We are excited to announce a doubleheader for the Peter Carr BQE Seminar Series. Please join us for the upcoming talks presented by Farid AitSahlia and Thomas Philips, on the following topics:
American Options Under Stochastic Volatility: Parameter Estimation and Pricing Efficiency
We present evidence that American option prices are insensitive to the accuracy of spot and long–term volatility estimates in the Heston (1993) model, for which drastically different parameter values can be obtained. Our results derive from a new accurate pricing technique that we developed and which exploits approximations to the non-central chi-square distribution in combination with a well-developed and efficient procedure for the constant volatility model of Black and Scholes, requiring only 3 or 4 hyperplanes to approximate the exercise surface. In addition, through an out–of–sample validation based on S&P 100 data, we also show that our method generates prices close to market values. In essence, our results contribute a practical illustration to the growing literature on model misspecification and robust pricing.
Farid AitSahlia is a clinical assistant professor and James D. Richardson Faculty Fellow in the Eugene Brigham Department of Finance in the Warrington College of Business at the University of Florida. He received his Ph.D. in Operations Research from Stanford University and his research has appeared in the Journal of Computational Finance, Advances in Applied Probability, Computational Management Science, Annals of Operations Research, Journal of Derivatives, among others. He co-authored with Kai Lai Chung the textbook “Elementary Probability Theory with Stochastic Processes and an Introduction to Mathematical Finance,” which has been translated into Russian and Chinese. Prior to embarking on an academic career, Farid spent time in industry, working at Hewlett-Packard Laboratories and at two successful start-ups in Silicon Valley (Financial Engines and DemandTec.) He currently serves as editor-in-chief of the Journal of Risk and on the editorial board of the book series “Modern Trends in Financial Engineering” at World Scientific Publishing.
Ultra-Simple Shiller's Cape: How One Year's Data Can Predict Equity Market Returns Better Than Ten
Professor Robert Shiller’s cyclically adjusted price/earnings ratio (CAPE) uses a 10-year average of real (i.e. CPI-adjusted) earnings to simultaneously filter noise in earnings and estimate corporate profitability over a business cycle. In this talk, I show how the CAPE methodology can be simultaneously simplified and enhanced by separating the filtering of noise from damping the effects of business cycles. By applying a simple non-linear filter, I obtain better forecasts of future earnings using one year's data than CAPE does with ten. In addition, I model temporal variation in profit margins using the sales-to-price ratio. I then construct two forecasts of the return of the S&P 500, one using earnings and the other using revenues, and exploit the forecast combination puzzle to construct a composite forecast that provides better out-of-sample forecasts than CAPE. My current forecast for the 10-year return of the S&P 500 is 3.4% / annum, suggesting that stocks will underperform bonds over the next decade. My forecasts can be computed in near-real-time and can be replicated using data supplied in the open-source R package PCRA.
Thomas K. Philips is an accomplished senior investment professional, researcher, educator, author, and subject matter expert on Risk Management, Portfolio Management, Performance Measurement, and Valuation. He currently teaches Quantitative Portfolio Management and Valuation Theory in the Department of Finance and Risk Engineering at NYU’s Tandon School of Engineering. He has a long history of achievement, including award-winning innovation and research that has influenced investment practice, product design, client service, and education. He is a highly sought-after speaker at seminars, conferences, and educational events.