Backtest multiple assets with different parameters of indicator

[rafalsza]

Hi
Please help me with backtest these assets with different indicator's parameters
e.g. multiplier = [3.0,3.1,3.2]
length = [7,10,12]

symbols = ["BTCUSDT", "ETHUSDT", "LTCUSDT", "BNBUSDT", "SOLUSDT"]

interval = '4h'
df = vbt.BinanceData.download(symbols,start='12 months ago UTC', interval=interval).concat()

df1 = vbt.pandas_ta('ha').run(df['Open'], df['High'], df['Low'], df['Close'])
multiplier = 3.
length = 7
st = vbt.pandas_ta('supertrend').run(df1.ha_high, df1.ha_low,df1.ha_close, length=length, multiplier=multiplier)
entries = st.supert_below(df1.ha_close)
exits = st.supert_above(df1.ha_close)
vbt.settings.portfolio['fees'] = 0.00075
vbt.settings.portfolio['sl_stop'] = 0.045
vbt.settings.portfolio['init_cash'] = 1000
vbt.settings.portfolio['freq'] = '4h'

portfolio1 = vbt.Portfolio.from_signals(df['Close'], entries, exits, group_by=True)
portfolio2 = vbt.Portfolio.from_signals(df['Close'], entries, exits)
cheight, cwidth = 600, 800
plot2 = portfolio2.value().vbt.plot(height=cheight, width=cwidth).show()
plot1 = portfolio1.plot_cum_returns(height=cheight, width=cwidth).show()
print(portfolio2.total_return(group_by='symbol'))
print(portfolio2.stats(group_by=True))
print(portfolio1.trades.records_readable)

[polakowo]

Pass them as lists.

[rafalsza]

thank you, an excellent framework so far :)

[rafalsza]

some small error I have now:
``
ValueError Traceback (most recent call last)

in ()
21 plot2 = portfolio2.value().vbt.plot(height=cheight, width=cwidth).show()
22 plot1 = portfolio1.plot_cum_returns(height=cheight, width=cwidth).show()
---> 23 print(portfolio2.total_return(group_by='symbol'))
24 print(portfolio2.stats(group_by=True))
25 print(portfolio1.trades.records_readable)

8 frames

/usr/local/lib/python3.7/dist-packages/vectorbt/base/column_grouper.py in get_group_lens(self, group_by, **kwargs)
272 """See get_group_lens_nb."""
273 if not self.is_sorted(group_by=group_by):
--> 274 raise ValueError("group_by must lead to groups that are coherent and sorted "
275 "(such as [0, 0, 1, 2, 2, ...])")
276 group_by = self.resolve_group_by(group_by=group_by, **kwargs)

ValueError: group_by must lead to groups that are coherent and sorted (such as [0, 0, 1, 2, 2, ...])

[polakowo]

You grouped by symbol, which comes like this in your columns [0, 1, 2, 0, 1, 2, ...]. Portfolio requires that they come like this [0, 0, 1, 1, 2, 2, ...]. You can sort this column level using Pandas and then group. But since you do it at the analysis step, just do total_return(group_by=False) and analyze this Series using Pandas, such as total_return(group_by=False).group_by('symbol').mean().