臺灣博碩士論文加值系統

本篇論文提出一個新的求算隱含相關性指數的方法，利用台灣五十ETF和其成分股的變異數來求算。變異數的估計值是利用歷史開盤、收盤、最高和最低價格。
因為是採用市場交易的價格來計算，此隱含相關性指數反應市場對於未來的看法，接著我們對台灣五十隱含相關性指數進行統計上的探討，實證顯示隱含相關性指數有顯著的自我相關，並且當市場下跌實隱含相關性指數會大幅上升。最後進行Granger causality檢定，結果顯示台灣五十指數報酬率會導致每周的台灣五十隱含相關性指數產生顯著的變動，每周的台灣五十隱含相關性指數也會導致台灣五十指數報酬產生顯著的變動。

This study proposes an innovative methodology for backing-out implied correlation measures from the variance of Taiwan 50 ETF and its constituent stocks. The volatility estimators are based upon the historical opening, closing, high, low prices.
This implied correlation index reflects the market view of the future level of the diversification in the market portfolio represented by the index. The methodology is applied to Taiwan 50 ETF. The statistical properties and the dynamics of the proposed implied correlation measure are examined. The evidence of this study indicates that the implied correlation index fluctuates substantially over time and displays strong dynamic dependence. Moreover, there is a systematic tendency for the implied correlation index to increase when the market index returns decrease, indicating limited diversification when it is needed most. Finally, the Granger causality tests is assessed and we find that the Taiwan 50 index returns Granger causes the weekly TWCIX changes and the weekly TWCIX changes Granger causes the Taiwan 50 index returns.

Chapter1 Introduction.....………………………………………………1



Chapter 2 Correlation Index Definition…………………….……4



Chapter 3 Empirical Application: Taiwan 50 Correlation Index…........6

3.1 Data and Methodology…………..………………………………….6

3.2 History and Statistical Properties of the Taiwan 50

Correlation Index…………………………………………………..8



Chapter 4 Stylized Facts About Correlation……………………13

4.1 Correlation Persistence and Memory…………………………13

4.2 Asymmetry in Correlation………………………………….….15



Chapter 5 Vector Autoregressions Analysis……………………19



Chapter 6 Conclusion........................22

Reference……………………………………….………………………24

Andersen, T., Bollerslev, T., Diebold, F., & Ebens, H. (2001a). The distribution of realized stock return volatility. Journal of Financial Economics, 61, 43–76.

Andersen, T., Bollerslev, T., Diebold, F., & Labys, P. (2001b). The distribution of realized exchange rate volatility. Journal of the American Statistical Association, 96, 42–55.

Ang, A., & Chen, J. (2002). Asymmetric correlations of equity portfolios. Journal of Financial Economics, 63, 443–494.

Beckers, S. (1983). Variances of security price returns based on high, low and closing prices. Journal of Business, Vol.56, No.1.

Blair, B. J., Poon, S. H., & Taylor, S. J. (2001). Forecasting S&P 100 volatility: The incremental information content of implied volatilities and highfrequency returns. Journal of Econometrics, 105, 5–26.

Bourgoin, F. (2001). Stress-testing correlations: An application to portfolio risk management. In C. Dunis, A. Timmermann, J. Moody (Eds.), Developments in forecast combination and portfolio choice. New York: Wiley.

Christensen, B. J., & Prabhala, N. R. (1998). The relation between implied and realized volatility. Journal of Financial Economics, 50, 125–150.

Erb, C. B., Harvey, C. R., & Viskanta, E. (1994). Forecasting international equity correlations. Financial Analysts Journal, 6, 32–45.

Fleming, J. (1998). The quality of market volatility forecasts implied by S&P 100 index option prices. Journal of Empirical Finance, 5, 317–345.

Fustenberg, G. M. von, & Jeon, B. N. (1989). International stock price movements: Links and messages. (Papers on Economic Activity I, 125–180). Washington, DC: Brookings.

Garman, M. B., & Klass, M. J. (1980). On the estimation of security price volatilities from historical data. Journal of Business, Vol.53, No.1.

Koch, P. D., & Koch, T. W. (1991). Evolution in dynamic linkages across national stock markets. Journal of International Money and Finance, 10, 231–251.
Lamoureux, C. G., & Lastrapes, W. D. (1993). Forecasting stock-return variance: Toward an understanding of stochastic implied volatilities. Review of Financial Studies, 6, 293–326.

Longin, F., & Solnik, B. (1995). Is correlation in international equity markets constant? Journal of International Money and Finance, 14, 3–26.

Lundin, M., Dacorogna, M. M., & Muller, U. A. (1999). Correlation of highfrequency financial time series. In P. Lequeux (Eds.), The financial markets tick-by-tick. London: Wiley.

Parkinson, M. (1980). The extreme value method for estimating the variance of the rate of return. Journal of Business, Vol.53, No.1.

Rogers, L. C. G., & Satchell, S. E. (1991). Estimating variance from high, low and closing prices. The Annals of Applied Probability, Vol. 1, No. 4, 504-512.

Sheedy, E. (1998). Correlation in currency markets: a risk-adjusted perspective. Journal of International Financial Markets, Institutions and Money, 8, 59–82.

Skintzi, V. D., & Refenes, A. N. (2005). Implied correlation index: a new measure of diversification. The Journal of Futures Markets, Vol. 25, No. 2, 171–197.

Swidler, S., & Wilcox, J. A. (2002). Information about bank risk in option prices. Journal of Banking and Finance, 26, 1033–1057.

Torben G., Andersen, Tim Bollerslev, Francis X. Diebold, & Paul Labys (2003). Modeling and forecasting realized volatility. Econometrica, Vol.71, No.2, 579-625.

Yang, D., & Zhang, Q. (2000). Drift-independent volatility estimation based on high, low, open and close prices. Journal of Business, Vol.73, No.3.