Stock market forecasting using computational intelligence: A survey
Stock market plays a key role in economical and social organization of a country. Stock
market forecasting is highly demanding and most challenging task for investors, professional …
market forecasting is highly demanding and most challenging task for investors, professional …
Application of evolutionary computation for rule discovery in stock algorithmic trading: A literature review
Despite the wide application of evolutionary computation (EC) techniques to rule discovery
in stock algorithmic trading (AT), a comprehensive literature review on this topic is …
in stock algorithmic trading (AT), a comprehensive literature review on this topic is …
Survey of stock market prediction using machine learning approach
Stock market is basically nonlinear in nature and the research on stock market is one of the
most important issues in recent years. People invest in stock market based on some …
most important issues in recent years. People invest in stock market based on some …
Support vector regression with chaos-based firefly algorithm for stock market price forecasting
Due to the inherent non-linearity and non-stationary characteristics of financial stock market
price time series, conventional modeling techniques such as the Box–Jenkins …
price time series, conventional modeling techniques such as the Box–Jenkins …
A highly accurate firefly based algorithm for heart disease prediction
Abstracts This paper proposes a heart disease diagnosis system using rough sets based
attribute reduction and interval type-2 fuzzy logic system (IT2FLS). The integration between …
attribute reduction and interval type-2 fuzzy logic system (IT2FLS). The integration between …
Combining multiple feature selection methods for stock prediction: Union, intersection, and multi-intersection approaches
CF Tsai, YC Hsiao - Decision support systems, 2010 - Elsevier
To effectively predict stock price for investors is a very important research problem. In
literature, data mining techniques have been applied to stock (market) prediction. Feature …
literature, data mining techniques have been applied to stock (market) prediction. Feature …
A bat-neural network multi-agent system (BNNMAS) for stock price prediction: Case study of DAX stock price
Creating an intelligent system that can accurately predict stock price in a robust way has
always been a subject of great interest for many investors and financial analysts. Predicting …
always been a subject of great interest for many investors and financial analysts. Predicting …
A multiple-kernel support vector regression approach for stock market price forecasting
CY Yeh, CW Huang, SJ Lee - Expert Systems with Applications, 2011 - Elsevier
Support vector regression has been applied to stock market forecasting problems. However,
it is usually needed to tune manually the hyperparameters of the kernel functions. Multiple …
it is usually needed to tune manually the hyperparameters of the kernel functions. Multiple …
Analysis of decision making factors for equity investment by DEMATEL and Analytic Network Process
WS Lee, AYH Huang, YY Chang, CM Cheng - Expert Systems with …, 2011 - Elsevier
Existing methodologies of equity investment, such as fundamental analysis, technical
analysis, and institutional investor analysis, explore important factors of stock price …
analysis, and institutional investor analysis, explore important factors of stock price …
A hybrid modeling approach for forecasting the volatility of S&P 500 index return
Forecasting volatility is an essential step in many financial decision makings. GARCH family
of models has been extensively used in finance and economics, particularly for estimating …
of models has been extensively used in finance and economics, particularly for estimating …