We propose a nonparametric Bayesian approach for the estimation of the pricing kernel. Historical stock returns and option market data are combined through the Dirichlet Process (DP) to construct an option-adjusted physical measure. The precision parameter of the DP process is calibrated to the...

We estimate post-jump volatility-decay risk premia as the predictable ‎difference between periods of high and low diffusive volatility. By ‎constructing straddle portfolios after positive and negative jumps occur, we ‎show that the gains that these hedged options' portfolios yield...

This paper aims to explore whether the cause of return premium associated with the Amihud (2002) illiquidity measure is the compensation for illiquidity or mispricing. This paper defines the Amihud premium as the difference in expected returns between high-Amihud-portfolio and...

Deep learning methods, which can accommodate wide ranges of various stock characteristics to identify optimal investment portfolio or stochastic discount factor (SDF), have been criticized for extracting their superior performances from difficult to arbitrage stocks, high limits-to-arbitrage...

Options depending on the forward skew are very popular. One such option is the forward starting call option - the basic building block of a cliquet option. Widely applied models to account for the forward skew dynamics to price such options include the Heston model, the Heston-Hull-White model...

In this article, we propose an equilibrium pricing rule for the contingent claims by applying the economic premium principle initiated by Buhlmann (1980). The derivative markets in our model are over-the-counter (OTC) markets and have counterparty risks. We reconstruct the economic premium...

We measure message processing time or latency inside an automated trading platform. We show that latency is a random variable that has a strong predictive power over both volatility and the volatility of volatility of a highly liquid asset over and above changes in message traffic. We argue that...

We investigate the time-scale relationships between the ten S&P sectors and the market through the use of wavelet analysis, a methodology that has widespread acceptance for investigating multi-horizon properties of time series. Our analysis of the data highlights that variation in the pattern of...

This paper exploits a natural experiment from the late 1800s in which many U.S. firms had inadvertently issued both taxable and tax-exempt bonds. Investors paid income tax on taxable bonds, but firms covered income tax on investors' behalf on tax-exempt bonds. Using a unique data-set of these...

We contrast two different asset pricing models, where the pricing kernel either (i) increases in the volatility dimension, reflecting investors' aversion to volatility, or (ii) could be non-monotonic in volatility, reflecting heterogeneity in investors' beliefs. The two models yield opposite...