Theses and Dissertations - UTB/UTPA

Date of Award


Document Type


Degree Name

Doctor of Philosophy (PhD)



First Advisor

Dr. Gökçe A. Soydemir

Second Advisor

Dr. Alberto Davila

Third Advisor

Dr. Marie T. Mora


In recent years there has been a growing debate on the possible linkages between the behavioral aspects of investors and stock prices. The financial economics have become more receptive to imperfect rational explanations and in this regard, investor psychology has emerged as a major determinant of stock prices. Under this approach, the central task is to examine how stock prices are related not only to risks, but also to the noise (Hirshleifer, 2001). After decades of study, the sources of risk premium in purely rational dynamic models are well understood; while, dynamic psychology based asset pricing theories are still in the infancy stage. This debate surrounding asset pricing has identified two prime suspects in setting stock prices: fundamentals and investor sentiments.

The theoretical framework describing the role investor sentiments play in determining stock prices is provided by researchers such as Black (1986), Trueman (1988), DeLong et al. (1990), Shleifer and Summers (1990), Lakonishok et al. (1991), Campbell and Kyle (1993), Shefrin and Statman (1994), Palomino (1996), Barberis et al.(1998), Daniel et al.(1998) and Hong and Stein (1999). A direct implication of these studies is certain groups of investors (noise traders) who often do not make investment decisions based on a company's fundamentals are capable of affecting stock prices by way of unpredictable changes in their sentiments.

Despite a substantial amount of literature on the role of investor sentiments in determining stock prices, there is still no coherent answer on whether these effects can be attributed entirely to investor exuberance, or to fully rational expectations based on the risk factors, or both. Using a unique monthly database of investor sentiments at the individual and institutional level, and by employing recent multivariate techniques, this study sheds new light on the issue of investor rationality.

The results of the generalized impulses generated from vector auto regression (VAR) models suggest the following: first, individual investor sentiments have a greater effect on the U.S. stock market returns, while institutional investor sentiments have a greater effect on large stocks; second, individual investors are more likely to be the noise traders in the case of the overall market, while institutional investors are more likely to be noise traders in the case of large stocks; third, the effect of sentiments induced fundamental trading is greater than the effect of sentiments induced noise trading in the cases of both the overall market and the large stocks; fourth, both the individual and institutional investors display significant extrapolation bias and undertake positive feedback trading; fifth: there is an asymmetric response to fundamental and noise trading by individual and institutional investors during optimistic and pessimistic periods; sixth, the institutional investor sentiments are transmitted internationally from the U.S. stock market to a greater extent than the individual investor sentiments; and lastly, the iv international effects of the U.S. stock market can be attributed to fundamental trading and not noise trading in the U.S.

The results lend more support to the risk based explanations of asset pricing. Investors could therefore improve their portfolio performance by considering the stability in risk factors as determinants of stock prices. Policy makers can concentrate their efforts to attain stability in fundamentals in order to reduce volatility and minimize investor uncertainty.


Copyright 2004 Rahul Verma. All Rights Reserved.

Granting Institution

University of Texas-Pan American