Deep learning and Quantitative Trading

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Key Topics:

Quantitative Models:

-Limitations of traditional models, like linear regression.

-Evolution and integration with AI technologies.

Deep Learning & Neural Networks:

-Advantages over traditional models, especially in handling non-linear data.

-Role in enhancing predictions and strategy formulation.

Skilled Developers:

-The significance of expertise in developing robust and efficient AI models.

-Addressing potential issues like overfitting and bias.

Data Management:

-Sourcing reliable and accurate market data.

-Ensuring consistent data quality and relevance.

Intervention in AI Models:

-Deciding when to intervene or halt a model.

-Identifying signs of model underperformance or divergence from expected outcomes.

Human Judgment vs. Automation:

-The balance between automated predictions and human decision-making.

-Understanding when to rely on which.

Model Interpretation:

-Emphasizing the need to understand and interpret model outputs correctly.

-Adapting strategies based on insights and market dynamics.

Disclaimer-

Alt Funds Network LLC and and its affiliates, episode guests, and the companies they represent do not provide tax, legal or accounting or investment advice. This material has been prepared for informational and educational purposes only, and is not intended to provide, and should not be relied on for, tax, legal or accounting advice. You should consult your own tax, legal, accounting, and investment professionals before engaging in any transaction or making any financial or legal decision based on your specific situation.