Behavioral Asset Pricing Research Articles

All's Well that Ends Well? On the Importance of How Returns are Achieved

We demonstrate that investor satisfaction and investment behavior is influenced substantially by the price path by which the final investor return is achieved. In a series of experiments, we analyze various different price paths. Investors are most satisfied if their assets first fall in value and then recover, and they are least satisfied with the opposite pattern, independent of whether the final return is positive or negative. Price paths systematically influence risk preferences, return beliefs, and ultimately trading decisions. Our results enable a much more holistic perspective on a wide range of topics in finance, such as the disposition effect, risk-taking behavior after previous gains and losses, and behavioral asset pricing.

Behavioral Finance: Peter Bernstein and The Journalof Portfolio Management

Behavioral finance is under construction as a solid structure of finance. It substitutes normal people for rational people in standard finance, behavioral portfolio theory for mean-variance portfolio theory, and behavioral asset pricing models for the CAPM and other models where expected returns are determined only by risk. Behavioral finance also distinguishes rational markets from hard-to-beat markets in the discussion of efficient markets and examines why so many investors believe that beating the market is easy. Peter Bernstein encouraged and guided the author of this article as he contributed to the construction of behavioral finance in the pages of The Journal of Portfolio Management (JPM). The JPM’s fortieth anniversary, the first ten-year anniversary without Peter, is an opportunity for the author to express his gratitude to Peter once more and describe his work published in JPM.

Behavioral finance: Finance with normal people

Behavioral finance is under construction as a solid structure of finance. It incorporates parts of standard finance, replaces others, and includes bridges between theory, evidence, and practice.Behavioral finance substitutes normal people for the rational people in standard finance. It substitutes behavioral portfolio theory for mean-variance portfolio theory, and behavioral asset pricing model for the CAPM and other models where expected returns are determined only by risk. Behavioral finance also distinguishes rational markets from hard-to-beat markets in the discussion of efficient markets, a distinction that is often blurred in standard finance, and it examines why so many investors believe that it is easy to beat the market. Moreover, behavioral finance expands the domain of finance beyond portfolios, asset pricing, and market efficiency and is set to continue that expansion while adhering to the scientific rigor introduced by standard finance.

Reflexivity, expectations feedback and almost self-fulfilling equilibria: economic theory, empirical evidence and laboratory experiments

We discuss recent work on bounded rationality and learning in relation to Soros' principle of reflexivity and stress the empirical importance of non-rational, almost self-fulfilling equilibria in positive feedback systems. As an empirical example, we discuss a behavioral asset pricing model with heterogeneous expectations. Bubble and crash dynamics is triggered by shocks to fundamentals and amplified by agents switching endogenously between a mean-reverting fundamental rule and a trend-following rule, based upon their relative performance. We also discuss learning-to-forecast laboratory experiments, showing that in positive feedback systems individuals coordinate expectations on non-rational, almost self-fulfilling equilibria with persistent price fluctuations very different from rational equilibria. Economic policy analysis may benefit enormously by focusing on efficiency and welfare gains in correcting mispricing along almost self-fulfilling equilibria.

The Monetary Policy Implications of Behavioral Asset Bubbles

I introduce behavioral asset pricing rules into a wider dynamic stochastic general equilibrium framework. Asset price bubbles emerged endogenously within the model. I find that in this model monetary policy rules that target the mispricing of the asset have a destabilizing effect; however, a monetary policy rule that targets deviations in the price of the asset from its trend can be welfare enhancing. Such a rule would also have the benefit of being straightforward to implement.

Investor Sentiment and Stock Price: Evidence from India

The impact of investor sentiment on stock market price has been a subject of long standing interest to both economists and practitioners. Following the theoretical argument of behavioral asset pricing, recent literature confirms the possible linkage between the aggregate investor sentiment and stock returns. In this paper we examine the causal relationship between investor sentiment index constructed from various market related implicit proxies, and aggregate stock market indices such as BSE sensex and NSE Nifty indices. The Johansen co-integration test is applied to measure the long-term relationship between the sentiment index and market indices and Error Correction Method has been used to check the short-term relationship between the two variables. Granger causality test is used to check the causal relationship between them. Our results suggest that, given the evidence of comovements of sentiment and market index there is significant long-run and short-run relationship between the two indices. Consistent with the existing literature which suggest that the sentiment effect is a short-run phenomena, our findings gives an indication that long term investment strategy can effectively mitigate the sentiment risk. The results for causality test suggest that there exist a unidirectional causal relationship between the sentiment index and market indices.

A discussion of Hong-Stein model

In this paper, we discuss a kind of behavioral asset pricing model, called Hong-Stein model. Although this model succeeded in explaining the momentum and reversal effects, we find it usually reaches two extremes: the absolute value of autocorrelation of return sequence is so large that the direction of returns could be easily forecasted, or the value is so small that the elements in return sequence are almost independent of each other. The empirical results show that these two extremes are not supported by the real market data.

The Risk Premium for Minority Banks Altruistic Portfolios in Underserved Communities

Motivated by behavioural asset pricing theory, we extend Vasicek (1977, 2002) factor pricing models to a statistical risk accounting model to characterize the compensating risk premium required to sustain minority banks’ (MBs) altruistic motive to provide credit in underserved communities. Our model predicts that increased bank capitalization, and brokered deposit (BD) exceptions, compensate risk when the incremental internal rate of return they induce is negatively correlated with the internal rate of return on extant MB loan portfolios. Thus implying, paradoxically, that loan portfolios levered by increased capital, and brokered deposits, militate against altruistic motives. This suggests that for a given amount of altruism, minority banks are better served by tactical portfolio allocation in an expanded investment opportunity set. Using Federal Reserve Statistical Release (12/2011) on select FFIEC Form 031 (“Call Report”) data, we fit a risk-return function for minority banks and estimate the compensating risk premium for return on assets.

Bank Run Exposure in a Paycheck to Paycheck Economy with Liquidity Preference and Loss Aversion to Decline in Consumption

According to recent Getting Paid in America Survey Results, about 69% of respondents receive their pay biweekly, and about 72% of those surveyed would find it difficult to meet financial obligations if their paycheck was delayed by one week. Additionally, about 96% of those surveyed received their pay by direct deposit. In that milieu, we introduce a simple consumption based behavioral asset pricing model, with consumption ratcheting, in a veritable paycheck to paycheck economy, which supports a dynamic bank run exposure process induced by bank clientele liquidity preference and loss aversion to decline in - which induce a run on the bank. A representative agent‘s fear, about whether transitory shocks to permanent income in the next period will adversely affect consumption, is resolved upon receipt of her paycheck. At which point, in order for markets to clear, our agent use revolving credit, i.e., credit card or overdrafts, to pay for consumption not covered by bad shocks to income. We show that endogenous loss aversion, induced by uncertainty over comparatively small probabilities of bad shocks to income, is enough to trigger a bank run - from which we characterize an abstract topological space for bank runs. For application, we compute endogenous probability of suspension of convertibility as a function of (1) the stopping time of a bank run, and (2) a comparatively small probability of bad shocks to - provided that loss aversion is outside taboo limits defined on our bank run topological space. Further, we show that even though cash reserve is linear in liquidity risk, its beta, i.e. bank run exposure, is highly nonlinear in bank clientele loss aversion to declines in and or consumption. In fact, our asymptotic theory shows that bank run exposure is in the class of Hidden Markov Models over latent states of bank clientele loss aversion to fluctuations in income. Econometrically, this implies, inter alia, that as a function of liquidity risk, fluctuations in the bank‘s cash reserves are underestimated. Consequently, the bank is faced with a pseudo underinvestment problem - it needs to hold higher cash reserves to meet increased fluctuations in demand for liquidity induced by loss aversion which crowds out its ability to make loans for some positive NPV projects. In which case, one of the bank‘s risk management problem is to control its bank run exposure process to a goal of optimal investment.

Behavioral Economics and Asset Pricing

Mean-Variance (M-V) analysis and the CAPM are derived in the expected utility framework. Behavioral Economists and Psychologists (BE&P) advocate that expected utility is invalid, suggesting Prospect Theory as a substitute paradigm. Moreover, they show that the M-V rule, which is the foundation of the CAPM, is not always consistent with peoples' choices. Thus, BE&P cast doubt on the validity of expected utility paradigm and of the M-V rule, hence the CAPM is theoretically questionable. In addition, there is very little empirical support to the CAPM. We show in this study that the CAPM is theoretically valid even when one accepts the BE&P framework and even when expected utility is invalid. Moreover, within the BE&P framework there is a strong experimental support for the CAPM.

The impact of individual and institutional investor sentiment on the market price of risk

We examine the effect of individual and institutional investor sentiment on the market price of risk derived from DJIA and S&P500 index returns. Consistent with behavioral asset pricing models, we find significant positive response of rational sentiment suggesting greater incentive for rational investors to engage in arbitrage when the compensation for taking risk is greater. Further, an increase in irrational optimism leads to a significant downward movement, but an increase in rational sentiment does not lead to a significant change market price of risk. These results are robust for both market indexes, DJIA and S&P500 and for both individual and institutional investor sentiment.

Affect in a Behavioral Asset-Pricing Model

Affect in a Behavioral Asset-Pricing Model

Affect in a Behavioral Asset-Pricing Model

Stocks, like houses, cars, watches, and other products, exude “affect”—that is, they are considered good or bad, beautiful or ugly; they are admired or disliked. Affect plays an overt role in the pricing of houses, cars, and watches, but according to standard financial theory, it plays no role in the pricing of financial assets. This article outlines a behavioral asset-pricing model in which expected returns are high not only when objective risk is high but also when subjective risk is high. High subjective risk comes with negative affect. Investors prefer stocks with positive affect, which boosts the prices of such stocks and depresses their returns.

Affect in a Behavioral Asset Pricing Model

Stocks, like houses, cars, watches and most other products exude affect, good or bad, beautiful or ugly, admired or despised. Affect plays a role in pricing models of houses, cars and watches but, according to standard financial theory, affect plays no role in pricing of financial assets. We outline a behavioral asset pricing model where expected returns are high when objective risk is high and also when subjective risk is high. High subjective risk comes with negative affect. Investors prefer stocks with positive affect and their preference boosts the prices of such stocks and depresses their returns.

Momentum, Dividend Policy, and Market Conditions

Non-dividend-paying firms generate higher momentum profit (0.73% per month) than the dividend payers following up markets. Extant literature suggests that the higher momentum profits following up markets can be explain via behavioral or rational asset pricing models. The rational asset pricing models suggest that the higher momentum profits following up markets stem from higher return autocorrelations during these periods since firms are closer to exercising their growth options when prices are rising (Sagi and Seasholes's (2006)). Thus, the higher momentum profit for the non-payers following up markets should be due to higher return autocorrelations for these stocks relative to their dividend-paying counterparts. This suggests higher expected returns for the non-dividend-paying winners relative to their dividend-paying counterparts and lower expected returns for the non-dividend-paying losers relative to their dividend-paying counterparts. While the evidence is consistent with the latter prediction, it is inconsistent with the former prediction. Specifically, the average return of the non-dividend-paying winners (1.85% per month) is not significantly higher than that of their dividend-paying counterparts (1.78%). Consequently, it is hard to explain the evidence via higher return autocorrelations for the non-dividend-paying stocks following up markets. The behavioral models suggest that the higher momentum profits following up markets are due to the price increases during these markets. In particular, the price increases increase aggregate overconfidence and reduce investor risk-aversion during up markets, and these work to increase momentum profits (Cooper, Guitierrez, and Hameed (2004)). Thus, the behavioral models suggest that the higher momentum profits among the non-dividend-paying stocks stem from higher price appreciations among these stocks when the markets are advancing. Consistent with this prediction, the evidence suggests that price appreciations among the non-dividend-paying stocks are higher than those among the dividend payers. This is due to asymmetric valuation of the dividend signal and the fact that growth opportunities are more important for the non-dividend-paying stocks. The evidence is, therefore, more consistent with the behavioral explanation for the higher momentum profit following up markets than the rational asset pricing explanation.

A behavioral asset pricing model with a time-varying second moment

We develop a simple behavioral asset pricing model with fundamentalists and chartists in order to study price behavior in financial markets when chartists estimate both conditional mean and variance by using a weighted averaging process. Through a stability, bifurcation, and normal form analysis, the market impact of the weighting process and time-varying second moment are examined. It is found that the fundamental price becomes stable (unstable) when the activities from both types of traders are balanced (unbalanced). When the fundamental price becomes unstable, the weighting process leads to different price dynamics, depending on whether the chartists act as either trend followers or contrarians. It is also found that a time-varying second moment of the chartists does not change the stability of the fundamental price, but it does influence the stability of the bifurcations. The bifurcation becomes stable (unstable) when the chartists are more (less) concerned about the market risk characterized by the time-varying second moment. Different routes to complicated price dynamics are also observed. The analysis provides an analytical foundation for the statistical analysis of the corresponding stochastic version of this type of behavioral model.

Do Stock Price Bubbles Influence Corporate Investment?

Building on recent developments in behavioral asset pricing, we develop a model in which an increase in the dispersion of investor beliefs under short-selling constraints predicts a bubble, or a rise in a stock's price above its fundamental value. Our model predicts that managers respond to bubbles by issuing new equity and increasing capital expenditures. We test these predictions, as well as others, using the variance of analysts' earnings forecasts - a proxy for the dispersion of investor beliefs - to identify the bubble component in Tobin's Q. When comparing firms traded on the New York Stock Exchange with those traded on NASDAQ, we find that our model successfully captures key features of the technology boom of the 1990s. We obtain further evidence supporting our model by using a panel-data VAR framework. We find that orthogonalized shocks to dispersion have positive and statistically significant effects on Tobin's Q, net equity issuance, and real investment - results that are consistent with the model's predictions.