Fama-French Approach Research Articles

Prioritization of the IT Sector in the CEE Stock Markets: Investment Policies, Trends and Hidden Gems

Objective: The main purpose of the research is to show that the Central and Eastern European (CEE) market is an essential component of the global stock market. It displays similar patterns to developed countries, and there is a special emphasis on information technology. Research Design & Methods: The study is supported by various machine learning methods and economic analysis, in addition to using Python and R packages. In order to gain a more comprehensive insight into the developments in CEE-region trends, the paper considers a comparative portfolio that focuses on German business, and there is a simulation of the incorporation of the Ukrainian IT sector. Constructing a business strategy in accordance with the Fama–French approach is boosted by incorporating neural networks. Findings: An examination of the performance of Czech, Polish, and Hungarian firms on the stock exchanges suggests that the investment policy oriented towards software is a reasonable choice. The results yielded by the IT companies unmistakably reveal the substantial benefits of their stock market ventures, as well as indicating the ongoing trend of investor reliance. The problem of IT business valuation is highlighted as one of the pitfalls of investing. Implications & Recommendations: The research proposes that maintaining a priority focus on IT, even in challenging circumstances, ensures steady regional advancement. Contribution & Value added: This research brings a unique emphasis to the status and outlook of the IT sector, contributing to the existing toolkit, even in the face of repeated crises.

Factor Sufficiency in Asset Pricing: An Application for the Brazilian Market

The multifactor asset pricing model derived from the Fama–French approach is extensively used in asset risk premium estimation procedures. Even including a considerable number of factors, it is still possible that omitted factors affect the estimation of this model. In this work, we compare estimators robust to the presence of omitted factors in estimating the risk premium in the Brazilian market. Initially, we analyze the panel of asset returns using the mean group and common correlated effect estimators to detect the presence of omitted factors. We then compare the results with those obtained by a estimator robust to omitted variables, which uses a principal components approach to correct the estimation in the case of the omission of latent factors. We conclude that there is evidence of omitted factors, and the best predictor for the expect returns is the common correlated effects estimator.

Central and Eastern Europe (CEE) Banking on the Stock Market: Turbulence of 2020 – 2022

Recently, there have been many studies on the impact of the pandemic and Russia’s war against Ukraine on the stock markets, while very few of them directly affect the banking sector. The issue of banks’ strategies in such circumstances is suffocated by little coverage, especially since even the authors of the Fama-French analysis emphasized the difficulty of applying this approach in the banking sector. The presence of non-linearity in such strategies was emphasized. Analyzing the banking market and strategies of CEE banks, the authors applied a wide range of machine learning and clustering methods and modified the Fama-French approach by using neural networks. No clear gradation of CEE banks in terms of the impact of the pandemic and war was found. At the same time, the proposed method made it possible to single out the most vulnerable market participants and analyze the reasons for their current state.

Evaluation of Long Term Performance for Initial Public Offerings (IPO) in Malaysia: A Fama-French Method

The objective of this study is to evaluate performance of initial public offerings for 16 sharia compliant companies listed on the Malaysia Stock Exchange. Data of stock price are collected from Thomson Reuters Datastream for 36 months starting from January 2016 until December 2018. The method implemented is using Fama-French approach that evaluates expected return with three factors namely Market Risk Premium (MRP), Small Minus Big (SMB) and High Minus Low (HML). Result shows the abnormal return for 36 months is -3.399 which indicates negative value. The negative value of y-intercept gives interpretation that market (FTSE Bursa Malaysia KLCI) performed better than portfolio. The findings of this study will help investors to understand the financial dynamic behavior in Malaysia Stock Exchange. In addition, it will help investors to select appropriate financial assets for investment portfolio in gaining better return.

Towards a more ethical market: the impact of ESG rating on corporate financial performance

PurposeThis paper fits in a research field dealing with the impact of Corporate Ethics Assessment on Financial Performance. The authors argue how environmental, social and governance (ESG) paradigm, meant to measure corporate social performance by rating issuance, can impact on abnormal returns of Italian firms listed on Financial Times Stock Exchange Milano Indice di Borsa (FTSE MIB) Index, developing a panel data analysis which runs from 2007 to 2015.Design/methodology/approachThis study aims at exploring whether socially responsible investors outperform an excess market return on Italian Stock Exchange because of their investment behavior, testing statistically the relationship between the yearly ESG assessment issued by Standard Ethics Agency on FTSE MIB’s companies and their abnormal returns. To verify the impact of an ESG Rating on a company’s abnormal return, the authors developed a panel data analysis through a Fixed Effects Model. They measured abnormal returns via Fama–French approach, running a yearly Jensen’s Performance Index for each company under investigation.FindingsThe empirical results denote in Italy both a growing interest to corporate social responsibility (CSR) and sustainability by managers over the past decade, as well as an improving quality in ESG assessments because of a reliable corporate disclosure. Thus, despite investors have been applying ESG criteria in their stock – picking operations, the authors found a not positive and statistically significant impact in terms of market premium, when they have been undertaking a socially responsible investment (SRI).Practical implicationsThe findings described above show that ethics is not yet a reliable fundraising tool for Italian-listed companies, despite SRIs having a positive growth rate over past decade. Investors seem to be not pricing CSR on Stock Exchange Market; therefore, listed companies cannot be rewarded with a premium price because of their highly stakeholder oriented behavior.Originality/valueThis paper explores, for the first time in Italy, when market extra-returns (if any) are related to corporate social performance and how managers leverage ethics to build capital added value.

Dynamic Functional Regression with Application to the Cross-section of Returns

Motivated by testing the significance of risk factors for a cross-section of returns, we develop an inferential framework which involves function-on-scalar regression. Asymptotic theory is developed assuming the factors form a weakly dependent vector-valued time series, and the regression errors are weakly dependent functions. To accommodate the empirical behavior of the cross-section of returns and of the factors, we allow both the factors and the error functions can exhibit mild departures from stationarity. This requires new asymptotic theory which leads to several tests for the significance of function-valued regression coefficients. The new approach to the study of the significance of risk factors for a cross-section of returns complements the established Fama–French approach based on portfolio construction. It is more suitable if the statistical significance of the risk factors is to be rigorously controlled.

The Cross-Section of Stock Returns: An Application of Fama-French Approach to Nepal

We study a sample of the companies listed on the Nepal Stock Exchange (NEPSE) for the predictors of the returns on these companies’ stocks. Using the sample period of December 2004 through July 2011, we study the sample of 134 companies out of a universe of 176 companies. We construct the marketwide indicators of Fama-French approach: capitalization (Small and Big) and book-to-market ratio (Low, Middle and High). The standard CAPM and three-factor regression equations are estimated. The typical Fama and French results are not obtained. At best, the results are mixed. They show that Nepalese capital market provides excess return for big value-stocks and lower excess return for small growth-stocks. It is possible that this result is attributable to the biases in the listed corporate sector. Financial sector companies dominate the listing on the Nepal Stock Exchange. Because of the impossibility of elimination financial companies from the sample, it is impossible to be categorical about this attribution. We recommend that the study be replicated after a few years when either more companies become available or longer time series of data becomes available.

Tests of Long-Term Abnormal Performance: Analysis of Power

In tests of long-term performance, researchers are faced with several research design choices. For instance, when estimating abnormal returns, what specific firm characteristics should be used as matching criteria to select control firms? What weights should be placed on each characteristic? Should an event firm be matched with one control firm or multiple control firms or with a reference portfolio? Should we use the calendar-time portfolio approach? We provide guidance to researchers on these questions by evaluating the power of the test using simulation analyses. We find that the quality of matching when selecting control firms has little impact on the power of the test. Among the alternative approaches studied, the Fama-French calendar-time portfolio approach obtains the highest power in random samples. Interestingly, we find that the higher power of this approach is attributable to the return aggregation method rather than the use of multiple risk factors or the in-sample fit of the model. In most nonrandom samples, the Fama-French approach obtains the highest power – the one exception being samples with extreme event-time clustering. Overall, for a reasonable sample size, the power of the best available methodology to detect economically significant abnormal returns is quite low.