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feat(Sweep): separated level-1 and level-2 sweep configs, skip assets with too few samples to train on, simplified model mapping (#84)

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* feat: Added ensemble models to sweep and configured naming convention.

* fix: Default value was misconfigured.

* feat(Sweep): separated level-1 and level-2 sweep configs, skip assets with too few samples to train on, simplified model mapping

* fix(Sweep): syntax error

* chore(Sweep): set sweep names accordingly

* fix(Sweep): set sliding window

* fix(Sweep): adjusted sweep config

* fix(Sweep): removed invalid feature extractor preset

Co-authored-by: Mark Aron Szulyovszky <mark.szulyovszky@gmail.com>
This commit is contained in:
Daniel Szemerey
2021-12-23 23:48:59 +01:00
committed by GitHub
parent eea88103f4
commit fc4e59a7d2
7 changed files with 76 additions and 32 deletions
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utils/evaluate.py
+2 -3
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from typing import Literal
from sklearn.metrics import mean_absolute_error, accuracy_score, r2_score, f1_score, precision_score, recall_score
from sklearn.metrics import accuracy_score, f1_score, precision_score, recall_score
from quantstats.stats import skew, sortino
from utils.metrics import probabilistic_sharpe_ratio, sharpe_ratio, average_holding_period
from utils.metrics import probabilistic_sharpe_ratio, sharpe_ratio
from utils.helpers import get_first_valid_return_index
import pandas as pd
import numpy as np
def backtest(returns: pd.Series, signal: pd.Series, transaction_cost = 0.00) -> pd.Series:
delta_pos = signal.diff(1).abs().fillna(0.)