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Data Science: A Prerequisite To Machine Learning and Investment Research
Erez Katz, CEO and Co-founder of Lucena Research. Is your data research ready? Key concepts for quantitative investment research and why data science is the crucial first step before machine learning can be applied.
Using Machine Learning to Convert Unstructured to Structured Data
Using Machine Learning to Create Structured Data from Unstructured Communications One of the alternative data providers we have been working with in the past two years is Prattle Analytics. Prattle applies natural language processing on central banks’ communications in order to extract…
Applying Deep Reinforcement Learning to Trading
Lucena Research Co-Founder Dr. Tucker Balch provides an introduction to machine learning, specifically applying deep reinforcement learning for stock trading.
How To Forecast Securities Using Neural Networks
Using Deep Neural Nets to Forecast Stock Prices There’s been a lot of buzz surrounding machine learning to forecast securities. In the webinar we will highlight a unique approach to identifying investment opportunities through the use of deep neural networks.
Money Machines – Interview with Prattle Analytics
AI Powered Investment Research Posted with permission from Prattle. original
How Machine Learning Can Validate Your Data For Stock Forecasting
Erez Katz, CEO and Co-founder of Lucena Research
How to Empirically Measure Alternative Data’s True Value
Erez Katz, CEO and CoFounder of Lucena Research How to Empirically Evaluate Alternative Data Through Backtest and Model Portfolio Performance