[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 paper examines racial disparities in mortgage processing time prior to the global financial crisis. We find that Black borrowers are underrepresented and experience a longer processing time than white borrowers among the mortgages securitized by government-sponsored enterprises (GSEs). At the same time, Black borrower are overrepresented and face a similar processing time among privately securitized (PLS) mortgages. Additionally, Black borrowers are strongly associated with faster segments of the mortgage markets, faster lenders within each segment, and the types of loan products that are processed faster, all of which subsequently experienced higher defaults.

The empirical pricing kernels estimated from index options are non-monotone (Rosenberg and Engle, 2002, Bakshi et al., 2010) and the corresponding risk-aversion functions can be negative (Aït-Sahalia and Lo, 2000, Jackwerth, 2000). We show theoretically that these and several other properties of empirical pricing kernels are consistent with rank-dependent utility model with probability weighting function, which overweights tail events. We also estimate the pricing kernels nonparametrically from the Standard & Poor's 500 index options and construct empirical probability weighting functions. The estimated probability weights typically have the inverse-S shape, which overweights tail events and is widely supported by the experimental decision theory.

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

Despite their mediocre mean performance, actively managed mutual funds are distinct from passive funds in their return distributions. Active value funds better hedge downside risk, while active growth funds better capture upside potential. Since such performance features may appeal to investors with tail‐overweighting preferences, we show that preferences for downside protection and upside potential estimated from the empirical pricing kernel can help explain active fund flows in the value and growth categories, respectively. This effect of investor risk preferences varies significantly with funds' downside‐hedging and upside‐capturing ability, with levels of active management, and across retirement and retail funds.

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.

Utilizing a unique and novel setting of disclosure mandate threshold under Regulation AB (Reg AB), we investigate the relationship between disclosure and trust in asset securitization. Post-Reg AB enactment, we observe a significant bunching of originators just below the disclosure threshold. Less trustworthy originators are more likely to adjust their portfolio sizes to remain below this threshold, particularly when loan originators and deal sponsors are unaffiliated, which are cases in which disclosure plays a greater role in reducing information asymmetry. Additionally, these originators are more likely to misrepresent loan quality. Our findings reveal a strong relationship between disclosure and trust—trustworthy originators disclose more and originate higher-quality loans, while less trustworthy originators disclose less and produce lower-quality loans.

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.

Examining the contractual disclosures during the sale of private‐label residential mortgage‐backed securities before the 2008 financial crisis, we find that textual contents in the risk‐factor section predict subsequent losses and yet were not reflected in pricing. Insurance companies, especially life insurers and insurers with low regulatory capital ratios, are more exposed to textual risks. Consistent with issuers hedging litigation risks with disclosure, we find that textual contents are associated with second‐lien underreporting and preissuance written communications. Overall, we find that investors neglected risks in the purportedly safe assets before the crisis.

We offer the first empirical evidence on the adverse effect of credit default swap (CDS) coverage on subprime mortgage defaults. Using a large database of privately securitized mortgages, we find that higher defaults concentrate in mortgage pools with concurrent CDS coverage, and within these pools the loans originated after or shortly before the start of CDS coverage have an even higher delinquency rate. The results are robust across zip code and origination quarter cohorts. Overall, we show that CDS coverage helped drive higher mortgage defaults during the financial crisis.