Algorithmic Trading & Indicators Intermediate

Calculate Implied Volatility Rank (IVR) & IV Percentile (IVP) in Python

Determine whether options are statistically cheap or expensive by computing 52-week Implied Volatility Rank (IVR) and IV Percentile (IVP) in Python.

#pandas#numpy

Problem Statement

Option sellers get crushed when selling options during low-IV regimes right before volatility expansion. Computing 252-day IV Rank and IV Percentile identifies high-premium selling environments (IVR > 50).

Formula / Core Logic

IV_Rank = 100 * (Current_IV - 52wk_Low_IV) / (52wk_High_IV - 52wk_Low_IV) IV_Percentile = % of days in past 252 days where IV < Current_IV

Installation

pip install pandas numpy

implied-volatility-rank-ivr-percentile-ivp-python.py

import pandas as pd
import numpy as np

def calculate_ivr_ivp(df, iv_col='IV', window=252):
    df = df.copy()
    iv_min = df[iv_col].rolling(window).min()
    iv_max = df[iv_col].rolling(window).max()
    df['IV_Rank'] = np.round(100 * (df[iv_col] - iv_min) / (iv_max - iv_min), 2)
    df['IV_Percentile'] = df[iv_col].rolling(window).apply(lambda x: (np.sum(x < x.iloc[-1]) / (len(x) - 1)) * 100, raw=False).round(2)
    return df