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首页> 外文期刊>Quantitative finance >Apparent criticality and calibration issues in the Hawkes self-excited point process model: application to high-frequency financial data
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Apparent criticality and calibration issues in the Hawkes self-excited point process model: application to high-frequency financial data

机译:霍克斯自激点过程模型中的表观重要性和校准问题:应用于高频金融数据

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We present a careful analysis of possible issues on the application of the self-excited Hawkes process to high-frequency financial data. We analyse a set of effects leading to significant biases in the estimation of the criticality index' n that quantifies the degree of endogeneity of how much past events trigger future events. We report the following model biases: (i) evidence of strong upward biases on the estimation of n when using power law memory kernels in the presence of outliers, (ii) strong effects on n resulting from the form of the regularization part of the power law kernel, (iii) strong edge effects on the estimated n when using power law kernels and (iv) the need for an exhaustive search of the absolute maximum of the log-likelihood function due to its complicated shape. Moreover, we demonstrate that the calibration of the Hawkes process on mixtures of pure Poisson process with changes of regime leads to completely spurious apparent critical values for the branching ratio (), while the true value is actually . More generally, regime shifts on the parameters of the Hawkes model and/or on the generating process itself are shown to systematically lead to a significant upward bias in the estimation of the branching ratio. We demonstrate the importance of the preparation of the high-frequency financial data, in particular: (a) the impact of overnight trading in the analysis of long-term trends, (b) intraday seasonality and detrending of the data and (c) vulnerability of the analysis to day-to-day non-stationarity and regime shifts. Special care is given to the decrease of quality of the timestamps of tick data due to latency and grouping of messages to packets by the stock exchange. Altogether, our careful exploration of the caveats of the calibration of the Hawkes process stresses the need for considering all the above issues before any conclusion can be sustained. In this respect, because the above effects are plaguing their analyses, the claim by Hardiman et al. [Eur. Phys. J. B - Cond. Matter Comp. Syst., 2013, 86, 442] that financial market has been continuously functioning at or close to criticality () cannot be supported. In contrast, our previous results on E-mini S&P 500 Futures Contracts and on major commodity future contracts are upheld.
机译:我们对将自激霍克斯过程应用于高频金融数据的可能问题进行了仔细的分析。我们分析了一组导致严重性指数'n估计上的重大偏差的影响,这些影响量化了过去事件触发未来事件的内生性程度。我们报告了以下模型偏差:(i)在存在异常值时使用幂定律记忆核时,对n的估计存在强烈的向上偏差的证据,(ii)由幂的正则化部分的形式对n产生强烈影响定律核,(iii)使用幂定律核时,对估计的n有很强的边缘影响;(iv)由于对数似然函数的形状复杂,需要穷举搜索对数似然函数的绝对最大值。此外,我们证明了在纯Poisson过程与制度变化的混合物上对Hawkes过程进行校准会导致分支比完全虚假的表观临界值( ),而真正的值实际上是 。更一般地,在霍克斯模型的参数和/或在生成过程本身上的状态变化被显示为系统地导致分支比的估计中的明显的向上偏差。我们证明了准备高频财务数据的重要性,尤其是:(a)隔夜交易对长期趋势分析的影响;(b)数据的日内季节性和去趋势性;(c)脆弱性分析日常的非平稳性和政权转移。特别要注意的是,由于等待时间和证券交易所将消息分组到数据包而导致的滴答数据时间戳质量下降。总而言之,我们对霍克斯过程校准的注意事项的仔细探索强调,在得出任何结论之前,必须考虑所有上述问题。在这方面,由于上述影响困扰着他们的分析,Hardiman等人的主张。 [欧元。物理J.B-条件物质补偿Syst。,2013,86,442],金融市场一直处于临界状态或接近临界状态( 。相反,我们先前在E-mini S&P 500期货合约和主要商品期货合约上的结果得到了维持。

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