Understanding the Volatility Skew

Oct 13, 2025 by pynkocean.com 106 views

Introduction

The Black-Scholes (BS) model is a widely used option pricing model that assumes constant volatility. However, in the real world, this assumption does not hold, and we observe a volatility skew. The volatility skew is a phenomenon where the prices of out-of-the-money (OTM) options are higher or lower than their theoretical values, depending on the strike price. In this article, we will discuss whether there are arbitrage possibilities on the volatility skew.

Understanding the Volatility Skew

The volatility skew is a result of the non-constant volatility assumption in the BS model. In reality, volatility is not constant and can vary depending on the strike price. This variation in volatility leads to a skew in the option prices, where OTM options are priced higher or lower than their theoretical values.

Theoretical Background

The BS model assumes that the underlying asset follows a geometric Brownian motion with constant volatility. However, in reality, the underlying asset's price process is more complex and can be described by a stochastic volatility model. The stochastic volatility model takes into account the time-varying nature of volatility, which leads to a volatility skew.

Arbitrage Opportunities

Arbitrage opportunities arise when there is a mispricing in the market. In the context of the volatility skew, arbitrage opportunities can be identified by comparing the prices of OTM options with their theoretical values. If the prices of OTM options are higher or lower than their theoretical values, an arbitrageur can exploit this mispricing by buying or selling the options.

Types of Arbitrage

There are two types of arbitrage opportunities that can be identified in the context of the volatility skew:

Statistical arbitrage: This type of arbitrage involves identifying mispricings in the market by analyzing statistical relationships between option prices and underlying asset prices.
Market-making arbitrage: This type of arbitrage involves exploiting mispricings in the market by buying or selling options and then hedging the position with the underlying asset.

Example of Arbitrage Opportunity

Suppose we have a stock with a current price of $100 and a volatility of 20%. The BS model predicts that the price of a 1-year OTM call option with a strike price of $120 is $5. However, the market price of the option is $7. In this case, an arbitrageur can buy the option at $7 and sell it at $5, making a profit of $2.

Challenges in Arbitrage

While arbitrage opportunities may exist in the context of the volatility skew, there are several challenges that need to be addressed:

Transaction costs: Arbitrageurs need to consider the transaction costs associated with buying and selling options, such as commissions and bid-ask spreads.
Risk management: Arbitrageurs need to manage their risk exposure by hedging their positions with the underlying asset.
Market liquidity: Arbitrageurs need to consider the market liquidity of the options and the underlying asset.

Conclusion

In conclusion, arbitrage opportunities may exist in the context of the volatility skew. However, there are several challenges that need to be addressed, including transaction costs, risk management, and market liquidity. Arbitrageurs need to carefully analyze the market and identify mispricings in the option prices before exploiting them.

Recommendations

Based on our analysis, we recommend the following:

Use statistical models: Arbitrageurs should use statistical models to identify mispricings in the market.
Hedge positions: Arbitrageurs should hedge their positions with the underlying asset to manage their risk exposure.
Monitor market liquidity: Arbitrageurs should monitor the market liquidity of the options and the underlying asset to ensure that they can execute their trades at favorable prices.

Future Research Directions

There are several future research directions that can be explored in the context of the volatility skew:

Developing new models: Researchers can develop new models that take into account the time-varying nature of volatility and the volatility skew.
Analyzing market microstructure: Researchers can analyze the market microstructure to understand how the volatility skew arises and how it can be exploited.
Evaluating the performance of arbitrage strategies: Researchers can evaluate the performance of arbitrage strategies in the context of the volatility skew.

References

Black, F., & Scholes, M. (1973). The pricing of options and corporate liabilities. Journal of Political Economy, 81(3), 637-654.
Merton, R. C. (1973). Theory of rational option pricing. Bell Journal of Economics and Management Science, 4(1), 141-183.
Hull, J. C. (2015). Options, futures, and other derivatives. Pearson Education.

Appendix

The appendix provides additional information on the volatility skew and arbitrage opportunities.

Volatility Skew

The volatility skew is a phenomenon where the prices of OTM options are higher or lower than their theoretical values, depending on the strike price. The volatility skew arises due to the non-constant volatility assumption in the BS model.

Arbitrage Opportunities

Statistical Arbitrage

Statistical arbitrage involves identifying mispricings in the market by analyzing statistical relationships between option prices and underlying asset prices.

Market-Making Arbitrage

Market-making arbitrage involves exploiting mispricings in the market by buying or selling options and then hedging the position with the underlying asset.

Challenges in Arbitrage

There are several challenges that need to be addressed in arbitrage, including transaction costs, risk management, and market liquidity.

Conclusion

Introduction

In our previous article, we discussed the concept of the volatility skew and its implications for option pricing. We also explored the possibility of arbitrage opportunities arising from the volatility skew. In this article, we will answer some frequently asked questions (FAQs) related to the volatility skew and arbitrage.

Q: What is the volatility skew?

A: The volatility skew is a phenomenon where the prices of out-of-the-money (OTM) options are higher or lower than their theoretical values, depending on the strike price. This arises due to the non-constant volatility assumption in the Black-Scholes (BS) model.

Q: What causes the volatility skew?

A: The volatility skew is caused by the time-varying nature of volatility, which is not accounted for in the BS model. In reality, volatility is not constant and can vary depending on the strike price, leading to a skew in the option prices.

Q: What are the implications of the volatility skew for option pricing?

A: The volatility skew has significant implications for option pricing. It means that the prices of OTM options are not accurately reflected by the BS model, leading to mispricings in the market.

Q: Can arbitrage opportunities be identified in the context of the volatility skew?

A: Yes, arbitrage opportunities can be identified in the context of the volatility skew. By comparing the prices of OTM options with their theoretical values, arbitrageurs can exploit mispricings in the market.

Q: What are the types of arbitrage opportunities that can be identified in the context of the volatility skew?

A: There are two types of arbitrage opportunities that can be identified in the context of the volatility skew:

Statistical arbitrage: This type of arbitrage involves identifying mispricings in the market by analyzing statistical relationships between option prices and underlying asset prices.
Market-making arbitrage: This type of arbitrage involves exploiting mispricings in the market by buying or selling options and then hedging the position with the underlying asset.

Q: What are the challenges in arbitrage in the context of the volatility skew?

A: There are several challenges that need to be addressed in arbitrage in the context of the volatility skew, including:

Transaction costs: Arbitrageurs need to consider the transaction costs associated with buying and selling options, such as commissions and bid-ask spreads.
Risk management: Arbitrageurs need to manage their risk exposure by hedging their positions with the underlying asset.
Market liquidity: Arbitrageurs need to consider the market liquidity of the options and the underlying asset.

Q: How can arbitrageurs identify mispricings in the market?

A: Arbitrageurs can identify mispricings in the market by analyzing statistical relationships between option prices and underlying asset prices. They can also use market data and other information to identify mispricings.

Q: What are the benefits of arbitrage in the context of the volatility skew?

A: The benefits of arbitrage in the context of the volatility skew include:

Profitability: Arbitrageurs can make profits by exploiting mispricings in the market.
Risk management: Arbitrageurs can manage their risk exposure by hedging their positions with the underlying asset.
Market efficiency: Arbitrageurs can contribute to market efficiency by identifying and exploiting mispricings in the market.

Q: What are the limitations of arbitrage in the context of the volatility skew?

A: The limitations of arbitrage in the context of the volatility skew include:

Transaction costs: Arbitrageurs need to consider the transaction costs associated with buying and selling options, such as commissions and bid-ask spreads.
Risk management: Arbitrageurs need to manage their risk exposure by hedging their positions with the underlying asset.
Market liquidity: Arbitrageurs need to consider the market liquidity of the options and the underlying asset.

Conclusion

In conclusion, the volatility skew is a phenomenon that arises due to the non-constant volatility assumption in the Black-Scholes model. Arbitrage opportunities can be identified in the context of the volatility skew by comparing the prices of OTM options with their theoretical values. However, there are several challenges that need to be addressed, including transaction costs, risk management, and market liquidity.

Recommendations

Based on our analysis, we recommend the following:

Use statistical models: Arbitrageurs should use statistical models to identify mispricings in the market.
Hedge positions: Arbitrageurs should hedge their positions with the underlying asset to manage their risk exposure.
Monitor market liquidity: Arbitrageurs should monitor the market liquidity of the options and the underlying asset to ensure that they can execute their trades at favorable prices.

Future Research Directions

There are several future research directions that can be explored in the context of the volatility skew and arbitrage:

Developing new models: Researchers can develop new models that take into account the time-varying nature of volatility and the volatility skew.
Analyzing market microstructure: Researchers can analyze the market microstructure to understand how the volatility skew arises and how it can be exploited.
Evaluating the performance of arbitrage strategies: Researchers can evaluate the performance of arbitrage strategies in the context of the volatility skew.

References

Black, F., & Scholes, M. (1973). The pricing of options and corporate liabilities. Journal of Political Economy, 81(3), 637-654.
Merton, R. C. (1973). Theory of rational option pricing. Bell Journal of Economics and Management Science, 4(1), 141-183.
Hull, J. C. (2015). Options, futures, and other derivatives. Pearson Education.

Appendix

The appendix provides additional information on the volatility skew and arbitrage opportunities.

Volatility Skew

Arbitrage Opportunities

Statistical Arbitrage

Statistical arbitrage involves identifying mispricings in the market by analyzing statistical relationships between option prices and underlying asset prices.

Market-Making Arbitrage

Market-making arbitrage involves exploiting mispricings in the market by buying or selling options and then hedging the position with the underlying asset.

Challenges in Arbitrage

There are several challenges that need to be addressed in arbitrage, including transaction costs, risk management, and market liquidity.