CAJ | 학술논문

金融资产不但存在方差风险,还存在时变偏度风险和时变峰度风险,这使得仅从金融资产的前两阶矩出发来研究风险变化显得十分局限.GJRSK-M模型是描述金融资产的高阶矩风险的有效工具,可对单个金融资产的分布进行拟合,而M-Copula函数能连接组合金融资产的边缘分布,因此本文建立了M-Copula-GJRSK-M模型来研究沪深两股票市场的相依性.实证表明,上证综指和深圳成指对数收益率存在高阶矩风险和风险的非对称性,即指数下跌时,条件方差风险和条件高阶矩风险会增大,且在极端情况下,两市上涨的概率要大于下跌的概率.
금융자산불단존재방차풍험,환존재시변편도풍험화시변봉도풍험,저사득부종금융자산적전량계구출발래연구풍험변화현득십분국한.GJRSK-M모형시묘술금융자산적고계구풍험적유효공구,가대단개금융자산적분포진행의합,이M-Copula함수능련접조합금융자산적변연분포,인차본문건립료M-Copula-GJRSK-M모형래연구호심량고표시장적상의성.실증표명,상증종지화심수성지대수수익솔존재고계구풍험화풍험적비대칭성,즉지수하질시,조건방차풍험화조건고계구풍험회증대,차재겁단정황하,량시상창적개솔요대우하질적개솔.
Financial assets not only have variance risk, but also have time-varying skewness risk and kurtosis risk, which makes risk change study very limited if only based on the first or the second moment of the financial assets. GJRSK-M model is an effec- tive tool for higher moments risk description of the financial assets and can fit for the distribution of individual financial assets, however, M-Copula function can connect marginal distribution of portfolio financial assets, thus, this paper establishes M-Copula- GJRSK-M model to study the interdependence between Shanghai and Shenzhen stock market. The empirical results show that there are higher moment risk and risk asymmetry of the logarithm earnings rate of Shanghai composite index and Shenzhen component index, i.e, conditional variance risk and conditional higher moment risk increase when the index falls, furthermore, the probabili- ty for the index rise of the two stock markets is bigger than that of the index fall under the extreme condition.