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Technical Stock Return and the Empirical Analysis of CAPM

Undergraduate #109
Discipline: Social, Behavioral, and Economic Sciences
Subcategory: Mathematics and Statistics
Session: 1
Room: Park Tower 8216

Basirat Haroon - Bowie State University
Co-Author(s): Dr. Tibebe Assefa; Staie Raphael



We empirically tested a modified version of Capital Asset Pricing Model (CAPM) using the past twenty-one years of 30 largest companies of NASDAQ traded at the NASDAQ exchange. CAPM is widely used by analysts, investors and corporate managers, the model focuses on the risk of a firm relative to the market return as the basis for the measure of risk and calculates beta (risk measure) in terms of portfolio. We used quarterly data from 1998Q1 until 2018 Q4. The dependent variable is quarterly returns and the independent variables are market risk premium (Rm-Rf), HML, SMB, Real GDP growth, Ten year Treasury yield, and the change in VIX. The S&P 500 stock index is used as a market return and the three month Treasury bill is used as the risk-free rate. The results show that Risk Premium, Real GDP growth, VIX, and SMB are good predictors of overall stock returns. Surprisingly ten year Treasury yield was a statistically significant predictor of stock returns in the whole sample with a positive relationship with stock returns. However, when we break the sample into two groups before and after 2009 before 2009 the ten year Treasury yield becomes positively related to stock returns only after 2009 (Sample II) in the system GMM model. Indicating that the unexpected relationship between stock returns and ten-year treasury yield could possibly be explained by a stock market in the second sample period is in the recovery period and stock returns are increasing while the interest rate is also increasing. In general, our results indicate that risk premium, real GDP growth, and Treasury Yield are consistent predictors of stock returns – with a positive coefficient. On the other hand, SMB and the change in VIX are negatively significant and weak predictors of stock returns.

Funder Acknowledgement(s): SURI; DSA; Bowie State University; Mcnair

Faculty Advisor: Dr. Tibebe Assefa, tassefa@bowiestate.edu

Role: Thoroughly collected large amounts of data using several database resources such as WRDS, FED st Louis, and Yahoo Finance. Successfully leveraged regressional and statistical tools such as MS Excel and SPSS to adequately analyze data Appropriately analyzed several authentic literature reviews and applied them to the research Adequately created remarkable presentation slides and posters to help present findings and to give recommendations Properly checked facts, proofread, and edited research documents to ensure accuracy

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This material is based upon work supported by the National Science Foundation (NSF) under Grant No. DUE-1930047. Any opinions, findings, interpretations, conclusions or recommendations expressed in this material are those of its authors and do not represent the views of the AAAS Board of Directors, the Council of AAAS, AAAS’ membership or the National Science Foundation.

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