Forecasting the Direction of BIST 100 Returns with Artificial Neural Network Models

Tolga Genc, Semin Paksoy, S. Kiliç
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引用次数: 3

Abstract

In this paper, Artificial Neural Networks (ANN) models are used to forecast the direction of Borsa Istanbul 100 (BIST100) index returns. Weekly time-lagged values of exchange returns, gold price returns and interest rate returns are used as input to ANN models in the training process. Results of the study showed that BIST100 index returns follow a specific pattern in time. Estimated ANN models provide valuable information to the investors and that BIST100 stock market is not fully informational efficient.
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用人工神经网络模型预测BIST 100收益方向
本文采用人工神经网络(ANN)模型对伊斯坦布尔指数(Borsa Istanbul 100)的收益方向进行预测。在训练过程中,每周的交换回报、黄金价格回报和利率回报的滞后值被用作人工神经网络模型的输入。研究结果表明,BIST100指数的收益在时间上具有一定的规律。估计的人工神经网络模型为投资者提供了有价值的信息,并且BIST100股票市场不是完全信息有效的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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