performance_measure.py

# =============================================================================
# Measuring the performance of a buy and hold strategy
# Author : Mayank Rasu

# Please report bug/issues in the Q&A section
# =============================================================================

# Import necesary libraries
import pandas_datareader.data as pdr
import numpy as np
import datetime

# Download historical data for required stocks
ticker = "^GSPC"
SnP = pdr.get_data_yahoo(ticker,datetime.date.today()-datetime.timedelta(1825),datetime.date.today())


def CAGR(DF):
    "function to calculate the Cumulative Annual Growth Rate of a trading strategy"
    df = DF.copy()
    df["daily_ret"] = DF["Adj Close"].pct_change()
    df["cum_return"] = (1 + df["daily_ret"]).cumprod()
    n = len(df)/252
    CAGR = (df["cum_return"][-1])**(1/n) - 1
    return CAGR

def volatility(DF):
    "function to calculate annualized volatility of a trading strategy"
    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):
    "function to calculate sharpe ratio ; rf is the risk free rate"
    df = DF.copy()
    sr = (CAGR(df) - rf)/volatility(df)
    return sr
    
def sortino(DF,rf):
    "function to calculate sortino ratio ; rf is the risk free rate"
    df = DF.copy()
    df["daily_ret"] = DF["Adj Close"].pct_change()
    neg_vol = df[df["daily_ret"]<0]["daily_ret"].std() * np.sqrt(252)
    sr = (CAGR(df) - rf)/neg_vol
    return sr

def max_dd(DF):
    "function to calculate max drawdown"
    df = DF.copy()
    df["daily_ret"] = DF["Adj Close"].pct_change()
    df["cum_return"] = (1 + df["daily_ret"]).cumprod()
    df["cum_roll_max"] = df["cum_return"].cummax()
    df["drawdown"] = df["cum_roll_max"] - df["cum_return"]
    df["drawdown_pct"] = df["drawdown"]/df["cum_roll_max"]
    max_dd = df["drawdown_pct"].max()
    return max_dd
    
def calmar(DF):
    "function to calculate calmar ratio"
    df = DF.copy()
    clmr = CAGR(df)/max_dd(df)
    return clmr