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| Format: | Recurso digital |
| Language: | English |
| Published: |
Zenodo
2025
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| Online Access: | https://doi.org/10.5281/zenodo.17292650 |
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| _version_ | 1866902164499070976 |
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| author | Rao, Arjun |
| author_facet | Rao, Arjun |
| contents | <p>This paper explores how mathematical tools used to study sound and signals can also reveal patterns in financial markets. By applying the Fourier Transform, a method that breaks down complex data into repeating cycles, the study identifies rhythmic trends in stock prices and builds a trading indicator based on them. Using historical market data, the strategy is tested for accuracy and risk-adjusted returns, showing strong performance across major stocks and indexes. The work highlights how mathematical analysis can deepen our understanding of financial behavior and guide data-driven investment decisions.</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_17292650 |
| institution | Zenodo |
| language | eng |
| publishDate | 2025 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Applications of the Fourier Transform as a Financial Indicator for Cyclical Asset Prices Rao, Arjun Quantitative analysis Applied mathematics <p>This paper explores how mathematical tools used to study sound and signals can also reveal patterns in financial markets. By applying the Fourier Transform, a method that breaks down complex data into repeating cycles, the study identifies rhythmic trends in stock prices and builds a trading indicator based on them. Using historical market data, the strategy is tested for accuracy and risk-adjusted returns, showing strong performance across major stocks and indexes. The work highlights how mathematical analysis can deepen our understanding of financial behavior and guide data-driven investment decisions.</p> |
| title | Applications of the Fourier Transform as a Financial Indicator for Cyclical Asset Prices |
| topic | Quantitative analysis Applied mathematics |
| url | https://doi.org/10.5281/zenodo.17292650 |