Book contents
- Frontmatter
- Contents
- Preface
- List of abbreviations
- 1 Determination of the accurate location of an aircraft
- 2 When to replace equipment
- 3 Secondary structure prediction using least squares and singular value decomposition
- 4 Secondary structure prediction using least squares and best basis
- 5 Secondary structure prediction with learning methods (nearest neighbors)
- 6 Secondary structure prediction with linear programming (LP)
- 7 Stock market prediction
- 8 Phylogenetic tree construction
- Appendix A Methods for function minimization
- Appendix B Online resources
- Index
7 - Stock market prediction
Published online by Cambridge University Press: 17 February 2011
- Frontmatter
- Contents
- Preface
- List of abbreviations
- 1 Determination of the accurate location of an aircraft
- 2 When to replace equipment
- 3 Secondary structure prediction using least squares and singular value decomposition
- 4 Secondary structure prediction using least squares and best basis
- 5 Secondary structure prediction with learning methods (nearest neighbors)
- 6 Secondary structure prediction with linear programming (LP)
- 7 Stock market prediction
- 8 Phylogenetic tree construction
- Appendix A Methods for function minimization
- Appendix B Online resources
- Index
Summary
Topics
Dynamic programming
Optimization of decision-based functionals
Simulation: modelling, validation, prediction
Introduction
BASIC Stock market prediction is a very interesting topic and could also be very profitable if done successfully. It falls well within our definition of modelling/prediction. We define “stock market prediction” as the techniques which extract information from past behavior to decide when to buy or sell which stock and at what price. This is called quantitative analysis or technical analysis, i.e. the use of mathematics to predict future behavior based on historical data. It is normally contrasted with fundamental analysis which analyses the health of the business in a very broad sense to predict the future behavior of stock prices.
There are several reasons which make technical analysis a very good topic for the study of methods in modelling and prediction.
(i) The problem is simple and easy to define precisely.
(ii) All the main concepts of modelling/prediction appear in this problem.
(iii) There are abundant data – most publicly available through the World Wide Web.
(iv) New data are generated every day, which allows extensive and realistic validation.
Please note that the goal of this chapter is to illustrate methods in modelling and simulation. It is not a complete or up-to-date treatise on stock market prediction.
Definitions
We are going to use only buying/selling of regular stock and avoid more sophisticated tools such as options, futures etc. A few definitions are necessary to clarify the concepts.
- Type
- Chapter
- Information
- Scientific Computation , pp. 96 - 138Publisher: Cambridge University PressPrint publication year: 2009
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