2010
DOI: 10.1016/j.frl.2010.01.001
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A regime-switching term structure model with observable state variables

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Cited by 3 publications
(2 citation statements)
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“…Thus, the regime‐shift mechanism of the target rate is articulated over two state variables false(θt,ρtfalse) where ρt is the statistical latent regime in which θt evolves. We resort to a discrete time‐inhomogeneous Markov chain approach to capture the dynamics of these two state variables as in Ferland, Gauthier, and Lalancette (). This is motivated by the target rate that changes on FOMC meetings as a step function of multiples of ±25 basis points.…”
Section: Model For Interest‐rate Caps Under Fomc Meetingsmentioning
confidence: 99%
See 1 more Smart Citation
“…Thus, the regime‐shift mechanism of the target rate is articulated over two state variables false(θt,ρtfalse) where ρt is the statistical latent regime in which θt evolves. We resort to a discrete time‐inhomogeneous Markov chain approach to capture the dynamics of these two state variables as in Ferland, Gauthier, and Lalancette (). This is motivated by the target rate that changes on FOMC meetings as a step function of multiples of ±25 basis points.…”
Section: Model For Interest‐rate Caps Under Fomc Meetingsmentioning
confidence: 99%
“…The full estimation approach is a daunting task where 29 parameters are estimated simultaneously, all cast into a highly nonlinear objective function. To circumvent this obstacle, we first estimate the semi‐hidden Markov chain false(θt,ρtfalse) as in Ferland et al () and, in turn, use the resulting estimates to optimize the global likelihood function. The estimation results under the data‐generating measure are reported in the first part of Table .…”
Section: Estimationmentioning
confidence: 99%