The recent literature provides conflicting empirical evidence on the pricing of idiosyncratic risk. This paper sheds new light on the matter by exploiting the richness of option data. First, we find that idiosyncratic risk explains 28% of the variation in the risk premium on a stock. Second, we...

Security prices are important inputs for estimating credit risk. Yet, to obtain an accurate firm-specific credit risk assessment, one needs a reliable model and a methodology that filters the elements unrelated to the firm's fundamentals from market prices.In this article, we introduce a hybrid...

We propose the option realized variance as an observable variable to summarize information from high-frequency option data. This variable aggregates intraday option returns from midquote prices to compute the option's total variability for a given day. Using the S&P 500 index time series and...

This article presents a quadratic hedging framework for a general class of discrete-time affine multi-factor models and investigates the extent to which multi-component volatility factors, fat tails, and a non-monotonic pricing kernel can improve the hedging performance. A semi-explicit hedging...

We adopt a flexible filtering procedure to extract information from high-frequency data. Specifically, we provide a parsimonious framework to integrate realized measures from high frequency index and derivative prices. In a simulation study, we document the incremental information offered by...