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Bibliographic Details
Main Author: Rahman, Abdul
Format: Preprint
Published: 2024
Subjects:
Online Access:https://arxiv.org/abs/2405.14262
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author Rahman, Abdul
author_facet Rahman, Abdul
contents This paper investigates the potential of Bayesian optimization (BO) to optimize the atr multiplier and atr period -the parameters of the Supertrend indicator for maximizing trading profits across diverse stock datasets. By employing BO, the thesis aims to automate the identification of optimal parameter settings, leading to a more data-driven and potentially more profitable trading strategy compared to relying on manually chosen parameters. The effectiveness of the BO-optimized Supertrend strategy will be evaluated through backtesting on a variety of stock datasets.
format Preprint
id arxiv_https___arxiv_org_abs_2405_14262
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Unlocking Profit Potential: Maximizing Returns with Bayesian Optimization of Supertrend Indicator Parameters
Rahman, Abdul
Trading and Market Microstructure
Statistical Finance
This paper investigates the potential of Bayesian optimization (BO) to optimize the atr multiplier and atr period -the parameters of the Supertrend indicator for maximizing trading profits across diverse stock datasets. By employing BO, the thesis aims to automate the identification of optimal parameter settings, leading to a more data-driven and potentially more profitable trading strategy compared to relying on manually chosen parameters. The effectiveness of the BO-optimized Supertrend strategy will be evaluated through backtesting on a variety of stock datasets.
title Unlocking Profit Potential: Maximizing Returns with Bayesian Optimization of Supertrend Indicator Parameters
topic Trading and Market Microstructure
Statistical Finance
url https://arxiv.org/abs/2405.14262