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Erez Katz, CEO and Co-founder For us at Lucena, applying machine learning to the financial markets has taken an interesting turn in recent years.�?In theory, fitting a model to historical�?time series data�?and forecasting a KPI should be similar to how…
Webinar Overview On June 13th we will host a webinar dedicated to an open Q&A surrounding trending topics in Alt Data, Machine Learning, and Data Science for Finance. An emerging and rapidly evolving technical domain can cause great confusion and…
Join our newsletter to receive AI driven investment strategies and market trends.
Alternative-Data-Based�?Long and Short�?Portfolios In Action Earlier this year�?we announced�?a partnership with�?Wall Street Horizon.�?�?Our partnership will highlight how quality alternative data combined with�?predictive technology can benefit deploying successful investment signals.
Erez Katz, CEO and Co-founder of Lucena Research. How to test the robustness of a deep learning strategy. Best practices geared to test your quantitative investment strategy before risking capital.
How to Use Time Series Data and RNNs To Forecast Stock Prices. It’s important to configure deep net infrastructure to accommodate time series data.
Lucena Research Co-Founder Dr. Tucker Balch provides an introduction to machine learning, specifically applying deep reinforcement learning for stock trading.
Erez Katz, CEO and Co-founder of Lucena Research How To Use Deep Neural Networks To Forecast Stock Prices
Erez Katz, CEO and Co-founder of Lucena Research How A Convolutional Neural Net Predicts An Outcome and Forecasts Asset Prices.
Erez Katz, CEO and Co-founder Lucena Research How Machine Learning Can Protect Your Deep Value Fundamental Portfolio At Lucena, we’ve witnessed a growing interest in quantitative analysis technology. One question we usually receive from�? portfolio analysts is how can machine…
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.