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The Science Behind Stop-Loss & Target Gain – Learn When to Exit a Position

The Science Behind Stop-Loss & Target Gain – Learn When to Exit a Position

March 20, 2020 | Ai Driven Investment Strategies, Algorithmic Investing, Alternative Data, Convolutional Neural Networks, Deep Learning, Machine Learning, Neural Networks, Stock Forecasting, Time Series Data,

Co-Authored by: Erez M. Katz (CEO & Co-Founder) and Stuart Colianni (Quant)

Selecting Features with Permutation Importance

Selecting Features with Permutation Importance

March 2, 2020 | Ai Driven Investment Strategies, Algorithmic Investing, Alternative Data, Convolutional Neural Networks, Deep Learning, Machine Learning, Neural Networks, Stock Forecasting, Time Series Data,

Authored by: Stuart Colianni / Quantitative Analyst @ Lucena Research.

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A Dynamic Labeling Approach for Financial Assets Forecasting

A Dynamic Labeling Approach for Financial Assets Forecasting

February 26, 2020 | Ai Driven Investment Strategies, Algorithmic Investing, Alternative Data, Convolutional Neural Networks, Deep Learning, Machine Learning, Neural Networks, Stock Forecasting, Time Series Data,

Authored by: Tarun Bhatia, Stuart Colianni, Taylor Korf, and Erez Katz

Clustering for more effective model training

Clustering for more effective model training

February 26, 2020 | Ai Driven Investment Strategies, Algorithmic Investing, Alternative Data, Convolutional Neural Networks, Deep Learning, Machine Learning, Neural Networks, Stock Forecasting, Time Series Data,

Stuart Colianni, Quantitative Researcher at Lucena Research

Capsule Networks: Next Gen Deep Learning Computer Vision for Stock Forecasting​

Capsule Networks: Next Gen Deep Learning Computer Vision for Stock Forecasting​

July 15, 2019 | Ai Driven Investment Strategies, Convolutional Neural Networks, Data Science, Deep Learning, Machine Learning, Neural Networks, Predictive Analytics, Quantitative Analysis, Quantitative Investing, Stock Forecasting, Time Series Data,

Erez Katz, CEO and Co-founder of Lucena Research Capsule Networks are a fascinating, relatively new technology for image classification. Compared to CNNs, capsule networks have many benefits and phenomenal potential for image classification tasks, specifically time series forecasting.

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