Hidden Markov Models in Finance金融业中的隐马尔可夫模型 azw3 chm 地址 kindle 阿里云 下载 umd pdf

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.

1　An Exact Solution of the Term Structure of Interest Rateunder Regime.Switching Risk Shuwz.Yong Zeng

1.1　Introduction

1.2　A new representation for modeling regime shift

1.3　The model

1.3.1　TWO state variables

1.3.2　Pricing kernel

1.3.3　The risk.neutral probability measure

1.3.4　The term structure of interest rates

1.4　A tractable specification with exact solution

1.4.1　Affine regimeswitching models

1.5　Conclusions

References

2　The Term Structure of Interest Rates in a Hidden MarkovSetting

Robert，Elliott.Craig A.WiIson

2.1 Introduction

2.2　The Model

2.2.1　The Markov chain

2.2.2　The shortterm interest rate

2.2.3　The zerOcoupon bond value

2.3　Implementation

2.4　Results

2.5　Conclusion

References

3　On Fair Valuation of Participating Life Insurance Policies With Regime Switching Tak Kuen Siu

3.1 Introduction

3.2 The model dynamics

3.3　Dimension reduction to regime-switching PDE

3.4　Further investigation

References.

4　Pricing Options and Variance Swaps in Markov-Modulated Brownian Markets

Robert，Elliott.Anatoliy矿Swishchuk

4.1 Introduction

4.2　Literature review

4.3　Martingale characterization ofMarkov processes

4.4　Pricing options for Markovmodulated security markets

4.4.1　Incompleteness of Markovmodulated Brownian security markets

4.4.2　The Black-Scholes formula for pricing options in a Markovmodulated Brownian market

4.5　Pricing options for Markov-modulated Brownian markets with jumps

4.5.1　Incompleteness of Markovmodulated Brownian （B，S）-security markets withjumps

4.5.2　BlackScholes formula for pricing options in Markovmodulated Brownian fB，S）-security market with jumps

4.6 Pricing of Variancev swaps for stochastic volatility driven by Markov process.

4.6.1 Stochastic volatility driven by Markov process.

4.6.2　Pricing of variance swaps for stochastic volatility driven by Markov process

4.6.3 Example of variance SWap for stochastic volatility driven by tw0state COntinuous Markov chainA

A Some auxiliary results.

A.1 A FeynmannKac formula for the Markovmodulated

process（Ys（t），Xs（t））t＞s

A.2 Formula for the option price FT（ST） for the market

combined Markovmodulated（B，Sl-security market and

compound geometric Poisson process（see Section 4.4.2）

Referrences

　……

5 Smoothed Parameter Estimation for a Hidden Markov Model of Credit Quality

6 Expectde Shortfall Under a Model With Market and Credit Risks

7 Filtering of Hidden Weak Markov Chain-Discrete Range Observations

8 Filtering of a Partially Observed Inventory Sytem

9 An empirical investigation of the unbiased forward exchange rate hypothesis in a regime switching market

10 Early Warning Systems for Currency Crises：A Regime-Switchng Approach

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