# Forecasting Stock Market with Support Vector Regression and Butterfly Optimization Algorithm

arXiv: https://arxiv.org/abs/1905.11462 · HTML: https://mlsanity.com/paper/1905.11462/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 27 May 2019.

## Built on by (most cited first, 1 of 1)

- [Support Vector Regression Parameters Optimization using Golden Sine Algorithm and its application in stock market](https://mlsanity.com/paper/2103.11459/) (2021)

## Abstract (arXiv)

Support Vector Regression (SVR) has achieved high performance on forecasting future behavior of random systems. However, the performance of SVR models highly depends upon the appropriate choice of SVR parameters. In this study, a novel BOA-SVR model based on Butterfly Optimization Algorithm (BOA) is presented. The performance of the proposed model is compared with eleven other meta-heuristic algorithms on a number of stocks from NASDAQ. The results indicate that the presented model here is capable to optimize the SVR parameters very well and indeed is one of the best models judged by both prediction performance accuracy and time consumption.