复合极值理论在股市星期效应风险预测中的应用
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摘要
巧妙利用数据破坏了超阀值的成串出现这个特点,又考虑到了每年股市波动程度的不同,使用复合超阀值分布Poisson-GP拟合了上证指数和深圳成指星期一到星期五的尾部分布.采用极大似然估计给出了模型的估计,利用估计结果给出了上证指数和深圳成指星期一到星期五的风险预测.
Compound threshold distribution Poisson-GP is applied to fit the tail distribution of the Shanghai Composite Index and Shenzhen Component Index from Monday to Friday by making good use of data to break up the string of overthreshold values and takeing into account the different fluctuations of the stock market each year.Max-Likelihood Estimation is employed to estimate the parameters of model,and Value-at-Risk of Shanghai Composite Index and Shenzhen Component Index from Monday to Friday is given by using the estimated results.
Compound threshold distribution Poisson-GP is applied to fit the tail distribution of the Shanghai Composite Index and Shenzhen Component Index from Monday to Friday by making good use of data to break up the string of overthreshold values and takeing into account the different fluctuations of the stock market each year.Max-Likelihood Estimation is employed to estimate the parameters of model,and Value-at-Risk of Shanghai Composite Index and Shenzhen Component Index from Monday to Friday is given by using the estimated results.
引文
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[7] 田宏伟,詹原瑞,邱军.极值理论(EVT)方法用于受险价值(VaR)计算的实证比较与分析[J].系统工程理论与实践,2000(10):27-35.
[8] 李梦华,余东,刘子微,王华.基于EVT的EGARCH-M模型在动态VaR中的应用[J].黄冈师范学院学报,2010,30(3):102-107.
[9] Pickands III J.Statistical inference using extreme order statistics[J].The Annals of Statistics,1975,3(1):119-131.
[10] McNeil A J,Frey R.Estimation of tail-related risk measures for heteroscedastic financial time series:An extreme value approach[J].Emprical Finance,2000,7(3):271-300.
[2] 张普,陈亮,蒋月娥.海峡两岸股票市场日历效应研究—基于滚动样本的实证分析[J].常州大学学报:社会科学版,2018,19(1):64-72.
[3] 张成虎,武博华,郭勇.基于神经网络的我国沪深股市星期效应新探[J].西北大学学报:哲学社会科学版,2014,44(3):122-127.
[4] 刘汉中.周日效应下的VaR风险测量[J].系统工程,2004,22(11):59-61.
[5] 龚锐,陈仲常,杨栋锐.GARCH族模型计算中国股市在险价值(VaR)风险的比较研究与评述[J].数量经济技术经济研究,2005(7):67-81.
[6] 马玉林,陈伟忠,施红俊.极值理论在VaR中的应用及对沪深股市的实证分析[J].金融教学与研究,2003(6):25-27.
[7] 田宏伟,詹原瑞,邱军.极值理论(EVT)方法用于受险价值(VaR)计算的实证比较与分析[J].系统工程理论与实践,2000(10):27-35.
[8] 李梦华,余东,刘子微,王华.基于EVT的EGARCH-M模型在动态VaR中的应用[J].黄冈师范学院学报,2010,30(3):102-107.
[9] Pickands III J.Statistical inference using extreme order statistics[J].The Annals of Statistics,1975,3(1):119-131.
[10] McNeil A J,Frey R.Estimation of tail-related risk measures for heteroscedastic financial time series:An extreme value approach[J].Emprical Finance,2000,7(3):271-300.