esg_window_dressing.py

#!/usr/bin/env python
# coding: utf-8

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import numpy as np
import pandas as pd
import matplotlib.pyplot as plt

import ffn
import bt

get_ipython().run_line_magic('matplotlib', 'inline')

plt.style.use('ggplot')
plt.rcParams['figure.figsize'] = (12.0, 4)


# # Exploratory Data Analysis

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tickers = [
    # which tickers?
     'BZ=F',
     'NG=F',

#  '0P0000732C.TO', # nuttals fund
 'vet.to',
 'wcp.to',
 'arch',
    'btu',
 'whc.ax'
]


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# fetch some data
data = bt.get(
    tickers=tickers,
    start='2017-12-01',
    end='2022-06-16',
)
data


# ## backtest - good

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buy_days_before_qend = 1
sell_days_after_qend= 7

s = data.index.quarter.to_series().diff().abs().shift(-1).fillna(0)
s = s.replace(0, np.nan).ffill(limit=sell_days_after_qend).bfill(limit=buy_days_before_qend).fillna(0)
signal = data.copy()
signal[:] =np.array([s]*7).T
signal


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signal.loc['2021-03-25':'2021-04-15']


# # try for each equity

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data.columns


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tests = []
for c in data.columns:
    s1 = bt.Strategy(
        c,
        [
            bt.algos.RunDaily(),
            bt.algos.SelectWhere(signal[[c]]),
            bt.algos.WeighEqually(),
            bt.algos.Rebalance()
        ]
    )
    t1 = bt.Backtest(s1, data[[c]])
    tests.append(t1)

res = bt.run(*tests)

res.plot()

res.plot_security_weights()

res.display()
# res.stats.T['daily_sharpe'].sort_values()[::-1]


# # all

# In[75]:



s1 = bt.Strategy(
    'esg',
    [
        bt.algos.RunDaily(),
        bt.algos.SelectWhere(signal),
        bt.algos.WeighEqually(),
        bt.algos.Rebalance()
    ]
)
t1 = bt.Backtest(s1, data)


res = bt.run(t1)

res.plot()

res.plot_security_weights()

res.display()
res.stats.T['daily_sharpe'].sort_values()[::-1]


# In[76]:


# Lets try just 2021 onwards
s1 = bt.Strategy(
    'esg',
    [
        bt.algos.RunDaily(),
        bt.algos.SelectWhere(signal.loc['2021':]),
        bt.algos.WeighEqually(),
        bt.algos.Rebalance()
    ]
)
t1 = bt.Backtest(s1, data.loc['2021':])


res = bt.run(t1)

res.plot()

res.plot_security_weights()

res.display()
res.stats.T['daily_sharpe'].sort_values()[::-1]


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