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Asset pricing revolves around the core aspects of risk and expected return. The main objective of the study is to test different asset pricing models for the Indian securities market. This paper aims to analyse whether leverage and liquidity augmented five-factor model performs better than Capital Asset Pricing Model (CAPM), Fama and French three-factor model, leverage augmented four-factor model and liquidity augmented four-factor model.

The data for the current study comprises records on prices of securities that are part of the Nifty 500 index for a time frame of 14 years, that is, from October 2004 to September 2017 consisting of 183 companies using time series regression.

The results indicate that the five-factor model performs better than CAPM and the three-factor model. The model outperforms leverage augmented and liquidity augmented four-factor models. The empirical evidence shows that the five-factor model has the highest explanatory power among the entire asset pricing models considered.

The present study bears certain useful implications for various stakeholders including fund managers, investors and academicians.

This study presents a five-factor model containing two additional factors, that is, leverage and liquidity risk along with the Fama-French three-factor model. These factors are expected to give more value to the model in comparison to the Fama-French three-factor model.

The purpose of this paper is to examine socially responsible investment (SRI) fund performance and investigate the factors influencing fund performance.

The study uses return data from the Morningstar database for 152 SRI funds from January 1995 to May 2015. The initial analysis includes the use of various risk-adjusted performance measures, including Sharpe ratio, Treynor ratio, Information ratio, Sortino ratio and M². The study also uses four factor models, including Jensen single-factor model, Fama–French three-factor model, Carhart four-factor model and Fama–French five-factor model to explain SRI fund returns. Finally, a cross-sectional regression analysis is applied to investigate the determinants of SRI fund returns.

The results show that, on average, the SRI funds provide comparable risk-adjusted returns relative to various benchmark market indices. Market factor is significant in explaining SRI fund returns. Examining each factor model, the results do not support Fama–French’s three-factor model as neither size nor value factor is significant. The author finds weak support for Carhart’s momentum factor along with the market factor. Finally, the Fama–French five-factor model shows market, size and operating profit factors explain SRI fund returns. The study also finds the fund performance is stronger for funds with the higher turnover ratio, the larger fund size and more managerial experience and lower for funds with higher expense ratio. Also, funds formed with negative screening perform better than positive or mixed screened funds.

SRI funds have received considerable attention from investors. This study contributes to the literature by examining SRI fund performance and investigating factors influencing their performance using multiple factor models and cross-sectional regression analysis. The findings are relevant for investors who demand responsible investment opportunities without sacrificing returns for nonfinancial screenings. Findings also suggest that investors should consider fund characteristics when selecting SRI funds.

The purpose of this paper is to examine the performance of portfolios that are constructed based on environmental, social and governance (ESG) scores and consist of stocks located in Europe and Turkey.

In order to form the portfolios, firstly all stocks are ranked in a descending way based on ESG-based (ESG, environmental, social and governance) scores, separately. Then, 10% of stocks with the highest scores are included in the “Top” portfolio and 10% of stocks with the lowest scores are included in “Bottom” portfolio and totally performance of eight portfolios are investigated. Finally, capital asset pricing model (CAPM) and Fama-French three-factor model are employed as performance measurement benchmarks.

Results obtained from CAPM regression show that using ESG-based scores two portfolios underperform the market index. The results of the three-factor model provide that performances of Bottom ESG and Bottom GOV portfolios outperform the market excess return by 0.57% and 0.53%. The overall findings of this paper indicate that there is no relationship between socially responsible investment (SRI) and portfolio performance. These findings are in line with the efficient market hypothesis which indicates all information is reflected in prices.

The aim of the study is to provide insight on the question of “whether SRI has any effect on the portfolio performance”. As far as the literature review is concerned it is seen that this study provide additional insight by utilizing a longer time span together with data from numerous markets.

The dividend month premium is the phenomenon that firms have abnormal returns in predicted dividend month. This study aims to examine the dividend month premium in the Korean stock market, using common stocks listed on the KOSPI and KOSDAQ from January 1999 to December 2016. Abnormal returns are estimated using the following asset price models: capital asset pricing model, Fama–French three-factor model and the Fama–French–Carhart four-factor model. This study finds positive abnormal returns in predicted dividend months, and even for the within-firm portfolio that buys stocks in the predicted dividend months and sells the same stocks in other months. The price impact and the subsequent reversals are greater with lower liquidity and higher dividend yield, implying that the price pressure from dividend-seeking investors affects this dividend month premium. In addition, the anomalies with the pre-declaration stock are smaller than the post-declaration stock, suggesting the necessity to improve the cash dividend policy of post-declaration for market efficiency.

Fama–French model (FFM) has been successful in helping to predict the financial markets, but investors have been interested in creating more sophisticated models to better predict the performance of the stock market. The objective of the extended version is to create a more robust econometric model to better predict the performance of the Mexican Stock Market.

The study divides the Mexican Stock Market into six different portfolios. The criteria to build those portfolios are the same one used in Fama–French (1992). The study comprises 78 stocks listed in the Mexican Stock Market that are analyzed monthly during 1997–2018. The study analyzes the period before and after the 2008–2009 financial crisis to identify whether there are important changes. The estimation applies the traditional and an extended version of the FFM that include macroeconomic variables such as country risk, economic activity, inflation rate, and exchange rate and some financial variables recommended in the literature.

Results indicate that classic FFM variables are statistically significant in most cases, but relevant macroeconomic variables such as the interest rate, exchange rate and country risk stand out for being weakly relevant in most of the portfolios. However, it is noticed that some of these macroeconomic variables became relevant for different portfolios only after the 2008–2009 crisis, especially in portfolios which include small market capitalization firms.

The study includes the stocks listed in the Mexican Stock Market. One limitation is the small number of stocks available, which reduces the possibility of creating well diversified portfolios. This study includes 78 stocks. The stocks removed from the sample are from firms that were not listed during six consecutive months or whose market capitalization did not change in the same period. Outlier data were removed from the sample to capture in better way the general performance of the stock market.

The objective of the extended version is to create a more robust econometric model than the traditional model. It is expected that such estimations can be helpful to investors to make better decisions when they try to predict performance in the stock market.

An extended version of the FFM can be helpful to investors to make better decisions when they try to predict performance in the stock market.

To the best of our knowledge there are no more studies in the literature of the Mexican financial market that apply the same methodology.

This study aims to comparatively analyze the systematic, idiosyncratic and downside risk exposure of both Islamic and conventional funds in Pakistan to see which of the funds has higher risk exposure.

The study analyzes different types of risks involved in both Islamic and conventional funds for the period from 2009 to 2016 by using different risk measures. For systematic and idiosyncratic risk single factor CAPM and multifactor models such as Fama French three factors model and Carhart four factors model are used. For downside risk analysis different measures such as downside beta, relative beta, value at risk and expected short fall are used.

The study finds that Islamic funds have lower risk exposure (including total, systematic, idiosyncratic and downside risk) compared with their conventional counterparts in most of the sample years, and hence, making them appear more attractive for investment especially for Sharīʿah-compliant investors preferring low risk preferences.

As this study shows, Islamic mutual funds exhibit lower risk exposure than their conventional counterparts so investors with lower risk preferences can invest in these kinds of funds. In this way, this research provides the input to the individual investors (especially Sharīʿah-compliant investors who want to avoid interest based investment) to help them with their investment decisions as they can make a more diversified portfolio by considering Islamic funds as a mean for reducing the risk exposure.

To the best of the author’s knowledge, this study is the first attempt at world level in looking at the comparative risk analysis of various types of the risks as follows: systematic, idiosyncratic and downside risk, for both Islamic and conventional funds, and thus, provides significant contribution in the literature of mutual funds.

This paper aims to investigate how organization capital influences different forms of corporate risk. It also explores how the relationship between organization capital and risks varies in the cross-section of firms.

To test the hypothesis, this study employs the ordinary least squares (OLS) regression model using a large sample of the United States (US) data over the 1981–2019 period. It also uses an instrumental variable approach and an errors-in-variables panel regression approach to mitigate endogeneity problems.

The empirical results show that organization capital is positively related to both idiosyncratic risk and total risk but negatively related to systematic risk. The cross-sectional analysis shows that the positive relationship between organization capital and idiosyncratic risk is significantly more pronounced for the subsample of firms with high information asymmetry and human capital. Moreover, the negative relationship between organization capital and systematic risk is significantly more pronounced for firms with greater efficiency and firms facing higher industry- and economy-wide risks.

The findings have important implications for investors and policymakers. For example, since organization capital increases idiosyncratic risk and total risk but reduces systematic risk, investors should take organization capital into account in portfolio formation and risk management. Moreover, the findings lend support to the argument on the recognition of intangible assets in financial statements. In particular, the study suggests that standard-setting bodies should consider corporate reporting frameworks to incorporate the disclosure of intangible assets into financial statements, particularly given the recent surge of corporate intangible assets and their critical impact on corporate risks.

To the best of the authors' knowledge, this is the first study to adopt a large sample to provide systematic evidence on the relationship between organization capital and a wide range of risks at the firm level. The authors show that the effect of organization capital on firm risks differs remarkably depending on the kind of firm risk a particular risk measure captures. This study thus makes an original contribution to resolving competing views on the effect of organization capital on firm risks.

This paper examines the role of illiquidity and duration factor in understanding the momentum profit in the Korean stock market. We find that the foreigner/institutional illiquidity factor explains the momentum effect. In addition, this paper finds that duration factor defined as the difference in returns of short-duration and long-duration stocks captures well the momentum profits. That is, a two-factor model with the market and duration factor performs much better than competing asset pricing models in explaining the momentum effect. Finally, when controlling for the duration factor, the explanatory power of the foreign/institutional illiquidity factor on the momentum profits disappears. In sum, our empirical finding indicates that the duration factor is the most important ingredient in understanding the momentum effect in the Korean stock market.

There have always been North Korea Risks in South Korea stock market since its opening. Some studies have concluded that it does not have a substantial impact on South Korea’s economy due to chronic geopolitical risks, while others have argued it has had an impact. However, in light of the Efficient Market Hypothesis (EMH) it can be argued that both opinions view that information about North Korea Risks affects stock markets and that stock prices react to it. This study analyzed the effects of North Korea Risks on South Korea’s stock market using event study methodology empirically, and it tested the semi-strong EMH-a market in which prices always fully reflect available information. The research results are following:

First of all, North Korea Risks have an impact on South Korea’s stock market and the data was statistically significant. In particular, stock market already reflected information about the forewarned events like nuclear test. However, market also responded to information about sudden events such as the impact of Kim Jung-il’s death on the South-North economic cooperation stock. Portfolio analysis demonstrated that small capital stocks were affected more than large caps. These results cannot reject the EMH.

Also, estimates of market model and that of Fama-French three-factor model did not show a statistically significant difference in different verification. There was no statistically significant difference between growth and value stock in large caps portfolio either. However, there was a statistically significant difference between defense stock and South-North economic cooperation stock, small caps and big caps, and weighted average and simple average.

The significance of this study lies in that it conducted the event study by variety estimation model with objective standards for selecting events when measuring the effect of North Korea Risks.