I develop a noisy rational expectations equilibrium model with a continuum of states and a full set of options that render the market complete. I show a major difference in equilibrium behaviour between models with constant absolute risk aversion (CARA) and non-CARA preferences. First, when...

U.S. trading in non-U.S. stocks has grown dramatically. Round-the-clock, these stocks trade in the home market, in the U.S. marketand, potentially, in both markets simultaneously. We use a state space model to study 24-hour price discovery. As opposed to thestandard variance ratio'' approach,...

For many assets, trading is fragmented across multiple exchanges. Price discovery measures summarize the informativeness of trading on each venue for discovering the assetś true underlying value. We explore intraday variation in price discovery using a structural model with time-varying...

We consider a market where traders have asymmetric information regarding the distribution of asset return and study price discovery of derivatives. The informed trader has private information regarding arbitrary higher moments of asset return, such as volatility or skewness, and exploits her...

Large investors often advertise private information at private talks or in the media. To analyse the incentives for information disclosure, I develop a two-period Kyle (1985) type model in which an informed short-horizon investor strategically discloses private information to enhance price...

In this paper, we introduce a new Bayesian approach to explain some market anomalies during financial crises and subsequent recovery. We assume that the earnings shock of an asset follows a random walk model with and without drift to incorporate the impact of financial crises. We further assume...

This paper implements a novel model-free methodology to measure skewness risk premia in individual stocks. The methodology takes the form of a trading strategy, a skewness swap. The return on the strategy shows a significant positive skewness risk premium in individual stocks. The risk premium...

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...

In this paper, we introduce two classes of indices which can be used to measure the market perception concerning the degree of dependency that exists between a set of random variables, representing different stock prices at a fixed future date. The construction of these measures is based on the...

At the end of January 2021, a group of stocks listed on US stock exchanges experienced sudden surges in their stock prices, which - coupled with high short interest – led to brief short squeeze episodes. We argue that these short squeezes were the result of coordinated trading by retail...