Rolling regression technique and cross-sectional regression: A tool to analyze Capital Asset Pricing Model
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DOIhttp://dx.doi.org/10.21511/imfi.18(4).2021.21
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Article InfoVolume 18 2021, Issue #4, pp. 241-251
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The Capital Asset Pricing Model (henceforth, CAPM) is considered an extensively used technique to approximate asset pricing in the field of finance. The CAPM holds the power to explicate stock movements by means of its sole factor that is beta co-efficient. This study focuses on the application of rolling regression and cross-sectional regression techniques on Indian BSE 30 stocks. The study examines the risk-return analysis by using this modern technique. The applicability of these techniques is being viewed in changing business environments. These techniques help to find the effect of selected variables on average stock returns. A rolling regression study rolls the data for changing the windows for every 3-month period for three years. The study modifies the model with and without intercept values. This has been applied to the monthly prices of 30 BSE stocks. The study period is from January 2009 to December 2018. The study revealed that beta is a good predictor for analyzing stock returns, but not the intercept values in the developed model. On the other hand, applying cross-section regression accepts the null hypothesis. α, β, β2 ≠ 0. Therefore, a researcher is faced with the task of finding limitations of each methodology and bringing the best output in the model.
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JEL Classification (Paper profile tab)E22, G12, G11, C32, F65
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References50
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Tables5
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Figures1
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- Figure 1. Jarque-Bera normality test
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- Table 1. The results of rolling regressions for different sub-periods in consideration of an intercept
- Table 2. Rolling regression for different sub-periods without an intercept
- Table 3. Heteroskedasticity tests using the Breush-Pagan-Godfrey method
- Table 4. Summary statistics of the first stage regression
- Table 5. Results of OLS estimates
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