EMPIRICAL ANALYSIS OF FACTORS AFFECTING THE EXPECTED RATE OF RETURN FOR ALL-ELECTRIC-VEHICLE MAKERS : USING REGRESSION ANALYSIS TO TEST THE SIGNIFICANCE OF THE CAPM AND FAMA FRENCH FACTORS ON THE CALCULATION OF THE EXPECTED RATE OF RETURN FOR 9 OF THE BIG

Abstract: The All-Electric Vehicle (AEV) industry development has intensified and is connected to governmentefforts to minimize greenhouse gas emissions and encourage people to buy electric vehicles. This hasled to all the lights turning on newly established all-electric vehicle makers and some older players. Thegrowth of these companies is depicted in their market capitalization, which has seen an unprecedentedrun. However, one can notice a knowledge gap in the analysis of factors affecting such companies'expected rate of return. This research focuses on analyzing the factors from three of the most knownasset pricing models - CAPM, Fama-French 3 Factor, and Fama-French 5 Factor models. It shows whichof these factors are significant in estimating the expected return rate for nine chosen companies and theimpact of each considerable factor on the return rate.Additionally, we calculate the expected return rate using the beforementioned models to verify whetherthere is an uptrend or not in the electric vehicle market. The current research is limited to companieslisted on the US stock market, with only all-electric vehicle production lines. We make an introductionto the AEV theoretical aspects and related market structure. We also present theoretical concepts behindthe expected rate of return perception.The analysis showed that the market risk premium impacts 100% of the companies. The SMB factorinfluences 55% of the companies while the HML factor only 11%. Finally, RMW affects 66% of thechosen dataset and CMA 77%. For all companies, there is a positive expected return rate. Looking atthe significant coefficients for each model, the results are the following: we can observe that for CAPMand all the companies, 100% of the coefficients are positive. For FF3FM, 93% of the significant factorsare positive, while only 7% are negative. Finally, for FF5FM, out of the 28 significant factors, 65% ofthe coefficients are positive, and 35% are negative.