Testing the predictability of the Cyprus Stock Exchange: The case of an emerging market

被引：4

作者：

Andreou, AS ^{[1
]}

Neocleous, CC ^{[1
]}

Schizas, CN ^{[1
]}

Toumpouris, C ^{[1
]}

机构：

[1] Univ Cyprus, Dept Comp Sci, CY-1678 Nicosia, Cyprus

来源：

IJCNN 2000: PROCEEDINGS OF THE IEEE-INNS-ENNS INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS, VOL VI | 2000年

关键词：

D O I：

10.1109/IJCNN.2000.859422

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

A systematic investigation of the effect of different neural network architecture alternatives for predicting the future course of stock prices in the Cyprus Stock Exchange (CSE) market is conducted. This market exhibited an abrupt increase in the general index price during the last year, thus forming a very interesting case for research purposes. The influence of various economic and political factors, from both the local and the international scene, have also been examined. The main conclusion drawn is that the CSE market is governed by unique conditions which when properly modeled can yield successful predictions.

引用

页码：360 / 365

页数：6

共 11 条

[1]

Azoff E.M., 1994, NEURAL NETWORK TIME

[2] THE BEHAVIOR OF STOCK-MARKET PRICES [J].