symbols = ["BTC-USD", "ETH-USD", "LTC-USD"]
price = vbt.YFData.download(symbols, missing_index='drop').get('Close')

windows = np.arange(2, 101)
fast_ma, slow_ma = vbt.MA.run_combs(price, window=windows, r=2, short_names=['fast', 'slow'])
entries = fast_ma.ma_crossed_above(slow_ma)
exits = fast_ma.ma_crossed_below(slow_ma)

pf_kwargs = dict(size=np.inf, fees=0.001, freq='1D')
pf = vbt.Portfolio.from_signals(price, entries, exits, **pf_kwargs)

fig = pf.total_return().vbt.heatmap(
    x_level='fast_window', y_level='slow_window', slider_level='symbol', symmetric=True,
    trace_kwargs=dict(colorbar=dict(title='Total return', tickformat='%')))
fig.show()