[R-SIG-Finance] Bayesian estimation of jump-diffusion processes andself-exciting counting processes
Jeffrey Todd Lins
jtl at saxobank.com
Wed Apr 2 10:08:18 CEST 2008
Jeffrey Todd Lins
Saxo Bank A/S
(Sent from my BlackBerry)
----- Original Message -----
From: r-sig-finance-bounces at stat.math.ethz.ch <r-sig-finance-bounces at stat.math.ethz.ch>
To: r-help <R-help at stat.math.ethz.ch>; r-sig-finance at stat.math.ethz.ch <r-sig-finance at stat.math.ethz.ch>
Sent: Wed Apr 02 06:49:54 2008
Subject: [R-SIG-Finance] Bayesian estimation of jump-diffusion processes andself-exciting counting processes
Could anybody give me some pointers to estimation of jump-diffusion
and self-exciting processes(or more generally, counting processes with
stochastic intensity, such as doubly stochastic processes, Cox
processes, Hawkes processes) using the Bayesian approach, esp. using
MCMC and BUGS, or more generally, how to estimate a state-space model
that contains both diffusion processes and jump or self-exciting
processes using Bayesian MCMC and BUGS(both in continuous time and in
discrete time). I've seen demonstration in BUGS for simple state-space
models, with diffusion processes. But I am having a lot of difficulty
finding literature and programs for using BUGS for state-space models
involving self-exciting counting processes with stochastic
intensities. Please give me some pointers! Thank you very much!
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