11 datasets found
  1. i

    Enhancing Stock Market Forecasting with Machine Learning A PineScript-Driven...

    • ieee-dataport.org
    • dataverse.harvard.edu
    Updated Nov 19, 2024
    + more versions
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    Gautam Narla (2024). Enhancing Stock Market Forecasting with Machine Learning A PineScript-Driven Approach [Dataset]. http://doi.org/10.21227/8cbk-bc40
    Explore at:
    Dataset updated
    Nov 19, 2024
    Dataset provided by
    IEEE Dataport
    Authors
    Gautam Narla
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    This study investigates the application of machine learning (ML) models in stock market forecasting, with a focus on their integration using PineScript, a domain-specific language for algorithmic trading. Leveraging diverse datasets, including historical stock prices and market sentiment data, we developed and tested various ML models such as neural networks, decision trees, and linear regression. Rigorous backtesting over multiple timeframes and market conditions allowed us to evaluate their predictive accuracy and financial performance. The neural network model demonstrated the highest accuracy, achieving a 75% success rate, significantly outperforming traditional models. Additionally, trading strategies derived from these ML models yielded a return on investment (ROI) of up to 12%, compared to an 8% benchmark index ROI. These findings underscore the transformative potential of ML in refining trading strategies, providing critical insights for financial analysts, investors, and developers. The study draws on insights from 15 peer-reviewed articles, financial datasets, and industry reports, establishing a robust foundation for future exploration of ML-driven financial forecasting. Tools and Technologies Used †PineScript PineScript, a scripting language integrated within the TradingView platform, was the primary tool used to develop and implement the machine learning models. Its robust features allowed for custom indicator creation, strategy backtesting, and real-time market data analysis. †Python Python was utilized for data preprocessing, model training, and performance evaluation.

  2. T

    CRB Commodity Index - Price Data

    • tradingeconomics.com
    • de.tradingeconomics.com
    • +17more
    csv, excel, json, xml
    Updated Jul 15, 2008
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    CRB Commodity Index - Price Data [Dataset]. https://tradingeconomics.com/commodity/crb
    Explore at:
    csv, json, excel, xmlAvailable download formats
    Dataset updated
    Jul 15, 2008
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 3, 1994 - Mar 26, 2025
    Area covered
    World
    Description

    CRB Index increased 16.18 points or 4.53% since the beginning of 2025, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. CRB Commodity Index - values, historical data, forecasts and news - updated on March of 2025.

  3. T

    Steel - Price Data

    • tradingeconomics.com
    • hu.tradingeconomics.com
    • +15more
    csv, excel, json, xml
    Updated Oct 22, 2016
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    TRADING ECONOMICS (2016). Steel - Price Data [Dataset]. https://tradingeconomics.com/commodity/steel
    Explore at:
    xml, csv, excel, jsonAvailable download formats
    Dataset updated
    Oct 22, 2016
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Mar 27, 2009 - Mar 26, 2025
    Area covered
    World
    Description

    Steel decreased 101 Yuan/MT or 3.05% since the beginning of 2025, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Steel - values, historical data, forecasts and news - updated on March of 2025.

  4. T

    Rhodium - Price Data

    • tradingeconomics.com
    • es.tradingeconomics.com
    • +17more
    csv, excel, json, xml
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    TRADING ECONOMICS, Rhodium - Price Data [Dataset]. https://tradingeconomics.com/commodity/rhodium
    Explore at:
    xml, json, excel, csvAvailable download formats
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Oct 3, 2012 - Mar 26, 2025
    Area covered
    World
    Description

    Rhodium increased 1,000 USD/t oz. or 21.86% since the beginning of 2025, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Rhodium - values, historical data, forecasts and news - updated on March of 2025.

  5. T

    Urea - Price Data

    • tradingeconomics.com
    • pl.tradingeconomics.com
    • +17more
    csv, excel, json, xml
    Updated Apr 15, 2022
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    Urea - Price Data [Dataset]. https://tradingeconomics.com/commodity/urea
    Explore at:
    csv, json, xml, excelAvailable download formats
    Dataset updated
    Apr 15, 2022
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jun 7, 2019 - Mar 26, 2025
    Area covered
    World
    Description

    Urea increased 41.75 USD/T or 12.37% since the beginning of 2025, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. This dataset includes a chart with historical data for Urea.

  6. T

    Baltic Exchange Dry Index - Price Data

    • tradingeconomics.com
    • sv.tradingeconomics.com
    • +16more
    csv, excel, json, xml
    Updated Mar 27, 2025
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    TRADING ECONOMICS (2025). Baltic Exchange Dry Index - Price Data [Dataset]. https://tradingeconomics.com/commodity/baltic
    Explore at:
    csv, excel, xml, jsonAvailable download formats
    Dataset updated
    Mar 27, 2025
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 4, 1985 - Mar 26, 2025
    Area covered
    World
    Description

    Baltic Dry increased 637 points or 63.89% since the beginning of 2025, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Baltic Exchange Dry Index - values, historical data, forecasts and news - updated on March of 2025.

  7. T

    JPYVND Japanese Yen Vietnamese Dong - Currency Exchange Rate Live Price...

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Jan 16, 2021
    + more versions
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    TRADING ECONOMICS (2021). JPYVND Japanese Yen Vietnamese Dong - Currency Exchange Rate Live Price Chart [Dataset]. https://tradingeconomics.com/jpyvnd:cur
    Explore at:
    xml, csv, excel, jsonAvailable download formats
    Dataset updated
    Jan 16, 2021
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 1, 2000 - Mar 27, 2025
    Description

    Prices for JPYVND Japanese Yen Vietnamese Dong including live quotes, historical charts and news. JPYVND Japanese Yen Vietnamese Dong was last updated by Trading Economics this March 27 of 2025.

  8. T

    Uranium - Price Data

    • tradingeconomics.com
    • da.tradingeconomics.com
    • +17more
    csv, excel, json, xml
    Updated Mar 6, 2025
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    TRADING ECONOMICS (2025). Uranium - Price Data [Dataset]. https://tradingeconomics.com/commodity/uranium
    Explore at:
    xml, excel, csv, jsonAvailable download formats
    Dataset updated
    Mar 6, 2025
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 1, 1988 - Mar 26, 2025
    Area covered
    World
    Description

    Uranium decreased 8.70 USD/LBS or 11.92% since the beginning of 2025, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Uranium - values, historical data, forecasts and news - updated on March of 2025.

  9. T

    Rubber - Price Data

    • tradingeconomics.com
    • da.tradingeconomics.com
    • +18more
    csv, excel, json, xml
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    Rubber - Price Data [Dataset]. https://tradingeconomics.com/commodity/rubber
    Explore at:
    excel, json, xml, csvAvailable download formats
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jul 1, 1997 - Mar 27, 2025
    Area covered
    World
    Description

    Rubber increased 2.60 US Cents/kg or 1.32% since the beginning of 2025, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Rubber - values, historical data, forecasts and news - updated on March of 2025.

  10. T

    Urals Oil - Price Data

    • tradingeconomics.com
    • pt.tradingeconomics.com
    • +18more
    csv, excel, json, xml
    Updated Jun 26, 2022
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    TRADING ECONOMICS (2022). Urals Oil - Price Data [Dataset]. https://tradingeconomics.com/commodity/urals-oil
    Explore at:
    csv, json, excel, xmlAvailable download formats
    Dataset updated
    Jun 26, 2022
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jun 22, 2012 - Feb 25, 2025
    Area covered
    Ural Mountains, World
    Description

    Urals Oil decreased 3.02 USD/Bbl or 4.41% since the beginning of 2025, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. This dataset includes a chart with historical data for Urals Crude.

  11. T

    Soda Ash - Price Data

    • tradingeconomics.com
    • fa.tradingeconomics.com
    • +17more
    csv, excel, json, xml
    Share
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    TRADING ECONOMICS, Soda Ash - Price Data [Dataset]. https://tradingeconomics.com/commodity/soda-ash
    Explore at:
    csv, xml, excel, jsonAvailable download formats
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 1, 2016 - Mar 26, 2025
    Area covered
    World
    Description

    Soda Ash decreased 48 Yuan/MT or 3.14% since the beginning of 2025, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Soda Ash - values, historical data, forecasts and news - updated on March of 2025.

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Gautam Narla (2024). Enhancing Stock Market Forecasting with Machine Learning A PineScript-Driven Approach [Dataset]. http://doi.org/10.21227/8cbk-bc40

Enhancing Stock Market Forecasting with Machine Learning A PineScript-Driven Approach

Explore at:
Dataset updated
Nov 19, 2024
Dataset provided by
IEEE Dataport
Authors
Gautam Narla
License

Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically

Description

This study investigates the application of machine learning (ML) models in stock market forecasting, with a focus on their integration using PineScript, a domain-specific language for algorithmic trading. Leveraging diverse datasets, including historical stock prices and market sentiment data, we developed and tested various ML models such as neural networks, decision trees, and linear regression. Rigorous backtesting over multiple timeframes and market conditions allowed us to evaluate their predictive accuracy and financial performance. The neural network model demonstrated the highest accuracy, achieving a 75% success rate, significantly outperforming traditional models. Additionally, trading strategies derived from these ML models yielded a return on investment (ROI) of up to 12%, compared to an 8% benchmark index ROI. These findings underscore the transformative potential of ML in refining trading strategies, providing critical insights for financial analysts, investors, and developers. The study draws on insights from 15 peer-reviewed articles, financial datasets, and industry reports, establishing a robust foundation for future exploration of ML-driven financial forecasting. Tools and Technologies Used †PineScript PineScript, a scripting language integrated within the TradingView platform, was the primary tool used to develop and implement the machine learning models. Its robust features allowed for custom indicator creation, strategy backtesting, and real-time market data analysis. †Python Python was utilized for data preprocessing, model training, and performance evaluation.

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