Investor Psychology and Security Market Under- and Overreactions

Beginning with Banz (1981), I review 30 years of research on the size effect in equity returns. Since Fama and French (1992), there has been a vigorous, ongoing debate on whether the size premium is a compensation for systematic risk. Since the late 1990s, research on the size effect has been characterized by two developments that are seemingly contradictory. At last, theoretical models have emerged in which the size effect arises endogenously as a result of systematic risk. However, recent empirical studies assert that the size effect has disappeared after the early 1980s. In this review, I address this disconnect between recent theoretical and empirical research.

Is Size Dead? A Review of the Size Effect in Equity Returns

No news is good news--or is it?

https://isiarticles.com/bundles/Article/pre/pdf/16030.pdf

Assessing the impact of oil returns on emerging stock markets: A panel data approach for ten Central and Eastern European Countries

Book-to-Market across Firm Size, Exchange, and Seasonality: Is There an Effect?

The Capital Asset Pricing Model (CAPM) of Sharpe (1964), Lintner (1965), and Black (1972) (SLB) states that, in equilibrium, the expected return on a security is a positive linear function of its beta, and beta suffice to describe the cross-section of expected returns. The empirical studies on the validity of the positive beta-return relationship of the SLB model have been extensively carried out for the past four decades using average realized stock returns and an index of security returns to proxy for expected returns of stocks and market portfolio respectively. Early studies have supported the positive linear relationship between beta and return (e.g., Lintner (1965)). However, studies conducted after Fama and MacBeth (1973) (FM) have found inconsistent evidence on this relationship. For example, Fama and French (1992) conclude that the relationship between beta and average return is flat. In the Tokyo Stock Exchange (TSE), Nimal and Horimoto (2005) report that the beta and average return relationship is not significant in all months and even it is negatively significant in non-January months in some periods. Also in Sri Lankan context Samarakoon (1997) finds negative beta-return relationship and Anuradha (2008) reports insignificant beta-return relation in the Colombo Stock Exchange (CSE). The question is whether the inconsistent evidence on the relationship between beta and average return is sufficient to conclude that the movements of realized return are not systematically related with their betas1). Pettengill, The Conditional Relation between Beta and Returns

The Conditional Relation between Beta and Returns

Increasing competition in the finance sector in Sri Lank has created a huge competition among the banking sector. The high level of competition improved the bank efficiency and efficiency creates risk to the banks. Therefore, risk management is a vital in achieving efficiency. Therefore, this study addresses the question on “whether the Sri Lankan banks are efficient and how risk management improves the banks’ efficiency?. The main objective of the study was to identify the efficiency of the banks by incorporating risk factors. This study adopted second Stage Data Envelopment Analysis based on Licensed Domestic Commercial Banks in Sri Lanka for the period from 2005 to 2011. At the first stage it use DEA to finds the efficiency scores by incorporating risk factors such as Credit, Market and Operational risk. In the second stage it applies Tobit regression to find the influence of external environment factors on bank efficiency. The mean efficiency of Sri Lankan banks is high when it compares with the other well countries such as India, UK, US, Taiwan and Islamic Banks located in London. Risk management has improved the efficiency of the Licensed Commercial Banks in Sri Lanka. Therefore, banks should identify their standing on the market on efficiency levels and should analyze their inefficiencies to improve the efficiencies further.

Does Risk Management affect on Bank Efficiency? An Analysis of Sri Lankan Banking Sector

There have been numerous studies that have attempted to explain the cross-sectional variation in average returns in developed and emerging markets. However, there is a dearth in the published evidence of research that has looked at frontier markets regarding this aspect. Sri Lanka is considered to be a frontier market and hence the objective of this study is to test the ability of the Carhart four-factor model to explain the variation in the cross-section of average stock returns in the Colombo Stock Exchange (CSE) and to evaluate it in comparison to the capital asset pricing model (CAPM) and the Fama and French three-factor model. The study finds that the four-factor model, incorporating the market factor, size factor, value factor and momentum factor, provides a satisfactory explanation of the variation in the cross-section of average stock returns in the CSE. Further, it is found that the four-factor model performs better than the CAPM and the three-factor model.

P. D. Nimal

Papers

The Conditional Relation between Beta and Returns

Does Risk Management affect on Bank Efficiency? An Analysis of Sri Lankan Banking Sector

The four-factor model and stock returns: evidence from Sri Lanka

The Conditional Relation between Beta and Returns : Evidence from Japan and Sri Lanka

An empirical analysis of capital asset pricing model