We develop and implement a new method for maximum likelihood estimation in closed-form of stochastic volatility models. Using Monte Carlo simulations, we compare a full likelihood procedure, where an option price is inverted into the unobservable volatility state, to an approximate likelihood...

We present an econometric method for estimating the parameters of a diffusion model from discretely sampled data. The estimator is transparent, adaptive, and inherits the asymptotic properties of the generally unattainable maximum likelihood estimator. We use this method to estimate a new...

In this paper, we estimate the behavioral component of the Grinblatt and Han (2002) model and derive several testable implications about the expected relationship between the preponderance of disposition-prone investors in a market and volume, volatility and stock returns. To do this, we use a...

The representative agent model (RA) has dominated macroeconomics for the last thirty years. This model does a reasonably good job of explaining the co-movements of consumption, investment, GDP and employment during normal times. But it cannot easily explain movements in asset prices. Two facts...

Asset pricing models such as the conditional CAPM are typically estimated with MLE using a monthly or quarterly horizon with data sampled to match the horizon even though daily data are available. We develop an overlapping data inference methodology (ODIN) that uses all of the data while...

We compare the performance of maximum likelihood (ML) and simulated method of moments (SMM) estimation for dynamic discrete choice models. We construct and estimate a simplified dynamic structural model of education that captures some basic features of educational choices in the United States in...

We analyze time-series of investor expectations of future stock market returns from six data sources between 1963 and 2011. The six measures of expectations are highly positively correlated with each other, as well as with past stock returns and with the level of the stock market. However,...

Using theories from the behavioral finance literature to predict that investors are attracted to industries with more salient outcomes and that therefore firms in such industries have higher valuations, we find that firms in industries that have high industry-level dispersion of profitability...

Theory suggests that, in the presence of local bias, the price of a stock should be decreasing in the ratio of the aggregate book value of firms in its region to the aggregate risk tolerance of investors in its region. We test this proposition using data on U.S. Census regions and states, and...

This paper surveys the field of asset pricing. The emphasis is on the interplay between theory and empirical work, and on the tradeoff between risk and return. Modern research seeks to understand the behavior of the stochastic discount factor (SDF) that prices all assets in the economy. The...