Download PDF Numerical Methods in Finance and Economics A MATLAB-Based Introduction Second Edition by Paolo Brandimarte

Sinopsis

Cornnion wisdom would probably associate the ideas of numerical methods aiid number crunching to problems in science and engineering, rather than finance. This irit.uit.ive view is contradicted by the relatively large number of books and scicritific journals devoted to computational finance; even more so, hy thc fact, that, these methods are not confined to academia, but are actually usrd in real life. As a result, there has been a steady increase in the number of academic programs devoted to quantitative finance, both at Master’s and Pt1.D. level, and they usually include a course on numerical methods. Furthermore, riiany people with a quantitative or numerical analysis background have started working in finance, including engineers, mathematicians, and physicists.
 

Indeed, as the tern1 financial engineering may suggest, computational finance is a field where different cultures meet. Hence, a wide array of students and practitioners, with diverse background, will hopefully be interested in a book on riurrirrical methods for finance. On t,he one hand, this is good news for the author. On the other one, the first difficult task is to get evcryonc on coniriion ground as far as financial theory and the basics of numerical aiialysis are concerned; if treatment is too brief, there is a significant risk of losing a considerable subset of readers along the way; if it is too detailed, aiiot,her subset will be considerably bored. The aim of the first three chapters is t,o “synchronize” readers with a background in Finance and readers with it scient.ific background, including students in Engineering, Mathematics, and Physics. In chapter 2, we will give the second subset of readers an overview of coiicept,s in finance, with an emphasis on asset pricing and portfolio management. The first subset of readers will find a reasonably self-contained treatment on classical topics of numerical analysis in chapter 3. 

Content

1. Motivation
2. Financial Theory
3. Basics of Numerical Analysis
4. Numerical Integration: Deterministic and Monte Carlo Methods
5. Finite Diflerence Methods for Partial Digerential Equations
6. Convex Optimization
7. Option Pricing by Binomial and Thnomial Lattices
8. Option Pricing by Monte Carlo Methods
9. Option Pricing by Finite Diflerence Methods
10. Dynamic Programming
11. Linear Stochastic Programming Models with Recourse
12. Non- Convex Optimization

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