Forex Exchange Calculator – Currency Exchange Rates

Portfolio Tracker + Rebalance Spreadsheet

Hello there!
v1.8a Modifications: - Fixed: Not every label showing in the "Portfolio". - Modified: Portfolio "% Gain" Graphic now showing values. - 52 W. Low / High Graphic in "Watchlist" replaced by Beta Graphic. - Minor tables corrections.
v1.8 Modifications: - Reported: Major bug fixed when changing regional and currency settings. - Formula fixed when calculating dividends income. - Several elements locked to avoid dragging on mobile devices. - Watchlist "1y Target" columns modified to make sorting possible. - Watchlist % Growth negative values fixed. - Minor tables fix.
v1.7b Modifications: - Fixed formula error in the Watchlist sheet. - Modified tables when scrolling for mobile devices / smaller screens.
v1.7a Modifications: - Fixed cell error in the Dividend sheet. - Replaced Dividend's graphic by 2D Donut instead of 2D Bar.
v1.7 Modifications: - Working as originally intended: * Just one file for any single country/currency. * Base file provided in Numbers never supported multicurrency independently of the formulas. * Will use as a base the ticker's original currency on which this one is traded. * Depending on the country you live in, the spreadsheet will calculate the proper "Cost Basis", "Market Value" and "Gain". * Support for all major countries and currencies. * The previous setting is based on the device's "Language & Region" configuration. Can be overridden, instructions in the "Documentation" sheet.
v1.6 Modifications: - Added % Growth in the Portfolio sheet graphic. - Implemented Dividend income calculation per year in a new sheet. - Added some conditional colouring in the "Rebalance" sheet if "Desired %" is not 0% or 100%. - Some bugs fixes and table corrections.
v1.5 Modifications: * Added Multicurrency support and fixed several bugs in the Portfolio page: - "Market Value" and "Cost Basis" per Ticker will be added as in the ticker currency (Do not add a currency format to the cells!) - Total "Market Value" and Total "Cost Basis" will be calculated in the currency you do transactions (Either U.S. or CAD) - Total ticker's gains and the "Gain" total will be displayed in the currency you do transactions (Either U.S. or CAD)
If you find any error or problems and/or you need support for any other currency let me know.
submitted by priamXus to investing [link] [comments]

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submitted by GiuliettaShop to Popify [link] [comments]

How to optimise the speed of my Pandas code?

Hi learnpython,
My first attempt at writing my own project. Prior to this I had never used classes or Pandas so it's been a difficult learning curve. I was hoping to get some feedback on the overall structure - does everything look sensible? Are there better ways of writing some bits?
I also wanted to specifically check how I can increase the execution speed. I currently iterate rows which Pandas did say will be slow, but I couldn't see a workaround. The fact it is quite slow makes me think there is a better solution that I'm missing.
To run the code yourself download a .csv of Forex data and store in same folder as script - I used Yahoo finance GBP USD.
"""This program simulates a Double SMA (single moving average) trading strategy. The user provides a .csv file containing trade history and two different window sizes for simple moving averages (smallest number first). The .csv must contain date and close columns - trialled on Yahoo FX data). The program will generate a 'buy' signal when the short SMA is greater than the long SMA, and vice versa. The results of each trade are stored and can be output to a .csv file.""" import pandas as pd class DoubleSMA(): """Generates a Double SMA trading system.""" def __init__(self, name, sma_a, sma_b): """Don't know what goes here.""" self.name = name self.sma_a = sma_a self.sma_b = sma_b self.index = 0 self.order = 'Start' self.signal = '' def gen_sma(self, dataset, sma): """Calculates SMA and adds as column to dataset.""" col_title = 'sma' + str(sma) dataset[col_title] = dataset['Close'].rolling(sma).mean() return dataset def gen_signal(self, row, dataset): """Generates trade signal based on comparison of SMAs.""" if row[0] == (dataset.shape[0] - 1): #Reached final line of dataset; close current trade. self.order = 'Finish' elif row[3] > row[4]: self.signal = 'Buy' elif row[3] < row[4]: self.signal = 'Sell' def append_result(row, result, order): """Adds 'entry' details to results dataframe (i.e. opens trade).""" result = result.append({"Entry date": row[1], "Pair": "GBPUSD", "Order": order, "Entry price": row[2]}, ignore_index=True) return result def trade(row, order, signal, index, result): """Executes a buy or sell routine depending on signal. Flips between 'buy' and 'sell' on each trade.""" if order == 'Start': order = signal result = append_result(row, result, order) elif order == 'Finish': result.iloc[index, 1] = row[1] result.iloc[index, 5] = row[2] elif order != signal: #Close current trade result.iloc[index, 1] = row[1] result.iloc[index, 5] = row[2] index += 1 order = signal result = append_result(row, result, order) return order, index, result def result_df(): """Creates a dataframe to store the results of each trade.""" result = pd.DataFrame({"Entry date": [], "Exit date": [], "Pair": [], "Order": [], "Entry price": [], "Exit price": [], "P/L": []}) return result def dataset_df(): """Opens and cleans up the data to be analysed.""" dataset = pd.read_csv('GBPUSD 2003-2020 Yahoo.csv', usecols=['Date', 'Close']) dataset.dropna(inplace=True) dataset['Close'] = dataset['Close'].round(4) return dataset def store_result(result): """Outputs results table to .csv.""" result.to_csv('example.csv') def calc_pl(result): """Calculates the profil/loss of each row of result dataframe.""" pass #Complete later dataset = dataset_df() result = result_df() sma_2_3 = DoubleSMA('sma_2_3', 2, 3) dataset = sma_2_3.gen_sma(dataset, sma_2_3.sma_a) dataset = sma_2_3.gen_sma(dataset, sma_2_3.sma_b) dataset.dropna(inplace=True) dataset.reset_index(inplace=True, drop=True) for row in dataset.itertuples(): sma_2_3.gen_signal(row, dataset) sma_2_3.order, sma_2_3. index, result = trade(row, sma_2_3.order, sma_2_3.signal, sma_2_3.index, result) calc_pl(result) print(result) store_result(result) 
submitted by tbYuQfzB to learnpython [link] [comments]

[x-post] Calculating backtest bond profits from yields alone ???

Hello,
So I have been trading stocks, forex and commodities for a while using automated programs so I am in the domain, not a beginner.
I am just starting to get into bonds and I have one thing that I do not understand, wherever I find any bonds data (i.e. https://finance.yahoo.com/quote/%5ETYX?p=%5ETYX) it only lists yield.
If I wanted to simulate trading this bond, shouldn't I have the price also to be able to calculate P/L? I know that yield = coupon / price, but since I do not have coupon nor price data it seems to me like some information is missing. Can somebody explain me how to backtest bond trading with using yield data only?
submitted by hcoverl to algotrading [link] [comments]

Beginner question: Where do you get your stock data from?

I’ve been using web scraping but I have to use selenium as beautifulsoup won’t load dynamic elements/get all of the html. However, it would be very slow to have to load instances of yahoo finance for every stock I want to calculate, say, RSI for. Where do you guys get your data from for python and are there already libraries which can calculate values of indicators?
I’m coding in python and am totally self taught so I’ll do my best, but I’m essentially a novice. Unlike most people that I’ve seen, I have a passion for finance and already have a reasonable background on economics, fundamental, and technical analysis. Also, I only need stock data, I’m not worried about crypto or forex yet.
Thanks, noah8597
submitted by noah8597 to algotrading [link] [comments]

Calculating backtest bond profits from yields alone ???

Hello,
So I have been trading stocks, forex and commodities for a while using automated programs so I am in the domain, not a beginner.
I am just starting to get into bonds and I have one thing that I do not understand, wherever I find any bonds data (i.e. https://finance.yahoo.com/quote/%5ETYX?p=%5ETYX) it only lists yield.
If I wanted to simulate trading this bond, shouldn't I have the price also to be able to calculate P/L?
I know that yield = coupon / price, but since I do not have coupon nor price data it seems to me like some information is missing. Can somebody explain me how to backtest bond trading with using yield data only?
submitted by hcoverl to quant [link] [comments]

[x-post] Calculating backtest bond profits from yields alone ???

Hello,
So I have been trading stocks, forex and commodities for a while using automated programs so I am in the domain, not a beginner.
I am just starting to get into bonds and I have one thing that I do not understand, wherever I find any bonds data (i.e. https://finance.yahoo.com/quote/%5ETYX?p=%5ETYX) it only lists yield.
If I wanted to simulate trading this bond, shouldn't I have the price also to be able to calculate P/L? I know that yield = coupon / price, but since I do not have coupon nor price data it seems to me like some information is missing. Can somebody explain me how to backtest bond trading with using yield data only?
submitted by hcoverl to algorithmictrading [link] [comments]

[x-post] Calculating backtest bond profits from yields alone ???

Hello,
So I have been trading stocks, forex and commodities for a while using automated programs so I am in the domain, not a beginner.
I am just starting to get into bonds and I have one thing that I do not understand, wherever I find any bonds data (i.e. https://finance.yahoo.com/quote/%5ETYX?p=%5ETYX) it only lists yield.
If I wanted to simulate trading this bond, shouldn't I have the price also to be able to calculate P/L? I know that yield = coupon / price, but since I do not have coupon nor price data it seems to me like some information is missing. Can somebody explain me how to backtest bond trading with using yield data only?
submitted by hcoverl to quantfinance [link] [comments]

Mario speaks: Congress should listen up

Mario speaks: Congress should listen up submitted by AngelaMotorman to politics [link] [comments]

Big List of Financial News, Research, and Data Websites

Hello /investing, I was looking for a good resource list for financial news, research, and data on Google and Reddit, but didn't find many good lists. So I spent some time and compiled my own. I hope this is helpful for other people.
You can take a look at this list in two column format here.
I'm looking for useful websites that I have missed. If you have any suggestions, please leave them in the comments.
I list the domain authority of each website in parentheses which is a measure of the prestige of the website and quality of the information in a numerical range from 0 to 100.
Although I review a wide range of websites, I personally recommend the Financial Times, Bloomberg, Wall Street Journal, Business Insider, and Zero Hedge for news, and Quandl for data.

News

  1. Bloomberg (99)
  2. Reuters (96)
  3. Business Insider (95)
  4. MarketWatch (93)
  5. TheStreet (90)
  6. Zero Hedge (84)
  7. Seeking Alpha (83)
  8. Financial Post (82)
  9. Kiplinger (82)
  10. 24/7 Wall St (81)
  11. Benzinga (79)
  12. Institutional Investor (73)
  13. ValueWalk (70)
  14. Gurufocus (66)
  15. Institutional Investor’s Alpha (52)
  16. Market Folly (50)

Magazines

  1. Forbes (97)
  2. The Economist (95)
  3. Fortune (93)
  4. Time (92)
  5. Barron’s (85)
  6. The New Yorker (80)

Newspapers

  1. The Wall Street Journal (97)
  2. Financial Times (96)
  3. USA Today (88)
  4. BBC (87)
  5. The Global and Mail (87)
  6. The New York Times (80)
  7. The Guardian (80)
  8. Nikkei Asian Review (80)
  9. The Japan Times (70)

Networks

  1. CNN (95)
  2. CNBC (93)
  3. NBC (91)
  4. Fox Business (91)
  5. NPR (82)

Reddit

  1. /investing (73)
  2. /personalfinance (71)
  3. /business (65)
  4. /FinancialIndependence (64)
  5. /finance (62)
  6. /economics (59)
  7. /wallstreetbets (58)
  8. /stocks (55)
  9. /InvestmentClub (55)
  10. /economy (52)
  11. /options (51)
  12. /SecurityAnalysis (49)
  13. /Forex (49)
  14. /algotrading (49)
  15. /StockMarket (47)

Tools

  1. Yahoo! Finance (94)
  2. Google Finance (93)
  3. Investopedia (87)
  4. Morningstar (87)
  5. Investing.com (72)
  6. ETF.com (64)
  7. Finviz (60)
  8. Thinknum (38)
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submitted by cokechan to investing [link] [comments]

Cryptocurrency markets challenges and solutions

This has been bugging me for a while so thank you for endulging my rambling. TL;DR at the end.
I'd like for everyone to just think about what we're trying to do here. Don't forget what the ultimate goal is. Anyone remember? Is it to make a profit? No, that's a secondary goal. The primary goal is to develop widespread adoption of cryptocurrency as an alternative to fiat currency. Anyone remember this lofty goal or did we all forget this while chasing 30% daily price swings. We're trying to complete with USD, GBP, EUR, and CNY, remember?
This is EUR vs. USD. You'll note that this is all data (or click on "All" button on the bottom), going back to 1993 through today. What do you notice? You'll notice an open of $1.22 to €1. After a few months, it fell about 10%, then rose up 24% over the next two years only to drop about 40% over seven years and then almost doubling over eight years only to drop about a third in the last ten years to where it is today - almost where we were 25 years ago (approximately).
This is BTC vs. USD. You'll note that this is all data going back to 2011. During the last seven years it has... oh my God are you kidding me?! This is LTC vs. USD.
Let's not forget what we're talking about. We're talking about currency. For currency to be used, it needs to be relatively stable. Now compare the charts above. Let's say we created a new country called Cryptonia. Which of these would you like to use as currency? EUR? BTC? LTC? My money is on EUR. Why? Because it's relatively stable.
Now let's fast forward a bit and pretend that Cryptonia has adopted Litecoin as its official currency. Our largest trading partner is the US. How would transactions between merchants work in this scenario, taking into account the last few days. I'll use the following prices:
Let's run through a transaction:
1/16
1/17
1/18:
Conclusion:
This works both ways as far as you can do the math in USD vs. LTC to see how this screws over at least one party due to the wild price swings. Note: fiat currency does the same thing with one key difference explained later on.
Don't forget that this is all within 3 days. Now sure, obviously the last few days isn't something that happens every day ... but doesn't it? Look at the examples of EUR:USD. Any sharp spikes or drops have taken months to execute - enough time for relative prices to adjust. Look at cryptocurrency prices - the swings (from a percentage basis) are wild on a regular basis. In short, cryptocurrency isn't acting like currency. It's acting like an asset and not just an asset but a highly speculative one. The IRS is right to treat it like an asset because if it looks like an asset, and it acts like an asset, then it is an asset.
Where do I believe this should go? I believe cryptocurrency market needs to mature. I believe these drastic price swings need to stop. When will this happen? I believe it'll happen when the cryptocurrency market reaches a happy plateau where the market cap has reached a point where the buyers and sellers mostly eliminate one another and the relatively large price swings - from a percent point of view - are as boring as Mr. Stein. EUR vs. USD went up 0.03% today. 0.03%. In LTC-speek, that's going up $0.58 for the whole day. Oh and it was a wild ride too. Why it went all the way down to $1.21697 and all the way up to 1.22645. I know, I know - tie me down because I'm out of control.
Is this the only problem? No. Cryptocurrency has another problem and that's the sheer number of types of coins available. How many coins are available? 1,448. Nearly 1,500 coins all competing with each other for market share. We have Bitcoin at about $200b all the way to something like Digital Money Bits (DMB, an appropriate acronym). What is it? Who cares, it's worth $3,832. Not $3.832 billion or million but literally $3,832 with a volume of $35,509 today and hey, just this June, its market cap reached an all time high of $62,000! You missed the recent run-up though and boy did you miss it. On January 1st, its market cap was worth almost five hundred dollars! Yep, about two Litecoins! But look at it now - it went from $500 market cap to $3,832 in less than three weeks. Clearly this one is shooting to the moon.
This is a problem. Decentralization has an unfortunate side effect of - duh - nobody being in charge. There's no real clearance for these and some people with a little bit of money can literally copy and paste a whitepaper and have this chart and have a serious valuation of almost $17b from $140 million in literally 30 days. This doesn't act like a currency either. This is a problem.
Don't forget, this isn't like the dot-com era. We're not launching IPO's and .com companies that have different ideas. Amazon isn't like Ebay, or Google, or Yahoo, or Facebook or anything else. They all have different ideas for different segments of the population. We are in the cryptocurrency market. The world today has 180 fiat currencies. Cryptocurrency market is approaching 1,500. We need to trim the fat and the outright forgeries. Market cap isn't enough to weed them out. There needs to be something, a stabilizing force, that should act as a clearinghouse for launch of new cryptocurrencies. The market has failed to destroy shitcoins. Heck, it rewarded them based on lies, paid endorsements, FOMO, and FUD for other coins. This doesn't help the cryptocurrency market. It helps a few people get really wealthy really quickly and you are left holding the bag, so to speak. Should coins only be allowed to be introduced when its network reaches a certain hash rate? Isn't that the only objective point of value we have - number of mathematical calculations and power used in those calculations? You can't fake that.
What's another problem with cryptocurrency? It's what it represents. The governments don't see crypto as a positive force. After all, it directly competes with their own currencies. Can the governments shut this down? No - this is the Internet, after all. But they can kill it in other ways. I don't know how many people here remember but my first brush with Bitcoin was the ransomware viruses which wanted $300 in Bitcoin to unlock files. Bitcoin was seen as something tied to illegal activities. If governments - and let's say the US, South Korea, and China in particular - ban Bitcoin and cryptocurrencies in particular then what they'll really do is make transactions illegal. What's the on-ramp and off-ramp to/from crypto? The banks which are already regulated. Now let's say you're in the US, your bank account is tied to your Coinbase account and you have some cryptocurrency. US issues a regulation which states that trading cryptocurrency is now illegal. It issues orders to all US banks to shut down related accounts. The following things will happen: cryptocurrency prices will tank and everyone is going to scramble taking money out which would likely overload the system, causing massive delays.
But let's say you're left holding your crypto and it's been a month. What can you do with it? Not much. Crypto isn't accepted in enough places yet. You can continue holding, hoping the price and ability to extract will come back one day. After all, you can't get your money back. Your bank closed your related account. You can open another one at any new bank but they'll either ban you from connecting your account to Coinbase or they'll confiscate any money coming from Coinbase and charge you with a crime. Now have the governments banned crypto? No - you can use and trade crypto all you want since it can't be traced. But have they effectively? Yes. Ironically, it's the banks that'll save us and I think that's why Ripple blew up. After all, if you have a cryptocurrency that sucks the bank's [censored] and plays along, you can get:
I think that's why something like Ripple blew up - because it doesn't care much about regular people, it wants to be the speedy highway for bank<->bank transfers.
What's a solution to this problem? More regulation and playing nice with the governments. Crypto isn't going mainstream if you shut out all governments. It needs to be connected. This means working with regulators to make sure that KYC laws are followed, that people report and pay money on any gains, and that - to a point - there's some supervision and tracing of transactions in a way that if you're robbed, you can get your money back. This will create a new job field, which - considering our current growth - will create a whole slew of high-paying white-collar jobs. Considering the high-level of transactions, banks would start this, followed by private companies, governments, and law-enforcement agencies. A good way to start this is what CBOE and CME have started to do - legitimize the currency. This is a foot in the door to the real holy grail: FOREX markets. When it's legitimized and not in serious competition with governments, it'll be embraced and its availability - along with instant transfers and low fees - will be widely supported by serious platforms.
Until these problems are fixed, the cryptocurrency market will remain what it is today: a speculative asset and not a currency. During the time it's taken me to write this post, Litecoin has gone up 2.6%. Euro remains at 0.03% gain.
Thanks for reading!
TL;DR
submitted by SsurebreC to LitecoinTraders [link] [comments]

任泽平:里根改革助力军转民 新经济崛起股市长牛

任泽平:里根改革助力军转民 新经济崛起股市长牛

0评论 2017-09-29 08:03:45 来源:泽平宏观 作者:任泽平 如何捕捉5G概念最强龙头(教程)
上世纪70、80年代,美国面临美苏争霸、日本崛起、滞涨等重大挑战。经过里根供给侧改革、沃尔克控制通胀等努力,美国在90年代以后互联网信息技术“新经济”崛起,苏联解体,日本落入失去的二十年,美国重新领导世界,美股走出史前大牛市。
文:任泽平、张庆昌
导读:
上世纪70、80年代,美国面临美苏争霸、日本崛起、滞涨等重大挑战。经过里根供给侧改革、沃尔克控制通胀等努力,美国在90年代以后互联网信息技术“新经济”崛起,苏联解体,日本落入失去的二十年,美国重新领导世界,美股走出史前大牛市。
摘要:
上世纪70、80年代面临的挑战:冷战、美苏争霸、日本崛起、滞涨。二战后,苏联阵营壮大,冷战升级,美苏全球争霸。朝鲜、越南战争导致政府支出和赤字上升。20世纪70年代以后,日本汽车、半导体等出口崛起,冲击美国市场。西欧战后重建,经济规模总量和美国相当。布雷顿森林体系崩溃。两次石油危机爆发。适龄劳动力人口增速下降,产能过剩。经济滞涨,凯恩斯主义失灵。
沃克尔控制通胀。1980年核心CPI高达13.5%,1982年失业率高达10.8%。沃尔克紧缩货币与管理预期、金融自由化相结合。固定货币供应量增长,为美联储和政府添加枷锁,让其难以主动放松货币。给投资者稳定预期。通过固定量的货币供应增长,在那个动荡的年代,可以给投资者建立一个物价锚。紧货币可以堵住产能过剩行业的无效融资需求,有利于产能出清。同时加快推行金融自由化,推动新兴行业融资。通胀水平从1980年的13.5%大幅下降到1986年的 1.9%。
里根经济学:降税、放松管制。两次修订税收法案,大规模减税;放松市场管制,放松了航空、铁路、汽车运输、电信、有线电视、经纪业、天然气等许多行业的干预和管制;放松反托拉斯法的实施,鼓励企业合理的竞争;放松石油价格管制;放松对汽车行业的管制;放松劳动力价格管制;加大对中小企业支持;鼓励企业创新,推动产业结构转型;推进利率市场化改革;减少社会福利;签订广场协议,贬值美元,降低贸易赤字。
重新领导世界:苏联解体、日本失落二十年、新经济崛起、控制通胀、经济复苏、股市长牛。“星球大战”拖垮了苏联,冷战期间军费开支巨大,但军需促进了工业发展,奠定了后20年新兴行业的发展;广场协议后,日元大幅升值,资产泡沫破裂,失去二十年;CPI从1980年的13.5%降低到1982年底的4.5%;从1982年末开始,美国经济开始复苏,一直到里根任期结束GDP增长率维持在3.5%以上;里根时期,标准普尔500指数涨2.3倍,之后经过87年调整,又走出了长达13年的大牛市。
里根时期供给侧改革催生了上世纪90年代“新经济”的崛起。计算机及Internet网络的诞生都与军方有关,里根时期的经济复苏及金融自由化为军队技术转为民用奠定了基础。1993年9月克林顿上台后迅速拟定了“全国信息基础设施”(即信息高速公路)发展方案。2000年美国信息技术产业已占GDP的10%以上,对经济增长的贡献度远超过制造业,一批伟大的互联网信息技术和公司诞生并崛起。
目录
1.上世纪70、80年代面临的挑战:冷战、美苏争霸、日本崛起、滞涨
1.1. 国际:美苏争霸,冷战升级
1.2. 国际:日本、西欧经济迅速崛起,冲破以美元为中心的布雷顿森林体系
1.3. 国际:两次石油危机
1.4. 国内:适龄劳动力人口增速下降和产能过剩
1.5. 国内:经济滞涨,凯恩斯主义失灵
2.沃克尔控制通胀
2.1. 通胀加剧,沃克尔两面承压
2.2. 紧缩货币与管理预期、金融自由化相结合
2.3. 货币中间目标转为调节货币供应量
2.4. 通胀水平由1980年的13.5%大幅下降到1986年的 1.9%
2.5. 启示:紧货币与发展多层次资本市场相结合
3.里根经济学:降税、放松管制
3.1. 里根经济学的精髓及理论基础
3.2. 两次修订税收法案,大规模减税
3.3. 放松市场管制
3.4. 推进利率市场化改革
3.5. 减少社会福利
3.6. 签订广场协议,贬值美元,降低贸易赤字
4.重新领导世界:苏联解体、日本失落二十年、新经济崛起、经济复苏、股市长牛
4.1. 苏联解体
4.2. 广场协议之后,日本房地产泡沫破裂,失去二十年
4.3. 国内通胀有效控制
4.4. 经济复苏
4.5. 里根时期,标准普尔500指数涨2.3倍,之后经过调整,又走出13年的大牛市
5.里根时期供给侧改革催生了上世纪90年代新经济的崛起
5.1. 计算机及Internet网络的诞生都与军方有关
5.2. 里根时期的经济复苏及金融自由化为军队技术转为民用奠定了基础
5.3. 上世纪90年代,美国新经济崛起
5.4. 2000年纳斯达克泡沫破裂,却催生了了互联网信息技术的大发展
正文:
上世纪70、80年代,美国外部军事上面临苏联挑战,经济上面临日本挑战,布雷顿森林体系崩溃,内部面临滞涨、劳动年龄人口增速下降等一系列重大挑战。经过里根时期供给侧改革、沃尔克控制通胀等努力,美国在90年代以后“新经济”崛起,苏联解体,日本落入失去的二十年,美国重新领导世界。美国在80年代前后面临的挑战与应对具有重大启示和借鉴意义。
1.上世纪70、80年代面临的挑战:冷战、美苏争霸、日本崛起、滞涨
1.1. 国际:美苏争霸,冷战升级
冷战,美苏争霸。二战后,苏联的经济军事力量逐渐扩大,经济总量从占美国的1/3迅速升到2/3。在钢、煤、油等重要工业产品上,苏联的产量已经超过了美国。苏联的军事实力更急剧膨胀、不论常规武器或者核武器,已经赶上甚至在某些方面超过了美国。
朝鲜、越南战争导致政府支出和赤字上升。1950年6月25日,朝鲜战争爆发,持续三年。战争中,美国动用了其陆军兵力的三分之一;海军兵力的二分之一;空军兵力的五分之一;还有大量精锐部队,“开国元勋师”——骑兵第一师,“美利坚之剑”——陆战第一师,“王牌飞行队”——航空兵第四联队等。最后,美国伤亡惨重,并未赢得战争。1955年11月,越南战争爆发,持续20年,是二战以后,美国参战人数最多,影响最大的战争,但是美国在越南战争中失败。
1.2. 国际:日本、西欧经济迅速崛起,冲破以美元为中心的布雷顿森林体系
20世纪70年代以后,日本经济和出口保持相对高速增长。当时,美国经济由于受到石油危机等因素的影响,遭到沉重的打击。而日本却顺利地进行了产业调整,节能汽车和电子机械产品行销世界,工业竞争力在国际上空前提高,出口大幅增加,全面冲击了美国工业。
汽车、半导体等出口竞争力快速提升,冲击美国市场。70年代初期,德国大众汽车公司生产的汽车是美国最畅销的外国车。随后受益于两次石油危机和日本节能技术,日本丰田和本田汽车在美国市场的销售量先后超过了德国大众。1980 年,日本汽车在美国的销售量达到 192 万辆,占美国市场总销量的20%,占美国进口汽车量的80%。其次,在技术尖端产业,1985年,日本成为世界上最大的半导体集成电路出口国,超过美国。此外,日本在钢铁、交通、通讯等领域的竞争力也强于美国。例如,1978年,在世界最大的22座现代化熔铁炉中,有14座属于日本,美国一座也没有。
西欧战后重建,经济规模总量和美国相当。二战后,借助于美国的大量援助和恰当的经济发展政策,西欧国家经济快速恢复和发展。1967年欧共体正式成立,1974年欧共体GDP占世界的比重为20.12%,同期美国占比为24.36%。而到了在20世纪70年代末,欧共体的经济实力已超过美国。在国际贸易领域,1950-1979年,美国占资本主义出口总额的比重从18.3%下降到12.1%,而西欧则从29.3%上升到38.7%。在国际金融领域,1960-1970年美国占世界黄金储备的比重从47.2%下降到29.9%,西欧则从32.7%上升到40.8%。
以美元为中心的国际货币体系——布雷顿森林体系瓦解。1944年7月,西方主要国家的代表在联合国国际货币金融会议上确立了该体系。后来,由于西欧、日本的崛起,美国经常账户出现逆差;通胀率逐渐上升,导致美元贬值,最终,在1973年,美元与黄金脱钩,布雷顿森林体系瓦解。
图1 黄金价格大幅上升
![美国里根时期供给侧改革的挑战、应对与启示](http://getimg.jrj.com.cn/images/2017/09/weixin/one_20170929080350041.jpg)
数据来源:Wind,国泰君安(行情14.62 +0.97%, 诊股 )证券研究
1.3. 国际:两次石油危机
石油价格大涨。1973年10月中东战争爆发,为了打击以色列及同盟国家,阿拉伯石油输出国宣布石油禁运,暂停出口,导致有史以来第一次原油价格飞涨。原油价格从1973年的每桶不到3美元涨到13美元。第二次石油危机(1979-1980年),伊朗政局发生剧烈变动,石油产量从每天580万桶骤降到100万桶,原油价格从13美元/桶迅速升至34美元/桶。
1.4. 国内:适龄劳动力人口增速下降和产能过剩
进入20世纪70年代后,美国适龄劳动力人口增速下降。1971年,美国14-64岁适龄劳动力人口增速为1.9%。之后,该数值一路下滑,到1980年,该值下降到0.7%。
图2 适龄人口增速下滑
![美国里根时期供给侧改革的挑战、应对与启示](http://getimg.jrj.com.cn/images/2017/09/weixin/one_20170929080351629.jpg)
数据来源:Wind,国泰君安证券研究
耐用品制造业产能利用率大幅下滑。70年代后,面对国外的竞争,国内的商品竞争力下降,出现了产能相对过剩。其中初级金属,机械,汽车及零部件,航空航天及其它交通行业下跌最为严重。
图3 劳动力增速和产能利用率下降
![美国里根时期供给侧改革的挑战、应对与启示](http://getimg.jrj.com.cn/images/2017/09/weixin/one_20170929080353629.jpg)
数据来源:Wind,国泰君安证券研究
1.5. 国内:经济滞涨,凯恩斯主义失灵
凯恩斯学派的失败“二战”后,美国政府不断增加社会福利开支,并加强对经济的管制以抑制垄断、负外部性等各种市场失灵;认为采用凯恩斯主义所倡导的财政货币刺激,就能实现充分就业和经济增长;并以为,如果采用凯恩斯主义的干预政策,美国可以从根本上防止20世纪30年代大萧条悲剧的重演。结果,政府过度依赖刺激政策,经济出现滞涨。
经济滞涨。在凯恩斯主义的刺激下,政府债务规模快速上升,70年代末联邦政府总支出占GDP比重达到约25%,相对“二战”结束时翻了一倍。同时,通胀率从60年代中后期开始逐渐上升,70年代已经演变成滞涨。1980年6月,核心CPI高达13.6%,1982年11月,失业率高达10.8%。
2.沃克尔控制通胀
2.1. 通胀加剧,沃克尔两面承压
通胀加剧,居民生活水平下降,企业无心投资。里根在就任总统后的电视演说中提到,1960年的1美元到1981年只值3角6分,这导致个人储蓄率大幅下降。尽管工资随着通胀同步上涨,但是美国对名义收入征税而非实际购买力征税的做法,导致工资上涨将人们推到更高的税收等级,通胀和边际税率的提高沉重打击人民的生活水平。社会分配严重不均,尤其是年轻人和靠固定收入为生的老人陷入困境。这种环境也影响了市场的投资预期,工人怠工,企业无心进行研发,失业率上升。
提到沃克尔的名字,人们首先想到的就是成功控制了通胀,但在当时,沃克尔面临巨大的压力。沃克尔在一次访谈中说,“如果 1979年以前有人告诉我,我会当上美联储主席并且把利率提升到20%,我肯定会凿个洞钻进去大哭一场。”持续通胀会影响居民生活水平和企业投资,降低社会福利。但采取紧缩的货币政策会冲击房地产市场和加剧债务人的债务量。沃克尔回忆道,“房地产公司的老板们每天都来拜访我,他们不停地询问这一切何时才能结束。”“还不起贷款的农民们将卡车开进华盛顿,堵在美联储总部的门口。”
2.2. 紧缩货币与管理预期、金融自由化相结合
沃尔克的政策一定程度上属于理性预期学派的预期管理。第一,固定货币供应量增长,为美联储自身和政府添加了枷锁,让其难以主动放松货币;第二,给投资者稳定预期。通过固定量的货币供应增长,在那个动荡的年代,可以给投资者建立一个物价锚。
紧货币的同时,政府在推行金融自由化,提高资金的使用效率。一方面,紧货币可以堵住产能过剩行业的无效融资需求,利于产能出清。另一方面,加快推行金融自由化,有利于新兴行业的融资。
2.3. 货币中间目标转为调节货币供应量
1970年—1979年10月货币政策的操作目标为联邦基金利率。在凯恩斯主义的思维模式下,政府以刺激经济和就业为导向。而且,由于1968年放弃了基础货币的黄金准备金要求,使得基础货币供应约束大大弱化。在这样的大背景下,财政部和白宫通常会对美联储施压,放松货币政策,将财政赤字货币化。特别是在美国的大选之年,如1972、1976年,联储主席阿瑟伯恩斯都受到了白宫的政治压力。
为控制通胀,1979年10月—1982年10月转为以非借入准备金数量为主要操作目标,以有效控制货币总量为中间目标,允许联邦基金利率在较大的范围内波动。联邦储备委员会1981年规定的货币供应量Ml增长指标为3-6%,而实际上只有2.1%。在这期间,联邦基准利率最高达22%。
1983年—1987年10月,以借入准备金成为联储判断银行体系资金紧张情况的主要指标及操作目标。随着通胀的逐渐回落,美联储不再强调控制M1的重要性,而是力图熨平银行体系准备金需求的短期波动,使联邦基金利率更为稳定。当非借入准备金不足时,公开市场交易室则以贴现窗口资金补足,进而实现以贴现窗口利率影响联邦基金利率。1987年10月股市崩盘期间,美联储暂时放弃了上述操作方式,转为盯住联邦基金利率目标水平,并确保银行体系获得足够流动性。1988年危机过后,美联储重新恢复了上述方式。
2.4. 通胀水平由1980年的13.5%大幅下降到1986年的1.9%
通胀水平下降。沃克尔顶住各方压力,坚持把利率提高至20%以上,达到历史最高水平。即便利率大幅上升导致了1982年的严重衰退,当时美联储只是轻微下调利率,类似地,当1986年中期美国经济出现通缩迹象,美联储为巩固治理通胀成果,只是顺势微调利率,仍然维持在6%以上水平。双管齐下,使得尼克松时期的高通胀现象开始缓解,通胀水平由1980年的13.5%下降到1986年的1.9%。
2.5. 启示:紧货币与发展多层次资本市场相结合
控制通胀,必要时进行预期管理。回顾20世纪70年代,当时的美国政府并没有认识到随着高油价产生的两大变化,居民的高通胀预期和高通胀提高了自然失业率。在这样的大环境下,政府一味地追求就业,使失业率降低到先前认定的自然失业率一下,无异于对通胀火上烧油。在沃克尔任美联储主席之后,采用固定货币增速的手段达到了紧货币和控制预期的目的,最终解决了通胀问题。
紧货币与发展多层次资本市场相结合,利于产能出清和新兴行业的崛起。紧货币可以堵住落后产能行业的融资需求,而加速推进金融自由化,发展多层次的资本市场,可以为新兴行业提供融资需求,促进新兴行业快速崛起。
图4 紧货币抗通胀
![美国里根时期供给侧改革的挑战、应对与启示](http://getimg.jrj.com.cn/images/2017/09/weixin/one_20170929080355630.jpg)
数据来源:Wind,国泰君安证券研究
3.里根经济学:降税、放松管制
3.1. 里根经济学的精髓及理论基础
减税、放松管制和紧货币是精髓。1980年,共和党候选人里根以绝对的优势当选为美国第40任总统。面对棘手的经济形势,里根进行了大刀阔斧的改革。主要内容包括:减税、降低社会福利、放松对部分行业的管制、推进利率市场化改革等。其中,减税、放松管制和紧货币是里根经济学的精髓。
供给学派:生产的增长取决于劳动力和资本等生产要素的供给和有效利用。个人和企业提供生产要素和从事经营活动是为了谋取报酬,对报酬的刺激能够影响人们的经济行为。自由市场会自动调节生产要素的供给和利用,应当消除阻碍市场调节的因素。具体内容包括拉佛曲线、弗里德曼货币理论等。
拉佛曲线。当税率在一定的限度以下时,提高税率能增加政府税收收入,但超过这一限度时,再提高税率反而导致政府税收收入下降。因为较高的税率将抑制经济的增长,使税基减小,税收收入下降。反之,如果减税,可以刺激经济增长,扩大税基,税收收入增加。
弗里德曼货币理论。引起名义国民收入发生变化的主要原因在于货币当局决定的货币供应量的变化。短期,货币供应量的变化主要影响产量,部分影响物价,但长期,产出量完全是由非货币因素(如劳动和资本的数量,资源和技术状况等)决定的,货币供应只决定物价水平。经济体系本质上是稳定的,只要让市场机制充分发挥其调节经济的作用,经济将能在一个可以接受的失业水平条件下稳定发展。
3.2. 两次修订税收法案,大规模减税
1981年8月通过《1981经济复苏税法》(坎普-罗斯减税法案) 。主要内容有:第一,1981年10月降低税率5%,在1982、1983年的7月再分别削减10%,并且从1985年起实施个人所得税和通胀指数挂钩;第二,将非劳动所得的最高税率从70%降至50%;第三,边际税率从14%-70%降为11%-50%;第四,缩短固定资产折旧年限并简化分类,加速固定资产折旧;第五,对企业投资给予纳税优惠:如购买汽车或研究设备减税6%;添置机器设备减税10%。
1986年,颁布了《1986年税制改革法案》。该法案的颁布旨在降低税率、扩大税基、堵塞税收漏洞、实现税收公平。具体主要内容有:第一,全面降低个人所得税率。把纳税等级从14级简化为3级,最高税率从50%降为35%,使全部个人所得税降低约7%;第二,简化和改革公司所得税。公司所得税率从46%降低到 34%;第三,允许公司支付的一半股息免税,取消对银行坏账的特别税收减免,将资本收益税从20%减到17.5%。第四,限制或取消了过去给予部分个人和公司的税收减免优惠政策。涉及60余项特惠待遇,如取消销售税扣除、不动产税扣除、慈善捐助扣除、资本收益免税扣除、中老年特别免税扣除等。
3.3. 放松市场管制
里根政府放松了航空、铁路、汽车运输、电信、有线电视、经纪业、天然气等许多行业的干预和管制,通过引入竞争使产品和服务质量明显提高,价格明显降低,增进了社会福利,有效增强了经济活力。
专门成立撤销和放宽规章条例特别小组。1981年3月,里根批准成立以副总统布什为主任的撤销和放宽规章条例的特别小组,负责指导和监督部分规章条例执行的具体工作。这个特别小组仅在1981年就审核了 91项现行管制条例,其中撤销和放宽了65项,包括《空气清洁法》、《水污染控制法》、《矿工安全法》、《汽车交通安全法》、《反噪音法》等。
里根政府主要在以下几个方面放松了政府管制:
第一,放松反托拉斯法的实施,鼓励企业合理的竞争。政府颁布新的公司合并指导文件,旨在促进有利于经济效率的合并,阻止那些消弱竞争的合并。根据该文件,美国司法部对过去1200多宗判例重新审查,其中一些案例得到改判或撤销。例如,1982年,司法部反托拉斯处撤除了对IBM的长期诉讼。同年,美国司法部结束了对美国电话电报公司长达十年、耗资数亿美元的诉讼。结果是让美国电话电报公司放弃22个地方电话公司,同时允许该公司进行跨行业经营,进入计算机制造和信息处理领域。这一作法鼓励了企业以新方式相互联合,与之前的竞争者建立战略性合作关系。
第二,放松石油价格管制。1981年,政府颁布行政命令,取消了对石油和汽油价格的管制。取消后最初的两个月每加仑油价上升了12美分,但随后开始出现下降,降至低于管制前的水平。同年,美国本土新钻油井就比1980年增加了33%。与此同时,石油消费下降6%。
第三,放松对汽车行业的管制。里根政府开始对限制美国汽车工业的规章条例进行全面的审查,环境保护署和运输部宣布对34项有关规章予以重新考虑。这些管制改革使汽车工业成本得到降低,使消费者每年节省15亿美元。
第四,放松劳动力价格管制。1982年,里根政府修订《戴维斯?贝肯法》,减少了对劳动力市场价格的干预。变化主要有:对“通行工资”重新下定义,使之更加符合市场价格的实际水准;允许企业雇佣非正式的员工,不受最低工资限制;制止过去农村地区工资攀比城市标准的做法。
第五,加大对中小企业支持。政府通过立法为中小企业发展消除制度障碍。例如,1982年出台《小企业创新发展法》;1983年《小企业出口扩大法》。同时,为中小企业发展提供税收、资金等全方位支持。
第六,鼓励企业创新,成功促进了产业结构转型。里根政府通过立法不断鼓励企业创新同时保障企业创新成果。《小企业创新发展法》(1982)、《国家合作研究法》(1984)、《联邦技术转让法》(1986)、《综合贸易与竞争法》(1988)密集的法律文件的出台促进了技术转让、技术推广以及技术应用。而《半导体芯片保护法》(1984)、《计算机安全法》(1987)等一系列法律则保护了刚出现的信息技术,确保研发者的合法权利。另外,1984年颁布的《国家合作研究法》允许竞争企业进行合作研究开发,并从法律上明确合作研发豁免于反托拉斯法3倍惩罚,使得产业政策与反垄断法高度统一起来。
3.4. 推进利率市场化改革
20世纪80年代初期,美国开始全面利率市场化改革。1980年3月,美国国会通过了《存款机构放松管制和货币控制法》,主要内容有,分6年逐步取消对定期存款利率的最高限;批准全美的商业银行和储蓄机构开立可转让支付命令账户和自动转账服务账户;扩大储蓄机构的经营范围,对所有存款机构规定统一的法定准备金要求;将FDIC存款保险从每户40000美元增加到100000美元。
1982年颁布的《加恩-圣杰曼存款机构法》,详细地制定了废除和修正“Q条例”的步骤。为扩大银行业资产负债经营能力,还列明了一些其他与利率市场化相关的改革,包括进一步扩大储蓄机构的经营范围,授权存款机构开立货币市场存款账户,允许FDIC和联邦储蓄与贷款保险公司(FSLIC)在紧急情况下兼并有困难的机构和银行。
1983年10月,美国存款机构放松管制委员会取消了31天以上的定期存款以及最小余额为2500美元以上的极短期存款利率上限;1986年1月,取消了所有存款形式对最小余额的要求,同时取消了支付性存款的利率限制;1986年4月,取消了存折储蓄账户的利率上限;对于贷款利率,除住宅贷款、汽车贷款等极少数例外,也一律不加限制。至此,“Q条例”完全终结,利率市场化得以全面实现。
金融自由化摒弃了近半个世纪以来金融监管体制对银行业发展过度限制的某些方面,使金融产品可以自由定价、金融创新大量涌现、各类金融机构业务交叉及金融市场国际化趋势加强。
3.5. 减少社会福利
减少社会福利,提高个人工作积极性。1981年12月,美国社会保险改革委员会成立,并于1983年提出了改革方案,主要内容包括:提高社会保障税;对领取较高保险年金收入的人征收所得税;延迟退休年龄等。
3.6. 签订广场协议,贬值美元,降低贸易赤字
1985年9月,为解决美国贸易赤字问题,美日德法英签订广场协议,之后美元大幅贬值。20世纪80年代初期,美国财政赤字剧增,对外贸易逆差大幅增长。美国希望通过美元贬值来增加产品的出口竞争力,以改善美国国际收支不平衡状况。1985年9月22日,美日德法英在纽约广场饭店达成协议。之后,五国政府联合干预外汇市场,诱导美元对主要货币的汇率有秩序地贬值,以解决美国巨额贸易赤字问题的协议。1985年9月,美元兑日元在1美元兑250日元上下波动,协议签订后不到3个月的时间里,美元迅速下跌到1美元兑200日元左右,跌幅20%。
4.重新领导世界:苏联解体、日本失落二十年、新经济崛起、经济复苏、股市长牛
4.1. 苏联解体
美国以经济为依托,进行“星球大战”竞赛。1983年3月,里根发表演讲,宣布将特勒提出的设想发展为战略防御计划,与苏联在太空展开军备竞赛。但这个时候两个国家背后的经济却发生了明显的变化。经过大刀阔斧的供给侧改革,美国经济在1982年底开始复苏。而苏联受制于体制僵化,过分扩大军费开支,透支了经济发展,最终被美国的“星球大战”竞赛拖垮。
苏联解体背后最根本的原因是体制僵化导致的经济衰退。高度集权的计划经济在早期可以集中人力、物力等解决经济中的重大问题,但是到后期,受制于体制原因,要素错配不能流入新兴行业,最终会积弱成疾。1989年1月,老布什接替里根出任美国总统。当时,石油价格已暴跌至每桶约10美元,苏联实际上已经破产。戈尔巴乔夫向国际社会游说,希望每年能得到150亿美元救命贷款。在万般无奈的情况下,他致电老布什请求帮助。11月9日,柏林墙被德国示威者拆除。1991年12月25日,戈尔巴乔夫辞去苏联总统职务,苏联解体。
4.2. 广场协议之后,日本房地产泡沫破裂,失去二十年
回顾日本经济30年来的发展,1985年的广场协议是一个转折点。广场协议后,日元大幅升值,导致日本出口竞争力备受打击。同时,日元升值进一步推升了日本资产泡沫。最终,受日本加息刺激影响,股市、房市泡沫相继破裂。
图5 日本经济下滑
![美国里根时期供给侧改革的挑战、应对与启示](http://getimg.jrj.com.cn/images/2017/09/weixin/one_20170929080357630.jpg)
数据来源:Wind,国泰君安证券研究
4.3. 国内通胀有效控制
以高利率维持较低通胀率。里根政府采纳货币学派的主张,降低货币供应量的增长率和提高贴现率,使得利率保持较高水平从而降低通货膨胀率。从1980年开始,美国实际利率基本维持在6%至8%的高水平,高利率对通货膨胀率起到了一定的抑制作用,CPI也从1980年的13.5%降低到1982年的6.2%,其后基本维持在在5%以下;另外,PPI也从1980年的14.1%降至1982年的2%,之后也基本维持在6%以下,里根政策对于通货膨胀率的治理还是非常有效果的。
4.4. 经济复苏
前期经济仍处于衰退。里根政府通过削减税率来增加储蓄、投资和生产,但是较高利率抑制了投资,抵消了减税对投资的刺激作用。因此,实施改革前期,除了通货膨胀率有所下降以及美元指数上行外,美国仍然处于危机和衰退之中。1981-1982年,美国工业生产指数从1981年8月起持续下跌,一直持续到1982年第四季度,比两年前直降8.7%;失业率也从两年前的7.4%上升至10.8%;GDP从1981年7月急剧下跌,在1982年11月降到谷底,-1.9%,人均GDP降至-2.85%。
后期经济复苏增长。从1982年末开始,美国经济开始复苏。1983年GDP增速达到4.6%,一直到里根任期结束GDP增长率维持在3.5%以上;失业率也从1983年7月开始逐渐降低,至1989年末一直维持在6%以下;工业生产指数于1983年2月开始稳定上升,至1989年12月达到68.3,比1983年初增长29.8%。
产业结构升级。里根政府采取的产业结构调整政策效果逐渐显现,主要体现在制造业内部分工加强,传统产业在改造中焕发生机;新兴服务业发展迅速,高技术服务业成为新的经济增长点;就业人口加速向服务部门转移,表明了美国消费结构的变化和经济重心的转移。1980-1984年整个工业年增长率为2.9%,而高技术产业年均增长率却高达14%。高技术行业主要包括电子工业、生物技术工业、“自动化生产体系”工业、航空工业以及核能工业等。
金融混业经营,提高市场竞争力。20世纪70年代后期,美国通胀居高不下,居民储蓄的积极性逐渐下降,传统银行业务陷入窘境。同时,布雷顿森林体系的解体也给美国经济金融造成了巨大冲击,美国在全球经济的霸主地位受到挑战,美国银行业的国际竞争力减弱,银行业的国际化竞争日趋激烈。面对这样的内忧外患,美国政府不得不对金融体系做出调整,里根政府实行以放松管制和实行金融业务自由化的金融制度改革,逐步迈向金融制度自由化。例如,1980年联邦政府颁布了《储蓄机构放松管制与货币控制法案》,该法案解除了存款和贷款利率上限。随后,1982年里根又颁布了《加恩-圣杰曼吸收存款机构法》,该法案扩大了银行机构的业务权限,允许跨州并购破产银行等储蓄机构,鼓励跨州金融互惠协议,建立地区性网络银行以此促进不同类型金融机构的竞争,同时商业银行可以兼营投资银行业务与保险业务,上述措施为后来银行业实现全面混业经营和竞争(1999年《金融服务现代化法》)打下了基础。
4.5. 里根时期,标准普尔500指数涨2.3倍,之后经过调整,又走出13年的大牛市
随着里根改革的推进,美股逐渐上涨,仅在1984年上半年略微调整,之后走出长达3年的大牛市。整个里根执政时期,标普500指数从105点涨到353点。1987年10月,美国股市调整。之后,美国股市走出13年的大牛市,纳斯达克指数从1987年10月的291点涨到2000年3月的5048点,涨了16倍多。
图6 里根上台后,经济逐渐复苏
![美国里根时期供给侧改革的挑战、应对与启示](http://getimg.jrj.com.cn/images/2017/09/weixin/one_20170929080359630.jpg)
数据来源:Wind,国泰君安证券研究
5.里根时期供给侧改革催生了上世纪90年代新经济的崛起
5.1. 计算机及Internet网络的诞生都与军方有关
1946年2月14日,世界上第一台电脑ENIAC在美国宾夕法尼亚大学诞生。第二次世界大战期间,美国军方要求宾州大学Mauchly博士和他的学生Eckert设计以真空管取代继电器的“电子化”电脑——ENIAC(Electronic Numerical Integrator and Calculator,电子数字积分器与计算器),目的是用来计算炮弹弹道。
Internet是在美国早期的军用计算机网ARPANET(阿帕网)的基础上经过不断发展变化而形成的。1969年,美国国防部高级研究计划局(Advance Research Projects Agency,ARPA)开始建立一个命名为ARPANET的网络。当时建立这个网络的目的是出于军事需要,计划建立一个计算机网络,当网络中的一部分被破坏时,其余网络部分会很快建立起新的联系。1985年,美国国家科学基金会(National Science Foundation,NSF)建立计算机网络NSFNET,用于支持科研和教育的全国性规模的NSFNET,并以此作为基础,实现同其他网络的连接。20世纪90年代初,商业机构开始进入Internet,使Internet开始了商业化的新进程。1995年,NSFNET停止运作,Internet已彻底商业化了。
另外,国防工业在核能、集成电路、飞机、新材料等行业也拥有先进的技术。
5.2. 里根时期的经济复苏及金融自由化为军队技术转为民用奠定了基础
经济复苏为军费开支提供了基础,而军事的需求又带动了技术的研发。在冷战的几十年中,其间包括朝鲜和越南战争,美国军费开支在GNP中平均所占的比重为7.4%,是第一次世界大战前国家安全开支比例的9倍。对军工产品的需求和军队的加速扩张改变了经济的总量。新的工业部分成为美国现代经济增长的一个方面。这些新部门在经济中的重要性逐步显露出来,积累资本和劳动,为美国冷战后几十年产出的增长打下了坚实的基础。
美国的金融自由化为技术的商业化早期的发展奠定了基础。在政府的支持下,美国的风险投资业于80年代得到了迅猛发展。1979年风险投资额仅为25亿美元, 1997年已达6000亿美元,18年间增加了240倍。它们的资金主要投向信息技术、生命科学等高科技产业。例如,英特尔(Intel)、微软(Micorsoft)、苹果(Apple)、雅虎(Yahoo)、3Com等一大批新兴企业都得益于风投。
5.3. 上世纪90年代,美国新经济崛起
1993年9月,克林顿上台后迅速拟定了“全国信息基础设施”(即信息高速公路)发展方案。在强大的政策支持和资金投入下,美国信息技术产业在之后的几年以超出经济两倍的增长迅速崛起,一跃成为美国第一大支柱产业。在1997年,美国微软公司的产值就达到了90亿美元,超过了美国三大汽车公司产值的总和。到了2000年,美国信息技术产业已占GDP的10%以上,对经济增长的贡献度远超过制造业。
5.4. 2000年纳斯达克泡沫破裂,却催生了了互联网信息技术的大发展
2000年3月-2001年4月14日,纳斯达克指数下跌68%,互联网泡沫破裂。在纳斯达克上市的企业有500家破产,有40%退市,80%的企业跌幅超过80%,3万亿的纸面财富被蒸发。InfoSpace,2000年3月达到每股1305美元,2001年4月下跌到22美元。Boo.com,在6个月中花费了1.8亿美元试图创造全球网上时尚店,最终在2000年5月倒闭。
虽然纳斯达克互联网泡沫破裂,无数公司破产,但也催生了一批伟大的企业。网络泡沫时期的宠儿亚马逊、Priceline已从互联网崩盘的灰烬中重生。亚马逊在2000年时仍是一家图书销售网站。而目前,亚马逊已成为全球领先的电商服务,同时也是最大的云计算服务提供商。科技热潮时期的中坚力量(包括微软(Microsoft)、英特尔(Intel)和思科(Cisco))现在仍是纳斯达克备受关注的成分股。
信息技术的大发展。随着微软、英特尔等大公司的超常规发展和国际互联网络的迅速普及,以信息技术为代表的高科技产业成为经济增长的主要来源之一,信息技术产业占GDP的比重也在短短的几年内从5.2%提升到8.2%。新经济为美国实现了产业结构的调整。同时,技术进步带来了劳动生产率的提高,增强了美国在国际市场上的竞争力。
![美国里根时期供给侧改革的挑战、应对与启示](http://getimg.jrj.com.cn/images/2017/09/weixin/one_20170929080401631.jpg)
本文转载自“泽平宏观”。作者授权金融界网站发布,未经授权,请勿转载。如果您有干货观点或文章,愿意为广大投资者提供最权威最专业的参考意见。无论您是权威专家、财经评论家还是智库机构,我们都欢迎您积极踊跃投稿,入驻金融界网站名家专栏,邮箱地址:[[email protected]](mailto:[email protected]),咨询电话:010-83363000-3477。期待您的加入!
submitted by newsArchives to s1ref [link] [comments]

[Graph] Krugman's "Bitcoin is not a stable store of value" debunked.

I decided to utilize historic values to examine Krugman's statement:
To be successful, money must be both a medium of exchange and a reasonably stable store of value. And it remains completely unclear why BitCoin should be a stable store of value.
No one will deny that Bitcoin is currently extremely volatile. This is not an examination of that point. This is focused purely on the question of whether, historically, Bitcoin has proven to be a good store of value. No one can predict the future, so the best we have is historical data.
This is particularly of interest to me, give the recent tumble in Bitcoin price, as well as recent reports of the third worst collapse of the dollar in the past decade.
Methodology
To examine the quality of Store of Value, I examined the historical prices of seven different assets. I envisioned a buyer of the asset purchasing it on a given day, and holding it for some length of time (X), ranging between one day and about 3.5 years (which is all the data we have for Bitcoin).
The measurement is this: if you choose a random day to buy the asset, and you buy it at the mid-point price that day, and hold it for X days, what is the probability that it will still have 100% of its value after X days. It seems like a reasonable assumption is that an asset that is a good store of value would perform well in this scenario, and retain 100% of its value a high percentage of the time.
The seven assets were:
  1. Bitcoin purchased on Bitstamp. Data provided by BitcoinCharts.
  2. Bitcoin purchased on Mt. Gox. Data provided by BitcoinCharts.
  3. Bitcoin Freely Exchangeable: For this measurement, I used Mt. Gox prices as mentioned above, until May 13, 2013 (the day before the US Government seized funds), and Bitstamp prices since then. This is an attempt to eliminate the odd pricing on Mt. Gox due to the withdrawal challenges.
  4. The Dow Jones FXCM Dollar Index, data provided by Google Finance. The data for this index was available going back to 4/18/2011. It's an index of the dollar, presumably comparing to other currencies. (This may be mislabeled, calling it a fund. Not sure.)
  5. Spider Gold Shares GLD, an ETF for Gold. Data provided by Yahoo Finance. This data goes back to 11/18/2004.
  6. Spider Gold Shares GLD, for the period that Bitcoin has been traded. Same data source as #5, but a subset of the data.
  7. The US Dollar (1914-2013), reflecting the US monthly inflation rates. This data was provided by usInflationCalculator.com.
In all cases, I used the average of the daily high and the daily low, when available. In the case of the Dollar (1914-2013), I used monthly inflation rates.
In all cases, I set the purchase date to one of the days that the asset was traded. In the case of the Dollar (1914-2013), I utilized the first of the month. And I set the ending valuation date as the next time the asset traded, after X days elapsed. In the case of the Dollar (1914-2013), this would be the first of some future month, after X days had passed.
Results
Here's the Graph.
The best performing asset was buying Bitcoins on Bitstamp. In all cases historically, if you held the asset for 274 days, the asset was still worth 100% of your original investment.
Mt. Gox and the Freely Exchangeable Bitcoin measurements were similar: After 622 days, 100% of the time, your original invested value was retained.
The Dollar fund (index, actually) underperformed all Bitcoin options, when measuring periods less than 243 days. But for periods of between 471 days and 1033 days, 100% of the time, the dollar fund retained its complete value. (No data for periods longer than 1033 days).
The Gold ETF underperformed Bitcoin, whether you looked at the period of Bitcoin being on the market, or the life of the ETF.
And, no surprise, the dollar as measured by inflation, came in dead last. In the past 100 years, it has only retained its value month-over-month about 15% of the time. And the longer you held it, generally, the worse off you were.
All data is available at the sources above, and the computations are available.
The graph of the results is licensed for you to use widely with attribution.
I hope this helps when you are talking to the Krugmans of the world.
(Edit: it's -> its)
submitted by E-GovLink to Bitcoin [link] [comments]

[Hiring] Sr. and Intermediate Web Developers

That Oil & Gas industry company you're currently writing apps for looking a little shaky? Wanna move on? Consider this...
My company, Investopedia.com, are hiring both Senior (5+ years exp.) and Intermediate (3 to 5 years exp.) web developers to build a new development team here in Edmonton (development was formerly in Shanghai, China but we're moving it back here). We're primarily a PHP shop with some Java web services and Python data collection & analytic systems.
It's a super fun office to work in, we've got a mini-golf course in the office, plentiful snacks, a good fitness benefit, and several team social events each year (we went curling for Christmas last year, it was a blast!). Both positions come with the possibility of some travel to New York City and/or Los Angeles. Salary ranges are quite good for the Edmonton area, we're owned by IAC (Ask.com, About.com, Match.com etc.) who are a silicon valley company and they pay silicon valley wages.
The company is very successful and we're looking to grow it greatly in the near future.
Here's the HR BS about the company:
"Think Silicon Valley, but without the hassle of leaving Edmonton’s beautiful climate. Founded in Edmonton in 1999, Investopedia is a top consumer destination site for investing education, personal finance, market analysis, and trading tools – such as trading simulators, calculators, and test prep quizzes. At Investopedia, it’s our mission to provide trusted financial information to help people make intelligent investment decisions.
Investopedia has more than 14 million monthly unique viewers and 45 million page views each month. The site offers over 14,000 financial definitions, 4,000 articles, 2,000 FAQs, and hundreds of videos covering all aspects of finance and investing. We also offer successful stock and forex simulators, as well as a quiz application for people taking their finance professional exams, and an iOS app showcasing our finance dictionary.
Owned by IAC/InterActiveCorp, Investopedia collaborates frequently with other business units in the Inform Media Group, including Ask.com, About.com, and Dictionary.com. We have strategic partnerships with a range of companies, such as Microsoft, Google, Bloomberg, and Yahoo Finance."
Here's the job postings:
Sr.: https://iacsearch-openhire.silkroad.com/epostings/index.cfm?fuseaction=app.jobinfo&id=23&jobid=298&company_id=17111&version=7&source=ONLINE&JobOwner=993119&level=levelid1&levelid1=36360&parent=Web%20Development&startflag=2
Int.: https://iacsearch-openhire.silkroad.com/epostings/index.cfm?fuseaction=app.jobinfo&id=23&jobid=296&company_id=17111&version=7&source=ONLINE&JobOwner=993119&level=levelid1&levelid1=36360&parent=Web%20Development&startflag=2
You can apply at the links above or feel free to send me a message if you have any questions. We're looking for good people with solid development skills, if this is you please apply!
submitted by MrTheFinn to EdmontonJobs [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)

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  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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[Hiring] Sr. and Intermediate Web Developers, Edmonton, AB

That Oil & Gas industry company you're currently writing apps for looking a little shaky? Wanna move on? Consider this...
My company, Investopedia.com, are hiring both Senior (5+ years exp.) and Intermediate (3 to 5 years exp.) web developers to build a new development team here in Edmonton (development was formerly in Shanghai, China but we're moving it back here). We're primarily a PHP shop with some Java web services and Python data collection & analytic systems.
It's a super fun office to work in, we've got a mini-golf course in the office, plentiful snacks, a good fitness benefit, and several team social events each year (we went curling for Christmas last year, it was a blast!). Both positions come with the possibility of some travel to New York City and/or Los Angeles. Salary ranges are quite good for the Edmonton area, we're owned by IAC (Ask.com, About.com, Match.com etc.) who are a silicon valley company and they pay silicon valley wages.
The company is very successful and we're looking to grow it greatly in the near future.
Here's the HR BS about the company:
"Think Silicon Valley, but without the hassle of leaving Edmonton’s beautiful climate. Founded in Edmonton in 1999, Investopedia is a top consumer destination site for investing education, personal finance, market analysis, and trading tools – such as trading simulators, calculators, and test prep quizzes. At Investopedia, it’s our mission to provide trusted financial information to help people make intelligent investment decisions.
Investopedia has more than 14 million monthly unique viewers and 45 million page views each month. The site offers over 14,000 financial definitions, 4,000 articles, 2,000 FAQs, and hundreds of videos covering all aspects of finance and investing. We also offer successful stock and forex simulators, as well as a quiz application for people taking their finance professional exams, and an iOS app showcasing our finance dictionary.
Owned by IAC/InterActiveCorp, Investopedia collaborates frequently with other business units in the Inform Media Group, including Ask.com, About.com, and Dictionary.com. We have strategic partnerships with a range of companies, such as Microsoft, Google, Bloomberg, and Yahoo Finance."
Here's the job postings:
Sr.: https://iacsearch-openhire.silkroad.com/epostings/index.cfm?fuseaction=app.jobinfo&id=23&jobid=298&company_id=17111&version=7&source=ONLINE&JobOwner=993119&level=levelid1&levelid1=36360&parent=Web%20Development&startflag=2
Int.: https://iacsearch-openhire.silkroad.com/epostings/index.cfm?fuseaction=app.jobinfo&id=23&jobid=296&company_id=17111&version=7&source=ONLINE&JobOwner=993119&level=levelid1&levelid1=36360&parent=Web%20Development&startflag=2
You can apply at the links above or feel free to send me a message if you have any questions. We're looking for good people with solid development skills, if this is you please apply!
submitted by MrTheFinn to albertajobs [link] [comments]

Forex Compounding Interest Calculator How to Use Yahoo Finance - YouTube YouTube Why You're Failing as a Trader + Candle Sticks & Volume ... C# Tutorial 102: How to make a Live Currency Converter ... Best Volume Indicators You Can't Afford To Miss (Volume ...

Calculate live currency and foreign exchange rates with this free currency converter. You can convert currencies and precious metals with this currency calculator. Currency Converter. With our online currency converter you can calculate foreign exchange rates for more than 150 currencies and 6 precious metals. The Currency Converter uses daily Deltastock exchange rates and other leading market data contributors to supply precise information. Full currency converter. Has a database of historical values, and also allows bank commissions in the calculation. Exchange rates change all the time, and our live Currency Converter updates with it, making it the ideal tool to keep your eye on the market rate for any given currency. You don’t even need an account with us; just select the currency pair you want to see and our inbuilt market Exchange Rate Calculator will give you their latest market values. Forex Calculator What's it going to cost? Just use our Calculator - it's simple! First National Bank a division of FirstRand Bank Limited (the Bank) provides these calculators, which you accept are for convenience to provide results based on your input and assumptions and should not be used for any other purpose whatsoever. The Bank gives no warranty, express or implied, as to the accuracy ... Get fast and easy calculator for converting one currency to another using the latest live exchange rates. Also, get the latest news that could affect currency exchange rates. OANDA's currency calculator tools use OANDA Rates ... Please refer to the NFA's FOREX INVESTOR ALERT where appropriate. OANDA Europe Limited is a company registered in England number 7110087, and has its registered office at Floor 3, 18 St. Swithin's Lane, London EC4N 8AD. It is authorised and regulated by the Financial Conduct Authority, No: 542574. OANDA Japan Co., Ltd. First Type I ... Exchange rate updated from Yahoo Currency Converter. How to Use: Enter the desired amount. Select the “from” currency. Select the “to” currency. MYR Currency Exchange Rate on May 2017: 1 US Dollar = RM4.27 1 Singapore Dollar = RM3.08 1 Australian Dollar = RM3.17 1 UK Pound Sterling = RM5.47 1 Euro Dollar = RM4.77. RM1 = 7.99 Thai Baht RM1 = 3119.36 Indonesian Rupiah RM1 = 262.66 Korean ... Forex exchange rates in greenland news fountain gate cinemas cec live currency exchange rates stan forex exchange rate converter trading holland bank zanaco forex exchange rate us dollar to zambian kwacha conversion hong kong dollar hkd to canadian cad exchange rates history canada cad canadian dollars exchange rate calculator fx. Search for Forex Currency Converter at AllSearchSite.com! Browse Results · Related Answers · Find Answers · Related Information Services: Search Multiple Engines, Instant Results, Efficient Search, Find Information

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Forex Compounding Interest Calculator

Basic resources that yahoo finance offers. Future videos will now be posted in new channelhttps://www.youtube.com/channel/UCFCTutEm98uUFO3Q5-rHUdw/ #Stocks #Money #Trading Everyone wants the flash and the quick money...that's NOT how successful traders do it...They do it slowly and systematically. Get a ... Enjoy the videos and music you love, upload original content, and share it all with friends, family, and the world on YouTube. Volume-based trading is the technique of assessing the health of a trend based on volume activity. Discover the best volume indicators to incorporate in your... Discusses how to download two companies' stock returns from Yahoo Finance, and calculate (a) the variance and standard deviation of each stock, and (b) the cova... For Questions Contact Dr. Theodis Gamet At 206-354-1523 or email him at [email protected] currency converter help c# How best to calculate derived currency rate conversions using C# Updating the rates in my currency converter c# currency converter...

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