Some methods for calculating financial metrics

fin_metrics.py

# helper functions
def CAGR(DF):
    "Calculates the Compound Annual Growth Rate"
    df = DF.copy()
    df['daily_ret'] = df['Adj Close'].pct_change()
    df['cum_return'] = (1 + df['daily_ret']).cumprod()
    return (df['cum_return'])**(252/len(df)) - 1

def volatility(DF):
    "Calculates the daily Volatility over a year, given we trade 252x a year"
    df = DF.copy()
    df['daily_ret'] = df['Adj Close'].pct_change()
    vol = df['daily_ret'].std()*np.sqrt(252)
    return vol

def sharpe(DF, rf=None):
    "Sharpe ratio. RF = risk free rate. If not specified then rf=zero"
    df = DF.copy()
    if not rf:
        rf = np.array([0]*len(df))
    sr = (CAGR(df) - rf)/volatility(df)
    return sr