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The first systematic application of these highly specialized tools to financial problems
Applies theses tools to option pricing, interest rate theory, credit risk modeling, volatility estimation, electricity and other commodity pricing
Provides an accurate picture of core financial components by filtering out the random noise in financial markets
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.
Content Level »Research
Keywords »Finance - Markov - Markov chain - Markov model - Markov models - Variance - credit risk modeling - early warning systems - interest rates - inventory system - life insurance valuation - market risk - model - modeling - regime-switching