金融市場結構轉換次數的偵測

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盧羿安(Yi-an Lu) 查詢紙本館藏

畢業系所

統計研究所

論文名稱

金融市場結構轉換次數的偵測
(Detectiong numbers of switching change in financial markets)

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摘要(中)

本文旨在利用 Huang et al. (1998) 所提出的一經驗法則－希伯特－黃轉換 (Hilbert-Huang transform，HHT) 分析方法－對一時間區間內之股價結構轉換 (regime switch) 的次數做一判斷。一般熟知經濟體制顯示其偶爾會從一個結構 (regime) 跳到另一個。一個國家的經濟，週期性地從膨脹轉換 (switch) 到緊縮而後再轉換回去。而一金融市場也會週期性地從低波動 (low-volatility) 轉換到高波動 (high-volatility) 的結構而後再轉換回去。模擬的結果發現，變動的形式為波動變動 (volatility shift) 時，其判斷轉換的時間點較趨勢變動 (drift shift) 來的精準；實證的部分採用臺指 50，並以美國次級房屋信貸風暴為時間區間，對此段時間內判斷出有四次結構轉換。

摘要(英)

The purpose of this thesis is to utilize an empirical rule, Hilbert-Huang transform (HHT) proposed by Huang et al. (1998), to determine numbers of regime switching on the stock in a time interval. It is well known that economic systems exhibit occasional jumps from one regime to another. A nation’s economy periodically switches from expansion to contraction and back again, and the dynamics differ between these two regimes. A financial market periodically switches from a low-volatility regime to a high-volatility regime and back again. Simulation result shows that the time period of switching of volatility shift determined by HHT is more accurate than the time period of switching of drift shift. Empirically, we adopt Taiwan 50 index at the event of the U.S. subprime mortgage, and we get that there are four regime switching in this time period.

關鍵字(中)

★ 結構轉換
★ 希伯特黃轉換

關鍵字(英)

★ regime switching
★ HHT

論文目次

目錄
中文摘要　………………………………………………………………… i
英文摘要　………………………………………………………………… ii
誌謝　　　………………………………………………………………… iii
目錄　　　………………………………………………………………… iv
第一章序論　…………………………………………………………… 1
　　　 1.1 研究目的　…………………………………………………… 1
　　　 1.2 文獻回顧　…………………………………………………… 3
第二章研究方法　……………………………………………………… 5
　　　 2.1 瞬時頻率 (instantaneous frequency)　……………………… 5
　　　 2.2 經驗模態分解法 (The Empirical Modes Decomposition
　　　　　 method，EMD)　……………………………………………
6
　　　 2.3 希伯特能譜分析 (The Hilbert spectral analysis)　………… 11
第三章模擬　…………………………………………………………… 13
　　　 3.1 判斷法則　…………………………………………………… 13
　　　 3.2 趨勢變動 (drift shift)　…………………………………… 14
　　　　　 3.2.1 常態分配 (normal distribution)　…………………… 14
　　　　　 3.2.2 幾何布朗運動 (geometric Brownian motion)　……… 17
　　　　　 3.2.3 馬可夫轉換模型 (Markov switching model)　……… 19
　　　 3.3 波動變動 (volatility shift)　………………………………… 21
　　　　　3.3.1 常態分配 (normal distribution)　 …………………… 21
　　　　　3.3.2 幾何布朗運動 (geometric Brownian motion)　……… 24
　　　　　3.3.3 馬可夫轉換模型 (Markov switching model)　……… 26
第四章實證研究　……………………………………………………… 28
第五章結論　…………………………………………………………… 33
參考文獻　………………………………………………………………… 34

參考文獻

Bollerslev, T., Engle, R. F., and Wooldridge, J. M. (1988), "A Capital Asset
　Pricing Models with Time-Varying Covariances", Journal of Political
　Economy, 96, 116-131.
Campbell, J. Y. (1993), "Intertemporal Asset Pricing without Consumption
　Data", American Economic Review, 83, 487-512.
Chang, J., and Hung, M. (2000), "An International Asset Pricing Model with
　Time-Varying Hedging Risk", Review of Quantitative Finance and
　Accounting, 15, 235-257.
Hamilton, J. D. (1989), “A New Approach to the Economic Analysis of
　non-stationary Time Series and the Business Cycle”, Economics, 57, 357-384.
Hamilton, J. D., and Susmel, R. (1994), "Autoregressive Conditional
　Heteroskedasticity and Changes in Regime", Journal of Econometrics, 64,
　307-333.
Huang, N. E., Wu, M. C., Long, S. R., Shen, S. S. P., Qu, W., Glosersen, P., and
　Fan, K. L. (2003), “A Confidence Limit for Empirical Mode Decomposition
and Hilbert Spectral Analysis”, Proc. R. Soc. London. A 459, 2317-2345.
Huang, N. E., Shen, Z., Long, S. R., Wu, M. C., Shin, H. H., Zheng, Q., Yen, N.
C., Tung, C. C., and Liu, H. H. (1998), “The Empirical Mode Decomposition
and the Hilbert Spectrum for nonlinear and non-stationary Time Series
Analysis”, Proc. R. Soc. London. A 454, 903-995.
Li, Y. (1997), "Intertemporal Asset Pricing without Consumption Data:
Empirical Tests", Journal of Financial Research, 20, 53-69.
Nefti, S. N. (1984), “Are economic time series asymmetric over business cycle”,
　Journal of Political Economy, 92, 307-328
Schaller, H., and Nordan, S. van (1997), "Regime Switching in Stock Market　
　Returns", Applied Financial Economics, 7, 177-191.
Schwert, G. W. (1989), "Business Cycles, Financial Crises, and Stock Volatility",
　Carnegie-Rochester Conference Series on Public Policy, 31, 83-126.
Susmel, R. (2000), "Switching Volatility in Private International Equity
　Markets", International Journal of Financial and Economics, 5, 265-283.
Turner, C. M., Startz, R., and Nelson, C. R. (1989), “A Markov Model of
　Heteroscedasticity, Risk and learning in the Stock Market”, Journal of
　Financial Economics, 25, 3-22.

指導教授

傅承德(Cheng-der Fuh)

審核日期

2008-6-24

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