Share the state between iterations

support

related topic: Different Sharpe ratios in backtest and competition filter

support

related topic: Please advise on p settings. Thanks.

support

This feature has been implemented.
See: https://quantiacs.com/documentation/en/reference/evaluation.html#stateful-multi-pass-backtesting

spancham

@support
Please advise what to do here. Thanks.

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-1-434dffafaefc> in <module>
     50     analyze=True,
     51     build_plots=True,
---> 52     collect_all_states=False # if it is False, then the function returns the last state, otherwise - all states
     53 )

TypeError: backtest() got an unexpected keyword argument 'collect_all_states'

support

@spancham
Helllo.

Update the library, please. run this in you environmnent:

conda install 'quantiacs-source:qnt>=0.0.250'

Regards.

spancham

Hi @support
Thanks but I tried that and it still did not work.
Just so you understand, I do NOT work locally, I only work in the Quantiacs online cloud Jupyter env.
I ran the update you suggested in my Quantiacs online Jupyter and it still did not work. I'm guessing you guys keep the env updated though.
I'm still getting the same error:
TypeError: backtest() got an unexpected keyword argument 'collect_all_states'

Any suggestions pls?

support

@spancham

Hello. Sorry, there was a typo. Try this:

conda install 'quantiacs-source::qnt>=0.0.250' -n qntdev

(double ':' )

Regards.

spancham

@support
Sorry friend, that still does not work.
I am working in the Quantiacs online cloud Jupyter environment.
I am NOT working locally.
I copied your example template as is and just added load_data().
Below is what I am running:

import xarray as xr
import numpy as np
import qnt.data as qndata
import qnt.backtester as qnbt

def load_data(period):
    data = qndata.futures_load_data(tail=period)
    return data

def strategy(data, state):
    close = data.sel(field="close")
    last_close = close.ffill('time').isel(time=-1)

    # state may be null, so define a default value
    if state is None:
        state = {
            "ma": last_close,
            "ma_prev": last_close,
            "output": xr.zeros_like(last_close)
        }

    ma_prev = state['ma']
    ma_prev_prev = state['ma_prev']
    output_prev = state['output']

    # align the arrays to prevent problems in case the asset list changes
    ma_prev, ma_prev_prev, last_close = xr.align(ma_prev, ma_prev_prev, last_close, join='right') 

    ma = ma_prev.where(np.isfinite(ma_prev), last_close) * 0.97 + last_close * 0.03

    buy_signal = np.logical_and(ma > ma_prev, ma_prev > ma_prev_prev)
    stop_signal = ma < ma_prev_prev

    output = xr.where(buy_signal, 1, output_prev)
    output = xr.where(stop_signal, 0, output)

    next_state = {
        "ma": ma,
        "ma_prev": ma_prev,
        "output": output
    }
    return output, next_state


weights, state = qnbt.backtest(
    competition_type="futures",  # Futures contest
    lookback_period=365,  # lookback in calendar days
    start_date="2006-01-01",
    strategy=strategy,
    analyze=True,
    build_plots=True,
    collect_all_states=False # if it is False, then the function returns the last state, otherwise - all states
)

Error I'm getting is:

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-1-434dffafaefc> in <module>
     50     analyze=True,
     51     build_plots=True,
---> 52     collect_all_states=False # if it is False, then the function returns the last state, otherwise - all states
     53 )

TypeError: backtest() got an unexpected keyword argument 'collect_all_states'

The reason I want to get the 'state' working is that I have a pairs trading strategy that needs it.
Any help would be greatly appreciated.
Thanks.

In a related issue, when I run the macroeconomic example, I get the following error:

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-1-62eeefb4e65f> in <module>
     76     strategy=strategy,
     77     analyze=True,
---> 78     build_plots=True
     79 )

~/book/qnt/backtester.py in backtest(competition_type, strategy, load_data, lookback_period, test_period, start_date, window, step, analyze, build_plots)
     66     data, time_series = extract_time_series(data)
     67     print("Run pass...")
---> 68     result = strategy(data)
     69     if result is None:
     70         log_err("ERROR! Strategy output is None!")

TypeError: strategy() missing 1 required positional argument: 'state'

support

Hello.

I guess there is a warning on the strategy "The strategy uses outdated libraries. Clone it to update the libraries."

Just clone this strategy, it will create a new environment with the latest library.

Regards.

spancham

@support
I am working in the Quantiacs online env in my account, why doesn't it catch the latest libraries?
Anyway, I created a new Jupyter notebook with the strategy as suggested and it still does NOT work, same error msg.

spancham

@support
ok I did what @antinomy said below and the 'state' strategy worked.
https://quantiacs.com/community/topic/46/macroeconomic-data-with-quantiacs/3?_=1619554449031

However, it broke my old strategies. So he further suggested to:
https://quantiacs.com/community/topic/46/macroeconomic-data-with-quantiacs/5?_=1619556376479
And my old strategies are running again.

Ok, so looks like for now for all strategies without a state I have to output and pass None to weights for the state & pass a state variable to the strategy.
Will keep you updated. Thanks for looking into the issue.

green.sheep

This post is deleted!