AI for Finance – Financial Trading with MATLAB

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Free | online | Arpad Forberger

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AI technologies are already widely used in the financial sector. For instance, according to Bloomberg, AI-driven trading accounts for roughly 40% of trading volume in European equity markets and roughly 80% in foreign exchange futures.

Two new workflows, deep learning and reinforcement learning, are transforming industries with their ability to allow computers to “self-learn” applications, including financial trading.

In this webinar, we will be showing how to use Reinforcement Learning to trade the financial markets without ever losing money.

The example uses an environment consisting of 3 stocks, 20000 USD cash, and 15 years of historical data. Source: AlphaVantage:


  • Reinforcement Learning
  • Machine Learning vs. Deep Learning vs. Reinforcement Learning
  • Reinforcement Learning Workflow
  • Case Study: Development of a self-learning financial trading agent
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AI for Finance – Financial Trading with MATLAB

About the Speaker(s)

  • Arpad Forberger

    Application Engineer

    Arpad is an application engineer at SciEngineer. His research and consulting work focus on technical computing and finite element modeling.

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Free | online | Arpad Forberger

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AI for Finance – Financial Trading with MATLAB

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