performance.py

# -*- coding: utf-8 -*-
"""
Created on Sun Nov 15 12:06:44 2015

@author: djunh
"""
from __future__ import print_function

import numpy as np
import pandas as pd


def create_sharpe_ratio(returns, periods=252):
    """
    Create the Sharpe ratio for the strategy, based on a 
    benchmark of zero (i.e. no risk-free rate information).

    Parameters:
    returns - A pandas Series representing period percentage returns.
    periods - Daily (252), Hourly (252*6.5), Minutely(252*6.5*60) etc.
    """
    return np.sqrt(periods) * (np.mean(returns)) / np.std(returns)


def create_drawdowns(pnl):
    """
    Calculate the largest peak-to-trough drawdown of the PnL curve
    as well as the duration of the drawdown. Requires that the 
    pnl_returns is a pandas Series.

    Parameters:
    pnl - A pandas Series representing period percentage returns.

    Returns:
    drawdown, duration - Highest peak-to-trough drawdown and duration.
    """

    # Calculate the cumulative returns curve 
    # and set up the High Water Mark
    hwm = [0]

    # Create the drawdown and duration series
    idx = pnl.index
    drawdown = pd.Series(index = idx)
    duration = pd.Series(index = idx)

    # Loop over the index range
    for t in range(1, len(idx)):
        hwm.append(max(hwm[t-1], pnl[t]))
        drawdown[t]= (hwm[t]-pnl[t])
        duration[t]= (0 if drawdown[t] == 0 else duration[t-1]+1)
    return drawdown, drawdown.max(), duration.max()