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Modeling Financial Intraday Jump Tail Contagion with High Frequency Data Using Mutually Exciting Hawkes Process

机译:使用相互刺激的鹰过程建模金融盘子内跳尾蔓延

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Financial extreme jumps in asset price may propagate across stock markets and lead to the market-wide crashes, which severely threatens the stability of the financial system. In order to analyzing the contagion features of jump tail risk, this paper proposes a mutually exciting contagion model based on Hawkes process with intraday high frequency data. We use a simple two-stage method that first extracts the jump component nonparametrically from the high frequency data and then models the intraday jump tail using mutually exciting Hawkes process. Moreover, we take both the occurrence time and magnitude of jump into account in modeling the conditional intensity of Hawkes process. The proposed method is applied to the five-minute high frequency data of the Chinese stock market. The empirical results show that, for the two main Chinese stock markets, only background intensity is significant in the Shanghai stock market, while mutually exciting effect is significant in the Shenzhen stock market. Both the location and size of jump in the Shanghai stock market have significant stimulation to the next occurrences of jump in the Shenzhen stock market. Furthermore, the proposed model performs very well in predicting the future jump tail events.
机译:资产价格的金融极端跃迁可能跨越股市繁殖,导致市场崩溃,严重威胁到金融体系的稳定性。为了分析跳跃尾风险的传感器特征,本文提出了一种基于带内高频数据的鹰过程的相互激发的传感模型。我们使用一个简单的两阶段方法,首先将跳跃分量从高频数据中的跳跃分量提取,然后使用相互刺激的鹰过程模拟日内跳尾。此外,我们认为跳跃的发生时间和幅度在模拟鹰过程的条件强度时。该方法适用于中国股市的五分钟高频数据。实证结果表明,对于两国主要的股票市场,只有背景强度在上海股市中很大,而在深圳股市中相互兴奋的效果是重要的。上海股市的跳跃的位置和大小都对深圳股市下一次跳跃的涨幅有重大刺激。此外,所提出的模型在预测未来的跳跃尾部事件方面非常好。

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