Computational Finance

An Introductory Course with R

  • Argimiro Arratia

Part of the Atlantis Studies in Computational Finance and Financial Engineering book series (ASCFFE, volume 1)

Table of contents

  1. Front Matter
    Pages i-x
  2. Argimiro Arratia
    Pages 1-36
  3. Argimiro Arratia
    Pages 37-70
  4. Argimiro Arratia
    Pages 71-107
  5. Argimiro Arratia
    Pages 109-143
  6. Argimiro Arratia
    Pages 177-206
  7. Argimiro Arratia
    Pages 207-237
  8. Argimiro Arratia
    Pages 239-265
  9. Argimiro Arratia
    Pages 267-282
  10. Back Matter
    Pages 283-301

About this book

Introduction

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.

Keywords

computational finance optimization heuristics portfolio optimization statistical computing time series analysis

Authors and affiliations

  • Argimiro Arratia
    • 1
  1. 1.Department of Computer ScienceUniversitat Politécnica de CatalunyaBarcelonaSpain

Bibliographic information

  • DOI https://doi.org/10.2991/978-94-6239-070-6
  • Copyright Information Atlantis Press and the authors 2014
  • Publisher Name Atlantis Press, Paris
  • eBook Packages Computer Science
  • Print ISBN 978-94-6239-069-0
  • Online ISBN 978-94-6239-070-6
  • Series Print ISSN 2352-3255
  • Series Online ISSN 2352-3115
  • About this book
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