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akaturk Academic measurement

Article detail · 2017

The Prediction of Precious Metal Prices via Artificial Neural Network by Using RapidMiner

Journal

Alphanumeric Journal

ISSN 2148-2225

YÖKSİS OpenAlex Open access · diamond TR Index Citations 48 Percentile 86.6% FWCI 1.88
Year
2017
Type
article

Data source split

  • YÖKSİS YÖKSİS article record
  • YÖKSİS venue Alphanumeric Journal
  • OpenAlex OpenAlex enrichment (abstract, citations, topics)

Abstract

English (OpenAlex)

In this paper, an Artificial Neural Network study has been implemented to forecast the prediction of precious metals such as gold, silver, platinum and palladium prices by using RapidMiner data mining software. The five performance measures; root mean squared error, absolute error, relative error, Spearman's Rho and Kendall’s Tau are utilized to evaluate artificial neural network model. This study concentrates on data which includes gold, silver, palladium, platinum, Brent Petrol, natural gas prices, 30 years’ bond, 10 years’ bond, 5 years’ bond, S&P 500, Nasdaq, Dow Jones, FTSE100, DAX, CAC40, SMI, NIKKEI, HANH, SENG and Euro/USD within the period of 4th of January 2010 to 14th of December 2015. The prices on the last quarter of 2015 is used for forecasting and validation. The results show that error rates are accurate in order to foresee the market trends.

Topics

  • Forecasting Techniques and Applications
  • Market Dynamics and Volatility
  • Stock Market Forecasting Methods

Primary topic Forecasting Techniques and Applications

Authors

  1. UFUK ÇELİK BANDIRMA ONYEDİ EYLÜL ÜNİVERSİTESİ
  2. ÇAĞATAY BAŞARIR BANDIRMA ONYEDİ EYLÜL ÜNİVERSİTESİ