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Is Your Data Predictive? How to Measure Before Risking Capital
Erez Katz, CEO and Co-founder of Lucena Research Here are the pitfalls data providers and data consumers should be aware of.
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 Use Deep Neural Networks To Forecast Stock Prices
Erez Katz, CEO and Co-founder of Lucena Research How To Use Deep Neural Networks To Forecast Stock Prices
How To Forecast Securities Using Neural Networks
Forecast Stocks Using Neural Networks There’s been a lot of buzz surrounding machine learning to forecast stock prices using neural networks. In the webinar we will highlight a unique approach to identifying investment opportunities through the use of deep neural networks.…
“The Journey of an Alternative Data Signal” Webinar
The AI and big data revolution have energized the financial market in ways not seen since the introduction of electronic trading in the 1980’s.
How Machine Learning Can Validate Your Data For Stock Forecasting
Erez Katz, CEO and Co-founder of Lucena Research There are many Machine Learning methods that can be used to validate data for stock forecasting. It’s important to understand and distinguish the methods before utilizing AI to validate and predict asset prices.
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 The growth of alternative data has driven data consumers to seek efficient methods of sifting through vast amounts of information.…