The paper estimates and examines the empirical plausibiltiy of asset pricing models that attempt to explain features of financial markets such as the size of the equity premium and the volatility of the stock market. In one model, the long run risks model of Bansal and Yaron (2004), low...

This paper shows how to build algorithms that use graphics processing units (GPUs) installed in most modern computers to solve dynamic equilibrium models in economics. In particular, we rely on the compute unified device architecture (CUDA) of NVIDIA GPUs. We illustrate the power of the approach...

Identification problems arise naturally in forward-looking models when agents observe more than economists. We illustrate the problem in several New Keynesian and macro-finance models in which the Taylor rule includes a shock unseen by economists. We show that identification of the rule's...

We propose two metrics for asset pricing models and apply them to representative agent models with recursive preferences, habits, and jumps. The metrics describe the pricing kernel's dispersion (the entropy of the title) and dynamics (time dependence, a measure of how entropy varies over...

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 evaluate the importance of "Limits to Arbitrage" to explain profitability of momentum strategies. Specifically, when the availability of arbitrage capital is in short supply, momentum cycles last longer, and breaks in momentum cycles are shorter. We demonstrate the robustness of our findings...

We find that price momentum in stocks was a pervasive phenomenon during the Victorian age (1866-1907) as well. Momentum strategy profits have little systematic risk even at business cycle frequencies; disappear periodically only to reappear later; exhibit long run reversal; and are higher...

This paper studies the ICAPM intertemporal relation between the conditional mean and the conditional variance of the aggregate stock market return. We introduce a new estimator that forecasts monthly variance with past daily squared returns -- the Mixed Data Sampling (or MIDAS) approach. Using...

We consider various MIDAS (Mixed Data Sampling) regression models to predict volatility. The models differ in the specification of regressors (squared returns, absolute returns, realized volatility, realized power, and return ranges), in the use of daily or intra-daily (5-minute) data, and in...

We combine self-collected historical data from 1867 to 1907 with CRSP data from 1926 to 2012, to examine the risk and return over the past 140 years of one of the most popular mechanical trading strategies — momentum. We find that momentum has earned abnormally high risk-adjusted returns — a...