drift/exploration.ipynb

In [1]:

import pandas as pd
import pandas_ta as ta
from config import get_default_ensemble_config
from config.preprocess import preprocess_config
from data_loader.load_data import load_data
import seaborn as sns
import numpy as np

model_config, training_config, data_config = get_default_ensemble_config()
model_config, training_config, data_config = preprocess_config(model_config, training_config, data_config)

config.target_asset'] = config.assets'][0]
X, returns, forward_returns = load_data(**data_config)

(__load_df pid=52067) /usr/local/anaconda3/envs/quant/lib/python3.9/site-packages/pandas/core/arraylike.py:364: RuntimeWarning: divide by zero encountered in log
(__load_df pid=52067)   result = getattr(ufunc, method)(*inputs, **kwargs)
(__load_df pid=52074) /usr/local/anaconda3/envs/quant/lib/python3.9/site-packages/pandas/core/arraylike.py:364: RuntimeWarning: divide by zero encountered in log
(__load_df pid=52074)   result = getattr(ufunc, method)(*inputs, **kwargs)
(__load_df pid=52071) /usr/local/anaconda3/envs/quant/lib/python3.9/site-packages/pandas/core/arraylike.py:364: RuntimeWarning: divide by zero encountered in log
(__load_df pid=52071)   result = getattr(ufunc, method)(*inputs, **kwargs)
(__load_df pid=52072) /usr/local/anaconda3/envs/quant/lib/python3.9/site-packages/pandas/core/arraylike.py:364: RuntimeWarning: divide by zero encountered in log
(__load_df pid=52072)   result = getattr(ufunc, method)(*inputs, **kwargs)
(__load_df pid=52069) /usr/local/anaconda3/envs/quant/lib/python3.9/site-packages/pandas/core/arraylike.py:364: RuntimeWarning: divide by zero encountered in log
(__load_df pid=52069)   result = getattr(ufunc, method)(*inputs, **kwargs)

In [3]:

X.columns

Out [3]:

Index(['ADA_USD_returns', 'ADA_USD_mom_10', 'ADA_USD_mom_20', 'ADA_USD_mom_30',
       'ADA_USD_mom_60', 'ADA_USD_mom_90', 'ADA_USD_vol_10', 'ADA_USD_vol_20',
       'ADA_USD_vol_30', 'ADA_USD_vol_60',
       ...
       'msol_standard_scaling_0', 'dormancy_standard_scaling_0',
       'liveliness_standard_scaling_0',
       'relative_unrealized_profit_standard_scaling_0',
       'relative_unrealized_loss_standard_scaling_0',
       'nupl_standard_scaling_0', 'sth_nupl_standard_scaling_0',
       'lth_nupl_standard_scaling_0', 'ssr_standard_scaling_0',
       'bvin_standard_scaling_0'],
      dtype='object', length=542)

In [6]:

X['liveliness_standard_scaling_0'].plot()

Out [6]:

<AxesSubplot:>

In [7]:

X['BTC_USD_returns'].plot()

Out [7]:

<AxesSubplot:>

In [7]:

# pd.plotting.scatter_matrix(X, figsize=(12, 12));

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