Titlebook: Natural Computing in Computational Finance; Volume 4 Anthony Brabazon,Michael O’Neill,Dietmar Maringer Book 2012 Springer-Verlag GmbH Berli

Decimate

Michael Kampouridis,Shu-Heng Chen,Edward Tsang documented parameters, Oracle10g Release 2 has 258, and Oracle11g Release 1 has 294. Presumably there is no single DBA who has memorized the meanings and permissible values for all those parameters. The . manual of each respective release is the definitive source for documented initialization param

使坚硬

low themselves to be led by the nose with their eyes open’ (1945: 28). This view casts the reader as a dupe, a willing player who falls victim to the author’s literary foils and deceptions. However, readers and reading are not easily reduced to such a simplistic equation. An essential element of the

MINT

组成

Calibrating Option Pricing Models with Heuristics,annot be applied.We investigate two models: Heston’s stochastic volatility model, and Bates’s model which also includes jumps. We discuss how to price options under these models, and how to calibrate the parameters of the models with heuristic techniques.

构想

A Comparison between Nature-Inspired and Machine Learning Approaches to Detecting Trend Reversals ification approaches on such a problem. Nature-Inspired methodologies are attracting growing interest due to their ability to cope with complex tasks like classification, forecasting, and anomaly detection problems. A swarm intelligence algorithm, namely Particle Swarm Optimization (PSO), and an arti

Deadpan

A Soft Computing Approach to Enhanced Indexation,nts. It is based on a combination of soft computing techniques for dealing with practical and computation aspects of this problem. We deviate from the main trend in enhanced indexation by considering a) restrictions on the total number of tradable assets and b) non-standard investment objectives, fo

强制性

Parallel Evolutionary Algorithms for Stock Market Trading Rule Selection on Many-Core Graphics Procnancial time series of recent stock price quotations, and focusses on the process of rule selection. It proposes an improvement of two popular evolutionary algorithms for rule selection by reinforcing them with two local search operators. The algorithms are also adapted for parallel processing on ma

Neuropeptides

和谐

An Evolutionary Algorithmic Investigation of US Corporate Payout Policy Determination,classical statistical methodologies have been adopted, foremost among these is the method of panel regression modelling. Instead, in this Chapter, we have informed our model specifications and our coefficient estimates using a genetic program. Our model captures effects from a wide range of pertinen

curettage

Tackling Overfitting in Evolutionary-Driven Financial Model Induction,finance where we seek to learn or induce a model from data. Models that overfit the data upon which they are trained prevent model generalisation, which is an important goal of learning algorithms..Early stopping is a technique that is frequently used to counteract overfitting, but this technique of