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calculating expectancy and sort pairs accordingly instead of delta

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This commit is contained in:
misagh 2018-09-24 17:47:50 +02:00
parent a806dd45f2
commit e8716f16ad
1 changed files with 12 additions and 9 deletions
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21
freqtrade/edge/__init__.py
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@ -355,20 +355,23 @@ class Edge():
return x
##############################
# The difference between risk reward ratio and required risk reward
# We use it as an indicator to find the most interesting pair to trade
def delta(x):
x = (abs(1/ ((x[x < 0].sum() / x[x < 0].count()) / (x[x > 0].sum() / x[x > 0].count())))) - (1/(x[x > 0].count()/x.count()) -1)
# Expectancy
# Tells you the interest percentage you should hope
# E.x. if expectancy is 0.35, on $1 trade you should expect a target of $1.35
def expectancy(x):
average_win = float(x[x > 0].sum() / x[x > 0].count())
average_loss = float(abs(x[x < 0].sum() / x[x < 0].count()))
winrate = float(x[x > 0].count()/x.count())
x = ((1 + average_win/average_loss) * winrate) - 1
return x
##############################
final = results.groupby(['pair', 'stoploss'])['profit_abs'].\
agg([winrate, risk_reward_ratio, required_risk_reward, delta]).\
reset_index().sort_values(by=['delta', 'stoploss'], ascending=False)\
.groupby('pair').first().sort_values(by=['delta'], ascending=False)
agg([winrate, risk_reward_ratio, required_risk_reward, expectancy]).\
reset_index().sort_values(by=['expectancy', 'stoploss'], ascending=False)\
.groupby('pair').first().sort_values(by=['expectancy'], ascending=False)
# Returning an array of pairs in order of "delta"
# Returning an array of pairs in order of "expectancy"
return final.reset_index().values
def backslap_pair(self, ticker_data, pair, stoploss):