# Machine learning approaches in stock market prediction: A systematic literature review

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/machine-learning-approaches-in-stock-market-prediction-a-systematic-literature/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Latrisha N. Mintarya,Jeta N.M. Halim,Callista Angie,Said Achmad,Aditya Kurniawan |
| Citations | 166 |
| DOI | 10.1016/j.procs.2022.12.115 |
| Fields | Decision Sciences,Engineering |
| Open Access | true |
| OA Status | diamond |
| OA URL | https://doi.org/10.1016/j.procs.2022.12.115 |
| OpenAlex ID | https://openalex.org/W4313886477 |
| Type | review |
| Year | 2023 |

## Paper authors

- [Said Achmad](https://scholariq.org/researchers/said-achmad/)

## Paper journal

- [Procedia Computer Science](https://scholariq.org/journals/procedia-computer-science/)

## Paper primary topic

- [Stock Market Forecasting Methods](https://scholariq.org/topics/stock-market-forecasting-methods/)

## Paper topics

- [Stock Market Forecasting Methods](https://scholariq.org/topics/stock-market-forecasting-methods/)
- [Forecasting Techniques and Applications](https://scholariq.org/topics/forecasting-techniques-and-applications/)
- [Energy Load and Power Forecasting](https://scholariq.org/topics/energy-load-and-power-forecasting/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.