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This dissertation contains three essays on observable covariates in option pricing. In the first essay, I propose firm-specific public news arrival from Factiva database as an observable covariate in equity options market and study how the public news arrival is priced. I first establish the empirical relationship between the firm-specific public news arrival and jumps in individual equity returns. Subsequently, I build a continuous-time stochastic volatility jump diffusion model where news arrivals driving the jump dynamics. When estimated on equity options data for 20 individual firms, the premia placed on jump frequency and size turn out to be consistent with the theories highlighting both positive and negative effects of public news arrival. The second essay, based on a joint work with Peter Christoffersen, Bruno Feunou and Chayawat Ornthanalai, studies how the stock market illiquidity affects the market crash risk. Our empirical approach is to estimate a continuous-time model with stochastic volatility and dynamic crash probability where stock market illiquidity is used as an observable covariate driving the crash probability. While the crash probability is time-varying, its dynamic depends only weakly on return variance once we include market illiquidity as an economic variable in the model. This finding suggests that the relationship between variance and jump risk found in the literature is largely due to their common exposure to market illiquidity. Our study highlights the importance of equity market frictions in index return dynamics and explains why prior studies find that crash risk increases with market uncertainty level. The third essay, based on a joint work with Peter Christoffersen and Bruno Feunou, proposes the realized jump variation measure constructed from the intraday S returns data as an observable covariate that helps pricing of index options. The volatility and jump intensity dynamics in the model are directly driven by model-free empirical measures of diffusive volatility and jump variation. Because the empirical measures are observed in discrete intervals, our option valuation model is cast in discrete time, allowing for straightforward filtering and estimation of the model. When estimated on S index options and returns the new model performs well compared with standard benchmarks.
"This dissertation is a collection of three essays that delve into the econometrics of option pricing. The primary objective of these essays is to develop and deploy diverse econometric techniques that enable the accurate extraction of valuable information embedded in option prices. Chapter 2 investigates jump contagion between international stock markets using options data. It introduces a multivariate option pricing model that assesses the contagious effects of market shocks. Chapter 3 tackles the challenge of estimating continuous-time option pricing models. It proposes a new filtering and estimation method for affine jump-diffusion models, enhancing computational efficiency and implementation ease. Finally, Chapter 4 develops a unified framework for non-parametric estimation of risk-neutral densities, option prices, and option sensitivities."--
This dissertation includes three essays on investments and time series econometrics. This work gives new insight into the behavior of implied marginal tax rates, implied volatility, and option pricing models. The first essay examines the movement of implied marginal tax rates. A body of research points to the existence of implied marginal tax rates that can be extracted from security or derivative prices. We use the LIBOR-based interest rate swap curve and the MSI-based interest rate swap curve to examine changes in the implied tax rate. We document multiple statistically and economically significant structural breaks in the long-run implied marginal tax rate that are not exclusively located in the financial crisis (one as recent as October, 2010). These breaks represent persistent divergence from long run averages and indicate that mean reversion models may not accurately describe the stochastic processes of implied marginal tax rates. In the second essay, I develop an asymmetric time series model of the VIX. I show that the VIX and realized volatility display significant nonlinear effects which I approximate with a smooth-transition autoregressive model. I find that under certain regimes the VIX depends almost exclusively on previous realized volatility. Under other regimes, I find that the VIX depends on both its lags and previous realized volatility. Since the VIX has become a popular hedging instrument, this finding has important implications for risk managers who elect to use the VIX and its related investment vehicles. It also has implications for the use of implied volatility in value-at-risk forecasting. The third essay presents a new model for option pricing model selection. There is a significant performativity issue intrinsic in much of the option pricing literature. Once an option-pricing model (OPM) gains widespread acceptance, volatilities tend to move so that the OPM fits well with observed prices. This often leads to systematic mispricing based purely on model results. A number of systematic issues such as volatility smile are present in OPMs. To remedy this issue, I propose a new method for ranking OPMs based on one step ahead forecasts. This model transforms the data to build a distribution of the stochastic term present in OPM. This sample distribution is then tested for normality so that OPMs can be ranked in a Bayesian-like framework by their closeness to a normal distribution.