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This paper aims to investigate whether the use of conditional and unconditional Fama and French (1993) three-factor and Carhart (1997) four-factor asset pricing models (APMs) captures the role of asset pricing anomalies in the context of emerging stock market like India.

The first step time series regression approach has been used to drive the risk-adjusted returns of individual securities. For examining the predictability of firm characteristics or asset pricing anomalies on the risk-adjusted returns of individual securities, the panel data estimation technique has been used.

Fama and French (1993) three-factor and Carhart (1997) four-factor model in their unconditional specifications capture the impact of book-to-market price and liquidity effects completely. When alternative APMs in their conditional specifications are tested, the importance of medium- and long-term momentum effects has been captured to a greater extent. The size, market leverage and short-term momentum effects still persist even in the case of alternative unconditional and conditional APMs.

The empirical analysis does not extend for different market scenarios like high and low volatile market or good and bad macroeconomic environment. Because of the constraint of data availability, the authors could not include certain important anomalies like net operating assets, change in gross profit margin, external equity and debt financing and idiosyncratic risk.

Although the active investment approach in stock market shares a common ground of semi-strong form of market efficiency hypothesis which also supports the presence of asset pricing anomalies, less empirical evidence has been explored in this regard to support or repute such belief of practitioners. Our empirical findings make an attempt in this regard to suggest certain anomaly-based trading strategy that can be followed for active portfolio management.

From an emerging market perspective, this paper provides out-of-sample empirical evidence toward the use of conditional Fama and French three-factor and Carhart four-factor APMs for the complete explanation of market anomalies. This approach retains its importance with respect to the comprehensiveness of analysis considering alternative APMs for capturing unique effects of market anomalies.

The purpose of this study is to explore the applicability of the Fama–French and Carhart models on the South African stock market (SASM). It examines the ability of the models to capture size, book-to-market (BM) and momentum effects on the SASM. The paper, additionally, explores the ability of the Fama–French–Carhart factors to predict the future growth of the South African economy.

The paper relies on data of 848 firms from January 1996 to April 2012 to examine the size, BM and momentum effects on the SASM. The paper constructs the test assets from a 3 × 3 sort on size and BM and a 3 × 3 sort on size and momentum. The paper estimates momentum as the past six-months’ cumulative return. The momentum portfolios are monthly rebalanced. Additionally, the size and BM portfolios are formed annually at the end of each June.

Evidence is provided that size, BM and momentum effects exist on the SASM; also, the small- and high-BM firm portfolios, respectively, appear riskier than the big- and low-BM firm portfolios. The paper provides evidence of past winners outperforming past losers aside from the small-firm group. Additionally, the models only partially capture the size and value effects on the SASM. The Carhart model partly captures the momentum effects, but the Fama–French model is unable to describe the returns to the momentum-sorted portfolios. The evidence shows that the models’ factors predict future gross domestic product growth.

The models do not fully describe returns on the SASM; any application of the models on the SASM should be done with caution. The Carhart model better describes returns than the Fama–French model on the SASM. The Fama–French–Carhart factors may relate to the underlying economic risk of the South African economy.

The purpose of this paper is to perform a relative assessment of performance benchmarks based on alternative asset pricing models to evaluate performance of mutual funds and suggest the best approach in Indian context.

Sample of 237 open-ended Indian equity (growth) schemes from April 2003 to March 2013 is used. Both unconditional and conditional versions of eight performance models are employed, namely, Jensen (1968) measure, three-moment asset pricing model, four-moment asset pricing model, Fama and French (1993) three-factor model, Carhart (1997) four-factor model, Elton et al. (1999) five-index model, Fama and French (2015) five-factor model and firm quality five-factor model.

Conditional version of Carhart (1997) model is found to be the most appropriate performance benchmark in the Indian context. Success of conditional models over unconditional models highlights that fund managers dynamically manage their portfolios.

A significant α generated over and above the return estimated using Carhart’s (1997) model reflects true stock-picking skills of fund managers and it is, therefore, worth paying an active management fee. Stock exchanges and credit rating agencies in India should construct indices incorporating size, value and momentum factors to be used for purpose of benchmarking.

The study adds new evidence as to applicability of established asset pricing models as performance benchmarks in emerging market India. It examines role of higher order moments in explaining mutual fund returns which is an under researched area.

The purpose of this paper is to present and demonstrate how the use of a multifactor model in the analysis of market timing skill can be misleading because the use of a multifactor model does not suit all investment styles equally well. If the factors of the analysis model do not span the portfolio holdings of a fund with less conventional investment strategy, the use of a multifactor model may even deteriorate the overall inference in measuring the market timing skill of a large sample of funds.

This study investigates the limitations of multifactor models in the analysis of market timing skill by applying the traditional Treynor-Mazuy and Henriksson-Merton analysis models of market timing skill using a set of “placebo” funds which are “natural” passive market timers.

The results of the study show that the incorporation of the Carhart four-factor model into the analysis of market timing skill considerably reduces the percentage of significant market timing results. But, as expected, the reduction of bias is not equal for different investment styles, and it works best when the factors of the analysis model are related to the investment style of the placebo portfolio.

This style-related limitation of multifactor models in the analysis of market timing skill may result in detecting funds with less conventional investment strategies as market timers since the factors used in the analysis are not likely to span their investment styles.

This study shows that the use of a multifactor model may lead to inferring passive market timers with less conventional investment styles as market timers. In addition, the findings of the study leave option replication approaches as more preferable bias corrections than multifactor extensions.

The purpose of this paper is to examine the effect of international financial reporting standards (IFRS) on the performance of UK investment closed-end trust funds with domestic equity focus using Carhart’s Four-Factor model.

The paper is based on the Efficient Market Hypothesis, which argues that all available information is already included in the price of assets, and therefore, investors cannot beat the market or generate abnormal returns.

The results show that on average, UK investment trusts neither do generate abnormal returns, nor is their performance persistent. This paper provides empirical evidence to support the efficient market hypotheses and provides proof that the adoption of IFRS has, on average, a decreasing impact on the excess returns generated by UK investment trusts.

The findings of this paper have business policy implications for investment trust in the UK.

The purpose of this paper is to examine the level of foreign exchange exposure of listed nonfinancial firms in South Africa. The study spans the period January 2002 and November 2015. Foreign exchange risk exposure is estimated in relation to the exchange rate of the South African Rand relative to the US$, the Euro, the British Pound and the trade-weighted exchange rate index.

The study is based on the augmented-market model of Jorion (1990). The Jorion (1990) is a capital asset pricing model-inspired framework which models share returns as a function of the return on the market index and changes in the exchange rate factor. The market risk factor is meant to discount the effect of macroeconomic factors on share returns, thus isolating the foreign exchange risk factor. In addition, the study further added the size, value, momentum, investment and profitability risk factors in line with the Fama–French three-factor model, Carhart four-factor model and the Fama–French five-factor model to account for the fact that equity capital markets in countries such as South Africa are known to be partially segmented.

Foreign exchange risk exposure levels were estimated at more than 40% for all the proxy currencies on the basis of the standard augmented market model. However, after controlling for idiosyncratic factors, through the application of the Fama–French three-factor model, the Carhart four-factor model and the Fama–French five-factor model, exposure levels were found to range between 6.5 and 12%.

These results indicate the importance of controlling for the effects of idiosyncratic facto0rs in the estimation of foreign exchange risk exposure in the context of emerging markets of Sub-Saharan Africa (SSA).

This is the first study to apply the Fama–French three-factor model, Carhart four-factor model and the Fama–French five-factor model in the estimation of foreign exchange exposure of nonfinancial firms in the context of a SSA country. These results indicate the importance of controlling for the effects of idiosyncratic factors in the estimation of foreign exchange risk exposure in the context of emerging markets.

The purpose of this paper is to create a quantitative measure that captures the effects of investor sentiment in an objective way.

The author introduced risk estimation bias (REB) to examine the effects of forecasting error of future market volatility on fund alpha. The author also used GARCH to model the volatility of the REB.

The author documented a statistically significant relation between REB and realized market volatility. The author also found that the REB plays a significant role in explaining fund alpha.

REB is the first quantitative measure to examine the effects of investor sentiment on risk estimation and fund performance. The GRACH properties of REB provide important information on how investor sentiment fluctuates over time.

The purpose of this paper is to investigate the return performance of a portfolio of US “vice stocks,” firms that manufacture and sell products such as alcohol, tobacco, gaming services, national defense and firearms, adult entertainment, and payday lenders.

Using daily return data from a portfolio of vice stocks over the period 1987-2016, the author computes the Jensen’s α (capital asset pricing model (CAPM)), Fama-French Three-Factor, Carhart Four-Factor, and Fama-French Five-Factor results for the complete portfolio, and each vice industry individually.

The results from the CAPM, Fama-French Three-Factor Model, and the Carhart Four-Factor Model show a positive and significant α for the vice portfolio throughout the sample period. However, the α’s significance disappears with the addition of the explanatory variables from the Fama-French Five-Factor Model.

The author provides academics and practitioners with results from a new model. As of this writing, the author is unaware of any articles published in peer-reviewed academic journals that investigate vice stocks within the framework of the Fama-French Five-Factor Model (2015). First, the existing literature does not shed light on the relationship between “profitability” and “aggressiveness” (the fourth and fifth factors of the Fama-French Model) and vice stock returns. Second, within the framework of the Fama-French Five-Factor Model, the author shows results not only from a portfolio of vice stocks, but from various vice industries as well.

This study examines the effect of business cycle, market return and momentum on the financial performance of socially responsible investing (SRI) mutual funds using data from two complete business cycles as defined by the National Bureau of Economic Research (NBER).

A “fund of funds” approach is used to identify the extent to which SRI financial performance is affected by the macroeconomic climate. The Fama-French Three-Factor model and the Carhart four-factor model are used to bring the results into alignment with commonly used finance methodologies.

The results indicate that SRI tends to preserve value during economic contraction more than it adds value during economic expansion. Market return is important during both expansion and contraction, while momentum is important only during expansion.

These findings suggest that double screening, for both financial and social performance, enables portfolio managers of SRI funds to have insight into those companies that are particularly vulnerable during times of economic contraction.

These results bring added clarity to the mixed findings found by previous researchers examining the relationship between corporate social performance (CSP) and financial performance.

This study reinforces the idea that the financial performance of companies with high ethical standards is comparable to the financial performance of the market as a whole during times of economic expansion and superior to the market as a whole during times of economic contraction.

Business cycle analysis, along with the Fama-French Three-Factor model and the Carhart four-factor model, brings SRI research more into the realm of conventional financial analysis than previous studies.

The purpose of this study is to update the investment literature by providing latest evidence of performance of Islamic mutual funds by using global sample mutual funds data to support with empirical facts.

This study analyzes the comparative performance of Islamic and conventional mutual funds by using capital asset pricing model, Fama & French’s three-factor model and Carhart’s four-factor model. Further, the study tested the coskenwness effect by using data envelopment analysis approach.

The authors find evidence that when size of the funds is controlled, Islamic investment underperform the conventional mutual funds in four out of six models. The size of underperformance varies from model to model: from 32 basis points in the Carhart’s four-factor model with the skewness factor to two basis points at the Fama and French’s three-factor model. Also the study finds that alpha(s) are only insignificant for conventional mutual funds when the skewness factor is included in the regression. While comparing the loading on Islamic mutual funds, results show that Islamic mutual funds are less risky than conventional mutual funds when they are controlled for skewness.

This study uses the different factor models of performance evolution which help in overcoming weakness of measuring the Islamic mutual funds’ performance.