[Based on a multivariate extension of the constrained locally polynomial estimator of Aït-Sahalia and Duarte (2003), we provide one of the first nonparametric estimates of probability densities of LIBOR rates under forward martingale measures and state-price densities (SPDs) implicit in interest rate cap prices. The forward densities and SPDs depend significantly on the slope and volatility of LIBOR rates, and mortgage markets activities have strong impacts on the shape of the forward densities. The SPDs exhibit a pronounced U-shape as a function of future LIBOR rates, suggesting that the state prices are high at both extremely low and high interest rates, which tend to be associated with recessions and periods of high inflation, respectively. Our results provide nonparametric evidence of unspanned stochastic volatility and suggest that the unspanned factors could be partly driven by activities in the mortgage markets.]

This article quantifies the impact of the battery electric vehicle subsidy program in China. We build a structural model of dynamic demand and Bertrand Nash supply to study price elasticity and changes in production costs. The model highlights four channels through which the subsidy program impacts the market: temporal elasticity, in response to a current price change; intertemporal elasticity, in response to a future price change; and multiplication effects through peer and learning by doing. Combining these estimates, we simulate outcomes under four subsidy schemes and find a phase-out policy could be the most cost-effective while achieving higher sales promotion compared with alternative policies that provide larger subsidies over more prolonged periods.

Based on a multivariate extension of the constrained locally polynomial estimator of At-Sahalia and Duarte (2003), we provide nonparametric estimates of the probability densities of LIBOR rates under forward martingale measures and the state-price densities (SPDs) implicit in interest rate cap prices conditional on the slope and volatility factors of LIBOR rates. Both the forward densities and the SPDs depend signicantly on the volatility of LIBOR rates, and there is a signicant impact of mortgage prepayment activities on the forward densities. The SPDs exhibit a pronounced U-shape as a function of future LIBOR rates, suggesting that the state prices are high at both extremely low and high interest rates, which tend to be associated with periods of economic recessions and high in ations, respectively. Our results provide nonparametric evidence of unspanned stochastic volatility and suggest that the unspanned factors could be partly driven by renancing activities in the mortgage markets. Over-the-counter interest rate derivatives, such as caps and swaptions, are among the most widely traded interest rate derivatives in the world. According to the Bank for International Settlements, in recent years, the notional value of caps and swaptions exceeds $ 10 trillion, which is many times

Based on intraday data for a large cross section of individual stocks and newly developed econometric procedures, we decompose the realized variation for each of the stocks into separate so-called realized up and down semi-variance measures, or “good” and “bad” volatilities, associated with positive and negative high-frequency price increments, respectively. Sorting the individual stocks into portfolios based on their normalized good minus bad volatilities results in economically large and highly statistically significant differences in the subsequent portfolio returns. These differences remain significant after controlling for other firm characteristics and explanatory variables previously associated with the cross section of expected stock returns.

ABSTRACT Most existing dynamic term structure models assume that interest rate derivatives are redundant securities and can be perfectly hedged using solely bonds. We find that the quadratic term structure models have serious difficulties in hedging caps and cap straddles, even though they capture bond yields well. Furthermore, at‐the‐money straddle hedging errors are highly correlated with cap‐implied volatilities and can explain a large fraction of hedging errors of all caps and straddles across moneyness and maturities. Our results strongly suggest the existence of systematic unspanned factors related to stochastic volatility in interest rate derivatives markets.

This paper studies the rise and fall of “Mini” options that are especially catered to retail investors for popular but high-priced securities. Using transaction-level data, we find that transaction costs of Mini options are much higher than those of standard options and the difference cannot be fully explained by cost-related determinants. Furthermore, we find evidence of price discrimination against retail investors from analyses of price elasticities of option traders, an event-study of changes in bid-ask spreads around earnings announcements, and comparisons of trade prices paid by Mini and standard option traders for the same security at approximately the same time.

Mini options are specially catered to retail investors with limited capital for trading options on extremely high-priced securities. The coexistence of both Mini and standard options for the same underlying security provides us a novel setting to investigate whether and how small retail investors use derivatives contracts differently compared to their counterparts. First, we find that the Mini option investors are more subject to constraints of limited attention. Specifically, Mini option investors trade more intensively near market opens, and their trading activities are more heavily influenced by attention-grabbing events and attention-distracting events. Second, we document that Mini option investors’ trading is more likely to be driven by market sentiment than standard option investors. Third, the trading performance of Mini option investors is also worse than that of standard option investors, with less positive intraday returns and more negative overnight returns.

ABSTRACT Using 3 years of interest rate caps price data, we provide a comprehensive documentation of volatility smiles in the caps market. To capture the volatility smiles, we develop a multifactor term structure model with stochastic volatility and jumps that yields a closed‐form formula for cap prices. We show that although a three‐factor stochastic volatility model can price at‐the‐money caps well, significant negative jumps in interest rates are needed to capture the smile. The volatility smile contains information that is not available using only at‐the‐money caps, and this information is important for understanding term structure models.