[R-SIG-Finance] Cox, Ingersoll, Ross/Vasicek parameter estimation via Kalman-Filter (SSPIR)

Leeds, Mark (IED) Mark.Leeds at morganstanley.com
Fri Apr 27 00:07:10 CEST 2007


harvey, ruiz and shepard ( 1992 ) have a paper on how to transform a
stochastic volatility model to a state space form.
Maybe there is a reference there or an idea for how to do the same for
CIR ? My guess is that it's
been done by someone somewhere but that's thew most I can tell you.

	
mark


-----Original Message-----
From: r-sig-finance-bounces at stat.math.ethz.ch
[mailto:r-sig-finance-bounces at stat.math.ethz.ch] On Behalf Of Arne
Krombach
Sent: Thursday, April 26, 2007 6:02 PM
To: r-sig-finance at stat.math.ethz.ch
Subject: [R-SIG-Finance] Cox, Ingersoll,Ross/Vasicek parameter
estimation via Kalman-Filter (SSPIR)

Dear R-Users,

 

I am trying to estimate the parameters for a CIR 1-/2-/3-Factor model
via Kalman filtering. The idea was to do it via the package SSPIR, but I
have problems to transform the CIR state space form into the SSPIR
syntax.
Actually, I am not quite sure if this is possible at all. 

 

Did anybody already realise a CIR/Vasicek -parameter estimation via R? 

 

To get an idea how a CIR-1-factor state space form looks like (Y= vector
of zerobond-yields with the maturities tau at month t):

 

Y(t,tau)= ( -1/tau * log A(tau) ) + (1/tau * B(tau) * x(t) + e

 

Where :

 

A(tau) = [(2 * h * e^( a + lambda + h) * tau/2) / (2 * h + (a + lambda +
h)
* (e^(tau * h) - 1)] ^(2 * b/ sigma^2)

B(tau) = [(2 * (e^(tau * h)  -1)) / 2 * h + (a + lambda + h) * (e^(tau *
h)
- 1)]

h = sqrt[(a + lambda)^2 + 2*sigma^2] 

 

which means that, besides the time varying factor x, the parameters a,
b, sigma, and lambda have to be estimated via Kalman filtering.

 

Is it possible to implement this in SSPIR? If you have any other
suggests or if you already implement comparable models in R, I would be
very grateful for your help.

 

Kind Regards,

 

Arne Krombach


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