数学的实践与认识
數學的實踐與認識
수학적실천여인식
MATHEMATICS IN PRACTICE AND THEORY
2009年
20期
41-47
,共7页
正交GARcH模型%CCC模型%VaR%股票组合
正交GARcH模型%CCC模型%VaR%股票組閤
정교GARcH모형%CCC모형%VaR%고표조합
O-GARCH%CCC%VaR%stock portfolio
运用VaR模型对股票组合进行风险测度的关键之一是得到组合条件协方差矩阵.而经典的多元GARCH模型来求解波动率面临着估计参数过多,计算量庞大的问题.因此,使用正交GARCH模型和CCC模型来估算波动率,并以沪深两市A股市场上四个行业的65只股票为样本,使用RMSE和MAD指标比较这些模型的预测能力,求得股票组合的VaR,得出前者效率高和后者预测能力略高的结论.
運用VaR模型對股票組閤進行風險測度的關鍵之一是得到組閤條件協方差矩陣.而經典的多元GARCH模型來求解波動率麵臨著估計參數過多,計算量龐大的問題.因此,使用正交GARCH模型和CCC模型來估算波動率,併以滬深兩市A股市場上四箇行業的65隻股票為樣本,使用RMSE和MAD指標比較這些模型的預測能力,求得股票組閤的VaR,得齣前者效率高和後者預測能力略高的結論.
운용VaR모형대고표조합진행풍험측도적관건지일시득도조합조건협방차구진.이경전적다원GARCH모형래구해파동솔면림착고계삼수과다,계산량방대적문제.인차,사용정교GARCH모형화CCC모형래고산파동솔,병이호심량시A고시장상사개행업적65지고표위양본,사용RMSE화MAD지표비교저사모형적예측능력,구득고표조합적VaR,득출전자효솔고화후자예측능력략고적결론.
The conditional covariance matrix plays a critical role in portfolio VaR computation. However, in the classical multivariate GARCH model large-scale portfolio is highly parameterized and difficult to estimate in practice. So this paper uses O-GARCH model and CCC model to calculate the volatilities of portfolio. Then 65 samples of stocks in A stock market of Shanghai and Shenzhen is examined by these models. Finally, we follow two criteria to judge the quality of the volatility forcasts and compute portfolio VaR by the conditional covariance matrix.
