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    Please use this identifier to cite or link to this item: http://nccur.lib.nccu.edu.tw/handle/140.119/50754


    Title: 以馬可夫轉換模型檢視隱含波動度
    Analyzing Implied Volatility with Marcov Switching Model
    Authors: 陳玫吟
    Chen ,Mei Yin
    Contributors: 郭維裕
    陳玫吟
    Chen ,Mei Yin
    Keywords: 隱含波動度(VIX、VXN)
    馬可夫轉換模型
    implied volatility (VIX、VXN)
    Marcov switching model
    Date: 2010
    Issue Date: 2011-09-29 16:37:04 (UTC+8)
    Abstract:   由於隱含波動度具有前瞻性的特質,以往有許多學者探討隱含波動度與標的股價指數間的關聯性,但多利用線性模型。而本研究與其他文獻不同之處在於,本文利用馬可夫轉換模型分析隱含波動度VIX和VXN(VIX為S&P500指數的隱含波動度,而VXN為Nasdaq-100指數的隱含波動度),馬可夫轉換模型為非線性模型,可捕捉不同區間轉換與不規則跳動,隱含波動度在特殊金融事件發生時會突然竄高,馬可夫轉換模型相對於一般線性模型更可捕捉此跳動,並將隱含波動度分為兩個區間。
      經由多變量迴歸分析後,本研究也發現隱含波動度的變動以及技術指標的趨勢(偏離五天移動平均值)皆會影響標的股價指數的報酬,但隱含波動度變動對於股價指數報酬的影響高於技術指標,且不同區間存在不同現象。
    Implied volatility indices are forward-looking, and lots of researches discuss the relationship between the implied volatility and underlying stock market returns. Dif-ferent from other studies, we use Marcov switching model to examine the implied volatility indices: S&P 500 volatility index (VIX) and NASDAQ-100 volatility index (VXN), then we separately exploit the different regime behavior about the relationship between implied volatility change, technical indicators and stock market returns.
    As a result, S&P 500 index and NASDAQ-100 index respond in opposite direc-tions to positive and negative S&P 500 volatility index (VIX) and NASDAQ volatility index (VXN) changes, where technical indicators do not have that much influence on stock market returns. In addition, the impact of implied volatility change, technical indicators to stock market returns indeed depend on different regimes.
    Reference: 中文文獻
    周幸蓉, 李. 梁. (2008). "台灣房地產景氣循環轉折點認定之研究-雙變量馬可夫轉換模型之應用." 台灣土地研究 11(2).
    林秋瑾, 馬. (2009). "房地產景氣特性之再確認—多變量馬可夫轉換之應用." 住宅學爆 18(1).
    楊聲勇, 黎. 林. 郭. (2002). "藉由馬可夫轉換模型分析美國股市與日、韓、港、新、台等亞洲主要股市連動性." 台灣財務金融研討會.
    英文文獻
    CBOE (2009). "The CBOE Volatility Index-VIX."
    Chiu, C. (2002). "Analysis of Historical and Implied Volatility of the S&P 100 and Nasdaq 100 Indices."
    Copeland, M. M. C. a. T. E. (1999). "Market Timing: Style and Size Rotation Using the VIX." Financial Analysts Journal 55(2).
    Giot, P. (2005). "Relationships Between Implied Volatility Indexes and Stock Index Returns." The Journal of Portfolio Management 31(3).
    Prithviraj S. Banerjee, J. S. D., David R. Peterson (2007). "Implied Volatility and Future Portfolio Returns." Journal of Banking & Finance 31(10).
    Simon, D. P. (2003). "The Nasdaq Volatility Index During and After the Bubble." The Journal of Derivatives 11(2).
    Tveterås, S. (2010). "Forecasting Commodity Prices with Switching Regimes: The Case of Fishmeal Prices." Journal of CENTRUM Cathedra 3(1).
    Whaley, R. E. (1993). "Derivatives on Market Volatility: Hedging Tools Long Overdue." The Journal of Derivatives 1(1).
    Whaley, R. E. (2000). "The Investor Fear Gauge." The Journal of Portfolio Management 26(3).
    Whaley, R. E. (2009). "Understanding the VIX." The Journal of Portfolio Management 35(3).
    Description: 碩士
    國立政治大學
    國際經營與貿易研究所
    98351002
    99
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0098351002
    Data Type: thesis
    Appears in Collections:[國際經營與貿易學系 ] 學位論文

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