Profit using trend trading
| Date | Return % |
|---|---|
| 2003-08-05 to 2004-01-01 | (78.28) |
| 2004-01-01 to 2005-01-01 | (2286.12) |
| 2005-01-01 to 2006-01-01 | (301.43) |
| 2006-01-01 to 2007-01-01 | (309.42) |
| 2007-01-01 to 2008-01-01 | 4172.06 |
| 2008-01-01 to 2009-01-01 | 3712.64 |
| 2009-01-01 to 2010-01-01 | 53.81 |
| 2010-01-01 to 2011-01-01 | 21.81 |
| 2011-01-01 to 2012-01-01 | (78.31) |
| 2012-01-01 to 2013-01-01 | 2.45 |
| 2013-01-01 to 2014-01-01 | (24.78) |
| 2014-01-01 to 2015-01-01 | (20.22) |
| 2015-01-01 to 2016-01-01 | (50.79) |
| 2016-01-01 to 2017-01-01 | (30.94) |
| 2017-01-01 to 2017-05-26 | (16.36) |
See https://github.com/vyq/turtle-trading/raw/master/the-original-turtle-trading-rules.pdf
Exit on price hitting trailing stop of 2 times average true range.
- Start date: 2003-08-05
- End date: 2017-05-25
- Cash: USD 1,000,000
- Trading calendar: US Futures
Suppress null warnings after first log message: https://www.quantopian.com/posts/warn-numpy-slash-lib-slash-nanfunctions-dot-py-319-runtimewarning-all-nan-slice-encountered
Initialize parameters. Executes at 1970-01-01 7 PM UTC-4. Intersect Quantopian futures universe with Turtle Trading markets.
Universe: https://www.quantopian.com/help#available-futures
Process data every minute. Executes from 6:31 AM to 5 PM UTC-4.
Clear stops 1 minute after market open.
Log long and short risk 1 minute before market close.
Get high, low, and close prices. Get 22 daily bars for computing average true range.
Drop markets with null prices.
Compute 20 and 55 day high. Get highest high for the past 20 and 55 days.
Compute 20 and 55 day low. Get lowest low for the past 20 and 55 days.
Get futures contracts.
Check if allowed to trade.
Do not trade if:
- Cash is less than or equal to 0
- Capital is less than or equal to 0
- Price is less than 1
- Open order exists for this market
- Exceed market risk limit
- Exceed direction risk limit
Compute average true ranges, or N. Use a rolling window that is 1 day larger than the moving average.
Average true range: https://mrjbq7.github.io/ta-lib/func_groups/volatility_indicators.html
TA-Lib module: https://www.quantopian.com/help#ide-module-import
Compute dollar volatilities, or dollars per point.
context.dollar_volatility = multiplier * average_true_range
Compute trade sizes, or amount per trade.
context.trade_size = context.capital * context.capital_risk_per_trade / context.dollar_volatility
Update long, short, and market risks.
Place stop orders at 2 times average true range.
If long and price is greater than or equal to cost_basis, then context.stop[market] = price - context.average_true_range[market] * context.stop_multiplier.
If long and price is less than cost_basis, then context.stop[market] = cost_basis - context.average_true_range[market] * context.stop_multiplier.
If short and price is greater than or equal to cost_basis, then context.stop[market] = cost_basis + context.average_true_range[market] * context.stop_multiplier.
If short and price is less than cost_basis, then context.stop[market] = price + context.average_true_range[market] * context.stop_multiplier.
Place limit orders on 20 or 55 day breakout.
Markets are fixed or dynamic:
- Fixed markets allow consistency over time
- Dynamic markets generate ideas over time
Context has limitations:
- Scalar value saved to context in
initialize()is accessible inhandle_data() - Scalar value saved to context in
handle_data()is accessible inbefore_trading_start()andschedule_function() - Scalar value saved to context in
before_trading_start()orschedule_function()is not accessible inhandle_data() - 3-dimensional array saved to context in
before_trading_start()orschedule_function()is not accessible inhandle_data()
Define context variable in initialize(), so that it can be used in other methods.
data.history() contains data from the first minute of the current market day, if called in handle_data().
before_trading_start() should not be used for futures as it executes at 8:45 AM UTC-4.
context.contract.multiplier equates to dollars per point.
context.trade_size will be less than or equal to 0 if context.dollar_volatility is larger than context.capital * context.capital_risk_per_trade.
Orders placed at end of day may fail to fill because of insufficient liquidity.
context.portfolio.positions[position].amount is negative if position is short.
There are dates where data.history() returns null prices for all markets.
Risk limits do not account for partial fills.
Direction risk limit is not capped at 12.