Pricing kernels implicit in option prices play a key role in assessing the risk aversion over equity returns. We deal with nonparametric estimation of the pricing kernel (PK) given by the ratio of the riskneutral density estimator and the historical density (HD). The former density can be represented as the second derivative w.r.t. the European call option price function, which we estimate by…

The difficulty of predicting stock returns has recently motivated researchers to start looking for more powerful tests, and the current study takes a step in this direction. Unlike existing tests, the test proposed here exploits the information contained in the heteroskedasticity of findings, which is expected to lead to higher power, a result that is confirmed by our results. In order to …

This article shows that economic fundamentals can generate reliable out-of-sample forecasts for exchange rates when prediction is based on a �kitchen-sink� regression that incorporates multiple predictors. The key to establishing predictability is estimating the kitchen-sink regression with the elastic-net shrinkage method, which improves performance by reducing the effect of les…

Standard Gaussian affine dynamic term structure models do not rule out negative nominal interest rates�a conspicuous defect with yields near zero in many countries. Alternative shadow-rate models, which respect the nonlinearity at the zero lower bound, have been rarely used because of the extreme computational burden of their estimation. However, by valuing the call option on negative…

In this article, we compare the local asymptotic and finite sample power of two recently proposed recursive right-tailed Dickey�Fullertype tests for an explosive rational bubble in asset prices. It is shown that the power of the two tests can differ substantially depending on the location of the explosive regime, and whether such a regime ends in collapse. Since this information is typica…

This article develops a state space method for estimating the integrated variance under the existence of market microstructure noise (MMN). Our method is based on a state space representation of the noisecontaminated RV (NCRV), namely, the realized variance (RV) calculated with observed prices contaminated by MMNs. The main idea of our method is to filter out the bias component, which we call t…

This article questions whether food exports to a given national market are impacted by a domestic retailer opening in that market. To answer this question, we considered an empirical gravitytype trade model. We tested our model with data on bilateral exports of food products sold in supermarkets (groceries) on a large panel of countries, as well as the foreign grocery sales of the world�s…

Technological changes in agriculture tend to alter the mass associated with segments or components of the yield distribution as opposed to simply shifting the entire distribution upwards. We propose modeling crop yields using mixtures with embedded trend functions to account for potentially different rates of technological change in different components of the yield distribution. By doing so we…

We present a Maximum Likelihood estimator for the standard commodity storage model with stockouts, based on prices only. While it imposes no additional assumptions on the model, the Maximum Likelihood estimator has small sample properties superior to those of the Pseudo Maximum Likelihood approach. We provide a proof that is crucial for applying our estimator to the model with normal harvests a…

A recently developed testing procedure is used to detect and date-stamp explosive episodes (�bubbles�) in corn, soybean, and wheat futures markets during 2004�2013. We find that the markets experienced price explosiveness only approximately two percent of the time and, when bubbles do occur, they are generally short-lived and small in magnitude. The correspondence between observe…