A Comparison between Regression, Artificial Neural Networks and Support Vector Machines for Predicting Stock Market Index
Journal Title: International Journal of Advanced Research in Artificial Intelligence(IJARAI) - Year 2015, Vol 4, Issue 7
Abstract
Obtaining accurate prediction of stock index sig-nificantly helps decision maker to take correct actions to develop a better economy. The inability to predict fluctuation of the stock market might cause serious profit loss. The challenge is that we always deal with dynamic market which is influenced by many factors. They include political, financial and reserve occasions. Thus, stable, robust and adaptive approaches which can provide models have the capability to accurately predict stock index are urgently needed. In this paper, we explore the use of Artificial Neural Networks (ANNs) and Support Vector Machines (SVM) to build prediction models for the S&P 500 stock index. We will also show how traditional models such as multiple linear regression (MLR) behave in this case. The developed models will be evaluated and compared based on a number of evaluation criteria.
Authors and Affiliations
Alaa Sheta, Sara Ahmed, Hossam Faris
Keywords
Related Articles
- EP ID EP137759
- DOI 10.14569/IJARAI.2015.040710
- Views 252
- Downloads 0
Highly Accurate Prediction of Jobs Runtime Classes
Separating the short jobs from the long is a known technique to improve scheduling performance. This paper describes a method developed for accurately predicting the runtimes classes of the jobs to enable the separ...
Location Monitoring System with GPS, Zigbee and Wifi Beacon for Rescuing Disable Persons
Location monitoring system for rescue disable persons by switching the location estimation methods with GPS, ZigBee and WiFi beacon is proposed. Rescue system with triage using health condition monitoring together...
NOISE SUPPRESSING EDGE ENHANCEMENT BASED ON GENETIC ALGORITHM TAKING INTO ACCOUNT COMPLEXITY OF TARGET IMAGES MEASURED WITH FRACTAL DIMENSION
Method for noise suppressing edge enhancement based on genetic algorithm taking into account complexity of target images measured with fractal dimension is proposed. Through experiments with satellite remote sensin...
Silent Speech Recognition with Arabic and English Words for Vocally Disabled Persons
This paper presents the results of our research in silent speech recognition (SSR) using Surface Electromyography (sEMG); which is the technology of recording the electric activation potentials of the human articul...
Psychological Status Monitoring with Cerebral Blood Flow: CBF, Electroencephalogram: EEG and Electro-Oculogram: EOG Measurements
Psychological status monitoring with cerebral blood flow (CBF), EEG and EOG measurements are attempted. Through experiments, it is confirmed that the proposed method for psychological status monitoring is valid. It...