Hidden Markov Models in Finance

ISBN-13: 9780387710815 / Angielski / Twarda / 2007 / 186 str.

Rogemar S. Mamon; Robert J. Elliott; Robert J. Elliott

Opis

A number of methodologies have been employed to provide decision making solutions globalized markets. Hidden Markov Models in Finance offers the first systematic application of these methods to specialized financial problems: option pricing, credit risk modeling, volatility estimation and more. The book provides tools for sorting through turbulence, volatility, emotion, chaotic events - the random "noise" of financial markets - to analyze core components.

Spis treści

An Exact Solution of the Term Structure of Interest Rate Under Regime-Switching Risk.- The Term Structure of Interest Rates in a Hidden Markov Setting.- On Fair Valuation of Participating Life Insurance Policies With Regime Switching.- Pricing Options and Variance Swaps in Markov-Modulated Brownian Markets.- Smoothed Parameter Estimation for a Hidden Markov Model of Credit Quality.- Expected Shortfall Under a Model With Market and Credit Risks.- Filtering of Hidden Weak Markov Chain -Discrete Range Observations.- Filtering of a Partially Observed Inventory System.- An empirical investigation of the unbiased forward exchange rate hypothesis in a regime switching market.- Early Warning Systems for Currency Crises: A Regime-Switching Approach.

Blurb

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.