<p><p>This book developed from classes in mathematical biology taught by the authors over several years at the Technische UniversitΓ€t MΓΌnchen. The main themes are modeling principles, mathematical principles for the analysis of these models and model-based analysis of data. The key topics of modern
Mathematical Finance: Deterministic and Stochastic Models
β Scribed by Jacques Janssen, Raimondo Manca, Ernesto Volpe di Prignano(auth.)
- Publisher
- Wiley-ISTE
- Year
- 2009
- Tongue
- English
- Leaves
- 856
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Synopsis
This book provides a detailed study of Financial Mathematics.Β In addition to the extraordinary depth the book provides, it offers a study of the axiomatic approach that is ideally suited for analyzing financial problems. This book is addressed to MBA's, Financial Engineers, Applied Mathematicians, Banks, Insurance Companies, and Students of Business School, of Economics, of Applied Mathematics, of Financial Engineering, Banks, and more.Content:
Chapter 1 Introductory Elements to Financial Mathematics (pages 1β12):
Chapter 2 Theory of Financial Laws (pages 13β40):
Chapter 3 Uniform Regimes in Financial Practice (pages 41β89):
Chapter 4 Financial Operations and their Evaluation: Decisional Criteria (pages 91β145):
Chapter 5 Annuities?Certain and their Value at Fixed Rate (pages 147β210):
Chapter 6 Loan Amortization and Funding Methods (pages 211β287):
Chapter 7 Exchanges and Prices on the Financial Market (pages 289β329):
Chapter 8 Annuities, Amortizations and Funding in the Case of Term Structures (pages 331β361):
Chapter 9 Time and Variability Indicators, Classical Immunization (pages 363β408):
Chapter 10 Basic Probabilistic Tools for Finance (pages 409β455):
Chapter 11 Markov Chains (pages 457β479):
Chapter 12 Semi?Markov Processes (pages 481β515):
Chapter 13 Stochastic or Ito Calculus (pages 517β552):
Chapter 14 Option Theory (pages 553β606):
Chapter 15 Markov and Semi?Markov Option Models (pages 607β640):
Chapter 16 Interest Rate Stochastic Models β Application to the Bond Pricing Problem (pages 641β685):
Chapter 17 Portfolio Theory (pages 687β701):
Chapter 18 Value at Risk (VaR) Methods and Simulation (pages 703β742):
Chapter 19 Credit Risk or Default Risk (pages 743β789):
Chapter 20 Markov and Semi?Markov Reward Processes and Stochastic Annuities (pages 791β830):
π SIMILAR VOLUMES
<p>This book explores discrete-time dynamic optimization and provides a detailed introduction to both deterministic and stochastic models. Covering problems with finite and infinite horizon, as well as Markov renewal programs, Bayesian control models and partially observable processes, the book focu
<div><div>This book explores discrete-time dynamic optimization and provides a detailed introduction to both deterministic and stochastic models. Covering problems with finite and infinite horizon, as well as Markov renewal programs, Bayesian control models and partially observable processes, the bo