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Analyzing the Impact of Market Jumps on Equity Returns: Research Insights

This research seminar delves into the effect of market jumps on individual equity returns, utilizing the Capital Asset Pricing Model. By examining data from notable companies like UPS and GE, we aim to understand the implications for hedging strategies and potential future work. Our objective is to introduce a dummy variable to capture market jumps and analyze their impact on equity returns, providing valuable insights for financial markets. Initial findings showcase the challenge of predicting equity returns based on market jump components. To enhance this study, future work includes formal implementation of the Scholes and Williams method, expansion to include more stocks, and experimentation with varied sampling intervals.

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Analyzing the Impact of Market Jumps on Equity Returns: Research Insights

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  1. Analyzing the Effect of a Market Jump on an Equity’s Returns Junior Research Seminar Economics 201FS

  2. Outline • Motivation • Capital Asset Pricing Model • Objective • Summation of Results • UPS • GE • Interpretation • Future Work

  3. Motivation • Look at the role of the market’s jumps in the financial markets • How do they effect returns of individual equities? • How fine can our sampling intervals be? • Potential consequences for hedging strategy

  4. Capital Asset Pricing Model Expected Return of Equity = Risk-free rate + (Beta * Market Premium) Beta = Cov(Market Return, Equity Return) / Var(Market Return) Assumptions: • Market return and residual are uncorrelated • Residuals are mutually uncorrelated • Residuals are difference between actual return and predicted return

  5. Average Beta: 0.4372

  6. Average Beta Over Time Interval: 0.4017 Beta (Yahoo Finance): 1.37

  7. Average Beta over Time Interval: 0.5830 Beta (Yahoo Finance): 0.41

  8. Objective • Introduce a dummy variable (Jmt), that depends on if the market (SPY) jumped • Lee/Mykland • rcmt = (1-Jmt)(rmt) • rjmt = (Jmt)(rmt) rit = αi + βic (1-Jmt)(rmt) + βij (Jmt)(rmt) + εit

  9. UPS Results 65,536 observations (about 68.5% of data)

  10. UPS Results

  11. UPS Results

  12. GE Results

  13. GE Results

  14. GE Results

  15. Interpretation • Market jump return component does not help predict the equity’s return at the 95% significance level when using five-minute returns

  16. Further Work • Implement formally the Scholes and Williams method (1977) • Extend work to other 40 stocks • Work with different sampling intervals

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