Option Greeks: Delta
Delta is the change in option premium expected from a small change in the stock price.
It is an important by-product of the Black-Scholes model.
There are three common uses of delta.
- Measure of option sensitivity
- Hedge ratio
- Likelihood of becoming in-the-money
Measure of Option Sensitivity
For a call option, the delta is represented as:
For a put option, the delta is represented as:
Delta indicates how many shares of stock are required to replicate the returns of the option. For example, assume that a call option has a delta of 0.75. If the stock price rises by $1.00, the call option will increase by about 75 cents.
Delta is always positive (between 0 and 1) for long calls and short puts and negative (between 0 and -1) for long puts and short calls. For a European option, the absolute values of the put and call deltas will sum to 1. In the Black-Scholes model, the call delta is exactly equal to N(d1).
The delta of an at-the-money option declines linearly over time and approaches 0.50 at expiration
The delta of an out-of-the-money option approaches zero as time passes
The delta of an in-the-money option approaches 1.0 as time passes
Hedge Ratio
Delta is also used a measure of the hedge ratio.
Assume a short option position has a delta of 0.50. If an investor owns 100 shares of the stock, he can create a perfect hedge by writing 2 calls. This is because the underlying stock always has a delta of one.
Similarly, if a portfolio of options in a stock is +2.50, the trader would be able to hedge the portfolio by selling short 250 shares of the underlying. This is called delta-hedging.
Likelihood of Becoming In-the-Money
Some traders also use delta is a measure of the probability that an option will be in the money at expiration.
For example, if an out-of the-money option has a delta 0.20, it indicates that the option has a 20% chance of being in the money at expiry, that is the stock price will be above the option striking price at expiration.
Lesson Resources
Data Science in Finance: 9-Book Bundle
Master R and Python for financial data science with our comprehensive bundle of 9 ebooks.
What's Included:
- Getting Started with R
- R Programming for Data Science
- Data Visualization with R
- Financial Time Series Analysis with R
- Quantitative Trading Strategies with R
- Derivatives with R
- Credit Risk Modelling With R
- Python for Data Science
- Machine Learning in Finance using Python
Each book includes PDFs, explanations, instructions, data files, and R code for all examples.
Get the Bundle for $39 (Regular $57)Free Guides - Getting Started with R and Python
Enter your name and email address below and we will email you the guides for R programming and Python.