不同市态下正态性转换时变VaR

VaR技术作为全球广为流行的金融风险管理技术,其测度的是极端情况下的风险头寸,但在传统假设下可能会极大地低估其值,这就会使得在实践中使用VaR值作为风险管理标准时面临更大的新的风险.考虑我国股市处于不同市场态势下对风险头寸的影响,就牛、熊市中分别估测VaR值.首先利用各种Delta-Gamma-Johnson转换函数对经验数据进行正态性调整.考虑通过转换机制调整后的经验数据仍然存在的异方差性特征,然后运用GARCH模型计算时变VaR值,以此来改善VaR的计算风险,探讨我国股票市场VaR技术的适用性和准确性.

VaR of Time-varying about Normality Transition of Sample Data

VaR that is a global popular financial risk management technology measure size of risk in extreme cases,but its size in traditional assumption may greatly be underestimated.This will make VaR as a risk management standard in the practice face greater new risk.We will discuss these result that different stages of the stock market impact size of risk,and measure size of risk in rise stage and drop stage of Stock market respectively in this paper.Firstly,we use Delta-Gamma-Johnson function to vary these empirical data into new sequence.make the new sequence-be Normal distribution.Then we estimate VaR of timevarying by GARCH model to improve risk when VaR is estimated because the new sequence adjusted by transformation mechanism keep heteroscedastic feature.We discuss if it is suitable and accurate to this technology to estimate VaR in Chinese stock market.