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Comparison of Dimension Reduction Methods for Time Series Factor Analysis: A Case Study
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 Title & Authors
Comparison of Dimension Reduction Methods for Time Series Factor Analysis: A Case Study
Lee, Dae-Su; Song, Seong-Joo;
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Value at Risk(VaR) is being widely used as a simple tool for measuring financial risk. Although VaR has a few weak points, it is used as a basic risk measure due to its simplicity and easiness of understanding. However, it becomes very difficult to estimate the volatility of the portfolio (essential to compute its VaR) when the number of assets in the portfolio is large. In this case, we can consider the application of a dimension reduction technique; however, the ordinary factor analysis cannot be applied directly to financial data due to autocorrelation. In this paper, we suggest a dimension reduction method that uses the time-series factor analysis and DCC(Dynamic Conditional Correlation) GARCH model. We also compare the method using time-series factor analysis with the existing method using ordinary factor analysis by backtesting the VaR of real data from the Korean stock market.
Factor analysis;time series factor analysis;Value at Risk(VaR);DCCGARCH;CCC GARCH;dimension reduction;
 Cited by
금융시계열 분석을 위한 다변량-GARCH 모형에서 비대칭-CCC의 도입 및 응용,박란희;최문선;황선;

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