JOURNAL BROWSE
Search
Advanced SearchSearch Tips
Comparison of Dimension Reduction Methods for Time Series Factor Analysis: A Case Study
facebook(new window)  Pirnt(new window) E-mail(new window) Excel Download
 Title & Authors
Comparison of Dimension Reduction Methods for Time Series Factor Analysis: A Case Study
Lee, Dae-Su; Song, Seong-Joo;
  PDF(new window)
 Abstract
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.
 Keywords
Factor analysis;time series factor analysis;Value at Risk(VaR);DCCGARCH;CCC GARCH;dimension reduction;
 Language
Korean
 Cited by
1.
금융시계열 분석을 위한 다변량-GARCH 모형에서 비대칭-CCC의 도입 및 응용,박란희;최문선;황선;

응용통계연구, 2011. vol.24. 5, pp.821-831 crossref(new window)
1.
Asymmetric CCC Modelling in Multivariate-GARCH with Illustrations of Multivariate Financial Data, Korean Journal of Applied Statistics, 2011, 24, 5, 821  crossref(new windwow)
 References
1.
김기영, 강현철 (2001). , 자유아카데미.

2.
송유진, 최문선, 황선영 (2008). 차원축소를 통한 다변량 시계열의 변동성분석 및 응용, <한국통계학회 논문집>, 15, 825-835.

3.
최성미, 홍선영, 최문선, 박진아, 백지선, 황선영 (2009). DCC 모델링을 이용한 다변량-GARCH 모형의 분석 및 응용, <응용통계연구>, 22, 995-1005. crossref(new window)

4.
황선영, 최문선, 도종두 (2009). 사후검증(Back-testing)을통한 다변량 GARCH 모형의 평가: 사례분석, <응용 통계연구>, 22, 261-270. crossref(new window)

5.
Bauwens, L., Laurent, S. and Rombouts, J. V. K. (2006). Multivariate GARCH models, A survey, Journal of Applied Econometrics, 21, 79-109. crossref(new window)

6.
Bollerslev, T. (1990). Modelling the coherence in short-run nominal exchange rates: A multivariate generalized ARCH model, The Review of Economics and Statistics, 72, 498-505. crossref(new window)

7.
Christoffersen, P. and Pellitier, D. (2004). Backtesting value-at-risk: A duration-based approach, Journal of Financial Econometrics, 2, 84-108. crossref(new window)

8.
Connor, G. (1995). The three type of factor models, A Comparison of their explanatory power, Financial Analysts Journal, 51, 42-46.

9.
Engle, R. F. (2002). Dynamic conditional correlation: A simple class of multivariate GARCH models, Journal of Business and Economic Statistics, 20, 339-350. crossref(new window)

10.
Gilbert, P. D. and Meijer, E. (2005). Time Series Factor Analysis with an Application to Measuring Money, Research Report 05F10, University of Groningen, SOM Research School.

11.
Kupiec, P. (1995). Techniques for verifying the accuracy of risk measurement models, Journal of Derivatives, 3, 73-84. crossref(new window)

12.
Tse, Y. K. and Tsui, A. K. C. (2002). A multivariate GARCH model with time-varying correlations, Journal of Business and Economic Statistics, 20, 351-362. crossref(new window)