Effects of Jumps and Small Noises in High-Frequency Financial Econometrics
Effects of Jumps and Small Noises in High-Frequency Financial Econometrics
复制标题
高频金融计量经济学中跳跃和小噪声的影响
DOI：
10.1007/s10690-017-9223-4
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发表时间：
2017
影响因子：
1.7
通讯作者：
Kunitomo
中科院分区：
文献类型：
--
作者：
Naoto;Kunitomo
一些新的高频金融数据分析的统计程序已经开发出来，以估计风险的数量和测试的基础连续时间的金融过程中的跳跃的存在。虽然微观市场噪声的作用在高频金融数据中很重要，但在潜在随机过程中存在噪声和跳跃的影响方面存在一些基本问题。当同时存在跳跃和（微观市场）噪声时，现有的统计方法在实际数据分析中的应用是否可靠并不明显。我们研究了跳跃和噪声对一些基本统计量的误指定效应，并以Ait-Sahalia和Jacod提出的跳跃检验程序（Ann Stat 37-1：184-222 2009; 38-5：3093-3123 2010）为例。我们发现，他们的第一个测试（测试存在的跳跃作为一个零假设）是渐近稳健的小噪声渐近意义上对可能的错误，而他们的第二个测试（测试无跳跃作为一个零假设）是相当敏感的噪声的存在。
Several new statistical procedures for high-frequency financial data analysis have been developed to estimate risk quantities and test the presence of jumps in the underlying continuous-time financial processes. Although the role of micro-market noise is important in high-frequency financial data, there are some basic questions on the effects of presence of noise and jump in the underlying stochastic processes. When there can be jumps and (micro-market) noise at the same time, it is not obvious whether the existing statistical methods are reliable for applications in actual data analysis. We investigate the misspecification effects of jumps and noise on some basic statistics and the testing procedures for jumps proposed by Ait-Sahalia and Jacod (Ann Stat 37–1:184–222 2009; 38–5:3093–3123 2010) as an illustration. We find that their first test (testing the presence of jumps as a null-hypothesis) is asymptotically robust in the small-noise asymptotic sense against possible misspecifications while their second test (testing no-jumps as a null-hypothesis) is quite sensitive to the presence of noise.