Faculty Publications | Volume 2 | Number 1 | January – June 2017 | Pages 71 – 82
Received: January 2017 | Published unedited: May 2017
Siphat Lim, PhD
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Management Accounting 2
CamEd Business School
SUMMARY
This study was conducted to predict the conditional variance as well as the volatility of the return of the CSX Index by employing the GARCH(1,1) model with daily data from 19 April 2012 to 12 June 2017. The estimated result of the GARCH(1,1) model which was derived by the maximum likelihood estimation method had revealed that the conditional variance was highly explained by the lagged of square residual as well as the lagged of forecast variance and no ARCH effect was found in this study. The explosive process did not exist, but a mean reverting variance process was detected since the persistence, 𝛼𝛼 + 𝛽𝛽 < 1. The long-run daily volatility was estimated to be 1.349403% per day or 21.42% per year.
Keywords: CSX Index, GARCH(1,1), Conditional Variance, Volatility.
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