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HAR-RV with Sector Variance

HAR-RV with Sector Variance. Sharon Lee February 18, 2009. Starting Point. Intuitively, the returns of an individual equity should be correlated with returns from its sector

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HAR-RV with Sector Variance

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  1. HAR-RV with Sector Variance Sharon Lee February 18, 2009

  2. Starting Point • Intuitively, the returns of an individual equity should be correlated with returns from its sector • Using the predictive model HAR-RV, how does incorporating sector realized volatility affect the predicted values for an equity?

  3. Consumer Goods Sector • Proctor & Gamble Co. (PG) • Avon Products, Inc. (AVP) • Colgate-Palmolive Co. (CL)

  4. Background Mathematics Realized Variance, where rt,j is the log-return Sector Realized Variance: Average of same sector stocks in S&P100

  5. PG: Annualized RV

  6. AVP: Annualized RV

  7. CL: Annualized RV

  8. Sector Annualized RV

  9. HAR-RV Model • HAR-RV makes use of average realized variance over daily, weekly, and monthly periods. • h=1 corresponds to daily periods, h=5 corresponds to weekly periods, h=22 corresponds to monthly periods • These time horizons correspond to day-ahead, 5-day ahead, and month-ahead predictions of average realized variance.

  10. PG: HAR-RV, one day

  11. PG: HAR-RV, day, week

  12. PG and Sector (HAR-RV,day)

  13. PG and Sector (HAR-RV, 5-day)

  14. Linear regression: First Pass • Regressing one-day and five-day PG lag terms on PG return: • Coefficients: • (Intercept) lag1 lag5 • 2.1459 0.4549 0.3180 • Regressing one-day and five-day PG lag terms and one-day and five-day sector lag terms on PG return: • Coefficients: • (Intercept) lag1 lag5 sector1 sector5 • 0.89684 0.08773 0.11054 0.49368 0.13244

  15. What’s Next • Figure out how to run regressions with t-tests for significance • Investigate R-squared values • Incorporate more stocks and sectors • Consider additional regressors

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