Carhart 4-factor Model Research Articles

Outperforming the market: a comparison of Star and NonStar analysts’ investment strategies and recommendations

AbstractWe employ StarMine to investigate the impact of analyst recommendations on stock performance. We test whether star-ranked analysts generate abnormal returns and outperform non-stars in short and long portfolios. Utilizing buy-and-hold calendar-time portfolio methodology, we calculate portfolio alphas using various asset pricing models, including CPM, the Fama and French 3-factor model, and the Carhart 4-factor model. Results indicate that all analyst groups can generate abnormal returns exceeding the market average. Star-ranked analysts outperform non-stars in short portfolios by 0.5523% in monthly alpha, though no significant difference exists in long portfolio alphas. We also conduct regressor endogeneity tests and explore investor sentiment mechanisms by utilizing the GARCH model and frequency-domain causality analysis, with NASDAQ as a proxy for investor sentiment. These tests reveal that the momentum factor is exogenous, and investor sentiments have a statistically significant positive effect on stock return volatility, with changes occurring between 5 and 10 days. This research underscores the value of analyst insights for investors, validates StarMine’s ranking effectiveness, and suggests market participants can benefit from incorporating analyst recommendations into their investment decisions. Our study makes a significant contribution to the existing literature by introducing a novel approach to understanding investor sentiment mechanisms through a causality model.

Mutual Fund Performance Persistence and Competition: Pakistan’s Open Ended Mutual Fund Performance Analysis

Mutual Funds through its professional managers enable small investors to enjoy benefits of capital market with small amount. This study with special focus on Pakistani Mutual Fund industry, tests the suitability of traditional measures and multifactor, asset pricing models on the Mutual Fund performance. Owing to rareness of the applicability of the multifactor models in comparison to traditional measures, in evaluating Mutual Fund performance in modern day Pakistani research, the study uses CAPM, Fama French, Carhart models in the performance evaluation of Pakistan Mutual Fund. The data of 100 open-end Mutual Funds, for the period 2005 to 2017 was collected from Mutual Fund Association of Pakistan; while the risk free rates data was collected from State Bank of Pakistan and Stock data from Pakistan Stock Exchange for predicting the results, Ratio analysis, CAPM, Fama French-3 Factor and Carhart-4 factor model were used to understand its suitability. The results demonstrated that application of CAPM, affect market factors of majority of the portfolios.Where as in other two models (Fama French, Carhart) the majority of the portfolios are insignificantly affected by the size factor, value factor and Momentum factor. The Gibbon Rose Shanken unveils the suitability of the best model and justify CAPM as the better model among the three competing models in evaluate on theMutual Fund performance in Pakistan. The study has certain implications for the managers of assets management companies as well as useful for the investors in knowing which funds perform better and which kind of funds are ideal for investment.

Capital market reactions to project finance loans

Theory predicts that bank loan announcements could increase share prices of loan recipients through a certification effect. We provide complementary evidence using the novel market setting of project finance loans. Since the loans are off-balance-sheet, there should be no certification effect. Applying an event study methodology and the Carhart 4-factor model to a large international dataset, we find that project sponsors do not experience positive abnormal returns after announcements, but lenders do. We also find that sponsors and lenders tend to experience greater equity return volatility after announcements.

Additional factor in asset-pricing: Institutional ownership

In this paper, we hypothesize that institutional investor variable is a proxy for some systematic risk factors, which should be incorporated into the asset-pricing model. Mimicking portfolio for institutional ownership, called IMI (Institutional minus Individual), is constructed. Including IMI to the Carhart's 4-factor model captures the common variations in returns better than all other models that are tested. Consistent with the literature, the new 5-factor model improves mispricing mostly in portfolios including stocks with the lowest and the highest institutional ownership. Empirical findings demonstrate that IMI most likely proxies for noise-trader risk.

Mapping public sector reforms through thematic networks: A case of computerized driving licensing authority, Khyber Pakhtunkhwa

In order to evaluate the performance of mutual fund industry in various financial markets a wide variety of researches have been conducted, which lead to different results. As Pakistani mutual fund industry is much younger as compared to the US and UK fund industries and thus limited work has been done to evaluate Pakistani mutual fund industry. Over the past few years the industry had showed a phenomenal growth and it makes it worthwhile to study the performance of mutual funds. The aim of this research study is to validate the Fama French 3-Factor Model and Carhart 4-Factor Model. Also this research attempts to test that which one of the included model performs better than the other so as to check there preferred suitability in measuring and evaluating the mutual fund performance in Pakistan. The monthly data of 323 open ended mutual funds for the period of 2008 to 2018 is analyzed. The GRS model validation test was applied, the results of the test found that the Carhart 4-Factor Model performed much better than the Fama French 3-Factor Model and from the CAPM as well. This research contributes to the body of knowledge by providing academicians and practitioners more knowledge regarding multifactor asset pricing model so as to make better investment decisions. Keywords: Mutual funds, performance evaluation, CAPM, Fama-French 3- factor model, Carhart 4-factor model

Performance evaluation of Pakistan’s mutual fund industry

In order to evaluate the performance of mutual fund industry in various financial markets a wide variety of researches have been conducted, which lead to different results. As Pakistani mutual fund industry is much younger as compared to the US and UK fund industries and thus limited work has been done to evaluate Pakistani mutual fund industry. Over the past few years the industry had showed a phenomenal growth and it makes it worthwhile to study the performance of mutual funds. The aim of this research study is to validate the Fama French 3-Factor Model and Carhart 4-Factor Model. Also this research attempts to test that which one of the included model performs better than the other so as to check there preferred suitability in measuring and evaluating the mutual fund performance in Pakistan. The monthly data of 323 open ended mutual funds for the period of 2008 to 2018 is analyzed. The GRS model validation test was applied, the results of the test found that the Carhart 4-Factor Model performed much better than the Fama French 3-Factor Model and from the CAPM as well. This research contributes to the body of knowledge by providing academicians and practitioners more knowledge regarding multifactor asset pricing model so as to make better investment decisions. Keywords: Mutual funds, performance evaluation, CAPM, Fama-French 3- factor model, Carhart 4-factor model

Risk factors explaining returns anomaly in emerging market banks – study on Indian banking system

The article provides evidence about the risk factors influence the pricing of banking stocks in the context of emerging economies like India. We use 10 years of data comprising of public and private banks for empirical evidence of abnormal returns. We deploy Fama-French 3-Factor and Carhart 4 Factor model, with and without innovations, to explain the presence of abnormal returns. Comprehending the limitation of the firm specific factors (size and value) accounting for the risk-based returns, we develop a parallel model based on conditioning information like the banks’ profitability, asset quality, capacity to leverage, operating margin and loss assets provisioning. We find that on inclusion of the bank-led performance parameters the explanatory power of the alternate model has significantly improved to 52.21 as compared against a value of 44.28 reported in case of Indian Banks using the Carhart 4-Factor Model (1997). We observe that our findings add-up to indicate significant propositions in estimating the bank specific risk factors that influence the prices and in-turn the returns of banking stocks in emerging markets.

The Risk of Skewness and Kurtosis in Oil Market and the Cross-Section of Stock Returns

We show that exposure to the risk of kurtosis in oil market drives the cross-section of stock returns from 1996 to 2014. The average monthly difference between the return of portfolio of stocks with low exposure and high exposure to the risk of kurtosis is -0.37%, showing that higher exposure to oil’s kurtosis risk will be penalized by lower average returns. We are able to confirm the significance of kurtosis risk within the statistical framework of Carhart 4-factor model. In contrast to the skewness risk, which is only a significant player in some of the sub-periods, kurtosis risk is keeping its significance through all sub-periods, as well as after taking market moments into account and within different maturities. The significance of the risk of skewness gets more evident moving from shorter to longer maturities. The risk of volatility, which has been shown to be a significant-priced risk in the cross-section of stock returns in literature, loses its significance after controlling for the third and fourth moments.

All Style Hedge Fund Analysis with Constant- and Time-Varying Factor Loading Models

Driven by vast historical growth and the recent crises, the hedge fund industry has undergone several changes. This thesis presents studies on the analysis of hedge fund returns within changing market states by applying different constant, asymmetric and time-varying factor loading models. Considered models include the CAPM, Fama-French 3-factor model, Carhart 4-factor model, Fama-French 5-Factor model, Agarwal-Naik 8-factor model and the Fung-Hsieh 7- and 8-factor models. In addition, and unlike previous research, 94 hedge fund strategy styles have been analysed individually to test whether the model performances differ among approaches. The first full-sample analysis exhibits generally low explanatory power whereby the more sophisticated models perform superiorly. Equity strategies, especially long-only funds, exhibit high adjusted R-Squared among all models, while fixed income, fundamental and technical hedge funds result in low significance. The CUSUM control chart based crisis/non-crisis dummy cannot substantially improve the explanatory power of the models. Hedge fund alpha and factor significance varies considerably among strategies and the power of the models remains similarly poor. Asymmetric up/down models exhibit slightly improved explanatory power while the significance of alpha diminishes. Replacing the conditional up/down variable by the crisis/non-crisis setting resulted in inferior results. Empirical analysis with asymmetric higher-moment models approves the asymmetries in hedge fund returns partially. Moreover, a time-varying approach substantially improves the explanatory power of all models while hedge fund alpha further diminishes. All dynamic models exhibit significant exposures on macro state variables for a high proportion of funds. To summarise, it has been shown how simple models can be fitted to increase the explanatory power. As a result, the adjusted R-Squared were improved by 73%. On a strategy level, equity funds are explained the best while fixed income, fundamental and technical hedge funds are the most difficult to analyse.

Exploiting Uncertainty with Market Timing in Corporate Bond Markets

The purpose of this article is to show the usefulness of technical analysis in credit markets. We document that an application of a simple moving average timing strategy to U.S. high yield and U.S. investment grade corporate bond portfolios sorted by option-adjusted spread generates investment timing portfolios that substantially outperform the corresponding benchmark. For portfolios with high uncertainty, as measured by the option-adjusted spread, the abnormal returns generate economically and statistically significant returns relative to the capital asset pricing model (CAPM), the Carhart 4-factor model and additionally the bond factor model from Asness et al. (2013). Our results remain robust to different moving average formation periods, transaction costs, long-short portfolio construction techniques and alternative definitions of information uncertainty.

Analysis of the Sector of Software & Computer Services with a New Carhart 4-Factor Model

In this paper, we analyze the sector of Software and Computer Services with a new Carhart four-factor model. The US is the leading world market for this sector and this sector is a source of significant economic opportunity in US. We compare this sector in US, UK and China to find out whether the US phenome-non has been replicated by other industrialized countries. LR, KS and AIC are used for testing parameter restrictions, residual check and model comparison, respectively. MLE is used to estimate parameters via Matlab. Empirical results show the Carhart 4 factors are still alive! The new 4-factor model fits the data well and has better in-sample fit than that of Carhart (1997) [1] and Fama-French (1993) [2]. This sector in these 3 countries can not earn statisti-cally significant extra Alpha returns. And the Beta value in this sector of US is close to the market.

Determinants of Expected Stock Returns: Large Sample Evidence from the German Market

This paper conducts a comprehensive asset pricing study based on a unique dataset for the German stock market. For the period 1963 to 2006 we show that value characteristics and momentum explain the cross-section of stock returns. Corresponding factor portfolios have significant premiums across various double-sorted characteristic-based test assets. In a horse race of competing asset pricing models the Fama-French 3-factor model does a poor job in explaining average stock returns. The Carhart 4-factor model performs much better, but a 4- factor model containing an earnings-to-price factor instead of a size factor does even slightly better.

Are Momentum Strategies Still Profitable for U.S. Equity?

This paper examines the performance of momentum strategies in previous years, and evaluates the effectiveness of the Fama and French 3-Factor Model and the Carhart 4-Factor Model in predicting momentum returns. Momentum strategies are less profitable after the time period considered in Jegadeesh and Titman (2001), and actually produce negative returns on average in the previous five years. The Fama and French 3-Factor Model performs well predicting returns for each individual portfolio constructed based off returns, but does poorly explaining the momentum strategy portfolio returns. Alternatively, the Carhart 4-Factor Model does a good job explaining the momentum strategy portfolio returns.