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Clustering and attention model based for intelligent trading

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Listed:
  • Mimansa Rana
  • Nanxiang Mao
  • Ming Ao
  • Xiaohui Wu
  • Poning Liang
  • Matloob Khushi

Abstract

The foreign exchange market has taken an important role in the global financial market. While foreign exchange trading brings high-yield opportunities to investors, it also brings certain risks. Since the establishment of the foreign exchange market in the 20th century, foreign exchange rate forecasting has become a hot issue studied by scholars from all over the world. Due to the complexity and number of factors affecting the foreign exchange market, technical analysis cannot respond to administrative intervention or unexpected events. Our team chose several pairs of foreign currency historical data and derived technical indicators from 2005 to 2021 as the dataset and established different machine learning models for event-driven price prediction for oversold scenario.

Suggested Citation

  • Mimansa Rana & Nanxiang Mao & Ming Ao & Xiaohui Wu & Poning Liang & Matloob Khushi, 2021. "Clustering and attention model based for intelligent trading," Papers 2107.06782, arXiv.org, revised Aug 2021.
    • Handle: RePEc:arx:papers:2107.06782
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    References listed on IDEAS

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    2. Mukul Jaggi & Priyanka Mandal & Shreya Narang & Usman Naseem & Matloob Khushi, 2021. "Text Mining of Stocktwits Data for Predicting Stock Prices," Papers 2103.16388, arXiv.org.
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