Estimating doubly stochastic Poisson process with affine intensities by Kalman filter

被引:1
|
作者
De Genaro, Alan [1 ,2 ]
Simonis, Adilson [3 ]
机构
[1] Univ Sao Paulo, Dept Econ, Sao Paulo, Brazil
[2] BM&FBOVESPA, Secur Commod & Futures Exchange, Sao Paulo, Brazil
[3] Univ Sao Paulo, Inst Math & Stat, Sao Paulo, Brazil
关键词
Doubly stochastic Poisson process; Affine diffusion; Kalman filter; Order book; TERM STRUCTURE; COX PROCESS; MODEL; TESTS;
D O I
10.1007/s00362-014-0606-6
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
This paper proposes a Kalman filter formulation for parameter estimation of doubly stochastic Poisson processes (DSPP) with stochastic affine intensities. To achieve this aim, an analytical expression for the probability distribution functions of the corresponding DSPP for any intensity from the class of affine diffusions is obtained. More detailed results are provided for one- and two-factor Feller and Ornstein-Uhlenbeck diffusions. A Monte Carlo study indicates that the proposed method is a reliable procedure for moderate sample sizes. An empirical analysis of one- and two-factor Feller and Ornstein-Uhlenbeck models is carried out using high frequency transaction data.
引用
收藏
页码:723 / 748
页数:26
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