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    Title: 台股風險值分析
    Value at risk based on independent component analysis
    Authors: 曾順延
    Contributors: 郭維裕
    曾順延
    Keywords: 風險值
    獨立成份分析
    Date: 2009
    Issue Date: 2013-09-05 16:47:56 (UTC+8)
    Abstract: 利用獨立成份分析的功能,解決求解投組分配的困難,再用LAVE,GARCH,跟RiskMetrics 三種不同的變異數方法去配適獨立成份的動態過程,並利用台股指數進行一天的風險值預期,共一千天,最後用回顧測試檢定模型的優劣
    The Value at Risk (VaR) measures the potential loss in value of risky asset or portfolio over a defined period for a given confidence interval. The traditional way needs to estimate corresponding distribution and process of portfolio, which is very difficult. Independent component analysis (ICA) is designed for detection of blind folded signals and retrieves out of a high-dimensional time series stochastically independent source components. We can use the property of independence to estimate distribution of portfolio easily. This paper uses three different volatility estimate methods in conjunction with independent component process to calculate value at risk.
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    [7] Y. CHEN, W. HÄRDLE, V. SPOKOINY, Portfolio value at risk based on independent components analysis, J. Comput. Appl. Math, 205 pp. 594—607,2007
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    [16] L. D. Lathauwer, An introduction to independent component analysis, 14:123–149, 2000
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    Description: 碩士
    國立政治大學
    國際經營與貿易研究所
    97351025
    98
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0097351025
    Data Type: thesis
    Appears in Collections:[國際經營與貿易學系 ] 學位論文

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