I have a bot that performs like this:
Dataset
Crypto
Start Date
31 Dec 2017
End Date
31 Dec 2021
Capital
100000
RETURNS
3231.22%
ALPHA
1.42
BETA
0.05
SHARPE
1.15
DRAWDOWN
-76.73%
And when I change the capital to 10000 i get:
RETURNS
-67.64%
ALPHA
0.76
BETA
-0.29
SHARPE
0.48
DRAWDOWN
-99.07%
If i increase the capital also it goes down.
How can this be?
Feel free to email me perhaps then Ill be able to shgare pictures and even code.
Namaste
Hi Jenny,
A sharp decline in the performance of the algorithm is unlikely when you increase/decrease the capital as you mentioned.
If you are backtesting in the Blueshift platform, please share the code with the Blueshift support (blueshift-support@quantinsti.com). If you have already shared this with the Blueshift team, you will get a reply soon.
If you are performing backtesting in python environment, please share the code and datasets used for further assistance.
Hope this helps!
Thank you
Look at it clearfully. Its super basic. I use a ratio depending on if its a buy or sell and if its the first or second asset and I multiply this by a percent based on the amount of pairs im trading at the time.
So if i have 2 assets ill multiply my ratio by 0.5 So each pair get the same weights.
if df1['numUnits'].iloc[-1]==1:
print("{} Long entry".format(get_datetime()))
order_target_percent(s1, ((1/(abs(((df1['hr'].iloc[-1])))+1)))(1/len(list_sect)))
print("{} Short entry".format(get_datetime()))
order_target_percent(s2, ((df1['hr'].iloc[-1]/(abs(((df1['hr'].iloc[-1])))+1)))((1/len(list_sect))))
if df1['numUnits'].iloc[-1]==-1:
print("{} Short entry".format(get_datetime()))
order_target_percent(s1, ((df1['hr'].iloc[-1]/(abs(((df1['hr'].iloc[-1])))+1)))((1/len(list_sect))))
print("{} Long entry".format(get_datetime()))
order_target_percent(s2, ((1/(abs(((df1['hr'].iloc[-1])))+1)))(1/len(list_sect)))
if df1['numUnits'].iloc[-1]==0:
print("{} Long exit".format(get_datetime()))
order_target_percent(s1, 0)
print("{} Long exit".format(get_datetime()))
order_target_percent(s2, 0)