Warped Looking Graph
#465
Replies: 1 comment
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This is because your data contains gaps. Pass something like this to pf.plot (you can provide gaps manually, see https://community.plotly.com/t/how-to-use-rangebreaks-for-a-datetime-index-at-levels-smaller-than-1-hour/46073): xaxis=dict(rangebreaks=[
dict(bounds=["sat", "mon"]), # hide weekends
dict(values=["2015-12-25", "2016-01-01"]) # hide Christmas and New Year's
]) |
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Hi,
I am new to VectorBT.
I am probably missing something in the docs that is super obvious, but I can't seem to get around this issue.
When I try to do simple analysis of a MA crossover for a particular stock for an interval of 5 min, it returns a warped graph. But, if I do the same thing with an interval of 1 day or more, this effect disappears.
What am I doing wrong? :)
`import vectorbt as vbt
start = '2022-06-01 +0500'
end = '2022-06-06 +0500'
interval = '5m'
stock_prices = vbt.YFData.download('RCAT', start=start, end=end, interval=interval).get('Close')
print(stock_prices)
fast_ma = vbt.MA.run(stock_prices, 10, short_name='fast')
slow_ma = vbt.MA.run(stock_prices, 20, short_name='slow')
entries = fast_ma.ma_crossed_above(slow_ma)
exits = fast_ma.ma_crossed_below(slow_ma)
pf = vbt.Portfolio.from_signals(stock_prices, entries, exits, init_cash=10000, fees=.005)
pf.plot().show()`
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