Hi,
I have been recently be working on this algo for a college seminar. I currently pick 25 stocks for my long positions and 25 for my short positions with equal weights; How can I make this weights more variable?
Let's say one of my indicators in my market_close_trades function gives me a huge positive signal to go long. How can I modify my code so that the algo invests more in that opportunity?
Thanks so much in advance,
Mattia
Variable weights instead of fixed ones
Some code I copy/pasted from my algorithms, so you might want to double check that
# this is the factor
overnight_returns = returns.iloc[-1]
# compute weights, helper function
def to_weights(factor):
demeaned_vals = factor - factor.mean()
return demeaned_vals / demeaned_vals.abs().sum()
# factor to weights
weights = to_weights(overnight_returns)
longs = weights[ weights > 0 ]
shorts = weights[ weights < 0 ].abs()
# limit number of securities
if context.max_long_sec:
longs = longs.order(ascending=False).head(context.max_long_sec)
if context.max_short_sec:
shorts = shorts.order(ascending=False).head(context.max_short_sec)
# normalize weights to 1.
longs /= longs.sum()
shorts /= shorts.sum()
longs /= 2
shorts /= 2
Hi Luca,
First of all thanks so much, thanks to your help I have definitively improved my long run result, from this:
To this one:
My only concern is:
if on the one hand in the "market_close_trades" function I found no issues in implementing the strategy; on the other hand, when I tried to do the exact same process for the "market_open_trades" it doesn't seem to work properly. Do I have do build a helper function for every single function individually? Or do you have any suggestions?
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