Financial time series forecasting with deep learning: A systematic literature review: 2005–2019
Financial time series forecasting is undoubtedly the top choice of computational intelligence
for finance researchers in both academia and the finance industry due to its broad …
for finance researchers in both academia and the finance industry due to its broad …
Deep learning for financial applications: A survey
Computational intelligence in finance has been a very popular topic for both academia and
financial industry in the last few decades. Numerous studies have been published resulting …
financial industry in the last few decades. Numerous studies have been published resulting …
[HTML][HTML] Contemporary symbolic regression methods and their relative performance
Many promising approaches to symbolic regression have been presented in recent years,
yet progress in the field continues to suffer from a lack of uniform, robust, and transparent …
yet progress in the field continues to suffer from a lack of uniform, robust, and transparent …
To explain or to predict?
G Shmueli - 2010 - projecteuclid.org
Statistical modeling is a powerful tool for develo** and testing theories by way of causal
explanation, prediction, and description. In many disciplines there is near-exclusive use of …
explanation, prediction, and description. In many disciplines there is near-exclusive use of …
Riccardo Poli, William B. Langdon, Nicholas F. McPhee: A Field Guide to Genetic Programming: Lulu. com, 2008, 250 pp, ISBN 978-1-4092-0073-4
M O'Neill - 2009 - Springer
The latest book on Genetic Programming, Poli, Langdon and McPhee's (with contributions
from John R. Koza) A Field Guide to Genetic Programming represents an exciting landmark …
from John R. Koza) A Field Guide to Genetic Programming represents an exciting landmark …
Artificial neural networks architectures for stock price prediction: Comparisons and applications
L Di Persio, O Honchar - International journal of circuits, systems and …, 2016 - iris.univr.it
Abstract We present an Artificial Neural Network (ANN) approach to predict stock market
indices, particularly with respect to the forecast of their trend movements up or down …
indices, particularly with respect to the forecast of their trend movements up or down …
Forecasting stock markets using wavelet transforms and recurrent neural networks: An integrated system based on artificial bee colony algorithm
TJ Hsieh, HF Hsiao, WC Yeh - Applied soft computing, 2011 - Elsevier
This study presents an integrated system where wavelet transforms and recurrent neural
network (RNN) based on artificial bee colony (abc) algorithm (called ABC-RNN) are …
network (RNN) based on artificial bee colony (abc) algorithm (called ABC-RNN) are …
Intelligent and robust prediction of short term wind power using genetic programming based ensemble of neural networks
The inherent instability of wind power production leads to critical problems for smooth power
generation from wind turbines, which then requires an accurate forecast of wind power. In …
generation from wind turbines, which then requires an accurate forecast of wind power. In …
[ΒΙΒΛΙΟ][B] Tools for computational finance
R Seydel, R Seydel - 2006 - Springer
Universitext is a series of textbooks that presents material from a wide variety of
mathematical disciplines at master's level and beyond. The books, often well class-tested by …
mathematical disciplines at master's level and beyond. The books, often well class-tested by …
Using a genetic algorithm to optimize an expert credit rating model
In this article, we show how an “expert” credit rating model can be optimized through the use
of a genetic algorithm, a way of combining expert intelligence with artificial intelligence. This …
of a genetic algorithm, a way of combining expert intelligence with artificial intelligence. This …