Stochastic Simulation and Applications in Finance with MATLAB Programs
Title | Stochastic Simulation and Applications in Finance with MATLAB Programs PDF eBook |
Author | Huu Tue Huynh |
Publisher | John Wiley & Sons |
Total Pages | 354 |
Release | 2011-11-21 |
Genre | Business & Economics |
ISBN | 0470722134 |
Stochastic Simulation and Applications in Finance with MATLAB Programs explains the fundamentals of Monte Carlo simulation techniques, their use in the numerical resolution of stochastic differential equations and their current applications in finance. Building on an integrated approach, it provides a pedagogical treatment of the need-to-know materials in risk management and financial engineering. The book takes readers through the basic concepts, covering the most recent research and problems in the area, including: the quadratic re-sampling technique, the Least Squared Method, the dynamic programming and Stratified State Aggregation technique to price American options, the extreme value simulation technique to price exotic options and the retrieval of volatility method to estimate Greeks. The authors also present modern term structure of interest rate models and pricing swaptions with the BGM market model, and give a full explanation of corporate securities valuation and credit risk based on the structural approach of Merton. Case studies on financial guarantees illustrate how to implement the simulation techniques in pricing and hedging. NOTE TO READER: The CD has been converted to URL. Go to the following website www.wiley.com/go/huyhnstochastic which provides MATLAB programs for the practical examples and case studies, which will give the reader confidence in using and adapting specific ways to solve problems involving stochastic processes in finance.
Simulation and Optimization in Finance
Title | Simulation and Optimization in Finance PDF eBook |
Author | Dessislava A. Pachamanova |
Publisher | John Wiley & Sons |
Total Pages | 786 |
Release | 2010-09-23 |
Genre | Business & Economics |
ISBN | 0470882123 |
An introduction to the theory and practice of financial simulation and optimization In recent years, there has been a notable increase in the use of simulation and optimization methods in the financial industry. Applications include portfolio allocation, risk management, pricing, and capital budgeting under uncertainty. This accessible guide provides an introduction to the simulation and optimization techniques most widely used in finance, while at the same time offering background on the financial concepts in these applications. In addition, it clarifies difficult concepts in traditional models of uncertainty in finance, and teaches you how to build models with software. It does this by reviewing current simulation and optimization methodology-along with available software-and proceeds with portfolio risk management, modeling of random processes, pricing of financial derivatives, and real options applications. Contains a unique combination of finance theory and rigorous mathematical modeling emphasizing a hands-on approach through implementation with software Highlights not only classical applications, but also more recent developments, such as pricing of mortgage-backed securities Includes models and code in both spreadsheet-based software (@RISK, Solver, Evolver, VBA) and mathematical modeling software (MATLAB) Filled with in-depth insights and practical advice, Simulation and Optimization Modeling in Finance offers essential guidance on some of the most important topics in financial management.
Handbook in Monte Carlo Simulation
Title | Handbook in Monte Carlo Simulation PDF eBook |
Author | Paolo Brandimarte |
Publisher | John Wiley & Sons |
Total Pages | 620 |
Release | 2014-06-20 |
Genre | Business & Economics |
ISBN | 1118594517 |
An accessible treatment of Monte Carlo methods, techniques, and applications in the field of finance and economics Providing readers with an in-depth and comprehensive guide, the Handbook in Monte Carlo Simulation: Applications in Financial Engineering, Risk Management, and Economics presents a timely account of the applicationsof Monte Carlo methods in financial engineering and economics. Written by an international leading expert in thefield, the handbook illustrates the challenges confronting present-day financial practitioners and provides various applicationsof Monte Carlo techniques to answer these issues. The book is organized into five parts: introduction andmotivation; input analysis, modeling, and estimation; random variate and sample path generation; output analysisand variance reduction; and applications ranging from option pricing and risk management to optimization. The Handbook in Monte Carlo Simulation features: An introductory section for basic material on stochastic modeling and estimation aimed at readers who may need a summary or review of the essentials Carefully crafted examples in order to spot potential pitfalls and drawbacks of each approach An accessible treatment of advanced topics such as low-discrepancy sequences, stochastic optimization, dynamic programming, risk measures, and Markov chain Monte Carlo methods Numerous pieces of R code used to illustrate fundamental ideas in concrete terms and encourage experimentation The Handbook in Monte Carlo Simulation: Applications in Financial Engineering, Risk Management, and Economics is a complete reference for practitioners in the fields of finance, business, applied statistics, econometrics, and engineering, as well as a supplement for MBA and graduate-level courses on Monte Carlo methods and simulation.
Stochastic Modeling in Economics and Finance
Title | Stochastic Modeling in Economics and Finance PDF eBook |
Author | Jitka Dupacova |
Publisher | Springer Science & Business Media |
Total Pages | 394 |
Release | 2005-12-30 |
Genre | Mathematics |
ISBN | 0306481677 |
In Part I, the fundamentals of financial thinking and elementary mathematical methods of finance are presented. The method of presentation is simple enough to bridge the elements of financial arithmetic and complex models of financial math developed in the later parts. It covers characteristics of cash flows, yield curves, and valuation of securities. Part II is devoted to the allocation of funds and risk management: classics (Markowitz theory of portfolio), capital asset pricing model, arbitrage pricing theory, asset & liability management, value at risk. The method explanation takes into account the computational aspects. Part III explains modeling aspects of multistage stochastic programming on a relatively accessible level. It includes a survey of existing software, links to parametric, multiobjective and dynamic programming, and to probability and statistics. It focuses on scenario-based problems with the problems of scenario generation and output analysis discussed in detail and illustrated within a case study.
Handbook of Computational Finance
Title | Handbook of Computational Finance PDF eBook |
Author | Jin-Chuan Duan |
Publisher | Springer Science & Business Media |
Total Pages | 791 |
Release | 2011-10-25 |
Genre | Business & Economics |
ISBN | 3642172547 |
Any financial asset that is openly traded has a market price. Except for extreme market conditions, market price may be more or less than a “fair” value. Fair value is likely to be some complicated function of the current intrinsic value of tangible or intangible assets underlying the claim and our assessment of the characteristics of the underlying assets with respect to the expected rate of growth, future dividends, volatility, and other relevant market factors. Some of these factors that affect the price can be measured at the time of a transaction with reasonably high accuracy. Most factors, however, relate to expectations about the future and to subjective issues, such as current management, corporate policies and market environment, that could affect the future financial performance of the underlying assets. Models are thus needed to describe the stochastic factors and environment, and their implementations inevitably require computational finance tools.
Term Structure of Profit Rates of Sukuk
Title | Term Structure of Profit Rates of Sukuk PDF eBook |
Author | Adesina-Uthman Ganiyat |
Publisher | Cambridge Scholars Publishing |
Total Pages | 340 |
Release | 2015-06-18 |
Genre | Business & Economics |
ISBN | 144387986X |
This book explores several non-traditional and under-researched fields in Islamic finance through its investigations into how the newly-emergent financial instrument Sukuk behaves in the broader field of finite-period financing and pricing in the market place. It provides readers with didactic information on the fundamental theories of term structure and in-depth information on this nascent financial instrument in the Islamic capital market. The book employs one and two-factor models of term structure in order to analyse sovereign and corporate Sukuk bonds from the world’s leading Islamic economy, Malaysia. For the purposes of the study, the book establishes “profit rate yield curves” in the tradition of the conventional bond yield curve in order to define different risk classes of Sukuk. The dynamics of term structure of profit rates are captured with the inclusion of volatility as a factor in one of the models. The book provides informative case studies for interested students and researchers in the field of financial economics and mathematical finance. It also provides examples that will serve to simplify future research in term structure analysis and reduce its computational inefficiency.
Stochastic Numerical Methods
Title | Stochastic Numerical Methods PDF eBook |
Author | Raúl Toral |
Publisher | John Wiley & Sons |
Total Pages | 518 |
Release | 2014-06-26 |
Genre | Science |
ISBN | 3527683127 |
Stochastic Numerical Methods introduces at Master level the numerical methods that use probability or stochastic concepts to analyze random processes. The book aims at being rather general and is addressed at students of natural sciences (Physics, Chemistry, Mathematics, Biology, etc.) and Engineering, but also social sciences (Economy, Sociology, etc.) where some of the techniques have been used recently to numerically simulate different agent-based models. Examples included in the book range from phase-transitions and critical phenomena, including details of data analysis (extraction of critical exponents, finite-size effects, etc.), to population dynamics, interfacial growth, chemical reactions, etc. Program listings are integrated in the discussion of numerical algorithms to facilitate their understanding. From the contents: Review of Probability Concepts Monte Carlo Integration Generation of Uniform and Non-uniform Random Numbers: Non-correlated Values Dynamical Methods Applications to Statistical Mechanics Introduction to Stochastic Processes Numerical Simulation of Ordinary and Partial Stochastic Differential Equations Introduction to Master Equations Numerical Simulations of Master Equations Hybrid Monte Carlo Generation of n-Dimensional Correlated Gaussian Variables Collective Algorithms for Spin Systems Histogram Extrapolation Multicanonical Simulations