Natural Computing in Computational Finance
@inproceedings{Brabazon2008NaturalCI, title={Natural Computing in Computational Finance}, author={Anthony Brabazon and Michael O’Neill}, booktitle={Natural Computing in Computational Finance}, year={2008} }
Natural Computing in Computational Finance is a innovative volume containing fifteen chapters which illustrate cutting-edge applications of natural computing or agent-based modeling in modern computational finance. Following an introductory chapter the book is organized into three sections. The first section deals with optimization applications of natural computing demonstrating the application of a broad range of algorithms including, genetic algorithms, differential evolution, evolution…
70 Citations
Natural Computing in Computational Finance (Volume 2): Introduction
- Economics
- 2009
The scale of NC applications in finance is illustrated by Chen & Kuo who list nearly 400 papers that had been published by 2001 on the use of evolutionary computation alone in computational economics and finance.
A Stock Market Decision Support System with a Hybrid Evolutionary Algorithm for Many-Core Graphics Processors
- Computer ScienceEuro-Par Workshops
- 2010
This paper proposes a computational intelligence approach to stock market decision support systems based on a hybrid evolutionary algorithm with local search for many-core graphics processors, which outperforms the classic approach in terms of the financial relevance of the investment strategies discovered as well as of the computing time.
Natural Computing in Computational Finance (Volume 4): Introduction
- Computer ScienceNatural Computing in Computational Finance
- 2012
The inspiration for natural computing methodologies typically stem from real-world phenomena which exist in high-dimensional, dynamic, environments characteristics which fit well with the nature of financial markets.
Quantum-Inspired Evolutionary Algorithms for Financial Data Analysis
- Computer ScienceEvoWorkshops
- 2008
The QIEA is described, a new computational approach which bears similarity with estimation of distribution algorithms (EDAs) which is applied to a finance problem, namely non-linear principal component analysis of implied volatilities.
Parallel Evolutionary Algorithms for Stock Market Trading Rule Selection on Many-Core Graphics Processors
- Computer ScienceNatural Computing in Computational Finance
- 2012
This chapter concerns stock market decision support systems that build trading expertise on the basis of a set of specific trading rules, analysing financial time series of recent stock price quotations, and proposes an improvement of two popular evolutionary algorithms for rule selection by reinforcing them with two local search operators.
Practical applications of evolutionary computation to financial engineering: robust techniques for forecasting, trading, and hedging (iba, h. and aranha, c.c.; 2012)[book review]
- Computer ScienceIEEE Computational Intelligence Magazine
- 2012
This book presents a systematic framework for a few significant problems in financial engineering with some evolutionary approaches to them and should be comprehensible not only for computer scientists interested in some applications, but also for financial experts or even market traders interested in advanced methods of automated trading and new tools for market analysis.
Robust optimization of algorithmic trading systems
- Computer Science
- 2017
This thesis concludes that Evolutionary Computation techniques such as GA and GP combined with robust optimization methods are very suitable for developing trading systems, and that the systems developed using these techniques can be used to provide significant economic profits in all market conditions.
A comparative study of the canonical genetic algorithm and a real-valued quantum-inspired evolutionary algorithm
- Computer ScienceInt. J. Intell. Comput. Cybern.
- 2009
The results show that the QIEA obtains highly competitive results when benchmarked against the GA within static environments, while substantially outperforming both binary and real‐valued representation of the GA in terms of running time.
A Neuro-evolutionary Approach to Intraday Financial Modeling
- Computer ScienceEvoApplications
- 2012
It is shown that it is possible to obtain extremely accurate models of the variations of the price of one stock based on the prices of the other components of the stock list, which may be used for statistical arbitrage.
Generating Directional Change Based Trading Strategies with Genetic Programming
- BusinessEvoApplications
- 2015
An alternative and novel approach is explored to use an intrinsic time scale based on Directional Changes combined with Genetic Programming to find an optimal trading strategy to forecast the future price moves of a financial market.
References
SHOWING 1-10 OF 13 REFERENCES
Portfolio management with heuristic optimization
- Economics
- 2005
Portfolio Management with Heuristic Optimization consist of two parts. The first part (Foundations) deals with the foundations of portfolio optimization, its assumptions, approaches and the…
Differential Evolution: A Practical Approach to Global Optimization (Natural Computing Series)
- Computer Science
- 2005
This volume explores the differential evolution (DE) algorithm in both principle and practice and is a valuable resource for professionals needing a proven optimizer and for students wanting an evolutionary perspective on global numerical optimization.
Index tracking with constrained portfolios
- EconomicsIntell. Syst. Account. Finance Manag.
- 2007
It is found that the index can be tracked satisfactorily with a subset of its components and, more important, that the deviation between computed actual tracking error and the theoretically achievable tracking error out of sample is negligibly affected by the portfolio's cardinality.
The Performance of Mutual Funds in the Period 1945-1964
- Economics
- 1967
In this paper I derive a risk-adjusted measure of portfolio performance (now known as Jensen's Alpha) that estimates how much a manager's forecasting ability contributes to the fund's returns. The…
Prospect Theory: Much Ado About Nothing?
- EconomicsManag. Sci.
- 2002
This work conducts an experimental study with mixed prospects, using, for the first time, recently developed investment criteria called Prospect Stochastic Dominance (PSD) and MarkowitzStochasticDominance (MSD), and rejects the S-shaped value function, showing that at least 62%--76% of the subjects cannot be characterized by such preferences.
The Index Tracking Strategies of Passive and Enhanced Index Equity Funds
- Economics
- 2003
This study represents the first empirical examination of the daily trading and portfolio configuration strategies of index and enhanced index equity funds. We document that passive funds benefit from…
The Persistence of Risk-Adjusted Mutual Fund Performance
- Economics
- 1995
The authors examine predictability for stock mutual funds using risk-adjusted returns. They find that past performance is predictive of future risk-adjusted performance. Applying modern portfolio…
Differential Evolution – A Simple and Efficient Heuristic for global Optimization over Continuous Spaces
- Computer ScienceJ. Glob. Optim.
- 1997
It is demonstrated that the new heuristic approach for minimizing possibly nonlinear and non-differentiable continuous spacefunctions Converges faster and with more certainty than manyother acclaimed global optimization methods.
A Mean/Variance Analysis of Tracking Error
- Business
- 1992
Investment managers are often hired to produce positive return performance over a benchmark index while keeping tracking error volatility to a minimum. This article provides the exact composition of…