An accessible implementation of interest rate models with Markov-switching

Zhou, Nanxin; Mamon, Rogemar

doi:10.1016/j.eswa.2011.09.053

Cited by 38 publications

(16 citation statements)

References 22 publications

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“…This may be a quite strong assumption, but there has been a considerable progress on regime-switching models for interest rates to potentially achieve practical implementation. Zhou and Mamon (2012) as well as the HMM filtering-based paper of Mamon (2011, 2013) and some references therein illustrate the calibration of parameters using market data, and if a reasonable estimate of market price of risk is given, risk-neutral parameters could be obtained. On the other hand, Xi et al (2012) provide market-consistent parameters using derivative prices through an inverse Stieltjes-moment method that could be adopted to interest-rate modelling.…”

Section: Pure Markov Interest Rate Modelmentioning

confidence: 99%

Mortality modelling with regime-switching for the valuation of a guaranteed annuity option

Huan¹,

Mamon²,

Liu³

et al. 2015

Insurance: Mathematics and Economics

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Section: Pure Markov Interest Rate Modelmentioning

confidence: 99%

Mortality modelling with regime-switching for the valuation of a guaranteed annuity option

Huan¹,

Mamon²,

Liu³

et al. 2015

Insurance: Mathematics and Economics

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“…Works involving Markov switched regimes and CIR dynamics appear in [15] where the bond valuation problem is considered (but not in the form of an American option; their approach will be relevant to the computation of the payoff of our American option although in their model only the mean reverting level is subject to Markov jumps) and in [16] where the term structure of the interest rates is analysed.…”

Section: Relatedmentioning

confidence: 99%

Valuation of the Prepayment Option of a Perpetual Corporate Loan

Papin

Turinici

2013

Abstract and Applied Analysis

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We investigate in this paper a perpetual prepayment option related to a corporate loan. The default intensity of the firm is supposed to follow a CIR process. We assume that the contractual margin of the loan is defined by the credit quality of the borrower and the liquidity cost that reflects the funding cost of the bank. Two frameworks are discussed: firstly a loan margin without liquidity cost and secondly a multiregime framework with a liquidity cost dependent on the regime. The prepayment option needs specific attention as the payoff itself is an implicit function of the parameters of the problem and of the dynamics. In the unique regime case, we establish quasianalytic formulas for the payoff of the option; in both cases we give a verification result that allows for the computation of the price of the option. Numerical results that implement the findings are also presented and are completely consistent with the theory; it is seen that when liquidity parameters are very different (i.e., when a liquidity crisis occurs) in the high liquidity cost regime, the exercise domain may entirely disappear, meaning that it is not optimal for the borrower to prepay during such a liquidity crisis. The method allows for quantification and interpretation of these findings.

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“…The authors of [118] also certified that regime switching models calibrated better and gave more accurate predictions when compared with their counterparts.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Mamon [118] also revealed that regime switching models could display some important observations in the market such as volatility clustering and heavy tail distributions of returns, as well as replication of irregular yield curve shapes. The authors of [118] also certified that regime switching models calibrated better and gave more accurate predictions when compared with their counterparts.…”

Section: Literature Reviewmentioning

confidence: 99%