英文标题：
《Testing of Binary Regime Switching Models using Squeeze Duration
Analysis》
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作者：
Milan Kumar Das and Anindya Goswami
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最新提交年份：
2018
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英文摘要：
We have developed a statistical technique to test the model assumption of binary regime switching extension of the geometric Brownian motion (GBM) model by proposing a new discriminating statistics. Given a time series data, we have identified an admissible class of the regime switching candidate models for the statistical inference. By performing several systematic experiments, we have successfully shown that the sampling distribution of the test statistics differs drastically, if the model assumption changes from GBM to Markov modulated GBM, or to semi-Markov modulated GBM. Furthermore, we have implemented this statistics for testing the regime switching hypothesis with Indian sectoral indices.
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中文摘要：
通过提出一种新的判别统计量，我们发展了一种统计技术来检验几何布朗运动（GBM）模型的二元区域切换扩展的模型假设。在给定时间序列数据的情况下，我们确定了一类可容许的区域切换候选模型用于统计推断。通过进行多个系统的实验，我们成功地表明，如果模型假设从GBM变为马尔可夫调制GBM或半马尔可夫调制GBM，则测试统计量的抽样分布会发生巨大变化。此外，我们利用印度部门指数对政权转换假说进行了统计检验。
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分类信息：

一级分类：Quantitative Finance 数量金融学
二级分类：Computational Finance 计算金融学
分类描述：Computational methods, including Monte Carlo, PDE, lattice and other numerical methods with applications to financial modeling
计算方法，包括蒙特卡罗，偏微分方程，格子和其他数值方法，并应用于金融建模
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