min_func_sharpe.py

def calculate_stats(allocs, prices):
    # standardize the price series
    prices_norm = prices / prices.iloc[0,:]
    # Get position values
    position_val = prices_norm * allocs
    # Sum to get portfolio value
    portfolio_val = position_val.sum(axis = 1)
    # Calculate portfolio cumulative return
    cr = (portfolio_val[-1] / portfolio_val[0]) - 1
    # Calculate portfolio daily return series
    port_daily_returns = (portfolio_val/portfolio_val.shift(1) - 1)
    # Calculate average daily return
    adr = port_daily_returns.mean()
    # Calculate standard deviation of daily return
    sddr = port_daily_returns.std()
    # Calculate Sharpe Ratio - For simplicity assuming risk free rate is 0
    sr = adr / sddr * np.sqrt(252)
    return cr, adr, sddr, sr

# Minimize the negative value of the Sharpe ratio as it's essentially the
# same as maximizing of the Sharpe ratio
def min_func_sharpe(allocs, prices):
    return -calculate_stats(allocs, prices)[3]