Estimating Volatility for Option Pricing
- A key challenge in using either Black-Scholes-Merton or a binomial option pricing model is accurately estimating the stock's return volatility.
- Two common approaches for estimating volatility:
- Historical Approach: This assumes that past volatility is representative of future volatility.
- For BSM, the annualized standard deviation of price returns is applied.
- σannual = σperiodic * √periods per year
- 250 trading days per year is a convention when the periodic standard deviation is daily; 12 is applied for monthly data; 52 is applied for weekly data.
- Implied Volatility Approach: This takes the current market price of the option and back solves for the implied value of volatility via the option pricing model.
- The output of the implied volatility approach is an estimate for volatility that equates the BSM price of the option to the market price of the option.
- Analysts and traders can use this approach to form opinions as to whether an option price is too high or too low based on their own expectations for volatility relative to the implied volatility priced into the option.
- CFA Level 2: Derivatives Part 2 – Introduction
- Introduction to Options
- Synthetic Options and Rationale
- One Period Binomial Option Pricing Model
- Call Option Price Formula
- Binomial Interest Rate Options Pricing
- Black-Scholes-Merton (BSM) Option Pricing Model
- Black-Scholes-Merton Model and the Greeks
- Dynamic Delta Hedging & Gamma Related Issues
- Estimating Volatility for Option Pricing
- Put-Call Parity for Options on Forwards
- Introduction to Swaps
- Plain Vanilla Interest Rate Swap
- Equity Swaps
- Currency Swaps
- Swap Pricing vs. Swap Valuing
- Pricing and Valuing a Plain Vanilla Interest Rate Swap
- Pricing and Valuing Currency Swaps
- Pricing and Valuing Equity Swaps
- Swaps as Theoretical Equivalents of Other Derivatives
- Swaptions and their Valuation
- Swap Credit Risk and Swap Spread
- Interest Rate Derivatives - Caps and Floors
- Credit Default Swaps (CDS)
- Credit Derivative Trading Strategies
R Programming Bundle: 25% OFF
Get our R Programming - Data Science for Finance Bundle for just $29 $39.Get it now for just $29