If you use equity options to increase leverage, generate income, or manage risk, you may struggle with the key analytical differences between these strategies and long-only products. FactSet's Portfolio Analysis application answers this need with features and data to help you properly analyze a portfolio’s composition, fundamental characteristics, and risk.

Analyze Risk of Non-Normal Portfolios

Equity options don’t exhibit normal distribution in their returns. When introduced into an equity-only portfolio, these securities change the distribution of the portfolio’s return. As a result, tracking error and other mean/variance statistics no longer describe the portfolio’s risk. To meet this need, use Monte Carlo Value-at-Risk in Portfolio Analysis.

Using a Monte Carlo technique, different factor return outcomes are simulated from the same risk models that you would select for a tracking error analysis. From each simulation outcome, the equity returns are implied and the option returns are computed through the appropriate options pricing model (Barone-Adesi, Whaley for American options and Black-Scholes for European options). The resulting security returns are aggregated into a single, simulated portfolio return for each outcome in the Monte Carlo Simulation.

The result of 5,000 simulations is a distribution of portfolio returns that more accurately describes your nonlinear portfolio than the normal distribution assumed by the variance-covariance method. View the resulting distribution as a chart or add statistics like VaR or Expected Tail Loss to any Portfolio Analysis Characteristics report.

Additionally, use the included Trade Model utility to simulate trades, such as selling covered calls to increase portfolio income, and then study the pre- and post-trade risk side-by-side in the same chart or report. Finally, create multi-portfolio and multi-period reports to compare the return distributions of two portfolios or study the change in risk over time.

Leverage FactSet’s Options Pricing Data

Drive these features with FactSet’s database of option prices, implied volatilities, and greek calculations. FactSet calibrates implied volatility surface models nightly from the latest option pricing data. From this data, at-the-money volatility is also computed for each underlying parent. The database provides a solution for those users who want to analyze options in Portfolio Analysis but don’t (or can’t) provide prices, greeks, and underlying identifiers as part of their nightly holdings upload to FactSet.