turtle-trading

Profit using trend trading

return

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)

strategy

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.

backtest

• 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

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

handle-data

Process data every minute. Executes from 6:31 AM to 5 PM UTC-4.

clear-stops

Clear stops 1 minute after market open.

log-risks

Log long and short risk 1 minute before market close.

get-prices

Get high, low, and close prices. Get 22 daily bars for computing average true range.

validate-prices

Drop markets with null prices.

compute-highs

Compute 20 and 55 day high. Get highest high for the past 20 and 55 days.

compute-lows

Compute 20 and 55 day low. Get lowest low for the past 20 and 55 days.

get-contracts

Get futures contracts.

is-trade-allowed

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

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

Compute dollar volatilities, or dollars per point.

context.dollar_volatility = multiplier * average_true_range

compute-trade-sizes

Compute trade sizes, or amount per trade.

context.trade_size = context.capital * context.capital_risk_per_trade / context.dollar_volatility

update-risks

Update long, short, and market risks.

place-stop-orders

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.

detect-entry-signals

Place limit orders on 20 or 55 day breakout.

reflect

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 in handle_data()
• Scalar value saved to context in handle_data() is accessible in before_trading_start() and schedule_function()
• Scalar value saved to context in before_trading_start() or schedule_function() is not accessible in handle_data()
• 3-dimensional array saved to context in before_trading_start() or schedule_function() is not accessible in handle_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.