Computational Finance: An Introductory Course with R

✍ Scribed by Argimiro Arratia (auth.)

• Publisher: Atlantis Press
• Year: 2014
• Tongue: English
• Leaves: 305
• Series: Atlantis Studies in Computational Finance and Financial Engineering 1
• Edition: 1
• Category: Library

✦ Synopsis

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.

✦ Table of Contents

Front Matter....Pages i-x
An Abridged Introduction to Finance....Pages 1-36
Statistics of Financial Time Series....Pages 37-70
Correlations, Causalities and Similarities....Pages 71-107
Time Series Models in Finance....Pages 109-143
Brownian Motion, Binomial Trees and Monte Carlo Simulation....Pages 145-175
Trade on Pattern Mining or Value Estimation....Pages 177-206
Optimization Heuristics in Finance....Pages 207-237
Portfolio Optimization....Pages 239-265
Online Finance....Pages 267-282
Back Matter....Pages 283-301

✦ Subjects

Simulation and Modeling; Statistics for Business/Economics/Mathematical Finance/Insurance; Quantitative Finance; Financial Economics; Statistics and Computing/Statistics Programs