We use prices of equity index options to quantify the impact of extreme events on asset returns. We define extreme events as departures from normality of the log of the pricing kernel and summarize their impact with high-order cumulants: skewness, kurtosis, and so on. We show that high-order...

We quantify the sources of risk in currency returns as a first step toward understanding the returns reported for the carry trade. To do this, we develop and estimate an empirical model of exchange rate dynamics using daily data for four currencies relative to the US dollar: the Australian...

We model the demand-pressure effect on prices when options cannot be perfectly hedged. The model shows that demand pressure in one option contract increases its price by an amount proportional to the variance of the unhedgeable part of the option. Similarly, the demand pressure increases the...

The paper analyzes foreign investment and asset prices in a context of uncertainty over future government policy. The model endogenizes the process of learning by foreign investors facing a potentially opportunistic government, which chooses strategically the timing of a policy reversal in order...

In this paper, we investigate the importance of different loss functions when estimating and evaluating option pricing models. Our analysis shows that it is important to take into account parameter uncertainty, since this leads to uncertainty in the predicted option price. We illustrate the...

This paper investigates the empirical relation between spot and forward implied volatility in foreign exchange. We formulate and test the forward volatility unbiasedness hypothesis, which may be viewed as the volatility analogue to the extensively researched hypothesis of unbiasedness in forward...

We introduce a frequency domain version of the EM algorithm for general dynamic factor models. We consider both AR and ARMA processes, for which we develop iterative indirect inference procedures analogous to the algorithms in Hannan (1969). Although our proposed procedure allows researchers to...

This paper develops a novel approach for estimating latent state variables of Dynamic Stochastic General Equilibrium (DSGE) models that are solved using a second-order accurate approximation. I apply the Kalman filter to a state-space representation of the second-order solution based on the...

Multivariate unobserved components (structural) time series models are fitted to annual post-war observations on real income per capita in countries in the euro zone. The aim is to establish stylized facts about convergence as it relates both to long-run income levels and to cycles. The analysis...

In this paper I explore whether knowledge of the time-series properties of premia in the pricing of forward foreign exchange can be usefully exploited in forecasting future spot exchange rates. I use signal-extraction techniques, based on recursive application of the Kalman filter, to identify...