Basic Stochastic Processes.

This book presents basic stochastic processes, stochastic calculus including Lévy processes on one hand, and Markov and Semi Markov models on the other. From the financial point of view, essential concepts such as the Black and Scholes model, VaR indicators, actuarial evaluation, market values, fai...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Devolder, Pierre
Otros Autores: Janssen, Jacques, Manca, Raimondo
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Hoboken : Wiley, 2015.
Colección:Mathematics and statistics series (ISTE)
Temas:
Stochastic processes.
Stochastic Processes
Processus stochastiques.
Stochastic processes
Acceso en línea:Texto completo

MARC

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049 |a UAMI 
100 1 |a Devolder, Pierre. 
245 1 0 |a Basic Stochastic Processes. 
260 |a Hoboken :  |b Wiley,  |c 2015. 
300 |a 1 online resource (327 pages) 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
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588 0 |a Print version record. 
505 0 |a Cover; Title Page; Copyright; Contents; Introduction; 1: Basic Probabilistic Tools for Stochastic Modeling; 1.1. Probability space and random variables; 1.2. Expectation and independence; 1.3. Main distribution probabilities; 1.3.1. Binomial distribution; 1.3.2. Negative exponential distribution; 1.3.3. Normal (or Laplace-Gauss) distribution; 1.3.4. Poisson distribution; 1.3.5. Lognormal distribution; 1.3.6. Gamma distribution; 1.3.7. Pareto distribution; 1.3.8. Uniform distribution; 1.3.9. Gumbel distribution; 1.3.10. Weibull distribution; 1.3.11. Multi-dimensional normal distribution. 
505 8 |a 1.3.12. Extreme value distribution1.3.12.1. Definition; 1.3.12.2. Asymptotic results; 1.3.12.3. Exact values of the norming constants; 1.3.12.4. Parameters estimation [ESC 97]; 1.3.12.5. Characteristic of extreme value distribution; 1.4. The normal power (NP) approximation; 1.5. Conditioning; 1.6. Stochastic processes; 1.7. Martingales; 2: Homogeneous and Non-homogeneous Renewal Models; 2.1. Introduction; 2.2. Continuous time non-homogeneous convolutions; 2.2.1. Non-homogeneous convolution product; 2.3. Homogeneous and non-homogeneous renewal processes. 
505 8 |a 2.4. Counting processes and renewal functions2.5. Asymptotical results in the homogeneous case; 2.6. Recurrence times in the homogeneous case; 2.7. Particular case: the Poisson process; 2.7.1. Homogeneous case; 2.7.2. Non-homogeneous case; 2.8. Homogeneous alternating renewal processes; 2.9. Solution of non-homogeneous discrete time evolution equation; 2.9.1. General method; 2.9.2. Some particular formulas; 2.9.3. Relations between discrete time and continuous time renewal equations; 3: Markov Chains; 3.1. Definitions; 3.2. Homogeneous case; 3.2.1. Basic definitions. 
505 8 |a 3.2.2. Markov chain state classification3.2.3. Computation of absorption probabilities; 3.2.4. Asymptotic behavior; 3.2.5. Example: a management problem in an insurance company; 3.3. Non-homogeneous Markov chains; 3.3.1. Definitions; 3.3.2. Asymptotical results; 3.4. Markov reward processes; 3.4.1. Classification and notation; 3.4.1.1. Classification of reward processes; 3.4.1.2. Financial parameters; 3.5. Discrete time Markov reward processes (DTMRWPs); 3.5.1. Undiscounted case; 3.5.1.1. First model; 3.5.1.2. Second model; 3.5.1.3. Third model; 3.5.1.4. Fourth model; 3.5.2. Discounted case. 
505 8 |a 3.5.2.1. Immediate cases3.5.2.1.1. First model; 3.5.2.1.2. Second model; 3.5.2.1.3. Third model; 3.5.2.1.4. Fourth model; 3.5.2.1.5. Fifth model; 3.5.2.1.6. Sixth model; 3.5.2.2. Due cases; 3.5.2.2.1. First model; 3.5.2.2.2. Second model; 3.5.2.2.3. Third model; 3.5.2.2.4. Fourth model; 3.6. General algorithms for the DTMRWP; 3.6.1. Homogeneous MRWP; 3.6.2. Non-homogeneous MRWP; 4: Homogeneous and Non-homogeneous Semi-Markov Models; 4.1. Continuous time semi-Markov processes; 4.2. The embedded Markov chain; 4.3. The counting processes and the associated semi-Markov process. 
500 |a 4.4. Initial backward recurrence times. 
520 |a This book presents basic stochastic processes, stochastic calculus including Lévy processes on one hand, and Markov and Semi Markov models on the other. From the financial point of view, essential concepts such as the Black and Scholes model, VaR indicators, actuarial evaluation, market values, fair pricing play a central role and will be presented. The authors also present basic concepts so that this series is relatively self-contained for the main audience formed by actuaries and particularly with ERM (enterprise risk management) certificates, insurance risk managers, students in Master i. 
504 |a Includes bibliographical references and index. 
590 |a ProQuest Ebook Central  |b Ebook Central Academic Complete 
650 0 |a Stochastic processes. 
650 2 |a Stochastic Processes 
650 6 |a Processus stochastiques. 
650 7 |a Stochastic processes  |2 fast 
700 1 |a Janssen, Jacques. 
700 1 |a Manca, Raimondo. 
758 |i has work:  |a Basic stochastic processes (Text)  |1 https://id.oclc.org/worldcat/entity/E39PCG3YbKQmFvkbQV3MJJv4dP  |4 https://id.oclc.org/worldcat/ontology/hasWork 
776 0 8 |i Print version:  |a Devolder, Pierre.  |t Basic Stochastic Processes.  |d Hoboken : Wiley, ©2015  |z 9781848218826 
830 0 |a Mathematics and statistics series (ISTE) 
856 4 0 |u https://ebookcentral.uam.elogim.com/lib/uam-ebooks/detail.action?docID=4041107  |z Texto completo 
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