Hi
I have been trying to write a simple example with both single pass and multi pass just to understand them better. But I can't get them to produce the same result. Here is what I use:

single pass version:

import xarray as xr
import qnt.ta as qnta
import qnt.data as qndata

data = qndata.futures_load_data(min_date='2006-01-01', max_date='2007-01-01', assets= ['F_ES'])

close = data.sel(field='close')
close_one_day_ago = qnta.shift(close, periods=1)

_open = data.sel(field='open')
open_one_day_ago = qnta.shift(_open, periods=1)

weights = xr.where(open_one_day_ago < close_one_day_ago, 1, 0)

The result looks like the following.

multi pass version:

import xarray as xr
import qnt.ta as qnta
import qnt.backtester as qnbt
import qnt.data as qndata

def load_data(period):
    return qndata.futures_load_data(tail=period, assets=['F_ES'])

def strategy(data):
    close = data.sel(field='close')
    close_one_day_ago = qnta.shift(close, periods=1)
    _open = data.sel(field='open')
    open_one_day_ago = qnta.shift(_open, periods=1)
    weights = xr.where(open_one_day_ago < close_one_day_ago, 1, 0)
    return weights

weights = qnbt.backtest(
    competition_type= 'futures',
    load_data= load_data,
    lookback_period= 365,
    start_date= '2006-01-01',
    end_date= '2007-01-01',
    strategy= strategy
)

The result look like the following.

Any help/hint/suggestion is greatly appreciated.

Hi @support ,

That makes perfect sense

Thank so much

regards

Hi

I am confused why the warning for trading non-liquid assets appears in the second scenario.

First scenario (no warning):

def strategy(data):
    close = spx_data.sel(field='close')
    rsi = qnt.ta.rsi(close, 14)
    rsi = qnt.ta.shift(rsi, periods=1)
    weights = xarray.where(rsi < 30, 1, 0) + xarray.where(rsi > 70, -1, 0)    
    return weights

weights = strategy(spx_data)
is_liquid = spx_data.sel(field='is_liquid')
weights = weights * is_liquid
weights = qnt.output.clean(weights, spx_data, 'stocks_nasdaq100')
stats = qnt.stats.calc_stat(spx_data, weights)

Second scenario (warning shows up):

def strategy(data):
    close = spx_data.sel(field='close')
    rsi = qnt.ta.rsi(close, 14)
    rsi = qnt.ta.shift(rsi, periods=1)
    weights = xarray.where(rsi < 30, 1, 0) + xarray.where(rsi > 70, -1, 0)
    filter = qnt.filter.filter_volatility_rolling(weights=weights, data=data, rolling_window=60, top_assets=20, metric='std', ascending=True)
    weights = weights * filter
    return weights

weights = strategy(spx_data)
is_liquid = spx_data.sel(field='is_liquid')
weights = weights * is_liquid
weights = qnt.output.clean(weights, spx_data, 'stocks_nasdaq100')
stats = qnt.stats.calc_stat(spx_data, weights)

Since the 'is_liquid' is applied after the weights are calculated, shouldn't there be no warning?

Thank you in advance

regards

Hi @stefanm ,

How reckless of me, "data" should have been f_es_data. They are perfectly synced now.
Thank you so much. I really appreciate the help.

sincerely

Hi @stefanm

Thank you for your detailed explanation

To be honest, I did think about the initialization period. But I added the extra (earlier) period for all data, not only for 'F_ES' as in the example (which should not matter?).

By the way, I used 'illegal' hand-picked single asset (as well as the trivial strategy) just to simplify the case.

Thanks for pointing out the opposite shift direction. It's a habit from different language (mql5).

I copied pasted the codes you modified; I still don't get the same results.

I only changed:

weights = strategy(f_es_data)

to

close = data.sel(field='close')
close_one_day_ago = qnta.shift(close, periods=1)

_open = data.sel(field='open')
open_one_day_ago = qnta.shift(_open, periods=1)

weights = xr.where(open_one_day_ago < close_one_day_ago, 1, 0)

kind regards

Dear @support

Thank you for your confirmation

regards

Hi
I have been trying to write a simple example with both single pass and multi pass just to understand them better. But I can't get them to produce the same result. Here is what I use:

single pass version:

import xarray as xr
import qnt.ta as qnta
import qnt.data as qndata

data = qndata.futures_load_data(min_date='2006-01-01', max_date='2007-01-01', assets= ['F_ES'])

close = data.sel(field='close')
close_one_day_ago = qnta.shift(close, periods=1)

_open = data.sel(field='open')
open_one_day_ago = qnta.shift(_open, periods=1)

weights = xr.where(open_one_day_ago < close_one_day_ago, 1, 0)

The result looks like the following.

multi pass version:

import xarray as xr
import qnt.ta as qnta
import qnt.backtester as qnbt
import qnt.data as qndata

def load_data(period):
    return qndata.futures_load_data(tail=period, assets=['F_ES'])

def strategy(data):
    close = data.sel(field='close')
    close_one_day_ago = qnta.shift(close, periods=1)
    _open = data.sel(field='open')
    open_one_day_ago = qnta.shift(_open, periods=1)
    weights = xr.where(open_one_day_ago < close_one_day_ago, 1, 0)
    return weights

weights = qnbt.backtest(
    competition_type= 'futures',
    load_data= load_data,
    lookback_period= 365,
    start_date= '2006-01-01',
    end_date= '2007-01-01',
    strategy= strategy
)

The result look like the following.

Any help/hint/suggestion is greatly appreciated.