Hidden Markov Models in Finance

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Format: Hardcover
Pub. Date: 2007-04-27
Publisher(s): Springer Nature
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Summary

A number of methodologies have been employed to provide decision making solutions to a whole assortment of financial problems in today's globalized markets. Hidden Markov Models in Finance by Mamon and Elliott will be the first systematic application of these methods to some special kinds of financial problems; namely, pricing options and variance swaps, valuation of life insurance policies, interest rate theory, credit risk modeling, risk management, analysis of future demand and inventory level, testing foreign exchange rate hypothesis, and early warning systems for currency crises. This book provides researchers and practitioners with analyses that allow them to sort through the random "noise" of financial markets (i.e., turbulence, volatility, emotion, chaotic events, etc.) and analyze the fundamental components of economic markets. Hence, Hidden Markov Models in Finance provides decision makers with a clear, accurate picture of core financial components by filtering out the random noise in financial markets.

Table of Contents

An Exact Solution of the Term Structure of Interest Rate under Regime-Switching Riskp. 1
Introductionp. 1
A new representation for modeling regime shiftp. 3
The modelp. 5
Two state variablesp. 5
Pricing kernelp. 5
The risk-neutral probability measurep. 5
The term structure of interest ratesp. 8
A tractable specification with exact solutionp. 9
Affine regime-switching modelsp. 9
Conclusionsp. 13
Referencesp. 13
The Term Structure of Interest Rates in a Hidden Markov Settingp. 15
Introductionp. 15
The Modelp. 17
The Markov chainp. 17
The short-term interest ratep. 20
The zero-coupon bond valuep. 21
Implementationp. 22
Resultsp. 25
Conclusionp. 30
Referencesp. 30
On Fair Valuation of Participating Life Insurance Policies With Regime Switchingp. 31
Introductionp. 31
The model dynamicsp. 33
Dimension reduction to regime-switching PDEp. 38
Further investigationp. 42
Referencesp. 42
Pricing Options and Variance Swaps in Markov-Modulated Brownian Marketsp. 45
Introductionp. 45
Literature reviewp. 47
Martingale characterization of Markov processesp. 48
Pricing options for Markov-modulated security marketsp. 51
Incompleteness of Markov-modulated Brownian security marketsp. 51
The Black-Scholes formula for pricing options in a Markov-modulated Brownian marketp. 53
Pricing options for Markov-modulated Brownian markets with jumpsp. 58
Incompleteness of Markov-modulated Brownian (B, S)-security markets with jumpsp. 58
Black-Scholes formula for pricing options in Markov-modulated Brownian (B, S)-security market with jumpsp. 60
Pricing of Variancev swaps for stochastic volatility driven by Markov processp. 62
Stochastic volatility driven by Markov processp. 62
Pricing of variance swaps for stochastic volatility driven by Markov processp. 63
Example of variance swap for stochastic volatility driven by two-state continuous Markov chainp. 64
Some auxiliary resultsp. 64
A Feynmann-Kac formula for the Markov-modulated process (ys(t),xs(t))t ≥ sp. 64
Formula for the option price fT(ST) for the market combined Markov-modulated (B, S)-security market and compound geometric Poisson process (see Section 4.4.2)p. 66
Referencesp. 67
Smoothed Parameter Estimation for a Hidden Markov Model of Credit Qualityp. 69
Introductionp. 69
Dynamics of the Markov chain and observationsp. 70
Reference probabilityp. 71
Recursive filterp. 71
Parameter estimatesp. 72
Smoothed estimatesp. 75
Appendixp. 80
Referencesp. 90
Expected Shortfall Under a Model With Market and Credit Risksp. 91
Introductionp. 91
Markov regime-switching modelp. 94
Weak Markov-regime switching modelp. 98
Concluding remarksp. 99
Referencesp. 99
Filtering of Hidden Weak Markov Chain -Discrete Range Observationsp. 101
Introductionp. 101
Basic Settingsp. 103
Change of Measurep. 105
A general unnormalized recursive filterp. 107
Estimation of states, transitions and occupation timesp. 109
State estimationp. 109
Estimators for the number of jumpsp. 109
Estimators for 1-state occupation timesp. 110
Estimators for 2-state occupation timesp. 111
Estimators for state to observation transitionsp. 111
Parameter re-estimationsp. 112
Error analysisp. 116
Conclusionp. 117
Referencesp. 118
Filtering of a Partially Observed Inventory Systemp. 121
Introductionp. 121
Model descriptionp. 123
Reference probabilityp. 124
Filteringp. 125
Filters for <$>G_n^{m \ell i}<$>, and <$>S_n^{\ell i}p. 128
Parameter re-estimationp. 131
Referencesp. 131
An empirical investigation of the unbiased forward exchange rate hypothesis in a regime switching marketp. 133
Introductionp. 134
Stylised features and statistical properties of foreign exchange ratesp. 135
Stationary and nonstationary time seriesp. 139
Cointegration and the unbiased forward exchange rate (UFER) hypothesisp. 142
Evidence from exchange rate market via a Markov regime-switching modelp. 146
Concluding remarksp. 151
Referencesp. 151
Early Warning Systems for Currency Crises: A Regime-Switching Approachp. 155
Introductionp. 155
A Markov-switching approach to early warning systemsp. 159
Data description and transformationp. 162
Estimation resultsp. 168
Indonesiap. 168
Koreap. 170
Malaysiap. 170
The Philippinesp. 171
Thailandp. 175
Forecast assessmentp. 176
Conclusionsp. 180
Referencesp. 182
Table of Contents provided by Publisher. All Rights Reserved.

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