Financial Engineering and Computation

Financial Engineering and Computation
Author: Yuh-Dauh Lyuu
Publisher: Cambridge University Press
Total Pages: 654
Release: 2002
Genre: Business & Economics
ISBN: 9780521781718

A comprehensive text and reference, first published in 2002, on the theory of financial engineering with numerous algorithms for pricing, risk management, and portfolio management.

Computational Finance

Computational Finance
Author: Argimiro Arratia
Publisher: Springer Science & Business Media
Total Pages: 305
Release: 2014-05-08
Genre: Computers
ISBN: 9462390703

The book covers a wide range of topics, yet essential, in Computational Finance (CF), understood as a mix of Finance, Computational Statistics, and Mathematics of Finance. In that regard it is unique in its kind, for it touches upon the basic principles of all three main components of CF, with hands-on examples for programming models in R. Thus, the first chapter gives an introduction to the Principles of Corporate Finance: the markets of stock and options, valuation and economic theory, framed within Computation and Information Theory (e.g. the famous Efficient Market Hypothesis is stated in terms of computational complexity, a new perspective). Chapters 2 and 3 give the necessary tools of Statistics for analyzing financial time series, it also goes in depth into the concepts of correlation, causality and clustering. Chapters 4 and 5 review the most important discrete and continuous models for financial time series. Each model is provided with an example program in R. Chapter 6 covers the essentials of Technical Analysis (TA) and Fundamental Analysis. This chapter is suitable for people outside academics and into the world of financial investments, as a primer in the methods of charting and analysis of value for stocks, as it is done in the financial industry. Moreover, a mathematical foundation to the seemly ad-hoc methods of TA is given, and this is new in a presentation of TA. Chapter 7 reviews the most important heuristics for optimization: simulated annealing, genetic programming, and ant colonies (swarm intelligence) which is material to feed the computer savvy readers. Chapter 8 gives the basic principles of portfolio management, through the mean-variance model, and optimization under different constraints which is a topic of current research in computation, due to its complexity. One important aspect of this chapter is that it teaches how to use the powerful tools for portfolio analysis from the RMetrics R-package. Chapter 9 is a natural continuation of chapter 8 into the new area of research of online portfolio selection. The basic model of the universal portfolio of Cover and approximate methods to compute are also described.

Practical Applications of Evolutionary Computation to Financial Engineering

Practical Applications of Evolutionary Computation to Financial Engineering
Author: Hitoshi Iba
Publisher: Springer Science & Business Media
Total Pages: 253
Release: 2012-02-15
Genre: Technology & Engineering
ISBN: 3642276482

“Practical Applications of Evolutionary Computation to Financial Engineering” presents the state of the art techniques in Financial Engineering using recent results in Machine Learning and Evolutionary Computation. This book bridges the gap between academics in computer science and traders and explains the basic ideas of the proposed systems and the financial problems in ways that can be understood by readers without previous knowledge on either of the fields. To cement the ideas discussed in the book, software packages are offered that implement the systems described within. The book is structured so that each chapter can be read independently from the others. Chapters 1 and 2 describe evolutionary computation. The third chapter is an introduction to financial engineering problems for readers who are unfamiliar with this area. The following chapters each deal, in turn, with a different problem in the financial engineering field describing each problem in detail and focusing on solutions based on evolutionary computation. Finally, the two appendixes describe software packages that implement the solutions discussed in this book, including installation manuals and parameter explanations.

Mathematical Modeling And Computation In Finance: With Exercises And Python And Matlab Computer Codes

Mathematical Modeling And Computation In Finance: With Exercises And Python And Matlab Computer Codes
Author: Cornelis W Oosterlee
Publisher: World Scientific
Total Pages: 1310
Release: 2019-10-29
Genre: Business & Economics
ISBN: 1786347962

This book discusses the interplay of stochastics (applied probability theory) and numerical analysis in the field of quantitative finance. The stochastic models, numerical valuation techniques, computational aspects, financial products, and risk management applications presented will enable readers to progress in the challenging field of computational finance.When the behavior of financial market participants changes, the corresponding stochastic mathematical models describing the prices may also change. Financial regulation may play a role in such changes too. The book thus presents several models for stock prices, interest rates as well as foreign-exchange rates, with increasing complexity across the chapters. As is said in the industry, 'do not fall in love with your favorite model.' The book covers equity models before moving to short-rate and other interest rate models. We cast these models for interest rate into the Heath-Jarrow-Morton framework, show relations between the different models, and explain a few interest rate products and their pricing.The chapters are accompanied by exercises. Students can access solutions to selected exercises, while complete solutions are made available to instructors. The MATLAB and Python computer codes used for most tables and figures in the book are made available for both print and e-book users. This book will be useful for people working in the financial industry, for those aiming to work there one day, and for anyone interested in quantitative finance. The topics that are discussed are relevant for MSc and PhD students, academic researchers, and for quants in the financial industry.Supplementary Material:Solutions Manual is available to instructors who adopt this textbook for their courses. Please contact [email protected].

Elementary Calculus of Financial Mathematics

Elementary Calculus of Financial Mathematics
Author: A. J. Roberts
Publisher: SIAM
Total Pages: 143
Release: 2009-01-01
Genre: Mathematics
ISBN: 0898718228

Financial mathematics and its calculus introduced in an accessible manner for undergraduate students. Topics covered include financial indices as stochastic processes, Ito's stochastic calculus, the Fokker-Planck Equation and extra MATLAB/SCILAB code.

An Introduction to Financial Option Valuation

An Introduction to Financial Option Valuation
Author: Desmond J. Higham
Publisher: Cambridge University Press
Total Pages: 300
Release: 2004-04-15
Genre: Mathematics
ISBN: 1139457896

This is a lively textbook providing a solid introduction to financial option valuation for undergraduate students armed with a working knowledge of a first year calculus. Written in a series of short chapters, its self-contained treatment gives equal weight to applied mathematics, stochastics and computational algorithms. No prior background in probability, statistics or numerical analysis is required. Detailed derivations of both the basic asset price model and the Black–Scholes equation are provided along with a presentation of appropriate computational techniques including binomial, finite differences and in particular, variance reduction techniques for the Monte Carlo method. Each chapter comes complete with accompanying stand-alone MATLAB code listing to illustrate a key idea. Furthermore, the author has made heavy use of figures and examples, and has included computations based on real stock market data.

Computational Methods in Finance

Computational Methods in Finance
Author: Ali Hirsa
Publisher: CRC Press
Total Pages: 440
Release: 2016-04-19
Genre: Business & Economics
ISBN: 1466576049

Helping readers accurately price a vast array of derivatives, this self-contained text explains how to solve complex functional equations through numerical methods. It addresses key computational methods in finance, including transform techniques, the finite difference method, and Monte Carlo simulation. Developed from his courses at Columbia University and the Courant Institute of New York University, the author also covers model calibration and optimization and describes techniques, such as Kalman and particle filters, for parameter estimation.

Machine Learning for Financial Engineering

Machine Learning for Financial Engineering
Author: György Ottucsák
Publisher: World Scientific
Total Pages: 261
Release: 2012
Genre: Business & Economics
ISBN: 1848168136

Preface v 1 On the History of the Growth-Optimal Portfolio M.M. Christensen 1 2 Empirical Log-Optimal Portfolio Selections: A Survey L. Györfi Gy. Ottucsáak A. Urbán 81 3 Log-Optimal Portfolio-Selection Strategies with Proportional Transaction Costs L. Györfi H. Walk 119 4 Growth-Optimal Portfoho Selection with Short Selling and Leverage M. Horváth A. Urbán 153 5 Nonparametric Sequential Prediction of Stationary Time Series L. Györfi Gy. Ottucsák 179 6 Empirical Pricing American Put Options L. Györfi A. Telcs 227 Index 249.

A Course in Derivative Securities

A Course in Derivative Securities
Author: Kerry Back
Publisher: Springer Science & Business Media
Total Pages: 358
Release: 2005-10-11
Genre: Business & Economics
ISBN: 3540279008

"Deals with pricing and hedging financial derivatives.... Computational methods are introduced and the text contains the Excel VBA routines corresponding to the formulas and procedures described in the book. This is valuable since computer simulation can help readers understand the theory....The book...succeeds in presenting intuitively advanced derivative modelling... it provides a useful bridge between introductory books and the more advanced literature." --MATHEMATICAL REVIEWS