Unlocking Profit Potential: Maximizing Returns with Bayesian Optimization of Supertrend Indicator Parameters
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arXiv
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| Format: | Preprint |
| Publié: |
2024
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| _version_ | 1866910457696092160 |
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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 |