Solved, Turtle Trading strategy

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edited Jun 24, 2020

It based on Richard Donchian strategy
We calculate the N using ATR(Average True Range) from Talib
Unit =0.01 of the account size / ATR

Here is the strategy and Add strategy is the core:

1st Buy: First time break Donchian upper limit(last 20 days max), buy 1 unit
2nd Buy: When price went up by 0.5N, we buy another 1 unit.
3rd Buy: Same, When price went up by 0.5N, we buy another 1 unit.
4th Buy: Same, but this is the last buy. We do not add anymore
SELL: when current price drop below 20 days min, we sell to 0.

Problems are:

I record the 1st buy construct a DataFrame called 'recordme' but by the time we reach 2nd buy, 'recordme' is still empty for some reason. I cannot find why it is not recording?

2015-02-09 16:30 rebalance:61 INFO Empty DataFrame  
Columns: [add_time, last_buy_price, symbols]  
Index: []

2.following strategy went wrong when it sees a empty Series. Here I was trying to substract a value instead of a Series. I don't know if we fix the 1 problem, this will be solved accordingly.

I've asked help once of this strategy, but it doesn't seem to fix the problem
from: if cur_price > add_price and add_unit < 4:
to: if cur_price > add_price[-1] and add_unit[-1] < 4:
I don't think its the prime problem though.
Notes:
True Range = Max(High-Low,abs(High-PreClose),abs(PreClose-Low))
ATR = MA(TrueRange, 20)
N = (PreN[-19：] + True Range) / 20

2 responses

Dan Whitnable

Jun 23, 2020

I'll try to answer your questions.

I record the 1st buy construct a DataFrame called 'recordme' but by the time we reach 2nd buy, 'recordme' is still empty for some reason. I cannot find why it is not recording?
The issue is the following code. recordme keeps getting set to a new empty dataframe at the beginning of rebalance. That is why it always appears empty. Probably want to do this only once in initialize.

def rebalance(context, data):  
    global recordme  
    hist = data.history(context.securities, ['high', 'low', 'close'], 200, '1d')  
    account_size = context.portfolio_size  
    recordme = pd.DataFrame({'symbols':[],'add_time':[],'last_buy_price':[]})

2.following strategy went wrong when it sees a empty Series. Here I was trying to subtract a value instead of a Series. I don't know if we fix the 1 problem, this will be solved accordingly.
Yes, the issue should be solved if recordme isn't set to a new empty dataframe each time the algo runs rebalance. However, you should never store prices like this. If there is a stock split one will end up comparing the split price with the previous un-split price. Maybe consider using the cost_basis attribute of a position. This will be the split-adjusted weighted average price of an open position. There's info on that attribute here.

Try those things and reply if you hit any roadblocks.

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ZT YE

Jun 24, 2020

@Dan, Thanks a lot! I think its fixed.

I have tried using last_price= context.portfolio.positions[context.securities].cost_basis, but it has problems
1.last_price= context.portfolio.positions[symbol('AAPL')].cost_basis,
SPY doesn't work here. I think either it doesn't take SPY as input because its a ETF.

2.context.portfolio.positions[context.securities].cost_basis.
somehow, I cannot using 'for loop' in it.

I will dig deeper, bigger chance is that I didn't research enough. But I am really happy its runs. Its been bugging me too long.
Thank you again

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