[Previous research concludes that options are mispriced based on the high average returns, CAPM alphas, and Sharpé ratios of various put selling strategies. One criticism of these conclusions is that these benchmarks are ill suited to handle the extreme statistical nature of option returns generated by nonlinear payoffs. We propose an alternative way to evaluate the statistical significance of option returns by comparing historical statistics to those generated by option pricing models. The most puzzling finding in the existing literature, the large returns to writing out-of-the-money puts, is not inconsistent (i.e.,is statistically insignificant) relative to the Black-Scholes model or the Heston stochastic volatility model due to the extreme sampling uncertainty associated with put returns. This sampling problem can largely be alleviated by analyzing market-neutral portfolios such as straddles or deltahedged returns. The returns on these portfolios can be explained by jump risk premiums and estimation risk.]

[We analyze auctions for the settlement of credit default swaps (CDS) theoretically and evaluate them empirically. The requirement to settle in cash with an option to settle physically leads to an unusual two-stage process. In the first stage, participants affect the amount of the bonds to be auctioned off in the second stage. Participants in the second stage may hold positions in derivatives on the assets being auctioned. We show that the final auction price might be either above or below the fair bond price because of strategic bidding on the part of participants holding CDS. Empirically, we observe both types of outcomes, with undervaluation occurring in most cases. We find that auctions undervalue bonds by an average of 6% on the auction day. Undervaluation is related positively to the amount of bonds exchanged in the second stage of the auction, as predicted by the theory. We suggest modifications of the settlement procedure to minimize the underpricing.]

The purpose of this paper is to bridge two strands of the literature, one pertaining to the objective or physical measure used to model an underlying asset and the other pertaining to the risk-neutral measure used to price derivatives. We propose a generic procedure using simultaneously the fundamental price, St, and a set of option contracts [(σitI)i=1,m] where m⩾1 and σitI is the Black–Scholes implied volatility. We use Heston's (1993. Review of Financial Studies 6, 327–343) model as an example, and appraise univariate and multivariate estimation of the model in terms of pricing and hedging performance. Our results, based on the S&P 500 index contract, show dominance of univariate approach, which relies solely on options data. A by-product of this finding is that we uncover a remarkably simple volatility extraction filter based on a polynomial lag structure of implied volatilities. The bivariate approach, involving both the fundamental security and an option contract, appears useful when the information from the cash market reflected in the conditional kurtosis provides support to price long term.

Abstract Exposures of expected future nominal depreciation rates to the current interest rate differential violate the UIP hypothesis in a pattern that is a nonmonotonic function of horizon. Forward expected nominal depreciation rates are monotonic. We explain the two patterns by simultaneously incorporating the weak form of PPP into a joint model of the stochastic discount factor, the nominal exchange rate, and domestic and foreign yield curves. Departures from PPP generate the first pattern. The risk premiums for these departures generate the second pattern. Thus, the variance of the stochastic discount factor is related to the real exchange rate.

We develop a three-factor no-arbitrage model for valuing mortgage-backed securities in which we solve for the implied prepayment function from the cross-section of market prices. This model closely fits the cross-section of mortgage-backed security prices without needing to specify an econometric prepayment model. We find that implied prepayments are generally higher than actual prepayments, providing direct evidence of significant macroeconomic-driven prepayment risk premiums in mortgage-backed security prices. We also find evidence that mortgage-backed security prices were significantly affected by Fannie Mae credit risk and the Federal Reserve’s quantitative easing programs.

ABSTRACT The currency depreciation rate is often computed as the ratio of foreign to domestic pricing kernels. Using bond prices alone to estimate these kernels leads to currency puzzles: the inability of models to match violations of uncovered interest parity and the volatility of exchange rates. This happens because of the FX bond disconnect , the inability of bonds to span exchange rates. Incorporating innovations to the pricing kernel that affect exchange rates but not bonds helps resolve the puzzles. This approach also allows one to relate news about cross‐country differences between international yields to news about currency risk premiums.

We develop an empirical model of bilateral exchange rates. It includes normal shocks with stochastic variance and jumps in an exchange rate and in its variance. The probability of a jump in an exchange rate corresponding to depreciation (appreciation) of the U.S. dollar is increasing in the domestic (foreign) interest rate. The probability of a jump in variance is increasing in the variance only. Jumps in exchange rates are associated with announcements; jumps in variance are not. On average, jumps account for 25% of currency risk. The dollar carry index retains these features. Options suggest that jump risk is priced.

Previous research concludes that options are mispriced based on the high average returns, CAPM alphas, and Sharpe ratios of various put selling strategies. One criticism of these conclusions is that these benchmarks are ill-suited to handle the extreme statistical nature of option returns generated by nonlinear payoffs. We propose an alternative way to evaluate the statistical significance of option returns by comparing historical statistics to those generated by option pricing models. The most puzzling finding in the existing literature, the large returns to writing out-of-the-money puts, is not inconsistent (i.e., is statistically insignificant) relative to the Black-Scholes model or the Heston stochastic volatility model due to the extreme sampling uncertainty associated with put returns. This sampling problem can largely be alleviated by analyzing market-neutral portfolios such as straddles or delta-hedged returns. The returns on these portfolios can be explained by jump risk premia and estimation risk.

ABSTRACT We propose two data‐based performance measures for asset pricing models and apply them to models with recursive utility and habits. Excess returns on risky securities are reflected in the pricing kernel's dispersion and riskless bond yields are reflected in its dynamics. We measure dispersion with entropy and dynamics with horizon dependence, the difference between entropy over several periods and one. We compare their magnitudes to estimates derived from asset returns. This exercise reveals tension between a model's ability to generate one‐period entropy, which should be large, and horizon dependence, which should be small.

ABSTRACT This paper examines model specification issues and estimates diffusive and jump risk premia using S&P futures option prices from 1987 to 2003. We first develop a time series test to detect the presence of jumps in volatility, and find strong evidence in support of their presence. Next, using the cross section of option prices, we find strong evidence for jumps in prices and modest evidence for jumps in volatility based on model fit. The evidence points toward economically and statistically significant jump risk premia, which are important for understanding option returns.