Application of neuro-fuzzy methods for stock market forecasting: a systematic review

Abstract

Predicting stock prices is a challenging task owing to the market's chaos and uncertainty. Methods based on traditional approaches are unable to provide a solution to the market predictability issue. Thus, contemporary models using accurate neuro-fuzzy systems are found to be the most effective approach to tackling the problem. However, the existing literature lacks a detailed survey of the application of neuro-fuzzy techniques for stock market prediction. This paper presents a systematic literature review of the use of neuro-fuzzy systems for predicting stock market prices and trends.  On this basis, articles issued in various reputed international journals from 2000 to July 2022 were examined, 11 duplicates and 4 non-exclusive articles were removed and, as consequent, 24 eligible studies were retrieved for inclusion. Thus, analysis and discussions were based on two major viewpoints: predictor techniques and accuracy metrics. The review reveals that the researchers, based on their knowledge and research interests, applied a diverse neuro-fuzzy technique and shown stronger preference for certain neuro-fuzzy methods, such as ANFIS. To draw conclusions about the model performance, researchers chose different statistical and non-statistical metrics according to the technique used. It was finally observed that neuro-fuzzy approaches outperform, within its limits, conventional methods. However, each has its own set of constraints regarding the challenges involved in putting it into practice. The complexity of the presented approaches is the most significant potential obstacle that they face. Therefore, stock market prediction is a difficult undertaking, and multiple elements should be considered for accurate prediction. Yet, despite the subject's prominence, there are still promising new frontiers to explore and develop.

Keywords: Fuzzy logic, Artificial neural network, Neuro-fuzzy, stock market forecasting

JEL Classification: F37

Paper type: Theoretical Research