Fama-French Factor Model Research Articles

It takes two to tango: Fundamental timing in stock market

AbstractIn this paper, we propose a fundamental timing strategy in both U.S. and Chinese stock markets to timing the fundamentals sorted portfolios such as value and profitability portfolios in the time‐series dimension. We find that fundamental timing strategies based on moving average (MA) timing signals could generate substantial performance gains relative to buy‐and‐hold strategies. The annualized average return of fundamental timing strategies reaches about 37% with Sharpe ratio nearly 1.30. These findings are robust to Fama–French factor model adjustment, alternative lag lengths of MA signals, holding days, and transaction costs. Moreover, the fundamental timing premium cannot be explained away by market timing or business cycle, and fundamental timing is more profitable among firms with high idiosyncratic volatility and high illiquidity.

Performance Evaluation of Pakistan's Mutual Fund Industry: Validating Fama French 3 And 5 Factor Model

In order to evaluate the performance of the mutual fund industry in various financial markets, a wide variety of researches have been conducted, which lead to different results. As the 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 the Pakistani mutual fund industry.Over the past few years, the industry has shown 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 Fama French 5-Factor Model. Also, this research attempts to test that which one of the included model performs better than the other so as to check their 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 Fama French 5-Factor Model performed much better than the Fama French 3-Factor Model.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.

Social media effect, investor recognition and the cross-section of stock returns

Investor recognition affects cross-sectional stock returns. In informationally incomplete markets, investors have limited recognition of all securities, and their holding of stocks with low recognition requires compensation for being imperfectly diversified. Using the number of posts on the Chinese social media platform Guba to measure investor recognition of stocks, this paper provides a direct test of Merton's investor recognition hypothesis. We find a significant social media premium in the Chinese stock market. We further find that including a social media factor based on this premium significantly improves the explanatory power of Fama-French factor models of cross-sectional stock returns, and these results are robust when we control for the mass media effect and liquidity effect. Finally, we find that investment strategies based on the social media factor earn sizable risk-adjusted returns, which signifies the importance of the social media premium in portfolio management.

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

Cross-Section of Expected Returns Based on Equity Duration

We analyze the cross-sectional expected return of KOSPI stocks using equity duration. From 1991 to 2018, we calculate equity durations for the KOSPI listed stocks (including de-listed stocks) and find that the shorter the equity duration, the higher the risk premium. Using the 4-factor model with equity duration added to the benchmark 3-factor model, the explanatory power of the 4-factor model is superior to that of the existing benchmark model in accounting for risk premiums. This is an unusual finding that is not readily explainable by the traditional CAPM or the Fama-French 3-factor model. This can be interpreted that the equity duration is a separate and significant risk factor dissociated from the HML of the 3-factor model.

The Private Income Tax Shock Premium

This paper investigates the asset pricing implications of tax policy changes. News about tax cuts decreases future tax revenues and increases future consumer demand and output. Using cross-sectional variation in industry exposure to structurally identified tax news, I develop a factor mimicking private income tax shocks. I construct an investment strategy, which generates annualized risk-adjusted returns of 5.16 % over the Fama-French 3-factor model. I rationalize the finding by arguing that firms with more elastic demands bear higher consumption risk, which works through a wealth effect.

A New Class of Change Point Test Statistics of Rényi Type

A new class of change point test statistics is proposed that utilizes a weighting and trimming scheme for the cumulative sum (CUSUM) process inspired by Rényi. A thorough asymptotic analysis and simulations both demonstrate that this new class of statistics possess superior power compared to traditional change point statistics based on the CUSUM process when the change point is near the beginning or end of the sample. Generalizations of these “Rényi” statistics are also developed to test for changes in the parameters in linear and nonlinear regression models, and in generalized method of moments estimation. In these contexts, we applied the proposed statistics, as well as several others, to test for changes in the coefficients of Fama–French factor models. We observed that the Rényi statistic was the most effective in terms of retrospectively detecting change points that occur near the endpoints of the sample.

Revisiting the price effect in US stocks

Nominal price does not predict average stock returns in the cross-section of US stocks using the NYSE break-pointed, value-weighted portfolio formation approach adopted in the recent asset-pricing literature. The evidence in support of return predictability is largely constrained to small stocks, with a “low price effect” more prevalent up to the 1970’s and a “high price effect” more prevalent from 1980 onwards. Among the six asset-pricing models tested in our study, only the Fama–French 3-factor model consistently yields positive alphas for trading strategies based on nominal stock prices.

Analystss Estimates of Cost of Equity Capital

We explore a large sample of analysts’ estimates of cost of equity capital (CoE) revealed in analysts’ reports to evaluate their determinants and ability to capture expected stock returns. We first document that CoE estimates are more likely to be provided by less experienced and less busy analysts and for harder-to-value firms. We also find that CoE estimates are significantly related to beta, size, book-to-market ratio, leverage and idiosyncratic volatility but not to profitability, investments or other return predictors. The CoE estimates also incrementally predict future stock returns, which possibly reflects analysts’ ability to garner information about expected returns through their direct interactions with investors. We also find that analysts increase their CoE estimates following extreme earnings surprises, indicating that companies with volatile earnings as perceived as more risky. Finally, based on a pair-wise comparison of CoE estimates with alternative expected return proxies (estimated from CAPM, Fama-French factor models or implied cost of capital models), we find that CoE estimates tend to be least noisy. We conclude that analysts’ CoE estimates, where available, are a useful proxy for expected stock returns.

Social Media Effect, Investor Recognition and the Cross-Section of Stock Returns

Investor recognition affects cross-sectional stock returns. In informationally incomplete markets, investors have limited recognition of all securities, and their holding of stocks with low recognition requires compensation for being imperfectly diversified. Using the number of posts on the Chinese social media platform Guba to measure investor recognition of stocks, this paper provides a direct test of Merton's investor recognition hypothesis. We find a significant social media premium in the Chinese stock market. We further find that including a social media factor based on this premium significantly improves the explanatory power of Fama-French factor models of cross-sectional stock returns, and these results are robust when we control for the mass media effect and liquidity effect. Finally, we find that investment strategies based on the social media factor earn sizable risk-adjusted returns, which signifies the importance of the social media premium in portfolio management.

It Takes Two to Tango: Fundamental Timing in Stock Market

In this paper, we propose a fundamental timing strategy in both U.S. and Chinese stock market to trade the fundamental sorted portfolios such as value and profitability portfolios in the time series dimension. We find that fundamental timing strategies based on moving average (MA) timing signals could generate substantial performance improvements relative to corresponding buy-and-hold fundamental strategies. The annualized average return of the 20-day MA fundamental timing strategies reaches about 37% with Sharpe ratio nearly 1.30. These findings are robust to Fama-French factor model adjustment, alternative lag lengths of MA signals, holding days, and transaction costs. Moreover, we find that the fundamental timing premium cannot be explained by market timing ability or business cycle, and fundamental timing is more profitable among firms with high idiosyncratic volatility and high illiquidity measures.

Bank Capitalization and the Cross-Section of Bank Stock Returns

We investigate the evolution of US bank capitalization and examine its role in the crosssection of bank stock returns. We use the book capital ratio (BCR), the market capital ratio (MCR) and the stressed capital ratio (SCR) as three proxies for bank capitalization and find that the MCR and the SCR have similar dynamics, while the BCR develops very differently. Our Fama-MacBeth cross-sectional regressions suggest a negative and significant relationship between bank capitalization and bank stock returns between 1994–2007, especially when bank capitalization is measured by the MCR or the SCR. We apply Fama-French factor models to estimate the risk-adjusted returns of our capital ratio-sorted decile portfolios and their sensitivities to systematic risk factors. We find that the BCR proxies for bank portfolio exposures to the market and value factors, while the MCR and the SCR contain some information on exposures to the market and size factors.

Cross Section of KOSPI Returns Based on Cash Flow Risk Factors

This paper introduces two risk factors which are the covariance between long-run consumption growth and cash flows and the duration of cash flow, and investigates how these factors serve to explain the KOSPI return risk premiums. Based on our empirical results comparing the proposed two-factor cash flow model with the standard benchmark models such as CAPM and Fama-French 3-factor model (FF-3F), using KOSPI equity including de-listed stocks, the cash flow model explains 74.7% of the cross-section of equity risk premium while CAPM and FF-3F model explains 41.9% and 64.1% to the maximum, respectively, showing that the cash-flow model is superior in explaining the risk premium factor structure compared with the benchmark models. Also, the pricing error is only 4% in the two-factor cash flow model, while CAPM and FF-3F are 7.7% and 4.7%, respectively, indicating the cash flow model outperforms the standard benchmark models in pricing error as well. These results can be interpreted that the cross section of the equity risk premium is related to a firm’s cash flow and long-run consumption, and therefore the growth rate of consumption in the long run rather than contemporaneous consumption growth rate has a greater influence on the determination of the risk premium.

Liquidity and size effects on the Johannesburg Stock Exchange (JSE)

ABSTRACTThis study explores the existence of a liquidity premium on the Johannesburg Stock Exchange (JSE) and its potential interaction with the well-documented size effect. It builds on the stream of South African literature that examines liquidity as a standalone factor and adds further weight to its existence. Over the 2000-2015 sample period, this study finds evidence of a significant liquidity effect. Importantly, the liquidity premium is found to be separate from the size effect. Furthermore, the liquidity premium captures a different underlying effect than the value premium. The efficacy of Liu’s (2006) Liquidity-Augmented Capital Asset Pricing Model (CAPM) as a useful asset-pricing model for the cross-section of returns on the JSE is examined and found to perform better than the Fama-French 3-Factor model.

Performance Evaluation of Pakistan's Mutual Fund through CAPM and Fama French 3-Factor Model

Mutual fund is selection for the common investors for investing in to the capital market. In the research paper Capital Asset Pricing Model (CAPM) and FAMA French 3 factor model applied for the measurement and evaluate the performance of the mutual fund. Daily data of mutual fund which are selected in open ended mutual fund of Pakistan and daily data collected from 2010 to 2016. Then applied these models and Capital Assets Pricing Model showed the significant result and R² value more co-related with the market returns and premium. FAMA French 3 factor model showed the not good results with the two factors SMB and HML. Time series regression model are applied between two competing models.

Family-Owned Firms and Stock Returns: Evidence from the Chinese Stock Market

We examine stock return performance of Chinese family-firms vs. Nonfamily-firms, and the impact on family-firm returns of firm size, having a founder as CEO, and levels of family ownership. We model returns with the Capital Asset Pricing Model (CAPM), the Fama-French 3-factor model, and a new 5-factor model we modified from Miralles-Marcelo, Miralles-Quirós, which adds factors for debt and illiquidity. In previous studies, though the prevalence is for family-firm outperformance, the results have been mixed. Using CAPM or the Fama-French 3-factor model, we find that family-firms outperform nonfamily-firms, but with the 5-factor model that outperformance vanishes, and this is robust to controlling for the GFC. For the founder CEO, firm size and family ownership considerations, again previous research has been mixed. With CAPM and Fama-French 3-factor models, we find that founder CEOs outperform nonfounder, large firms outperform small firms, and higher family ownership outperforms lower ownership. However, with the 5-factor model, only size remains as having significant impact. This study helps to reconcile conflicting results in previous research.

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.

A sparse enhanced indexation model with chance and cardinality constraints

Enhanced indexation aims to construct a portfolio to track and outperform the performance of a stock market index by employing both passive and active fund management strategies. This paper presents a novel sparse enhanced indexation model with chance and cardinality constraints. Its goal is to maximize the excess return that can be attained with a high probability, while the model allows a fund manger to limit the number of stocks in the portfolio and specify the maximum tolerable relative market risk. In particular, we model the asset returns as random variables and estimate their probability distributions by the Capital Asset Pricing Model or Fama-French 3-factor model, and measure the relative market risk with the coherent semideviation risk function. We deal with the chance constraint via distributionally robust approach and present a second-order cone programming and a semidefinite programming safe approximation for the model under different sets of potential distribution functions. A hybrid genetic algorithm is applied to solve the NP-hard problem. Numerical tests are conducted on the real data sets from major international stock markets, including USA, UK, Germany and China. The results demonstrate that the proposed model and the method can efficiently solve the enhanced indexation problem and our approach can generally achieve sparse tracking portfolios with good out-of-sample excess returns and high robustness.

Equity-Based Compensation for Firm Performance

The paper finds evidence that the equity-based compensation is positively related to firm performance and risk-taking. Both stock price and operating performance as well as firm's risk-taking increase with incentives provided by CEO stock options and stock holdings. The pay-performance sensitivity can explain stock returns better as an additional factor to the Fama-French 3-factor model. When CEOs are compensated with the higher PPS, firms experiences the higher return on asset. The higher pay-volatility sensitivity also leads to the higher risk-taking. While CEO incentive compensation has been perceived mixed on its effectiveness, this study provides support to the equity-based CEO compensation in reducing agency conflicts between CEOs and shareholders.