全球17個國際股價指數風險值之比較研究

近年來各國間的貿易、資金等互動頻繁，加上各式衍生性金融商品的推出，提高了風險管理的複雜度與困難度。2007年8月，美國爆發次級房貸的問題，連帶影響全球金融市場，更造成股、匯市劇烈的波動，也使得許多大型國際金融機構接連破產倒閉。因此本研究欲探討在此次受到美國次貸風暴影響較為劇烈之美、歐、亞三洲共17個國際股價指數，其中包括道瓊工業指數、那斯達克指數、S & P 500指數、費城半導體指數；倫敦金融時報指數、德國DAX指數、法國 CAC 40指數、瑞士SMI市場指數、盧森堡Lux指數；台灣發行量加權指數、日經225指數、首爾綜合指數、香港恆生指數、上海綜合指數、深圳綜合指數、新加坡海峽時報指數、泰國綜合指數。並將時間擷取為次貸風暴前、次貸風暴中與次貸風暴後，亦採用歷史模擬法、蒙地卡羅模擬法、GARCH、GJR-GARCH共4種風險值模型，分析17個國際股價指數在這三段期間中的風險值比較。在本研究的實證結果中，因次貸風暴期間的樣本數不足，使得歷史模擬法與蒙地卡羅模擬法無法正確的估計各指數的風險值。GARCH與GJR-GARCH模型所估計之風險值與事實較為貼近，表示此兩模型較不受到期間長短的影響。實證發現，在次貸風暴前亞洲股市的風險值是較高的，次貸風暴中轉變為美國股市受到衝擊最大，而泰國綜合指數在此次的風暴中並無受到太大的波及，並且在次貸風暴期間亞洲股市的風險值波動反而較歐洲為大。在次貸風暴過後，費城半導體指數目前仍是全球風險值最大的股價指數，而瑞士SMI指數所估計出的風險值為最小，且在風暴期間的跌幅並不深，可見此指數較為抗跌。

關鍵字

歷史模擬法；風險值； GJR-GARCH ； GARCH ；蒙地卡羅模擬法

並列摘要

Over the past decade, along with the popularity of mutual trades and financial derivatives increases, as well as the rapid development of various financial products, risk management becomes more complicate than that of the previous periods. Since August 2007, the subprime mortgage loan crisis occurred, global financial markets had been heavily affected. This Financial Tsunami crisis not only caused the dramatic turbulence in the stock international and foreign exchange markets, but also forced many large financial companies to go bankrupt. This study attempts to examine the impact of the serious extent of financial tsunami crisis on the 17 international stock indexes in the United States, Europe and Asia for past two years. This work divides the sample period into three sub-periods (namely, the period before financial tsunami, that during the financial tsunami and that after the financial tsunami). The research methods used were Historical simulation, Monte Carlo simulation, GARCH, and GJR-GARCH models. This work finds that the Historical simulation and Monte Carlo simulation methods could not correctly estimate each index because of the small sample size. However, the VaR value obtained by the GARCH and GJR-GARCH models matched with the realistic figures, suggesting that these two models have not been affected by the length of the period. Empirical findings indicate that the Asian stock market had the highest VaR before the Financial Tsunami period; while the U.S. stock market had the highest VaR value and Thailand Stock market had the lowest VaR value during the financial tsunami period； while Philadelphia Semiconductor stock index had the highest VaR value and Swiss SMI index had the lowest VaR value after the Financial Tsunami period.

並列關鍵字

Financial Tsunami ； GARCH model ； GJR-GARCH model ； Historical Simulation Method ； Monte Carlo Simulation Method ； Value-at-Risk (VaR)

參考文獻

高凱聲，2007，「美國次級房貸對經濟衝擊之探討」，空大學訓，頁60-70。

高櫻芬與謝家和，2002，「涉險值之衡量—多變量GARCH模型之應用」，經濟論文叢刊，30，273-312。

康景翔，2008，次級房貸風暴後股匯市風險值的衡量，中原大學國際貿易學系碩士論文。

楊雅惠，2008，「省思國際金融危機－從次貸風暴談起」，經濟前瞻，第118期，頁76-81。

楊雅惠，2008，「省思國際金融危機－從次貸風暴談起」，經濟廣場，第118期，頁76-81。

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全球17個國際股價指數風險值之比較研究

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