of 9.62%!! Wow not too bad right almost a 1:2 RR. However this is rarely (almost never) the case. In reality it does not often hit TP 5, normally TP 3 and if you are lucky TP 4. In the case of TP 3 your RR would be negative. This factored in with not knowing when to set your SL to entry and having little clue when to actually take profit as TP 4 and TP 5 is unlikely you will be left with a huge drawdown.
So now for the best part. How forex signal providers make it seem that they are profitable. Lets say this trade hits SL, never mind its just a 35 pip loss, dont sweat it. Hits TP3 ... wow! 107 pip gain!!! (17.2+35+55) What a good trade! Yup you risked 5% for a 3% gain, nice one. Now you understand how people get scammed by those forex gurus posting huge pip gains and little losses, PIP GAIN DOES NOT EQUAL PROFITABILITY DO NOT BE FOOLED
  1. Unrealistic RR
Constant signals of RR of 1:4 and higher?? Sign me up please. Yup some providers do this and once the trade is entered they tell you price looks like it is about to retrace blah blah blah and ask you to close it at 1:0.5. A well known forex signal provider still does this but no name shall be mentioned. Worst still etc. you risked 100 pips for "400pips". And the provider celebrates that you caught at least 50 pips! 50 pips is a lot if your risk is maybe 15 pips, but you risked 100? No please that was terrible.
  1. Not caring that different currencies have different pip sizes
For example GBPAUD EURUSD have completely different pip sizes, great you are 60 pips up in GBPAUD and down 45 in EURUSD, still 15 pips in profit! Nope, lets assume you opened 1 lot for each trade, you will be up $410usd for GBPAUD and down $450usd for EURUSD. It is a totaly unnecessary gamble hoping that the trades with a bigger pip value will be up. One way to "counter" this to calculate it such that each pip value is the same. Lets say you want 1 pip to be 1USD, for GBPAUD it will be a 0.145 lot size, for EURUSD 0.1.
These are the reasons why a reliable signal provider is extremely hard to find and instead of earning some money quickly you will find yourself in a hole and in the cycle of changing signal providers. I personally feel it is better to spend your money learning forex and strategies from courses provided online and eventually trade by yourself. The key in forex is patience, having a good risk to reward ratio and full faith in your strategy.
If you have made it this far, I would like to thank you for taking your time to read my first reddit post. I hope you found it informative and please leave some feedback!
Help to share this post to prevent others from being scammed by forex”gurus”!!
submitted by FX_D4N to Forex [link] [comments]

[educational] Stretgies for day trading based on Technical Analysis

[educational] Stretgies for day trading based on Technical Analysis

1. Breakout

Breakout strategies center around when the price clears a specified level on your chart, with increased volume. The breakout trader enters into a long position after the asset or security breaks above resistance. Alternatively, you enter a short position once the stock breaks below support.
After an asset or security trades beyond the specified price barrier, volatility usually increases and prices will often trend in the direction of the breakout.
You need to find the right instrument to trade. When doing this bear in mind the asset’s support and resistance levels. The more frequently the price has hit these points, the more validated and important they become.

Entry Points

This part is nice and straightforward. Prices set to close and above resistance levels require a bearish position. Prices set to close and below a support level need a bullish position.

Plan your exits

Use the asset’s recent performance to establish a reasonable price target. Using chart patterns will make this process even more accurate. You can calculate the average recent price swings to create a target. If the average price swing has been 3 points over the last several price swings, this would be a sensible target. Once you’ve reached that goal you can exit the trade and enjoy the profit.
https://preview.redd.it/0oj4a1xlvdh31.png?width=773&format=png&auto=webp&s=8f2aa07b0c7caeeb00c4f997c12e814abbd380da

2. Scalping

One of the most popular strategies is scalping. It’s particularly popular in the forex market, and it looks to capitalise on minute price changes. The driving force is quantity. You will look to sell as soon as the trade becomes profitable. This is a fast-paced and exciting way to trade, but it can be risky. You need a high trading probability to even out the low risk vs reward ratio.
Be on the lookout for volatile instruments, attractive liquidity and be hot on timing. You can’t wait for the market, you need to close losing trades as soon as possible.
https://preview.redd.it/dzaf7t1nvdh31.png?width=653&format=png&auto=webp&s=f3d96d74311de806c3809698df2a964e3eb4db5e

3. Momentum

Popular amongst trading strategies for beginners, this strategy revolves around acting on news sources and identifying substantial trending moves with the support of high volume. There is always at least one stock that moves around 20-30% each day, so there’s ample opportunity. You simply hold onto your position until you see signs of reversal and then get out.
Alternatively, you can fade the price drop. This way round your price target is as soon as volume starts to diminish.
This strategy is simple and effective if used correctly. However, you must ensure you’re aware of upcoming news and earnings announcements. Just a few seconds on each trade will make all the difference to your end of day profits.
https://preview.redd.it/z4r2o6covdh31.png?width=600&format=png&auto=webp&s=b054c77c4bc5978821e879eff73d613d728cb0cf

4. Reversal

Although hotly debated and potentially dangerous when used by beginners, reverse trading is used all over the world. It’s also known as trend trading, pull back trending and a mean reversion strategy.
This strategy defies basic logic as you aim to trade against the trend. You need to be able to accurately identify possible pullbacks, plus predict their strength. To do this effectively you need in-depth market knowledge and experience.
The ‘daily pivot’ strategy is considered a unique case of reverse trading, as it centers on buying and selling the daily low and high pullbacks/reverse.
https://preview.redd.it/4ya3txcpvdh31.png?width=776&format=png&auto=webp&s=f40216413b1376b2d6d5a67e4d09057f55be6ba1

5. Using Pivot Points

A day trading pivot point strategy can be fantastic for identifying and acting on critical support and/or resistance levels. It is particularly useful in the forex market. In addition, it can be used by range-bound traders to identify points of entry, while trend and breakout traders can use pivot points to locate key levels that need to break for a move to count as a breakout.

Calculating Pivot Points

A pivot point is defined as a point of rotation. You use the prices of the previous day’s high and low, plus the closing price of a security to calculate the pivot point.
Note that if you calculate a pivot point using price information from a relatively short time frame, accuracy is often reduced.
So, how do you calculate a pivot point?
  • Central Pivot Point (P) = (High + Low + Close) / 3
You can then calculate support and resistance levels using the pivot point. To do that you will need to use the following formulas:
  • First Resistance (R1) = (2*P) – Low
  • First Support (S1) = (2*P) – High
The second level of support and resistance is then calculated as follows:
  • Second Resistance (R2) = P + (R1-S1)
  • Second Support (S2) = P – (R1- S1)

Application

When applied to the FX market, for example, you will find the trading range for the session often takes place between the pivot point and the first support and resistance levels. This is because a high number of traders play this range.
It’s also worth noting, this is one of the systems & methods that can be applied to indexes too. For example, it can help form an effective S&P day trading strategy

6. Moving Average Crossover

You will need three moving average lines:
  • One set at 20 periods – This is your fast moving average
  • One set at 60 periods – This is your slow moving average
  • One set at 100 periods – This is your trend indicator
This is one of the moving averages strategies that generates a buy signal when the fast moving average crosses up and over the slow moving average. A sell signal is generated simply when the fast moving average crosses below the slow moving average.
So, You’ll open a position when the moving average line crosses in one direction and you’ll close the position when it crosses back the opposite way.
How can you establish there’s definitely a trend? You know the trend is on if the price bar stays above or below the 100-period line.

the source : https://www.daytrading.com/strategies
submitted by JalelTounsi to ethfinance [link] [comments]

A Guide For Foreign Exchange Trading

A Guide For Foreign Exchange Trading
The greatest intrigue of Foreign Exchange Trading is that it is so natural to get into it. One can open a forex account on a shoestring, with least stores extending from exceptionally little to as low as $1, despite the fact that it wouldn't bode well to open a record for that little measure of cash, as it wouldn't enable you to put any exchanges.

https://preview.redd.it/ep6flbsbby541.jpg?width=940&format=pjpg&auto=webp&s=51573faf757879865df09260c2f9debbd976d8cf
Forex, or remote trade, includes the exchanging of cash sets. At the point when you go long on EUUSD, for instance, you are trusting that the estimation of the Euro will build comparative with the U.S. Dollar. Similarly, as with any venture, you could figure wrong and the exchange could move against you.
That is the clearest hazard when exchanging the FX markets. You can cause an extra hazard by exchanging less well known (thus less fluid) money sets and by getting into a circumstance where the exchange itself is precarious, in light of the fact that you have not appropriately dealt with your edge record or you have picked a questionable specialist or exchanging trade.
It's valuable to remember that most by far of forex exchanges are made by banks, not people, and they are really utilizing forex to diminish the danger of money variance. They utilize complex calculations in their automated exchanging frameworks to deal with a portion of the dangers depicted underneath.
As an individual, you are less dependent upon a significant number of these dangers, and others can be limited through the sound exchange of the executives. Any speculation that offers potential benefit likewise has drawback chance, up to the point of losing considerably more than the estimation of your exchange when exchanging on edge. This article can help comprehend the dangers so you exchange effectively.
Coming up next are the significant hazard factors in FX exchanging:
Conversion standard Risk
Loan cost Risk
Credit Risk
Nation Risk
Liquidity Risk
Minimal or Leverage Risk
Value-based Risk
Danger of Ruin
Conversion standard Risk
Traffic sign to show conversion scale chance
Conversion standard hazard is the hazard brought about by changes in the estimation of money. It depends on the impact of persistent and typically unstable moves in the overall market interest balance. For the period the broker's position is remarkable, the position is dependent upon all value changes. This hazard can be very generous and depends on the available's view of what direction the monetary forms will move dependent on every single imaginable factor that occurs (or could occur) at some random time, anyplace on the planet.
Also, on the grounds that the off-trade exchanging of Forex is to a great extent unregulated, no day by day value limits are forced as existing for controlled fates trades. The market moves dependent on basic and specialized variables - progressively about this later.
The most well-known strategy actualized in exchanging is cutting misfortunes and riding beneficial situations, so as to safeguard that misfortune are kept inside sensible points of confinement. This presence of mind procedure incorporates:
The Position Limit
A position limit is the most extreme measure of any cash a dealer is permitted to convey, at any single time.
The Loss Limit
As far as possible is a measure intended to maintain a strategic distance from unsustainable misfortunes made by dealers by methods for setting stop misfortune levels. It is basic that you have to stop misfortune arranges to set up.
Basic Risk/Reward Ratios
The basic strategy merchants use as a rule when attempting to control swapping scale hazards is to quantify their proposed additions against their potential misfortunes. The thought is that most merchants will lose twice the same number of times as they benefit, so a straightforward manual for exchanging is to keep your hazard/reward proportion to 1:3. This is represented in detail in a later segment.
Official site
https://angelium.net
Angelium wallet
https://wallet.angelium.net
Facebook
https://www.facebook.com/angelium.official/
Twitter
https://twitter.com/AngeliumANL
Telegram (English)
https://github.com/angelium
Telegram (Chinese)
https://t.me/AngeliumChinese
Telegram (Japanese)
https://t.me/angelium_jp
Official Video
https://youtu.be/h61qO3ihoHA
Youtube channel
https://www.youtube.com/channel/UCYhiGcIxJARA6u309Qt1lbA
submitted by rafimalik to u/rafimalik [link] [comments]

How Important is Time of day?

Hi All,
Some quick background. I've done some day trading in penny stocks when I was younger and naive, lost about $1200. I watched a few videos, got cocky and thought this was a get rich quick ordeal.
Fast forward 6 years, I've taken an interest to Forex and have been dedicating a few hours every day after work studying. I just started paper trading yesterday. (I plan to do this for a few months until I'm consistent and find my own strategy). I made 1% gain on my money which was only about a gain of $8 but i'm not concerned with the dollar figure. More about the consistent % gain over time. I also learned how to calculate your risk/reward ratio and set your stop losses correctly to limit your potential loss.
On to my question. One of the appeals of Forex was being able to trade at any time of the day. I work full time 5 days a week from 6am to 3pm PST.
How viable is it to be trading after work at these hours. Specifically 3:30pm PST onward. This is the time of day I can concentrate and give it my full attention. I'm not trying to day trade Forex on my phone on lunch break. That sounds like a recipe for disaster. I need all the tools that a full fledged PC program offers.
Thank you!
submitted by steemax to Forex [link] [comments]

My experience with forex signals.

Hi my name is D and I have used multiple forex signal providers in the past and I would like to share my experience with the community in the hopes of warning others to wisely pick a signal provider and not burn their hard earned money like I did. ( I know this post is long but please give it a read before you start trading with any signal providers.)
So what made me start following signal providers? I had friends who were trading the forex market by themselves and making profits. I wanted to be like them however I was too impatient. I did not have the confidence to enter trades based on my own analysts as I was still in the learning stages but I still wanted to make some money from forex.
I started my search on instagram to find my first forex signal provider. It was then that I started my year long journey of subscribing to a signal provider and then switching to another one when the previous one was not profitable. (No. I did not switch provider right after a month as I believe every trader has bad months. I had multiple accounts to enter different signals from multiple providers.) After about a year, most of my accounts were down and I told myself I had to put a stop to this senseless burning of money. Today , I am proud to say that I am able to trade by myself profitably.
I risk 2% for every trade no matter the size of my SL and TP. SL of 20 pips with TP of 40 pips? 2%. SL of 50 pips with TP of 100 pips? 2%. My lot size will just be smaller. Every profitable trader will agree that risk management is everything and is what keeps you in the game in the long run.
Over the many months I have collated the data and managed to pinpoint the exact reasons why my accounts were in a deficit even when the signal provider will show that it was a profitable month. There will be 5 reasons that I will be covering and I hope you take note of each one because if you see a signal provider, it is a huge red flag that you will not be profitable if you follow it.
  1. Every post is showing off their lavish lifestyle and saying you should quit your 9-5 job
This is a huge huge red flag that the provider is not genuine. Real traders know that forex is not some get rich quick scheme and it takes months, even years of hardwork to start seeing results. They are trying to sell you a dream that you can get rich right away just by purchasing their signal package lol. Looking back, I realise that their analysts was total crap probably because they spent most of their time flexing on their gram. Genuine traders do not have to be such a douche about things as they know the value they offer and do not have to resort to such means to get attention.
  1. Bad risk reward ratio
Risk and reward ratio is everything. If your RR is 1:2. You only need to hit take profit 33% of the time to break even. 1:3? 25%, even better. Any percentage higher and you would be making money. Some signal providers only send trades with RR of maybe 1:1, some even lower than that. This means you have to hit take profit 50% of the time to break even. That is honestly pretty hard to do. So not only do you not make money, you end up losing.
  1. Setting multiple take profits
This is the biggest scam ever and how I was so stupid to not notice it sooner annoys me. Firstly, there is nothing wrong setting multiple take profits to secure some $$ first. However these providers do it in a way that makes it seem their week was profitable while in reality it was not. So let me show you how the maths works. I found an example of one of these trades from a provider I was once subscribed to. ( I have added in the number of pips from entry to save you from the calculations)
BUY XXXXXX NOW @ 1.59650 Sl: 1.59300 (35 pips) Tp1: 1.59822 (17.2 pips) Tp2: 1.60000 (35 pips) Tp3: 1.60200 (55 pips) Tp4: 1.60600 (95 pips) Tp5: 1.61000 (135 pips)
Wow! Looks good doesn't it. Nope it is actually not. Lets break it down. For calculation purposes assume that I risked 5% of my account for the entire trade. I would have to open 5 different positions, each risking 1% of my account. No now lets assume best case scenario and all the trades hit take profit, this is how much account growth I would have in total.
Tp1: 0.49% Tp2: 1% Tp3: 1.57% Tp4: 2.71% Tp5: 3.85%
Total of 9.62%!! Wow not too bad right almost a 1:2 RR. However this is rarely (almost ever) the case. In reality it does not often hit TP 5, normally TP 3 and if you are lucky TP 4. In the case of TP 3 your RR would be negative. This factored in with not knowing when to set your SL to entry and having little clue when to actually take profit as TP 4 and TP 5 is highly you will be left with a huge drawdown.
So now for the best part. How forex signal providers make it seem that they are profitable. Lets say this trade hits SL, never mind its just a 35 pip loss, dont sweat it. Hits TP3 ... wow! 107 pip gain!!! (17.2+35+55) What a good trade! Yup you risked 5% for a 3% gain, nice one. Now you understand how people get scammed by those forex gurus posting huge pip gains and little losses, PIP GAIN DOES NOT EQUAL PROFITABILITY DO NOT BE FOOLED
  1. Unrealistic RR
Constant signals of RR of 1:4 and higher?? Sign me up please. Yup some providers do this and once the trade is entered they tell you price looks like it is about to retrace blah blah blah and ask you to close it at 1:0.5. A well known forex signal provider still does this but no name shall be mentioned. Worst still etc. you risked 100 pips for "400pips". And the provider celebrates that you caught at least 50 pips! 50 pips is a lot if your risk is maybe 15 pips, but you risked 100? No please that was terrible.
  1. Not caring that different currencies have different pip sizes
For example GBPAUD EURUSD have completely different pip sizes, great you are 60 pips up in GBPAUD and down 45 in EURUSD, still 15 pips in profit! Nope, lets assume you opened 1 lot for each trade, you will be up $410usd for GBPAUD and down $450usd for EURUSD. It is a totaly unnecessary gamble hoping that the trades with a bigger pip value will be up. One way to "counter" this to calculate it such that each pip value is the same. Lets say you want 1 pip to be 1USD, for GBPAUD it will be a 0.145 lot size, for EURUSD 0.1.
These are the reasons why a reliable signal provider is extremely hard to find and instead of earning some money quickly you will find yourself in a hole and in the cycle of changing signal providers. I personally feel it is better to spend your money learning forex and strategies from courses provided online and eventually trade by yourself. The key in forex is patience, having a good risk to reward ratio and full faith in your strategy.
If you have made it this far, I would like to thank you for taking your time to read my first reddit post. I hope you found it informative and please leave some feedback!
submitted by FX_D4N to u/FX_D4N [link] [comments]

Research is very important in Forex trading

In the trading business, you will need to study consistently. Sometimes, you must look for new trading strategies. Whereas sometimes, you may try to improve your errors in the trading plan. Either way, you need to spend a significant amount of time learning strategies and skills. Moreover, you must understand the market conditions too. With fundamental analysis, you must keep track of the price changes. Then when you will get an indication of a price change, technical analysis can be used to find appropriate entry spots for the trades. Aside from the market analysis, traders also do not have enough ideas about money management. So, consistent research on currency trading is necessary to develop your edge. Your Forex trading business may not provide big profit potential in the beginning but with an improved trading edge, you can manage it. And the most exciting thing is, profit potential will be consistent with an efficient trading strategy.
This article is for motivating to the new Singaporean traders to spend time on appropriate research. With patience and concentration, any trader can develop an effective trading plan. So, focus on one is important to execute trades securely. After you have mastered a safe trading approach, increase the profit potential with an improved trading plan.

Improve the market analysis skills

To place any size trade, you need to understand the market condition. An effective process is to do the fundamental analysis first and then technical analysis. The fundamental influences help to identify the possible price trends. But you need to improve your skills to use valid news sources. If the information is not right and you are approaching a trade, it cannot manage a profit potential. So, rookie traders will need to time and research to improve the fundamental skills. Just focus on the news related to the price driving catalysts to predict the volatility.
After the fundamental analysis, you also need to justify the market change with technical analysis skills. It is a calculative approach to justify the fundamental analysis. Moreover, you also get chances to position the trades properly. Using appropriate tools, you need to look for suitable retracement for the trades. The Fibonacci strategy is appropriate for this work. There are more important tools to be used for technical analysis. You need to learn about trend lines, pivot points, oscillators, indicators and chart patterns, etc. so, research and acquire knowledge on Forex market analysis.

Acquire knowledge about trading

There are more things needed for trading aside from the market analysis. If you just think of risk exposure, it will take months to develop a decent money management plan. Sometimes, rookie traders take a longer time than a month due to their negligence on risk exposure. To secure your trades from potential losses, it is important to manage the investment. You cannot trade with too big lots. According to the expert traders, a 2% risk per trade and a 1:10 leverage is enough to execute trades in Forex.
After the money management, you need to focus on the profit targets. It must be set according to your trading method. If you choose 5R of profit while trading with scalping or day trading, majority of the trades will return potential losses. Big profit targets are for long term methods like the swing and the position trading process. If you do not research, our mind would not set the right profit target. So, you must spend a significant amount of time learning about currency trading.

Find appropriate entries and exits

With efficient market analysis, every trader must place the trades properly. It is another fact for a secured trading business aside from the money management. You need to scale the trades properly and find a solid trade setup. Without confirmation from the market analysis, you cannot place any trades. Your trading money will be unsecured if you place a random trade for a random signal. So, look for valid entry and exit points for the trades. Improve your skills with efficient market analysis strategies.
submitted by dwaynebuzzell to tradingfx [link] [comments]

b

If you guys could post other things that you've found useful too, that'd be great.
submitted by confluencefx to u/confluencefx [link] [comments]

Trading Double Top and Double Bottom

Trading Double Top and Double Bottom

Trading Double Top and Double Bottom
Double top and Double Bottom are price action pattern formations identified to predict the behavior of the market. As the name suggests, Double Top is when the price action forms two peaks almost equal to each other, and the Double Bottom is when the price action dips to form two consecutive bottoms with only a peak separating the two. Of all the chart pattern formations, Double Top and Double Bottom could pass as one of the easiest-to-identify.

Double Top Identification

Double Top is formed when the market follows the uptrend and then pulls back. The pullback must have created a peak to its left in order to form a trough. The price then again rallies to form the second peak almost equal to the first, then drops again lower than the trough. The second peak, unable to break through the limit set by the first, marks the resistance and reduction in buying, thereby calling out a potential reversal.
Trading Double Top

Neckline

The right place to draw the neckline is at the lowest point of the pullback. The price rises from the trough to form the second peak and drops back again to the neckline completing the formation of Double Top and the opportunity.

Entry

The right time to enter the trade is by the completion of the pattern formation. When the shaky line from the second peak downs to the neckline signifying the uptrend reversal, it plunges deep breaking through the neckline. Shorting is the obvious option for profit since the prices are dropping.

Exit

The safest exit with considerable profit is calculated from the neckline with the same value as the height of the peaks.

Stop Loss

In case, worse comes to worst and you misinterpret the chart for a double top, Stop Loss is the measure to keep your loss to the minimum. It is better to limit the loss to the latest peak created within the pattern.

Double Bottom Identification

On contrary to the double top, the double bottom is identified by a dip, followed by a rise, which is again followed by a dip. In the downtrend, the price forms a trough by pulling back to the upside. The price drops again to a point above the first trough unable to drop lower signifying the reducing sellers, thereby marking the downtrend reversal. The price then rallies all the way up until it falls short of buyers or reaches a balancing point.
Trading Double Bottom

Neckline

Here, Neckline is the plane drawn to connect both troughs through the edge of the middle peak.

Entry

Similar to the double top, it is best to enter the trade by the completion of the double bottom. When the price rallies towards the neckline, it goes all the way up breaking through the neckline. So going long at the neckline makes the most of the opportunity.

Exit

The position in the uptrend, marked from the neckline with the same value as the height of the troughs, is safe to close the trade.

Stop Loss

Stop Loss for the Double Bottom is set at the recent trough formed inside the pattern to limit the loss which is inevitable.Double Top and Double Bottom are trend reversal patterns, which even the traders who disregard the chart patterns look forward to. These are simple trading patterns and doesn’t require much expertise to be able to identify, but the only shortcoming is that the reward: risk ratio is not too tempting. The ratio can be made favorable by setting stop loss in a much closer position. It is advised to take the trade only when the potential for profit is sound.Start forex trading with the use of demo account before you investing the real capital. That way you can get a feel for the process of trading and decide if trading forex is for you also we provide the best trading platform for beginners. When you're consistently making good trades on the demo account, then you can go live with a real forex account. Limit your losses.
submitted by alfafinancials5 to u/alfafinancials5 [link] [comments]

Chainfund — An Introduction to The Effortless Blockchain Investment Platform

Chainfund — An Introduction to The Effortless Blockchain Investment Platform
Chainfund is founded in October 2017 with initial funds of more than US$1million from more than 100 investors and offers a 1-Click investment experience designed to be open and accessible to everyone. Chainfund substantiates their highly ambitious nature with their philosophy — investing in high potential Crypto-assets with long-term values and growth.
Founders Thanh Do and Yann Quelenn possess a high degree of expertise in Computer Science, Entrepreneurship, Quantitative Finance, Economics and FX trading from their background as a Full Stack Software Engineer and Market Strategist for SwissQuote respectively. The founders’ individual expertise perfectly matches one another in the efforts of building Chainfund from the ground up.
The founders’ individual expertise perfectly matches one another in the efforts of building Chainfund from the ground up.
Thanh Do is Chainfund’s CEO. He is a serial entrepreneur, blockchain enthusiast, and fintech software engineer. He has been the founder and CEO of EMVN — top 50 worldwide YouTube network with 1 billion views monthly. He has been a full-stack engineer in Swissquote Bank Switzerland, a leading fintech company in trading markets such as stock, forex, crypto, and eGambling. Thanh graduated as MSc in Computer Science from the prestigious Ecole Polytechnique Fédérale de Lausanne (EPFL), top-12 QS World University Ranking 2018.
Yann Quelenn - Co-founder & CIO
Yann Quelenn is an investment professional with strong technical and financial background. He worked in several institutions such as Swissquote Bank in Switzerland where he was Market Strategist. He was also FX Trader at Banque Privée Edmond de Rothschild and Portfolio Manager at Polaris Investment in Luxembourg. Yann has also a master’s from Bocconi University, one of the most prestigious European university, where he has got a degree in Quantitative Finance and Risk Management. He has been featured in many tier 1 media such as the Guardian, Bloomberg, Reuters and The Financial Times and has already participated in several speaking events.
Chainfund currently offers investors the Dynamic, Extreme, ICO portfolios and the new launched MNODE Fund on a seamless platform which provides:
- exploration to a range of efficiently diversified portfolios
- gateway for securely depositing money and receive your portfolio shares
- collection of ROI by selling shares
Chainfund’s low entry rate appeals to a broader audience. Starting from $1,000, investors will have full control of withdrawals, access to the latest AI risk management algorithms and receive the best proposals and diversificationoptions to maximize returns while mitigating risks by our committed team of finance professionals, experienced fund managers and researchers. All transactions within Chainfund, will be processed through smart contracts, thus ensuring security, transparency and accuracy.

Dynamic Fund

This fund focuses on long-term sustainability whilst exposing sufficient risk, meticulously calculated to capitalise on the overall growth of Crypto-assets based on mainstream adoption potential.
- 40% Allocation always in Top 10 Cryptocurrencies by Market Capitalization.
- Privacy Coins
- Blockchain Infrastructure Platforms
- Utility tokens backed by a real economic model
Dynamic Fund: 40% Allocation always in Top 10 Cryptocurrencies by Market Capitalization

Extreme Fund

This fund portrays the methodology of Value Investing. Focusing on undervalued, high-growth potential coins found lower by ranking in terms of Market Capitalization for maximum returns tempered with realistic risk management. The Extreme Fund possesses a much higher risk-to-reward ratio as compared to Dynamic Fund. The fund will also introduce short-term swing trades to find profits during times of market volatility.
- 10% Allocation in Top 10 Cryptocurrencies by Market Capitalization.
- Privacy Coins
- Blockchain Infrastructure Platforms
- Scalability and Interoperability solutions
- Utility tokens backed by a strong economic model.
- Short-term trades (20%)
Extreme Fund portrays the methodology of Value Investing

ICO Fund

With over $1.3 million has been raised in the Initial Coin Offerings (ICOs) market in 2017, Chainfund aims to take advantage of the new method in raising funds and capital by introducing an ICO Fund.
Leveraging from its strong network, Chainfund offers an opportunity for retail investors to participate in private and pre-sales for an ICO, traditionally only available to private accredited investors, venture capitalists and institutions. Through the power of syndication, investors are able gain access to higher bonus structures and benefit from a much higher Return-on-Investment (ROI).
Potential partnerships will be meticulously vetted by our dedicated team of analysts, researchers and financial experts. Investors will be provided with our Due Diligence Report prior to investing. Chainfund also strives to open up more opportunities for its investors in due time as the crypto-market continues to find itself amongst the more established asset classes.

ICO Fund’s recent partnerships & private agreements

MNODE Fund

The Masternode market has grown spontaneously in the past year with over 3 billion market capital and hundreds of other masternode enable coins, Chainfund developed MNODE aiming at leveraging the benefit of this new technology.
MNODE is a tokenized Masternode fund, featuring:
  • 1-click investment experience with all assets are tokenized by a single MASTER token, intuitive platform management
  • Zero fee structure
  • Power of Syndication that enable diversified portfolio and access to maximum bonus rewards
  • Fast reward distribution with rewards are credited to staked wallets bi-weekly
Our private sale for MNODE Fund Starts NOW ! Find out more here or contact us at [[email protected]](mailto:[email protected])
https://preview.redd.it/7liy1dr9nrh11.png?width=995&format=png&auto=webp&s=5b8d831bd2e9f8f6e5cf0cfe3b88142b9f3abb0a
Yet to come — a glimpse of the future
Chainfund Permissioned Blockchain — secure, auditable, scalable infrastructure to enable seamless experience, full transparency, and instant payment confirmations.
Register here to receive exclusively reports and experience 1-Click investment. Investment starts at $1000.
References:
Join us @ Telegram Global group — https://t.me/chainfund
Read our articles @ Medium — https://medium.com/chainfundch
Follow us @ Chainfund Official Channels:
submitted by IliyaZaki to Chainfund [link] [comments]

Subreddit Stats: cs7646_fall2017 top posts from 2017-08-23 to 2017-12-10 22:43 PDT

Period: 108.98 days
Submissions Comments
Total 999 10425
Rate (per day) 9.17 95.73
Unique Redditors 361 695
Combined Score 4162 17424

Top Submitters' Top Submissions

  1. 296 points, 24 submissions: tuckerbalch
    1. Project 2 Megathread (optimize_something) (33 points, 475 comments)
    2. project 3 megathread (assess_learners) (27 points, 1130 comments)
    3. For online students: Participation check #2 (23 points, 47 comments)
    4. ML / Data Scientist internship and full time job opportunities (20 points, 36 comments)
    5. Advance information on Project 3 (19 points, 22 comments)
    6. participation check #3 (19 points, 29 comments)
    7. manual_strategy project megathread (17 points, 825 comments)
    8. project 4 megathread (defeat_learners) (15 points, 209 comments)
    9. project 5 megathread (marketsim) (15 points, 484 comments)
    10. QLearning Robot project megathread (12 points, 691 comments)
  2. 278 points, 17 submissions: davebyrd
    1. A little more on Pandas indexing/slicing ([] vs ix vs iloc vs loc) and numpy shapes (37 points, 10 comments)
    2. Project 1 Megathread (assess_portfolio) (34 points, 466 comments)
    3. marketsim grades are up (25 points, 28 comments)
    4. Midterm stats (24 points, 32 comments)
    5. Welcome to CS 7646 MLT! (23 points, 132 comments)
    6. How to interact with TAs, discuss grades, performance, request exceptions... (18 points, 31 comments)
    7. assess_portfolio grades have been released (18 points, 34 comments)
    8. Midterm grades posted to T-Square (15 points, 30 comments)
    9. Removed posts (15 points, 2 comments)
    10. assess_portfolio IMPORTANT README: about sample frequency (13 points, 26 comments)
  3. 118 points, 17 submissions: yokh_cs7646
    1. Exam 2 Information (39 points, 40 comments)
    2. Reformat Assignment Pages? (14 points, 2 comments)
    3. What did the real-life Michael Burry have to say? (13 points, 2 comments)
    4. PSA: Read the Rubric carefully and ahead-of-time (8 points, 15 comments)
    5. How do I know that I'm correct and not just lucky? (7 points, 31 comments)
    6. ML Papers and News (7 points, 5 comments)
    7. What are "question pools"? (6 points, 4 comments)
    8. Explanation of "Regression" (5 points, 5 comments)
    9. GT Github taking FOREVER to push to..? (4 points, 14 comments)
    10. Dead links on the course wiki (3 points, 2 comments)
  4. 67 points, 13 submissions: harshsikka123
    1. To all those struggling, some words of courage! (20 points, 18 comments)
    2. Just got locked out of my apartment, am submitting from a stairwell (19 points, 12 comments)
    3. Thoroughly enjoying the lectures, some of the best I've seen! (13 points, 13 comments)
    4. Just for reference, how long did Assignment 1 take you all to implement? (3 points, 31 comments)
    5. Grade_Learners Taking about 7 seconds on Buffet vs 5 on Local, is this acceptable if all tests are passing? (2 points, 2 comments)
    6. Is anyone running into the Runtime Error, Invalid DISPLAY variable when trying to save the figures as pdfs to the Buffet servers? (2 points, 9 comments)
    7. Still not seeing an ML4T onboarding test on ProctorTrack (2 points, 10 comments)
    8. Any news on when Optimize_Something grades will be released? (1 point, 1 comment)
    9. Baglearner RMSE and leaf size? (1 point, 2 comments)
    10. My results are oh so slightly off, any thoughts? (1 point, 11 comments)
  5. 63 points, 10 submissions: htrajan
    1. Sample test case: missing data (22 points, 36 comments)
    2. Optimize_something test cases (13 points, 22 comments)
    3. Met Burt Malkiel today (6 points, 1 comment)
    4. Heads up: Dataframe.std != np.std (5 points, 5 comments)
    5. optimize_something: graph (5 points, 29 comments)
    6. Schedule still reflecting shortened summer timeframe? (4 points, 3 comments)
    7. Quick clarification about InsaneLearner (3 points, 8 comments)
    8. Test cases using rfr? (3 points, 5 comments)
    9. Input format of rfr (2 points, 1 comment)
    10. [Shameless recruiting post] Wealthfront is hiring! (0 points, 9 comments)
  6. 62 points, 7 submissions: swamijay
    1. defeat_learner test case (34 points, 38 comments)
    2. Project 3 test cases (15 points, 27 comments)
    3. Defeat_Learner - related questions (6 points, 9 comments)
    4. Options risk/reward (2 points, 0 comments)
    5. manual strategy - you must remain in the position for 21 trading days. (2 points, 9 comments)
    6. standardizing values (2 points, 0 comments)
    7. technical indicators - period for moving averages, or anything that looks past n days (1 point, 3 comments)
  7. 61 points, 9 submissions: gatech-raleighite
    1. Protip: Better reddit search (22 points, 9 comments)
    2. Helpful numpy array cheat sheet (16 points, 10 comments)
    3. In your experience Professor, Mr. Byrd, which strategy is "best" for trading ? (12 points, 10 comments)
    4. Industrial strength or mature versions of the assignments ? (4 points, 2 comments)
    5. What is the correct (faster) way of doing this bit of pandas code (updating multiple slice values) (2 points, 10 comments)
    6. What is the correct (pythonesque?) way to select 60% of rows ? (2 points, 11 comments)
    7. How to get adjusted close price for funds not publicly traded (TSP) ? (1 point, 2 comments)
    8. Is there a way to only test one or 2 of the learners using grade_learners.py ? (1 point, 10 comments)
    9. OMS CS Digital Career Seminar Series - Scott Leitstein recording available online? (1 point, 4 comments)
  8. 60 points, 2 submissions: reyallan
    1. [Project Questions] Unit Tests for assess_portfolio assignment (58 points, 52 comments)
    2. Financial data, technical indicators and live trading (2 points, 8 comments)
  9. 59 points, 12 submissions: dyllll
    1. Please upvote helpful posts and other advice. (26 points, 1 comment)
    2. Books to further study in trading with machine learning? (14 points, 9 comments)
    3. Is Q-Learning the best reinforcement learning method for stock trading? (4 points, 4 comments)
    4. Any way to download the lessons? (3 points, 4 comments)
    5. Can a TA please contact me? (2 points, 7 comments)
    6. Is the vectorization code from the youtube video available to us? (2 points, 2 comments)
    7. Position of webcam (2 points, 15 comments)
    8. Question about assignment one (2 points, 5 comments)
    9. Are udacity quizzes recorded? (1 point, 2 comments)
    10. Does normalization of indicators matter in a Q-Learner? (1 point, 7 comments)
  10. 56 points, 2 submissions: jan-laszlo
    1. Proper git workflow (43 points, 19 comments)
    2. Adding you SSH key for password-less access to remote hosts (13 points, 7 comments)
  11. 53 points, 1 submission: agifft3_omscs
    1. [Project Questions] Unit Tests for optimize_something assignment (53 points, 94 comments)
  12. 50 points, 16 submissions: BNielson
    1. Regression Trees (7 points, 9 comments)
    2. Two Interpretations of RFR are leading to two different possible Sharpe Ratios -- Need Instructor clarification ASAP (5 points, 3 comments)
    3. PYTHONPATH=../:. python grade_analysis.py (4 points, 7 comments)
    4. Running on Windows and PyCharm (4 points, 4 comments)
    5. Studying for the midterm: python questions (4 points, 0 comments)
    6. Assess Learners Grader (3 points, 2 comments)
    7. Manual Strategy Grade (3 points, 2 comments)
    8. Rewards in Q Learning (3 points, 3 comments)
    9. SSH/Putty on Windows (3 points, 4 comments)
    10. Slight contradiction on ProctorTrack Exam (3 points, 4 comments)
  13. 49 points, 7 submissions: j0shj0nes
    1. QLearning Robot - Finalized and Released Soon? (18 points, 4 comments)
    2. Flash Boys, HFT, frontrunning... (10 points, 3 comments)
    3. Deprecations / errata (7 points, 5 comments)
    4. Udacity lectures via GT account, versus personal account (6 points, 2 comments)
    5. Python: console-driven development (5 points, 5 comments)
    6. Buffet pandas / numpy versions (2 points, 2 comments)
    7. Quant research on earnings calls (1 point, 0 comments)
  14. 45 points, 11 submissions: Zapurza
    1. Suggestion for Strategy learner mega thread. (14 points, 1 comment)
    2. Which lectures to watch for upcoming project q learning robot? (7 points, 5 comments)
    3. In schedule file, there is no link against 'voting ensemble strategy'? Scheduled for Nov 13-20 week (6 points, 3 comments)
    4. How to add questions to the question bank? I can see there is 2% credit for that. (4 points, 5 comments)
    5. Scratch paper use (3 points, 6 comments)
    6. The big short movie link on you tube says the video is not available in your country. (3 points, 9 comments)
    7. Distance between training data date and future forecast date (2 points, 2 comments)
    8. News affecting stock market and machine learning algorithms (2 points, 4 comments)
    9. pandas import in pydev (2 points, 0 comments)
    10. Assess learner server error (1 point, 2 comments)
  15. 43 points, 23 submissions: chvbs2000
    1. Is the Strategy Learner finalized? (10 points, 3 comments)
    2. Test extra 15 test cases for marketsim (3 points, 12 comments)
    3. Confusion between the term computing "back-in time" and "going forward" (2 points, 1 comment)
    4. How to define "each transaction"? (2 points, 4 comments)
    5. How to filling the assignment into Jupyter Notebook? (2 points, 4 comments)
    6. IOError: File ../data/SPY.csv does not exist (2 points, 4 comments)
    7. Issue in Access to machines at Georgia Tech via MacOS terminal (2 points, 5 comments)
    8. Reading data from Jupyter Notebook (2 points, 3 comments)
    9. benchmark vs manual strategy vs best possible strategy (2 points, 2 comments)
    10. global name 'pd' is not defined (2 points, 4 comments)
  16. 43 points, 15 submissions: shuang379
    1. How to test my code on buffet machine? (10 points, 15 comments)
    2. Can we get the ppt for "Decision Trees"? (8 points, 2 comments)
    3. python question pool question (5 points, 6 comments)
    4. set up problems (3 points, 4 comments)
    5. Do I need another camera for scanning? (2 points, 9 comments)
    6. Is chapter 9 covered by the midterm? (2 points, 2 comments)
    7. Why grade_analysis.py could run even if I rm analysis.py? (2 points, 5 comments)
    8. python question pool No.48 (2 points, 6 comments)
    9. where could we find old versions of the rest projects? (2 points, 2 comments)
    10. where to put ml4t-libraries to install those libraries? (2 points, 1 comment)
  17. 42 points, 14 submissions: larrva
    1. is there a mistake in How-to-learn-a-decision-tree.pdf (7 points, 7 comments)
    2. maximum recursion depth problem (6 points, 10 comments)
    3. [Urgent]Unable to use proctortrack in China (4 points, 21 comments)
    4. manual_strategynumber of indicators to use (3 points, 10 comments)
    5. Assignment 2: Got 63 points. (3 points, 3 comments)
    6. Software installation workshop (3 points, 7 comments)
    7. question regarding functools32 version (3 points, 3 comments)
    8. workshop on Aug 31 (3 points, 8 comments)
    9. Mount remote server to local machine (2 points, 2 comments)
    10. any suggestion on objective function (2 points, 3 comments)
  18. 41 points, 8 submissions: Ran__Ran
    1. Any resource will be available for final exam? (19 points, 6 comments)
    2. Need clarification on size of X, Y in defeat_learners (7 points, 10 comments)
    3. Get the same date format as in example chart (4 points, 3 comments)
    4. Cannot log in GitHub Desktop using GT account? (3 points, 3 comments)
    5. Do we have notes or ppt for Time Series Data? (3 points, 5 comments)
    6. Can we know the commission & market impact for short example? (2 points, 7 comments)
    7. Course schedule export issue (2 points, 15 comments)
    8. Buying/seeking beta v.s. buying/seeking alpha (1 point, 6 comments)
  19. 38 points, 4 submissions: ProudRamblinWreck
    1. Exam 2 Study topics (21 points, 5 comments)
    2. Reddit participation as part of grade? (13 points, 32 comments)
    3. Will birds chirping in the background flag me on Proctortrack? (3 points, 5 comments)
    4. Midterm Study Guide question pools (1 point, 2 comments)
  20. 37 points, 6 submissions: gatechben
    1. Submission page for strategy learner? (14 points, 10 comments)
    2. PSA: The grading script for strategy_learner changed on the 26th (10 points, 9 comments)
    3. Where is util.py supposed to be located? (8 points, 8 comments)
    4. PSA:. The default dates in the assignment 1 template are not the same as the examples on the assignment page. (2 points, 1 comment)
    5. Schedule: Discussion of upcoming trading projects? (2 points, 3 comments)
    6. [defeat_learners] More than one column for X? (1 point, 1 comment)
  21. 37 points, 3 submissions: jgeiger
    1. Please send/announce when changes are made to the project code (23 points, 7 comments)
    2. The Big Short on Netflix for OMSCS students (week of 10/16) (11 points, 6 comments)
    3. Typo(?) for Assess_portfolio wiki page (3 points, 2 comments)
  22. 35 points, 10 submissions: ltian35
    1. selecting row using .ix (8 points, 9 comments)
    2. Will the following 2 topics be included in the final exam(online student)? (7 points, 4 comments)
    3. udacity quiz (7 points, 4 comments)
    4. pdf of lecture (3 points, 4 comments)
    5. print friendly version of the course schedule (3 points, 9 comments)
    6. about learner regression vs classificaiton (2 points, 2 comments)
    7. is there a simple way to verify the correctness of our decision tree (2 points, 4 comments)
    8. about Building an ML-based forex strategy (1 point, 2 comments)
    9. about technical analysis (1 point, 6 comments)
    10. final exam online time period (1 point, 2 comments)
  23. 33 points, 2 submissions: bhrolenok
    1. Assess learners template and grading script is now available in the public repository (24 points, 0 comments)
    2. Tutorial for software setup on Windows (9 points, 35 comments)
  24. 31 points, 4 submissions: johannes_92
    1. Deadline extension? (26 points, 40 comments)
    2. Pandas date indexing issues (2 points, 5 comments)
    3. Why do we subtract 1 from SMA calculation? (2 points, 3 comments)
    4. Unexpected number of calls to query, sum=20 (should be 20), max=20 (should be 1), min=20 (should be 1) -bash: syntax error near unexpected token `(' (1 point, 3 comments)
  25. 30 points, 5 submissions: log_base_pi
    1. The Massive Hedge Fund Betting on AI [Article] (9 points, 1 comment)
    2. Useful Python tips and tricks (8 points, 10 comments)
    3. Video of overview of remaining projects with Tucker Balch (7 points, 1 comment)
    4. Will any material from the lecture by Goldman Sachs be covered on the exam? (5 points, 1 comment)
    5. What will the 2nd half of the course be like? (1 point, 8 comments)
  26. 30 points, 4 submissions: acschwabe
    1. Assignment and Exam Calendar (ICS File) (17 points, 6 comments)
    2. Please OMG give us any options for extra credit (8 points, 12 comments)
    3. Strategy learner question (3 points, 1 comment)
    4. Proctortrack: Do we need to schedule our test time? (2 points, 10 comments)
  27. 29 points, 9 submissions: _ant0n_
    1. Next assignment? (9 points, 6 comments)
    2. Proctortrack Onboarding test? (6 points, 11 comments)
    3. Manual strategy: Allowable positions (3 points, 7 comments)
    4. Anyone watched Black Scholes documentary? (2 points, 16 comments)
    5. Buffet machines hardware (2 points, 6 comments)
    6. Defeat learners: clarification (2 points, 4 comments)
    7. Is 'optimize_something' on the way to class GitHub repo? (2 points, 6 comments)
    8. assess_portfolio(... gen_plot=True) (2 points, 8 comments)
    9. remote job != remote + international? (1 point, 15 comments)
  28. 26 points, 10 submissions: umersaalis
    1. comments.txt (7 points, 6 comments)
    2. Assignment 2: report.pdf (6 points, 30 comments)
    3. Assignment 2: report.pdf sharing & plagiarism (3 points, 12 comments)
    4. Max Recursion Limit (3 points, 10 comments)
    5. Parametric vs Non-Parametric Model (3 points, 13 comments)
    6. Bag Learner Training (1 point, 2 comments)
    7. Decision Tree Issue: (1 point, 2 comments)
    8. Error in Running DTLearner and RTLearner (1 point, 12 comments)
    9. My Results for the four learners. Please check if you guys are getting values somewhat near to these. Exact match may not be there due to randomization. (1 point, 4 comments)
    10. Can we add the assignments and solutions to our public github profile? (0 points, 7 comments)
  29. 26 points, 6 submissions: abiele
    1. Recommended Reading? (13 points, 1 comment)
    2. Number of Indicators Used by Actual Trading Systems (7 points, 6 comments)
    3. Software Install Instructions From TA's Video Not Working (2 points, 2 comments)
    4. Suggest that TA/Instructor Contact Info Should be Added to the Syllabus (2 points, 2 comments)
    5. ML4T Software Setup (1 point, 3 comments)
    6. Where can I find the grading folder? (1 point, 4 comments)
  30. 26 points, 6 submissions: tomatonight
    1. Do we have all the information needed to finish the last project Strategy learner? (15 points, 3 comments)
    2. Does anyone interested in cryptocurrency trading/investing/others? (3 points, 6 comments)
    3. length of portfolio daily return (3 points, 2 comments)
    4. Did Michael Burry, Jamie&Charlie enter the short position too early? (2 points, 4 comments)
    5. where to check participation score (2 points, 1 comment)
    6. Where to collect the midterm exam? (forgot to take it last week) (1 point, 3 comments)
  31. 26 points, 3 submissions: hilo260
    1. Is there a template for optimize_something on GitHub? (14 points, 3 comments)
    2. Marketism project? (8 points, 6 comments)
    3. "Do not change the API" (4 points, 7 comments)
  32. 26 points, 3 submissions: niufen
    1. Windows Server Setup Guide (23 points, 16 comments)
    2. Strategy Learner Adding UserID as Comment (2 points, 2 comments)
    3. Connect to server via Python Error (1 point, 6 comments)
  33. 26 points, 3 submissions: whoyoung99
    1. How much time you spend on Assess Learner? (13 points, 47 comments)
    2. Git clone repository without fork (8 points, 2 comments)
    3. Just for fun (5 points, 1 comment)
  34. 25 points, 8 submissions: SharjeelHanif
    1. When can we discuss defeat learners methods? (10 points, 1 comment)
    2. Are the buffet servers really down? (3 points, 2 comments)
    3. Are the midterm results in proctortrack gone? (3 points, 3 comments)
    4. Will these finance topics be covered on the final? (3 points, 9 comments)
    5. Anyone get set up with Proctortrack? (2 points, 10 comments)
    6. Incentives Quiz Discussion (2-01, Lesson 11.8) (2 points, 3 comments)
    7. Anyone from Houston, TX (1 point, 1 comment)
    8. How can I trace my error back to a line of code? (assess learners) (1 point, 3 comments)
  35. 25 points, 5 submissions: jlamberts3
    1. Conda vs VirtualEnv (7 points, 8 comments)
    2. Cool Portfolio Backtesting Tool (6 points, 6 comments)
    3. Warren Buffett wins $1M bet made a decade ago that the S&P 500 stock index would outperform hedge funds (6 points, 12 comments)
    4. Windows Ubuntu Subsystem Putty Alternative (4 points, 0 comments)
    5. Algorithmic Trading Of Digital Assets (2 points, 0 comments)
  36. 25 points, 4 submissions: suman_paul
    1. Grade statistics (9 points, 3 comments)
    2. Machine Learning book by Mitchell (6 points, 11 comments)
    3. Thank You (6 points, 6 comments)
    4. Assignment1 ready to be cloned? (4 points, 4 comments)
  37. 25 points, 3 submissions: Spareo
    1. Submit Assignments Function (OS X/Linux) (15 points, 6 comments)
    2. Quantsoftware Site down? (8 points, 38 comments)
    3. ML4T_2017Spring folder on Buffet server?? (2 points, 5 comments)
  38. 24 points, 14 submissions: nelsongcg
    1. Is it realistic for us to try to build our own trading bot and profit? (6 points, 21 comments)
    2. Is the risk free rate zero for any country? (3 points, 7 comments)
    3. Models and black swans - discussion (3 points, 0 comments)
    4. Normal distribution assumption for options pricing (2 points, 3 comments)
    5. Technical analysis for cryptocurrency market? (2 points, 4 comments)
    6. A counter argument to models by Nassim Taleb (1 point, 0 comments)
    7. Are we demandas to use the sample for part 1? (1 point, 1 comment)
    8. Benchmark for "trusting" your trading algorithm (1 point, 5 comments)
    9. Don't these two statements on the project description contradict each other? (1 point, 2 comments)
    10. Forgot my TA (1 point, 6 comments)
  39. 24 points, 11 submissions: nurobezede
    1. Best way to obtain survivor bias free stock data (8 points, 1 comment)
    2. Please confirm Midterm is from October 13-16 online with proctortrack. (5 points, 2 comments)
    3. Are these DTlearner Corr values good? (2 points, 6 comments)
    4. Testing gen_data.py (2 points, 3 comments)
    5. BagLearner of Baglearners says 'Object is not callable' (1 point, 8 comments)
    6. DTlearner training RMSE none zero but almost there (1 point, 2 comments)
    7. How to submit analysis using git and confirm it? (1 point, 2 comments)
    8. Passing kwargs to learners in a BagLearner (1 point, 5 comments)
    9. Sampling for bagging tree (1 point, 8 comments)
    10. code failing the 18th test with grade_learners.py (1 point, 6 comments)
  40. 24 points, 4 submissions: AeroZach
    1. questions about how to build a machine learning system that's going to work well in a real market (12 points, 6 comments)
    2. Survivor Bias Free Data (7 points, 5 comments)
    3. Genetic Algorithms for Feature selection (3 points, 5 comments)
    4. How far back can you train? (2 points, 2 comments)
  41. 23 points, 9 submissions: vsrinath6
    1. Participation check #3 - Haven't seen it yet (5 points, 5 comments)
    2. What are the tasks for this week? (5 points, 12 comments)
    3. No projects until after the mid-term? (4 points, 5 comments)
    4. Format / Syllabus for the exams (2 points, 3 comments)
    5. Has there been a Participation check #4? (2 points, 8 comments)
    6. Project 3 not visible on T-Square (2 points, 3 comments)
    7. Assess learners - do we need to check is method implemented for BagLearner? (1 point, 4 comments)
    8. Correct number of days reported in the dataframe (should be the number of trading days between the start date and end date, inclusive). (1 point, 0 comments)
    9. RuntimeError: Invalid DISPLAY variable (1 point, 2 comments)
  42. 23 points, 8 submissions: nick_algorithm
    1. Help with getting Average Daily Return Right (6 points, 7 comments)
    2. Hint for args argument in scipy minimize (5 points, 2 comments)
    3. How do you make money off of highly volatile (high SDDR) stocks? (4 points, 5 comments)
    4. Can We Use Code Obtained from Class To Make Money without Fear of Being Sued (3 points, 6 comments)
    5. Is the Std for Bollinger Bands calculated over the same timespan of the Moving Average? (2 points, 2 comments)
    6. Can't run grade_learners.py but I'm not doing anything different from the last assignment (?) (1 point, 5 comments)
    7. How to determine value at terminal node of tree? (1 point, 1 comment)
    8. Is there a way to get Reddit announcements piped to email (or have a subsequent T-Square announcement published simultaneously) (1 point, 2 comments)
  43. 23 points, 1 submission: gong6
    1. Is manual strategy ready? (23 points, 6 comments)
  44. 21 points, 6 submissions: amchang87
    1. Reason for public reddit? (6 points, 4 comments)
    2. Manual Strategy - 21 day holding Period (4 points, 12 comments)
    3. Sharpe Ratio (4 points, 6 comments)
    4. Manual Strategy - No Position? (3 points, 3 comments)
    5. ML / Manual Trader Performance (2 points, 0 comments)
    6. T-Square Submission Missing? (2 points, 3 comments)
  45. 21 points, 6 submissions: fall2017_ml4t_cs_god
    1. PSA: When typing in code, please use 'formatting help' to see how to make the code read cleaner. (8 points, 2 comments)
    2. Why do Bollinger Bands use 2 standard deviations? (5 points, 20 comments)
    3. How do I log into the [email protected]? (3 points, 1 comment)
    4. Is midterm 2 cumulative? (2 points, 3 comments)
    5. Where can we learn about options? (2 points, 2 comments)
    6. How do you calculate the analysis statistics for bps and manual strategy? (1 point, 1 comment)
  46. 21 points, 5 submissions: Jmitchell83
    1. Manual Strategy Grades (12 points, 9 comments)
    2. two-factor (3 points, 6 comments)
    3. Free to use volume? (2 points, 1 comment)
    4. Is MC1-Project-1 different than assess_portfolio? (2 points, 2 comments)
    5. Online Participation Checks (2 points, 4 comments)
  47. 21 points, 5 submissions: Sergei_B
    1. Do we need to worry about missing data for Asset Portfolio? (14 points, 13 comments)
    2. How do you get data from yahoo in panda? the sample old code is below: (2 points, 3 comments)
    3. How to fix import pandas as pd ImportError: No module named pandas? (2 points, 4 comments)
    4. Python Practice exam Question 48 (2 points, 2 comments)
    5. Mac: "virtualenv : command not found" (1 point, 2 comments)
  48. 21 points, 3 submissions: mharrow3
    1. First time reddit user .. (17 points, 37 comments)
    2. Course errors/types (2 points, 2 comments)
    3. Install course software on macOS using Vagrant .. (2 points, 0 comments)
  49. 20 points, 9 submissions: iceguyvn
    1. Manual strategy implementation for future projects (4 points, 15 comments)
    2. Help with correlation calculation (3 points, 15 comments)
    3. Help! maximum recursion depth exceeded (3 points, 10 comments)
    4. Help: how to index by date? (2 points, 4 comments)
    5. How to attach a 1D array to a 2D array? (2 points, 2 comments)
    6. How to set a single cell in a 2D DataFrame? (2 points, 4 comments)
    7. Next assignment after marketsim? (2 points, 4 comments)
    8. Pythonic way to detect the first row? (1 point, 6 comments)
    9. Questions regarding seed (1 point, 1 comment)
  50. 20 points, 3 submissions: JetsonDavis
    1. Push back assignment 3? (10 points, 14 comments)
    2. Final project (9 points, 3 comments)
    3. Numpy versions (1 point, 2 comments)
  51. 20 points, 2 submissions: pharmerino
    1. assess_portfolio test cases (16 points, 88 comments)
    2. ML4T Assignments (4 points, 6 comments)

Top Commenters

  1. tuckerbalch (2296 points, 1185 comments)
  2. davebyrd (1033 points, 466 comments)
  3. yokh_cs7646 (320 points, 177 comments)
  4. rgraziano3 (266 points, 147 comments)
  5. j0shj0nes (264 points, 148 comments)
  6. i__want__piazza (236 points, 127 comments)
  7. swamijay (227 points, 116 comments)
  8. _ant0n_ (205 points, 149 comments)
  9. ml4tstudent (204 points, 117 comments)
  10. gatechben (179 points, 107 comments)
  11. BNielson (176 points, 108 comments)
  12. jameschanx (176 points, 94 comments)
  13. Artmageddon (167 points, 83 comments)
  14. htrajan (162 points, 81 comments)
  15. boyko11 (154 points, 99 comments)
  16. alyssa_p_hacker (146 points, 80 comments)
  17. log_base_pi (141 points, 80 comments)
  18. Ran__Ran (139 points, 99 comments)
  19. johnsmarion (136 points, 86 comments)
  20. jgorman30_gatech (135 points, 102 comments)
  21. dyllll (125 points, 91 comments)
  22. MikeLachmayr (123 points, 95 comments)
  23. awhoof (113 points, 72 comments)
  24. SharjeelHanif (106 points, 59 comments)
  25. larrva (101 points, 69 comments)
  26. augustinius (100 points, 52 comments)
  27. oimesbcs (99 points, 67 comments)
  28. vansh21k (98 points, 62 comments)
  29. W1redgh0st (97 points, 70 comments)
  30. ybai67 (96 points, 41 comments)
  31. JuanCarlosKuriPinto (95 points, 54 comments)
  32. acschwabe (93 points, 58 comments)
  33. pharmerino (92 points, 47 comments)
  34. jgeiger (91 points, 28 comments)
  35. Zapurza (88 points, 70 comments)
  36. jyoms (87 points, 55 comments)
  37. omscs_zenan (87 points, 44 comments)
  38. nurobezede (85 points, 64 comments)
  39. BelaZhu (83 points, 50 comments)
  40. jason_gt (82 points, 36 comments)
  41. shuang379 (81 points, 64 comments)
  42. ggatech (81 points, 51 comments)
  43. nitinkodial_gatech (78 points, 59 comments)
  44. harshsikka123 (77 points, 55 comments)
  45. bkeenan7 (76 points, 49 comments)
  46. moxyll (76 points, 32 comments)
  47. nelsongcg (75 points, 53 comments)
  48. nickzelei (75 points, 41 comments)
  49. hunter2omscs (74 points, 29 comments)
  50. pointblank41 (73 points, 36 comments)
  51. zheweisun (66 points, 48 comments)
  52. bs_123 (66 points, 36 comments)
  53. storytimeuva (66 points, 36 comments)
  54. sva6 (66 points, 31 comments)
  55. bhrolenok (66 points, 27 comments)
  56. lingkaizuo (63 points, 46 comments)
  57. Marvel_this (62 points, 36 comments)
  58. agifft3_omscs (62 points, 35 comments)
  59. ssung40 (61 points, 47 comments)
  60. amchang87 (61 points, 32 comments)
  61. joshuak_gatech (61 points, 30 comments)
  62. fall2017_ml4t_cs_god (60 points, 50 comments)
  63. ccrouch8 (60 points, 45 comments)
  64. nick_algorithm (60 points, 29 comments)
  65. JetsonDavis (59 points, 35 comments)
  66. yjacket103 (58 points, 36 comments)
  67. hilo260 (58 points, 29 comments)
  68. coolwhip1234 (58 points, 15 comments)
  69. chvbs2000 (57 points, 49 comments)
  70. suman_paul (57 points, 29 comments)
  71. masterm (57 points, 23 comments)
  72. RolfKwakkelaar (55 points, 32 comments)
  73. rpb3 (55 points, 23 comments)
  74. venkatesh8 (54 points, 30 comments)
  75. omscs_avik (53 points, 37 comments)
  76. bman8810 (52 points, 31 comments)
  77. snladak (51 points, 31 comments)
  78. dfihn3 (50 points, 43 comments)
  79. mlcrypto (50 points, 32 comments)
  80. omscs-student (49 points, 26 comments)
  81. NellVega (48 points, 32 comments)
  82. booglespace (48 points, 23 comments)
  83. ccortner3 (48 points, 23 comments)
  84. caa5042 (47 points, 34 comments)
  85. gcalma3 (47 points, 25 comments)
  86. krushnatmore (44 points, 32 comments)
  87. sn_48 (43 points, 22 comments)
  88. thenewprofessional (43 points, 16 comments)
  89. urider (42 points, 33 comments)
  90. gatech-raleighite (42 points, 30 comments)
  91. chrisong2017 (41 points, 26 comments)
  92. ProudRamblinWreck (41 points, 24 comments)
  93. kramey8 (41 points, 24 comments)
  94. coderafk (40 points, 28 comments)
  95. niufen (40 points, 23 comments)
  96. tholladay3 (40 points, 23 comments)
  97. SaberCrunch (40 points, 22 comments)
  98. gnr11 (40 points, 21 comments)
  99. nadav3 (40 points, 18 comments)
  100. gt7431a (40 points, 16 comments)

Top Submissions

  1. [Project Questions] Unit Tests for assess_portfolio assignment by reyallan (58 points, 52 comments)
  2. [Project Questions] Unit Tests for optimize_something assignment by agifft3_omscs (53 points, 94 comments)
  3. Proper git workflow by jan-laszlo (43 points, 19 comments)
  4. Exam 2 Information by yokh_cs7646 (39 points, 40 comments)
  5. A little more on Pandas indexing/slicing ([] vs ix vs iloc vs loc) and numpy shapes by davebyrd (37 points, 10 comments)
  6. Project 1 Megathread (assess_portfolio) by davebyrd (34 points, 466 comments)
  7. defeat_learner test case by swamijay (34 points, 38 comments)
  8. Project 2 Megathread (optimize_something) by tuckerbalch (33 points, 475 comments)
  9. project 3 megathread (assess_learners) by tuckerbalch (27 points, 1130 comments)
  10. Deadline extension? by johannes_92 (26 points, 40 comments)

Top Comments

  1. 34 points: jgeiger's comment in QLearning Robot project megathread
  2. 31 points: coolwhip1234's comment in QLearning Robot project megathread
  3. 30 points: tuckerbalch's comment in Why Professor is usually late for class?
  4. 23 points: davebyrd's comment in Deadline extension?
  5. 20 points: jason_gt's comment in What would be a good quiz question regarding The Big Short?
  6. 19 points: yokh_cs7646's comment in For online students: Participation check #2
  7. 17 points: i__want__piazza's comment in project 3 megathread (assess_learners)
  8. 17 points: nathakhanh2's comment in Project 2 Megathread (optimize_something)
  9. 17 points: pharmerino's comment in Midterm study Megathread
  10. 17 points: tuckerbalch's comment in Midterm grades posted to T-Square
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The Fastest Way to Calculate Risk Reward on a Forex Trade ... The Hidden Metatrader Risk Reward Ratio Calculator ... Stock Trading: Reward/Risk Spreadsheet Calculator - YouTube How to Trade Forex Risk Reward Trade Calculator How to Calculate Risk & Reward in Day Trading MetaTrader Forex Risk Reward Ratio Indcator ver. 4.00 ... Forex Basics - Lot Sizes, Risk vs. Reward, Counting Pips ...

How to Calculate Risk Reward Ratio in Forex. by Fxigor. Share Tweet. The Complete Guide to Risk Reward Ratio. The risk-reward ratio is noted as conducting measures concerning the level of the reward that you could potentially achieve when you conduct a trade-in correlation to each dollar that you are willing to put up to risk. Take into consideration, for example, that if the risk-reward ratio ... I'll udpate this calculator to cover the fees soon. Calculate Your Risk Reward Ratio If you like my content, subscribe to my blog, share this post to Social Media Networks, and follow my Facebook and Twitter Page. The risk and reward calculator will help you to calculate the position's best targets and their respective reward-to-risk ratios based on the Fibonacci retracements from the local peak and bottom. It's a powerful tool to determine the potential risks before entering any positions. Reward:Risk Ratio Calculator. In the fields below, enter the parameters for your trade and you will get the reward:risk ratio and other related metrics. To fully understand the power of the Reward:Risk Ratio, read our post here: Reward:Risk Ratio Guide Below is the risk-reward calculator: The risk-reward ratio or risk-return ratio in trading represents the expected return and risk of a given trade or trades based on entry position and close position. A good risk-reward ratio tends to be less than 1, that is, the return (reward) is greater than the risk. How to Calculate Risk to Reward Ratio in Forex trading using risk calculator? In this area, we will jump into the mechanics of how to calculate the risk-reward proportion. The equation for computing risk versus reward proportion is generally direct. If you risk 50 pips on a trade and you set a profit focus of 100 pips, at that point your powerful risk to remunerate proportion for the trade ... Manually calculating risk to reward ratio could seem like a tedious process at times. You can use a simple calculator to find the effective risk to reward ratio of your trades, or you can use several tools to simplify the process, including a Microsoft Excel sheet or an online FX risk reward calculator. The risk/reward ratio is used by many forex traders to assess the expected return and the risk of a trade. For example, if a trader buys EUR/USD at 1.3500 and places his stop-loss order at 1.3450 and his take profit at 1.3650, he's risking 50 pips for a potential profit of 150 pips. The risk/reward ratio is therefore 150/50 = 3. A risk reward ratio of 3:1 statistically provides a trader with a ... When you are starting to get into Forex there are some a couple areas you need to pay big attention to one is risk management and the other is risk to reward ratio which also falls under risk management. If you are making trades and winning 9 out of 10 this isn’t as much of a problem. You can profit greatly and only win 6 out of 10 trades however with good risk to reward ratio.

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The Fastest Way to Calculate Risk Reward on a Forex Trade ...

Get the charts: http://www.tradingheroes.com/tradingview Calculating the risk reward on a trade can take some time. If you are tired of taking out your calcu... This video will explain in detail THE SIMPLE WAY to convert Lot Sizes, how Risk vs. Reward works, and also how to count Pips. These are the fundamentals of t... Reward Risk Ratio & Position Sizing Calculator - Duration: 6:43. ... The Fastest Way to Calculate Risk Reward on a Forex Trade - TradingView Tutorial - Duration: 1:37. Trading Heroes 33,678 views ... Quick explanation of my risk/reward spreadsheet. Click this link to download for free: https://drive.google.com/open?id=0BzJh5rMoj57MMjdINVNXaUdaSXc Risk Reward Ratio is one of the basic elements of money management, but many people don't know how to use it properly. Not talking about risk reward ratio tool ... Did you know that there is a hidden risk reward ratio calculator in Metatrader? This video will show you how to use and existing feature in Metatrader to eas... How to calculate risk/reward for beginners ... Forex Basics - Lot Sizes, Risk vs. Reward, Counting Pips - Duration: 36:25. Kingdom Kash 468,752 views. 36:25. How I learned To Find Hot Stocks All ...

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