Algorithmic Developers

Algo Developers also called Quantitative Analysts or Quants, design and implement trading algorithms that apply artificial intelligence, machine learning, and deep learning techniques for the purpose of allowing financial firms to price and trade securities. They are employed primarily by proprietary trading firms, investment banks, hedge funds, and other financial institutions that manage funds or have trading/investment operations.  Quants typically work directly with traders, providing them with algos for the purpose of pricing or trading.

Posts

Alternative Data Portfolio Returns on Intraday Hold Trading Strategy

The Value in Machine Learning Alternative Data for Investment Managers

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A long-short portfolio outperforms the equal-weight S&P 500 ETF by 37.9%/year (after transaction costs) using Precision Alpha Alternative Data. Over 91.5% of the total return is pure alpha.

Environmental, Social, and Governance Data December 30, 2019

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In our study of Environmental, Social, and Governance (ESG) data, we looked at holding positions based upon the G&S Quotient short term price predictor score. We found that 5-day holds and 20-day holds using this score were very interesting and produced positive returns. Based on this data set we saw that you could have traded and held some of these stocks and closed your positions at the end of the day last Friday. See the charts for $ADBE, $AAPL, $MSFT, and $LDOS

CloudQuant Proves the Value in Environmental Social and Governance Alternative Data

CloudQuant LLC has proven the value in the G&S Quotient Environmental, Social, and Governance (ESG) alternative dataset. The detailed data science study shows a long-short portfolio with a five-day or twenty-day position holding period produces an investment strategy with single year Sharpe Ratios as high as 2.046 and Alphas as high as 5.24%. The study shows that the dataset is highly distinct from other standard and so-called “smart-beta” factors.
Algo Trading powered by Alternative Data Sets

Conversations: Effects of Alternative Data Sets on Trading Algorithms

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What effect can alternative data sets have on trading algorithms?

We asked a few of our teammates and systematic traders what the effect of alternative data sets is on trading algos. We thought we could spread some insight as to why our alternative data is so valuable the also developers. We all start using the smallest and most basic data sets, such as the generic S&P500 stock prices. This is all just fine until you want to take your development to the next level. You can delve deeper into predicting the rise and fall of each stock using these specified alternative data sets. CloudQuant offers a wide and expanding variety of these data sets for free, giving our users easy access to alternative data in order to help them improve their trading strategies.
The teammates featured are:
  • Tayloe Draughon- Sr. Product Manager
  • James Chang- Quantitative Portfolio Manager
  • Morgan Slade- CEO
  • Steve Pettinato- Portfolio Manager
  • Paul Tunney- Client Success Manager
Alogo Allocation

Record First Year Growth and a New Allocation to a Trading Strategy

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Chicago, Illinois, USA, August 29, 2018 – CloudQuant LLC is pleased to announce a new crowdsourced trading strategy license agreement. This marks the eighth successful partnership with a global algo developer, since their public launch one year ago. Researchers receive 10% of net trading profits under the terms of the license agreement.
Trading strategies require thought

Conversations: Recommendations to Someone Starting out at CloudQuant

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The CloudQuant team discusses their helpful thoughts for beginners on CloudQuant. We want to boost everyone starting out on our platform in their algo development and backtesting. Everyone in our company uses the CloudQuant website and coding platform in one way or another. We all use our own application, just like the crowd researchers. When we say that our free backtesting tools are “institutional grade” we really mean it. Every algo we run in our trading and investment strategies is proven in the same backtesting engine as the crowd uses. We rely on the scorecards, the reports, and the simulated trades to ensure that our trading is successful.
backtest chart

Conversations: What we wish we knew when we started AlgoTrading

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CloudQuant’s portfolio managers and quantitative algo traders look back on their starts in Algorithmic Trading. This candid overview allows everyone to see the “Things We Wish We Knew When We Started AlgoTrading”.  This is a short collection of the interviews with some of our amazing coders here in the office
$QQQ ETH spreads wider than RTH spreads

US Stock Market pre-market and post-market bid-ask spreads are different than regular trading hours

Hours and Market Data on The US Stock Markets

Regular Trading Hours (RTH) in the US Stock Market is 9:30 a.m. to 4:00 p.m. Eastern Time. Trading can happen in the Pre-market hours (4:00 a.m. to 9:30 a.m. ET) and in the After Hours (post) market (4:00 p.m. to 8:00). The pre-market and post-market are sometimes called Extended Trading Hours (ETH). ETH markets do not behave the same as the RT sometimes called after-hours trading. To illustrate this here are a few graphs that show the spread over time for some of the QQQ, one of the most popular trading symbols in both RTH and ETH. The following chart clearly shows that the average bid-ask spread during each minute bar varies widely in ETH. $QQQ ETH spreads wider than RTH spreads
  • The blue highlights are the pre-market hours.
  • The yellow highlights are RTH.
  • The green highlights are the post-market hours.
  This chart was generated using CloudQuant’s free historical backtesting tool. The python historical market data is shown below.
from cloudquant.interfaces import Strategy

    class CQb5e7901ea3bc4e22b0ffd861ce3f0287(Strategy):

    # note that this doesn't start with "self" because it's a @classmethod
    @classmethod
    def is_symbol_qualified(cls, symbol, md, service, account):
        return symbol=="QQQ" 

    # called at the beginning of each instance
    def on_start(self, md, order, service, account):
        self.filename = "spread_{}.csv".format(self.symbol)
        service.write_file(self.filename, "time,symbol,spread")

    # called every minute before the first on_trade of every new minute, or 5 seconds after a new minute starts
    def on_minute_bar(self, event, md, order, service, account, bar):
        mybars = md.bar.minute(start=-1,include_extended=True)
        if len(mybars.spread) > 0:
            service.write_file(self.filename, "{},{},{}".format(service.time_to_string(event.timestamp), self.symbol, mybars.spread[-1]))
        else:
            service.write_file(self.filename, "{},{},{}".format(service.time_to_string(event.timestamp), self.symbol, 0))

Fields available in the 1 minute bar data

Bars Access to historic Formed bar data Daily and Minute. For data from the forming bars (current incomplete “live” bar) see md.L1. above
md.bars. Data Passed in This is the data you pass to the bar calls
start An offset. Normally negative -10 = 10 days/minutes ago. Or a timestamp.
end An offset. Optional. Normally negative -8 = 8 days/minutes ago. Or a timestamp.
include_empty Returns bars for empty minutes, Empty bars contain NaN if no trades happened in bar (use .valid to check bar)
include_extended MINUTE ONLY Include pre/post minute bars
bar_size MINUTE ONLY Minute bar size. Based off 9:30 start time
today_only MINUTE EXTENDED ONLY Limits the bars returned to today only
md.bars Data returned This is the data returned by the bar call
askvol the volume of trades that occurred at the ask during timeframe
avgdelta Average change in price between trades during time period.
bidvol the volume of trades that occurred at the bid during timeframe
bvwap DAILY ONLY the vwap for the bar, see md.L1.minute_vwap for the vwap for the current minute
bwap LIVE MINUTE ONLY the vwap for the minute bar but is only available on the live trading system
close final, or closing price for the bar
closing_trade DAILY ONLY closing price for the symbol’s primary exchange (6 print, MOC print)
count number of items contributing to the bar
high highest price for the bar
length time length for the bar (rolled bars – see bar_size above)
low lowest price for the bar
open first qualifying trade of the bar, so for daily bars this will be the first non odd-lot print after 9:30
opening_trade DAILY ONLYopening price for the symbol’s primary exchange (‘O’ print, MOO print)if 0.0 use .open
spread average difference between the ask and the bid for the bar
symbol symbol for the bar
timestamp timestamps for the beginning of each bar, use service.time_to_string(muts,format=”%Y-%m-%d %H:%M:%S.%f”) to pull the date/time
valid whether or not bar is valid
volume volume for the bar
vwap volume weighted average price(vwap) of the bar, for minute bars this is the vwap for the day up to this point

1 Day Spread Supporting Data

Time Symbo Spread
4:01:01 AM QQQ 0.4700
4:02:05 AM QQQ 0.8300
4:03:05 AM QQQ 0.0375
4:04:05 AM QQQ 0.0300
4:05:05 AM QQQ 0.0300
4:06:01 AM QQQ 0.0475
4:07:05 AM QQQ 0.0567
4:08:05 AM QQQ 0.0600
4:09:05 AM QQQ 0.0500
4:10:05 AM QQQ 0.0500
4:11:05 AM QQQ 0.0500
4:12:05 AM QQQ 0.0700
4:13:05 AM QQQ 0.0700
4:14:00 AM QQQ 0.0000
4:15:05 AM QQQ 0.0350
4:16:05 AM QQQ 0.0500
4:17:05 AM QQQ 0.0500
4:18:05 AM QQQ 0.0000
4:19:05 AM QQQ 0.0000
4:20:05 AM QQQ 0.0000
4:21:05 AM QQQ 0.0600
4:22:05 AM QQQ 0.0700
4:23:05 AM QQQ 0.0600
4:24:05 AM QQQ 0.0250
4:25:05 AM QQQ 0.0486
4:26:05 AM QQQ 0.0400
4:27:05 AM QQQ 0.0400
4:28:05 AM QQQ 0.0300
4:29:05 AM QQQ 0.0300
4:30:05 AM QQQ 0.0200
4:31:05 AM QQQ 0.0133
4:32:05 AM QQQ 0.0133
4:33:05 AM QQQ 0.0300
4:34:05 AM QQQ 0.0300
4:35:05 AM QQQ 0.0300
4:36:05 AM QQQ 0.0300
4:37:05 AM QQQ 0.0000
4:38:05 AM QQQ 0.0000
4:39:05 AM QQQ 0.0300
4:40:02 AM QQQ 0.0200
4:41:05 AM QQQ 0.0225
4:42:05 AM QQQ 0.0300
4:43:05 AM QQQ 0.0200
4:44:05 AM QQQ 0.0300
4:45:05 AM QQQ 0.0400
4:46:05 AM QQQ 0.0400
4:47:05 AM QQQ 0.0200
4:48:05 AM QQQ 0.0200
4:49:05 AM QQQ 0.0300
4:50:05 AM QQQ 0.0300
4:51:05 AM QQQ 0.0000
4:52:05 AM QQQ 0.0000
4:53:05 AM QQQ 0.0300
4:54:05 AM QQQ 0.0300
4:55:05 AM QQQ 0.0000
4:56:03 AM QQQ 0.0000
4:57:05 AM QQQ 0.0250
4:58:05 AM QQQ 0.0250
4:59:05 AM QQQ 0.0000
5:00:05 AM QQQ 0.0000
5:01:05 AM QQQ 0.0300
5:02:05 AM QQQ 0.0300
5:03:05 AM QQQ 0.0000
5:04:05 AM QQQ 0.0250
5:05:05 AM QQQ 0.0400
5:06:05 AM QQQ 0.0300
5:07:05 AM QQQ 0.0300
5:08:05 AM QQQ 0.0000
5:09:05 AM QQQ 0.0000
5:10:05 AM QQQ 0.0000
5:11:05 AM QQQ 0.0300
5:12:05 AM QQQ 0.0300
5:13:05 AM QQQ 0.0300
5:14:05 AM QQQ 0.0300
5:15:05 AM QQQ 0.0300
5:16:05 AM QQQ 0.0000
5:17:03 AM QQQ 0.0187
5:18:05 AM QQQ 0.0300
5:19:05 AM QQQ 0.0300
5:20:05 AM QQQ 0.0300
5:21:05 AM QQQ 0.0300
5:22:05 AM QQQ 0.0300
5:23:05 AM QQQ 0.0300
5:24:05 AM QQQ 0.0000
5:25:05 AM QQQ 0.0000
5:26:05 AM QQQ 0.0000
5:27:05 AM QQQ 0.0000
5:28:05 AM QQQ 0.0300
5:29:05 AM QQQ 0.0300
5:30:05 AM QQQ 0.0300
5:31:05 AM QQQ 0.0300
5:32:05 AM QQQ 0.0200
5:33:05 AM QQQ 0.0250
5:34:05 AM QQQ 0.0250
5:35:05 AM QQQ 0.0233
5:36:05 AM QQQ 0.0300
5:37:05 AM QQQ 0.0300
5:38:05 AM QQQ 0.0300
5:39:05 AM QQQ 0.0050
5:40:02 AM QQQ 0.0050
5:41:05 AM QQQ 0.0333
5:42:05 AM QQQ 0.0300
5:43:05 AM QQQ 0.0300
5:44:05 AM QQQ 0.0220
5:45:05 AM QQQ 0.0300
5:46:05 AM QQQ 0.0100
5:47:00 AM QQQ 0.0400
5:48:05 AM QQQ 0.0367
5:49:05 AM QQQ 0.0367
5:50:05 AM QQQ 0.0400
5:51:05 AM QQQ 0.0300
5:52:05 AM QQQ 0.0100
5:53:05 AM QQQ 0.0233
5:54:05 AM QQQ 0.0333
5:55:05 AM QQQ 0.0400
5:56:05 AM QQQ 0.0400
5:57:05 AM QQQ 0.0300
5:58:05 AM QQQ 0.0150
5:59:05 AM QQQ 0.0150
6:00:05 AM QQQ 0.0300
6:01:05 AM QQQ 0.0200
6:02:01 AM QQQ 0.0200
6:03:02 AM QQQ 0.0300
6:04:05 AM QQQ 0.0150
6:05:05 AM QQQ 0.0150
6:06:05 AM QQQ 0.0400
6:07:05 AM QQQ 0.0400
6:08:05 AM QQQ 0.0400
6:09:04 AM QQQ 0.0300
6:10:05 AM QQQ 0.0400
6:11:05 AM QQQ 0.0400
6:12:05 AM QQQ 0.0100
6:13:05 AM QQQ 0.0100
6:14:04 AM QQQ 0.0300
6:15:05 AM QQQ 0.0364
6:16:05 AM QQQ 0.0364
6:17:05 AM QQQ 0.0400
6:18:05 AM QQQ 0.0400
6:19:05 AM QQQ 0.0317
6:20:05 AM QQQ 0.0300
6:21:02 AM QQQ 0.0400
6:22:02 AM QQQ 0.0200
6:23:05 AM QQQ 0.0400
6:24:05 AM QQQ 0.0400
6:25:03 AM QQQ 0.0417
6:26:05 AM QQQ 0.0400
6:27:05 AM QQQ 0.0400
6:28:05 AM QQQ 0.0400
6:29:05 AM QQQ 0.0400
6:30:05 AM QQQ 0.0100
6:31:05 AM QQQ 0.0400
6:32:05 AM QQQ 0.0214
6:33:05 AM QQQ 0.0300
6:34:05 AM QQQ 0.0300
6:35:05 AM QQQ 0.0400
6:36:05 AM QQQ 0.0400
6:37:05 AM QQQ 0.0100
6:38:05 AM QQQ 0.0100
6:39:05 AM QQQ 0.0000
6:40:05 AM QQQ 0.0300
6:41:05 AM QQQ 0.0300
6:42:05 AM QQQ 0.0300
6:43:05 AM QQQ 0.0300
6:44:05 AM QQQ 0.0300
6:45:05 AM QQQ 0.0000
6:46:05 AM QQQ 0.0000
6:47:05 AM QQQ 0.0000
6:48:05 AM QQQ 0.0200
6:49:03 AM QQQ 0.0238
6:50:05 AM QQQ 0.0275
6:51:04 AM QQQ 0.0275
6:52:05 AM QQQ 0.0250
6:53:05 AM QQQ 0.0225
6:54:05 AM QQQ 0.0225
6:55:03 AM QQQ 0.0000
6:56:05 AM QQQ 0.0300
6:57:05 AM QQQ 0.0300
6:58:05 AM QQQ 0.0200
6:59:04 AM QQQ 0.0100
7:00:00 AM QQQ 0.0080
7:01:05 AM QQQ 0.0169
7:02:01 AM QQQ 0.0156
7:03:03 AM QQQ 0.0140
7:04:05 AM QQQ 0.0131
7:05:05 AM QQQ 0.0100
7:06:05 AM QQQ 0.0067
7:07:05 AM QQQ 0.0067
7:08:05 AM QQQ 0.0087
7:09:05 AM QQQ 0.0213
7:10:02 AM QQQ 0.0073
7:11:05 AM QQQ 0.0208
7:12:05 AM QQQ 0.0325
7:13:05 AM QQQ 0.0275
7:14:05 AM QQQ 0.0086
7:15:05 AM QQQ 0.0125
7:16:05 AM QQQ 0.0025
7:17:05 AM QQQ 0.0025
7:18:01 AM QQQ 0.0250
7:19:05 AM QQQ 0.0147
7:20:05 AM QQQ 0.0260
7:21:05 AM QQQ 0.0176
7:22:05 AM QQQ 0.0244
7:23:05 AM QQQ 0.0244
7:24:05 AM QQQ 0.0000
7:25:05 AM QQQ 0.0300
7:26:05 AM QQQ 0.0300
7:27:05 AM QQQ 0.0224
7:28:05 AM QQQ 0.0300
7:29:05 AM QQQ 0.0167
7:30:05 AM QQQ 0.0129
7:31:03 AM QQQ 0.0089
7:32:05 AM QQQ 0.0085
7:33:05 AM QQQ 0.0240
7:34:05 AM QQQ 0.0161
7:35:02 AM QQQ 0.0089
7:36:05 AM QQQ -0.0020
7:37:05 AM QQQ 0.0100
7:38:05 AM QQQ 0.0100
7:39:05 AM QQQ 0.0044
7:40:05 AM QQQ 0.0200
7:41:04 AM QQQ 0.0000
7:42:03 AM QQQ 0.0100
7:43:01 AM QQQ 0.0125
7:44:05 AM QQQ 0.0208
7:45:05 AM QQQ 0.0100
7:46:05 AM QQQ 0.0250
7:47:05 AM QQQ 0.0112
7:48:05 AM QQQ 0.0064
7:49:05 AM QQQ 0.0064
7:50:05 AM QQQ 0.0000
7:51:05 AM QQQ 0.0000
7:52:05 AM QQQ 0.0050
7:53:03 AM QQQ 0.0100
7:54:05 AM QQQ 0.0200
7:55:05 AM QQQ 0.0100
7:56:05 AM QQQ 0.0200
7:57:05 AM QQQ 0.0267
7:58:05 AM QQQ 0.0226
7:59:05 AM QQQ 0.0075
8:00:01 AM QQQ 0.0040
8:01:02 AM QQQ 0.0085
8:02:05 AM QQQ 0.0171
8:03:05 AM QQQ 0.0200
8:04:01 AM QQQ 0.0200
8:05:01 AM QQQ 0.0183
8:06:00 AM QQQ 0.0210
8:07:05 AM QQQ 0.0189
8:08:04 AM QQQ 0.0150
8:09:05 AM QQQ 0.0167
8:10:05 AM QQQ 0.0100
8:11:05 AM QQQ 0.0225
8:12:05 AM QQQ 0.0200
8:13:05 AM QQQ 0.0025
8:14:05 AM QQQ 0.0133
8:15:02 AM QQQ 0.0025
8:16:00 AM QQQ 0.0150
8:17:05 AM QQQ 0.0200
8:18:05 AM QQQ 0.0200
8:19:05 AM QQQ 0.0100
8:20:05 AM QQQ 0.0200
8:21:05 AM QQQ 0.0113
8:22:05 AM QQQ 0.0120
8:23:05 AM QQQ 0.0300
8:24:03 AM QQQ 0.0200
8:25:05 AM QQQ 0.0021
8:26:00 AM QQQ 0.0200
8:27:05 AM QQQ 0.0300
8:28:05 AM QQQ 0.0400
8:29:05 AM QQQ 0.0175
8:30:05 AM QQQ 0.0125
8:31:05 AM QQQ 0.0117
8:32:05 AM QQQ 0.0214
8:33:05 AM QQQ 0.0214
8:34:03 AM QQQ 0.0160
8:35:05 AM QQQ 0.0471
8:36:05 AM QQQ 0.0075
8:37:05 AM QQQ 0.0075
8:38:05 AM QQQ 0.0300
8:39:05 AM QQQ 0.0200
8:40:05 AM QQQ 0.0200
8:41:05 AM QQQ 0.0238
8:42:00 AM QQQ 0.0200
8:43:04 AM QQQ 0.0220
8:44:05 AM QQQ 0.0200
8:45:01 AM QQQ 0.0086
8:46:05 AM QQQ 0.0306
8:47:05 AM QQQ 0.0189
8:48:00 AM QQQ 0.0167
8:49:05 AM QQQ 0.0150
8:50:05 AM QQQ 0.0100
8:51:02 AM QQQ 0.0023
8:52:01 AM QQQ 0.0237
8:53:05 AM QQQ 0.0218
8:54:05 AM QQQ 0.0262
8:55:05 AM QQQ 0.0186
8:56:05 AM QQQ 0.0100
8:57:05 AM QQQ 0.0162
8:58:05 AM QQQ 0.0133
8:59:05 AM QQQ 0.0125
9:00:05 AM QQQ 0.0217
9:01:05 AM QQQ 0.0160
9:02:05 AM QQQ 0.0144
9:03:05 AM QQQ 0.0100
9:04:05 AM QQQ 0.0067
9:05:05 AM QQQ 0.0200
9:06:01 AM QQQ 0.0127
9:07:05 AM QQQ 0.0100
9:08:00 AM QQQ 0.0141
9:09:05 AM QQQ 0.0137
9:10:05 AM QQQ 0.0100
9:11:04 AM QQQ 0.0147
9:12:05 AM QQQ 0.0026
9:13:05 AM QQQ 0.0100
9:14:05 AM QQQ 0.0136
9:15:05 AM QQQ 0.0186
9:16:05 AM QQQ 0.0125
9:17:03 AM QQQ 0.0212
9:18:05 AM QQQ 0.0108
9:19:05 AM QQQ 0.0174
9:20:02 AM QQQ 0.0180
9:21:05 AM QQQ 0.0216
9:22:02 AM QQQ 0.0162
9:23:05 AM QQQ 0.0200
9:24:05 AM QQQ 0.0125
9:25:03 AM QQQ 0.0076
9:26:05 AM QQQ 0.0100
9:27:03 AM QQQ 0.0100
9:28:00 AM QQQ 0.0090
9:29:05 AM QQQ 0.0066
9:30:00 AM QQQ 0.0120
9:31:01 AM QQQ 0.0106
9:32:00 AM QQQ 0.0100
9:33:00 AM QQQ 0.0108
9:34:00 AM QQQ 0.0105
9:35:00 AM QQQ 0.0088
9:36:00 AM QQQ 0.0105
9:37:00 AM QQQ 0.0106
9:38:00 AM QQQ 0.0101
9:39:00 AM QQQ 0.0104
9:40:00 AM QQQ 0.0093
9:41:00 AM QQQ 0.0103
9:42:00 AM QQQ 0.0099
9:43:00 AM QQQ 0.0095
9:44:01 AM QQQ 0.0110
9:45:00 AM QQQ 0.0101
9:46:00 AM QQQ 0.0098
9:47:01 AM QQQ 0.0096
9:48:01 AM QQQ 0.0098
9:49:00 AM QQQ 0.0104
9:50:01 AM QQQ 0.0102
9:51:01 AM QQQ 0.0102
9:52:00 AM QQQ 0.0087
9:53:02 AM QQQ 0.0093
9:54:01 AM QQQ 0.0100
9:55:00 AM QQQ 0.0099
9:56:00 AM QQQ 0.0096
9:57:01 AM QQQ 0.0096
9:58:01 AM QQQ 0.0096
9:59:00 AM QQQ 0.0100
10:00:00 AM QQQ 0.0110
10:01:00 AM QQQ 0.0099
10:02:00 AM QQQ 0.0102
10:03:00 AM QQQ 0.0096
10:04:00 AM QQQ 0.0099
10:05:00 AM QQQ 0.0101
10:06:00 AM QQQ 0.0099
10:07:01 AM QQQ 0.0103
10:08:02 AM QQQ 0.0099
10:09:02 AM QQQ 0.0110
10:10:02 AM QQQ 0.0100
10:11:00 AM QQQ 0.0102
10:12:01 AM QQQ 0.0090
10:13:00 AM QQQ 0.0099
10:14:01 AM QQQ 0.0100
10:15:00 AM QQQ 0.0099
10:16:00 AM QQQ 0.0099
10:17:00 AM QQQ 0.0099
10:18:01 AM QQQ 0.0100
10:19:01 AM QQQ 0.0101
10:20:00 AM QQQ 0.0094
10:21:01 AM QQQ 0.0097
10:22:00 AM QQQ 0.0100
10:23:01 AM QQQ 0.0098
10:24:00 AM QQQ 0.0100
10:25:01 AM QQQ 0.0099
10:26:01 AM QQQ 0.0100
10:27:00 AM QQQ 0.0098
10:28:01 AM QQQ 0.0099
10:29:00 AM QQQ 0.0099
10:30:01 AM QQQ 0.0100
10:31:01 AM QQQ 0.0101
10:32:00 AM QQQ 0.0085
10:33:00 AM QQQ 0.0101
10:34:01 AM QQQ 0.0100
10:35:02 AM QQQ 0.0097
10:36:01 AM QQQ 0.0100
10:37:01 AM QQQ 0.0098
10:38:01 AM QQQ 0.0091
10:39:00 AM QQQ 0.0099
10:40:01 AM QQQ 0.0099
10:41:01 AM QQQ 0.0095
10:42:00 AM QQQ 0.0099
10:43:00 AM QQQ 0.0100
10:44:00 AM QQQ 0.0099
10:45:00 AM QQQ 0.0097
10:46:00 AM QQQ 0.0099
10:47:01 AM QQQ 0.0099
10:48:00 AM QQQ 0.0093
10:49:01 AM QQQ 0.0101
10:50:00 AM QQQ 0.0087
10:51:00 AM QQQ 0.0101
10:52:01 AM QQQ 0.0093
10:53:00 AM QQQ 0.0110
10:54:00 AM QQQ 0.0093
10:55:01 AM QQQ 0.0102
10:56:03 AM QQQ 0.0095
10:57:01 AM QQQ 0.0088
10:58:00 AM QQQ 0.0098
10:59:00 AM QQQ 0.0098
11:00:00 AM QQQ 0.0102
11:01:01 AM QQQ 0.0107
11:02:01 AM QQQ 0.0102
11:03:01 AM QQQ 0.0100
11:04:01 AM QQQ 0.0099
11:05:02 AM QQQ 0.0092
11:06:01 AM QQQ 0.0101
11:07:01 AM QQQ 0.0104
11:08:05 AM QQQ 0.0100
11:09:01 AM QQQ 0.0095
11:10:00 AM QQQ 0.0108
11:11:00 AM QQQ 0.0103
11:12:01 AM QQQ 0.0100
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Trevor Trinkino Quantitative Trader

Machine Learning FXCM Webinar with Trevor Trinkino of CloudQuant – Part 2/3

On May 15th Trevor Trinkino presented part two of a three-part Machine Learning webinar with FXCM. Part one is here.

Part 2  – Preprocess data for Random Forest. PnL and prediciton improvements…

In part two Trevor goes over how to clean and pre-process data from CloudQuant to use in a Random Forest Classifier. He then looks at the prediction and PnL improvements seen from utilizing this classifier as well as adjusting the hyper-parameters of the model. Files mentioned in the video are available from our Google Drive below.. Ipython Notebook Trades.csv FilteredClfFeatsBF100_50.csv MLClassData.csv