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基于任意时间窗口内具有无限到达率的资产价格跳跃行为近期引起学术界的广泛关注。本文对传统的无限活跃跳跃行为辨识方法——阈值p幂次变差(TM PV)方法存在的阈值时变性问题进行了修正,基于蒙特卡洛技术的模拟结果验证了改进之后的模型具有更好的效果。进一步,基于改进的TM PV模型对中国证券市场不同类型个股进行了实证研究,结果发现在中国证券市场无限活跃跳跃是一种常态下的价格行为,这种现象几乎每天都在发生,因此基于无限活跃跳跃的资产价格模型更适合于刻画我国证券市场的价格过程。
Asset price jumping based on infinite arrival rate in any time window has aroused widespread concern in academia. In this paper, the problem of threshold time-varying existing in the traditional method of infinite active jumping behavior-threshold p-power variation (TM PV) is modified. The simulation results based on Monte Carlo technique verify that the improved model has better performance Effect. Furthermore, based on the improved TM PV model, this paper empirically studies the different types of stocks in China’s securities market and finds that the infinitely active jump in China’s securities market is a normal price behavior, which occurs almost daily. Therefore, based on infinity The active and leaping asset price model is more suitable for describing the price process of the stock market in our country.