Application of data mining techniques in stock markets: A survey

By Ehsan Hajizadeh, H. D. Ardakani, Jamal Shahrabi. 2010

88 citations recorded by the source corpus.

Subfields: Economics & Operations Research

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Economics & Operations Research

1. A. Ozbayoglu
2. M. Ugur Gudelek
3. Frank Xing
4. Roy E. Welsch
5. Omer Berat Sezer
6. Erik Cambria

Citations in the corpus

• Financial Time Series Forecasting with Deep Learning : A Systematic Literature Review: 2005-2019 (2019, background): “A number of surveys were published for stock market forecasting studies based on various soft computing methods at different times [24, 25, 26, 27, 28, 29, 30, 31].”
• A Comprehensive Comparative Study of Artificial Neural Network (ANN) and Support Vector Machines (SVM) on Stock Forecasting (2021, background): “Forecasting the stock market, currency exchange rate, bank bankruptcies, understanding and managing financial risk, trading futures, credit rating, loan management, bank customer profiling, and money laundering analysis have always been vital financial tasks of Data Mining [30].”
• Natural language based financial forecasting: a survey (2017, methodology): “Consequently, many data mining techniques are applied to historical data to find these patterns [44].”