Open AccessA study on the estimation and prediction of volatility on financial assets
Author(s) -
Cheol Hyun An
Publication year - 2018
Publication title -
international journal of engineering and technology
Language(s) - English
Resource type - Journals
ISSN - 2227-524X
DOI - 10.14419/ijet.v7i3.33.21013
Subject(s) - econometrics , volatility (finance) , exchange rate , economics , forward volatility , autoregressive model , autocorrelation , implied volatility , mathematics , statistics , monetary economics
Volatility in financial markets due to changes in the internal and external financial market environment causes economic entities to increase uncertainty of economic activity, thus affecting the real economy. The volatility of stock index, interest rate, and exchange rate has a negative impact on the business performance of companies and financial institutions due to decline in the value of stocks, bonds, and derivatives held for short-term trading purposes. In this study, therefore, the KRW/USD exchange rate and the KOSDAQ index data from January 2005 to December 2017 were converted to log yield data for volatility estimation. Autocorrelation test of the error terms confirmed the partial autocorrelation function, and a Portmanteau Q-test was performed. Significant parameters were estimated by the stepwise autoregressive method. The Lagrange Multiplier test (L-M test) was used for the ARCH effect and the order of the model, and parameters were estimated by the Maximum Likelihood Method. Fit of the estimated model was found to follow the white noise according to the Portmanteau Q-test using standardized residuals. As the result, AR(1,2,3,13)-ARCH(1) model was selected as the volatility estimation model for KRW/USD exchange rate, and AR(1)-ARCH(1) model for KOSDAQ index.