multi_backtest_linreg_crypto.py

# API Key
with open("../eodHistoricalData-API.txt", "r") as f:
    api_key = f.read()

# Backtest over 1 year and train on about 1 year's worth of data
train_days = 365

range_of_bt = 365

# Usual Backtest
norm_performance = linRegModelBT(
    "BTC-USD", 
    days_to_backtest=range_of_bt, 
    days_to_train=train_days, 
    api_key=api_key,
    short=True, 
    inverse_strat=False
)

# Backtesting but without shorting
bullish_only = linRegModelBT(
    "BTC-USD", 
    days_to_backtest=range_of_bt, 
    days_to_train=train_days,
    api_key=api_key,
    short=False, 
    inverse_strat=False
)

# Do the inverse of the strategy
inverse_performance = linRegModelBT(
    "BTC-USD", 
    days_to_backtest=range_of_bt, 
    days_to_train=train_days,
    api_key=api_key,
    short=True, 
    inverse_strat=True
)

# Inverse and bullish
inverse_bullish = linRegModelBT(
    "BTC-USD", 
    days_to_backtest=range_of_bt, 
    days_to_train=train_days, 
    api_key=api_key,
    short=False, 
    inverse_strat=True
)


# Visualizing the Different Outcomes
outcomes = {
    "Normal Backtest": norm_performance,
    "Bullish Backtest": bullish_only,
    "Inverse Strategy": inverse_performance,
    "Inverse and Bullish": inverse_bullish
}

for i in outcomes.keys():

    fig = px.line(
        outcomes[i],
        x=outcomes[i].index,
        y=outcomes[i],
        title=f'{i} Performance',
        labels={"y": "Portfolio Balance",
                "ds": "Date"})

    fig.show()