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Empirical Traceability of Multi-Factor Extension of the CAPM during COVID-19

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CAPM Research Proposal

The COVID-19 pandemic is considered as one of the most detrimental events in recent human history and its effects on developed stock markets have been significant that makes it interesting to investigate its impacts on stock market returns.

 

Title of the research:

Empirical Traceability of Multi-Factor Extension of the CAPM during COVID-19

 

Aim of the research:

This research aims to investigate stock market anomalies observed during the COVID-19 by using the three-factor extension of the CAPM model.

 

Research Question

Does the three-factor model explain portfolio returns on the US stock market during COVID-19?

 

Hypothesis of the research:

The following hypotheses will be tested in the proposed study:

H0: COVID-19 had no impact on US Stock Returns

H0: COVID-19 had a significant impact on US Stock Returns

The Efficient Market Hypothesis (EMH) theory is relevant to the proposed study, which states that in an efficient market stock prices should reflect information available to analysts, investors, and shareholders. The occurrence of COVID-19 and its related information was publicly available and its impact on stock returns should have been the same for all firms. The Capital Asset Pricing Model (CAPM) assumes a linear relationship between expected stock returns and market risk factor beta. Its simplicity contributed to its global acceptance and adoption for understanding stock market behaviour. Over the years, the model has been criticized for its simplicity, unrealistic assumptions, and inability to predict stock market anomalies efficiently. Many researchers including Fama and Fench (1988) and Campbell (1987) identified various factors such as dividend yield, dividend-price ratio, and short term interest rate as determinants of stock market performance. Fama and Fench criticized the CAPM that its assumption of true market portfolio is not appropriate for estimating correct values of stock beta and market premium. They developed an extension of the CAPM by adding two factors in addition to the stock beta and the market risk premium. These include size of firms (SMB – small minus big) and book to market values (HML – high minus low). 

 

Literature overview:

Kostin, Runge, & Charifzadeh (2022) compared stock return data of emerging and development markets by using the three-factor and the five-factor models developed by Fama and Fench and found that emerging markets do not outperform developed markets during COVID-19. Hong, Bian, & Lee (2021) found return predictability and price volatility of S&P 500 and DJIA experienced a single structural break which gave significant opportunities for traders and speculators because of market inefficiencies. Horvath (2021) concluded that the results of Fama-Fench models were insignificant to explain US stock returns’ variations.

Research Method:

The proposed study will use Ordinary Least Squares (OLS) to conduct the three-factor model by using SPSS. The data will be collected for the period from December 2019 to May 2021. The data is a time series which would be analysed by following the econometric approach including linear regression, F-test and t-test. The three-factor model (Fama and Fench, 1996)

Ri,t − RFt = ai + bi(RMt − RFt) + siSMBt + hiHMLt + εi,t

The data for the study will be collected from Yahoo! Finance or Bloomberg for stock data, stock beta, and market return. Also, Darmouth.edu has data for Fama-French 3 research factors data. It is anticipated that the study will find a single break effect of COVID-19 on stock returns in the US.

 

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