Research in behavioral corporate finance takes two distinct approaches. The first emphasizes that investors are less than fully rational. It views managerial financing and investment decisions as rational responses to securities market mispricing. The second approach emphasizes that managers are less than fully rational. It studies the effect of nonstandard preferences and judgmental biases on managerial decisions. This survey reviews the theory, empirical challenges, and current evidence pertaining to each approach. Overall, the behavioral approaches help to explain a number of important financing and investment patterns. The survey closes with a list of open questions.

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The recent observed decline of business cycle variability suggests that broad macroeconomic risk may have fallen as well. This may in turn have some impact on equity risk premia. We investigate the latent structures in the volatilities of the business cycle and stock market valuations by estimating a Markov switching stochastic volatility model. We propose a sequential Monte Carlo technique for the Bayesian inference on both the unknown parameters and the latent variables of the hidden Markov model. Sequential importance sampling is used for filtering the latent variables and kernel estimator with a multiple-bandwidth is employed to reconstruct the parameter posterior distribution. We find that the switch to lower variability has occurred in both business cycle and stock market variables along similar patterns.

In this paper I investigate whether firms ’ physical investments react to the speculative over-pricing of their securities. I introduce investment considerations in an infinite horizon continuous time model with short sale constraints and heterogeneous beliefs along the lines of Scheinkman and Xiong (2003). I obtain closed form solutions for all quantities involved. I show that market based q and investment are increased, even though such investment is not warranted on the basis of long run value maximization. Moreover, I show that investment amplifies the effects of speculation on prices through an increase in the value of "growth " options. In the empirical section of the paper, I use a simple episode to test the hypothesis that investment reacts to over-pricing. With publicly available data on short sales during the 1920’s, I examine both the price reaction and the investment behavior of a number of companies that were introduced into the "loan crowd " during the first half of 1926. In line with Jones and Lamont (2002), I interpret this as evidence of overpricing due to speculation. I find that investment by these companies follows both the increase and the decline in "q " before and after the introduction, suggesting that companies in this sample reacted to security over-pricing. JEL Codes:

We use demand shifts induced by demographics to provide a novel evaluation of capital budgeting and market timing. Capital budgeting implies that industries anticipating positive demand shifts in the near future should issue more equity to finance capacity. To the extent that demographic shifts in the distant future are not incorporated into equity prices, market timing implies that industries anticipating positive demand shifts in the distant future should issue less equity due to undervaluation. The evidence supports both theories: new listings and equity issuance respond positively to demand shifts up to 5 years ahead, and negatively to demand shifts 5 to 10 years ahead.

Despite abundant evidence that firms ’ characteristics predict their asset returns, we know little about how much firms ’ asset prices deviate from their true values. Such mispricing could be distinct from observed return predictability if investors have biased beliefs that are not highly correlated with firms ’ characteristics. We use a model to estimate the extent of information processing biases that would reproduce empirical asset pricing anomalies. Our findings indicate that the magnitude of mispricing is several times larger than observed anomalies suggest. The model also provides novel insights into when and how information processing biases can cause substantial capital misallocation. We thank UT Austin and Columbia for research support. We appreciate helpful suggestions from Sheridan Titman and seminar participants at UT Austin and UNC Chapel Hill. Please send all correspondence to

We develop a multi-tasking model in which a firm can devote its efforts either to increasing sales growth, or to improving per-unit profit margins by, e.g., cutting costs. If the firm’s manager is concerned with the current stock price, she will tend to favor the growth strategy at those times when the stock market is paying more attention to performance on the growth dimension. Conversely, it can be rational for the stock market to weight observed growth measures more heavily when it is known that the firm is following a growth strategy. This two-way feedback between firms ’ business strategies and the market’s pricing rule can lead to purely intrinsic fluctuations in sales and output, creating excess volatility in these real variables even in the absence of any external source of shocks. We are grateful to the National Science Foundation for financial support,

This article empirically examines “disagreement ” models using JASDAQ market data by exploiting institutional investors ’ forecasts of future stock prices. We use the standard deviations of the one-month ahead forecasts of stock prices in the QSS Equity Survey as the measure of disagreement in the market. The results indicate that an increase in disagreement is associated with an increase in contemporaneous stock returns and lower average expected returns. In terms of the latter, while the survey data provides an average assessment of marketwide expectations, when disagreement is high the current market price tends to reflect the opinions of more optimistic market participants. These results contrast with comparable findings using TOPIX data (representing larger firms on the Tokyo Stock Exchange’s first section) that contradict the predictions of disagreement models. One reason posited is that firms on the JASDAQ market are much smaller and the number of market participants more limited. Accordingly, institutional “limits of arbitrage”, such as short-sale and liquidity constraints, are more binding and their influence on stock prices is thereby greater.

This paper provides a comprehensive firm level analysis of the relation between a firm’s capital investment and its equity return. We find that firm capital investment is negatively associated with future equity returns in the time-series. In the cross-section, portfolios of firms with low investment growth rates or low investment capital ratios have significantly higher expected returns than portfolios of firms with high investment growth rates or investment capital ratios. With a stochastic discount factor, a standard investment model can generate the same predictive patterns of investments as in the data. Furthermore, an investment growth factor, which is the return difference between low investment stocks and high investment stocks, contains similar

Does stock market misvaluation affect investment? We use cross-sectional variation between glamour (high stock price) and value (low stock price) portfolios to test whether there is a relationship between misvaluation and fixed investment. In a large sample of U.S. firms over the period 1980-2001, glamour firms invest substantially more than value firms. If glamour firms are responding to misvaluation rather than fundamentals, then they may be investing too much. We describe and implement four new tests designed to distinguish whether the high investment of glamour firms is the result of fundamental shocks or misvaluation shocks: investment reversals, stock market returns of “overinvesting ” glamour firms, the time path of the marginal product of capital, and overreaction tests. In addition, we provide parametric estimates of the effect of misvaluation on investment; the parametric estimates suggest that a one standard deviation increase in misvaluation raises investment by more than 40%. We consider the possibility that overinvestment might be due to excessive optimism on the part of managers-- and present empirical specifications designed to detect whether either the active financing mechanism (cheap equity finance) or managerial excess optimism influence overinvestment.