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We examine explicitly priced financial distress risk in post-1990 equity markets. We add a financial distress risk factor to Fama and French's (1993) three-factor model, based on Griffin and Lemmon's (2002) findings that financial distress is not fully captured by the book-to-market factor. We test three-factor and four-factor capital asset pricing models using both annual buy-and-hold analysis and monthly time series analysis across portfolios adjusted for common book-to-market, size, and financial distress factors. We find empirical support for an Ohlson (1980) O-score-based financial distress risk four-factor asset pricing model in the U.S. and Japanese markets.

Lai, Li, Conover, and Wu (2010) propose a four-factor financial distress model to explain stock returns in the U.S. and Japanese markets. We examine this model in the stock markets of Australia, and six Asian markets (Hong Kong, Indonesia, Korea, Malaysia, Singapore, and Thailand). We find broad empirical support for the four-factor financial distress risk asset-pricing model in those markets. The four-factor financial distress asset pricing model improves explanatory power beyond the Fama–French (1993) three-factor asset pricing model in six of the seven Asian-Pacific markets (12 of 14 portfolio groupings), while the Carhart (1997) momentum-based asset pricing model only improves explanatory power beyond the Fama–French model in three of the seven markets (4 of 14 portfolio groupings).

The aim of this study is to investigate the role of efficiency in capital asset pricing. The paper explores the impact of a four-factor model that involves an efficiency factor on the returns of Nasdaq technology firms.

The paper relies on data of 147 firms from July 2007 to June 2017 to examine the impact of efficiency on stock returns. The performances of the capital asset pricing model (CAPM), Fama–French three-factor model and the proposed four-factor model are evaluated based on the time series regression method. The parameters such as the GRS F-statistic and adjusted R² are used to compare the relative performances of all models.

The results show that all factors of the models are found to be valid in asset pricing. Also, the paper provides evidence that the explanatory power of the proposed four-factor model outperforms the explanatory power of the CAPM and Fama–French three-factor model.

Unlike most asset pricing studies, this paper presents a new asset pricing model by adding the efficiency factor to the Fama–French three-factor model. It is documented that the efficiency factor increases the predictive ability of stock returns. Evidence implies that investors consider efficiency as one of the main factors in pricing their assets.

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.

This research aims to examine hedge funds’ performance, risk and flow before and after the implementation of the Stop Trading on Congressional Knowledge (STOCK) Act.

This paper includes the use of different factor models to highlight the performance and risk of hedge funds before and after the implementation of the STOCK Act. Hedge fund holdings are retrieved from Thomson Reuters Lipper Hedge Fund Database (TASS).

This study finds significant differences before and after the implementation of the STOCK Act. The results for the entire sample period indicate that hedge funds suffered lower-alpha, standard deviation and idiosyncratic risk after the implementation of the STOCK Act.

The paper’s originality and value lie in addressing the relationship gap between the STOCK Act and hedge fund performance.

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 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 research is to examine relationships between emotional intelligence and the four factor model of cultural intelligence – metacognitive CQ, cognitive CQ, motivational CQ, and behavioral CQ.

Confirmatory factor analyses and hierarchical regression analyses on data from 381 students in Korea are conducted.

The results support discriminant validity of the four factor model of cultural intelligence scale (CQS) in relation to the emotional intelligence (EQ) construct. This study also demonstrates that the EQ factors related to social competence (social awareness and relationship management) explain CQ over and beyond the EQ factors related to self‐competence (self‐awareness, and relationship management). Finally, the results present that specific factors of EQ are related to specific factors of CQ.

The findings of this study demonstrate how CQ and EQ are distinct, but related constructs, which has not been conducted by prior research.

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 present findings from two studies exploring the Health of the Nation Outcome Scale’s (HoNOS) utility within a new payment by results (PbR) system for mental health services in England.

In the first study principal axis factoring extraction was used to explore a sample of 23,641 HoNOS ratings. In a second study confirmatory factor analysis was used to evaluate four subscale structures on a new sample of 34,716 HoNOS ratings.

No HoNOS factor structure evaluated in this study demonstrated adequate fit statistics across several clinical presentations. A new four-factor model was the only structure to achieve fit statistics across all clinical populations, but can only be championed on a “best fit” basis as opposed to “good fit” at the present time.

Data used in the current studies relate to six NHS mental health service providers. Replication using a national sample is recommended. Exploration of different HoNOS factor structures for different mental health clusters within the PbR system in England is also recommended. However, it is also possible that removing redundant or adding new items may result in a more stable HoNOS generic factor structure.

This is the first HoNOS evaluation as a generic outcome measure for use within a PbR system and provides important insights into its mental health utility and limitations. The findings have significant implications for those developing the national PbR quality and outcomes framework for England’s mental health services. However, there are also implications for all nations in which HoNOS is used to report mental health outcomes.