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New Additions to the Factor Zoo

By Akshay Nautiyal and Ernest Chan This has been a summer of feature engineering for First, we launched the US stock cross-sectional features and the time-series market-wide features. Most recently,  we launched the features based on options activities, ETFs,...


Metalabeling and the duality between cross-sectional and time-series factors

Features are inputs to supervised machine learning (ML) models. In traditional finance, they are typically called “factors”, and they are used in linear regression models to either explain or predict returns. In the former usage, the factors are contemporaneous with...


Introducing: Pre-engineered Stock Fundamental Features at is pleased to announce the launch of our new pre-engineered stock fundamental features. These features are ratios and indicators that have been constructed from the quarterly and annual financial statements of public companies. In the US, these are the...


Predicting Profitability: Introducing PredictNow.Ai a Live Machine Learning Tool to Alpaca

What is PredictNow.Ai? is a no-code machine learning SaaS-based in Toronto, Canada that is primarily focused on helping traders apply machine learning to their investment strategies in order to predict the profitability of their next trade. can calculate...

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