Articlegold2019

Stock Market Analysis: A Review and Taxonomy of Prediction Techniques

Dev Shah · Haruna Isah · Farhana H. Zulkernine

465 citations0/0 files storedInternational Journal of Financial Studies

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Stock Market Forecasting Methods Financial Markets and Investment Strategies Forecasting Techniques and Applications

Abstract

Stock market prediction has always caught the attention of many analysts and researchers. Popular theories suggest that stock markets are essentially a random walk and it is a fool’s game to try and predict them. Predicting stock prices is a challenging problem in itself because of the number of variables which are involved. In the short term, the market behaves like a voting machine but in the longer term, it acts like a weighing machine and hence there is scope for predicting the market movements for a longer timeframe. Application of machine learning techniques and other algorithms for stock price analysis and forecasting is an area that shows great promise. In this paper, we first provide a concise review of stock markets and taxonomy of stock market prediction methods. We then focus on some of the research achievements in stock analysis and prediction. We discuss technical, fundamental, short- and long-term approaches used for stock analysis. Finally, we present some challenges and research opportunities in this field.

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References

1970Efficient Capital Markets: A Review of Theory and Empirical Work 2011Twitter mood predicts the stock market 1980Do Stock Prices Move Too Much to be Justified by Subsequent Changes in Dividends?2000Irrational Exuberance 1959Dividends, Earnings, and Stock Prices 1995Random Walks in Stock Market Prices 2014Stock Price Prediction Using the ARIMA Model 2017A deep learning framework for financial time series using stacked autoencoders and long-short term memory

Cited by

2020Deep Learning for Stock Market Prediction 2023Stock price prediction with optimized deep LSTM network with artificial rabbits optimization algorithm 2021Prediction of stock price direction using a hybrid GA-XGBoost algorithm with a three-stage feature engineering process 2021Stock Market Prediction Using Machine Learning Techniques: A Decade Survey on Methodologies, Recent Developments, and Future Directions 2020Deep learning and time series-to-image encoding for financial forecasting 2023Forecasting Stock Market Prices Using Machine Learning and Deep Learning Models: A Systematic Review, Performance Analysis and Discussion of Implications

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