800+ New Crypto Features
By Quentin Viville, Sudarshan Sawal, and Ernest Chan PredictNow.ai is excited to announce that we’re expanding our...
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”,...
Introducing: Pre-engineered Stock Fundamental Features at Predictnow.ai
Predictnow.ai is pleased to announce the launch of our new pre-engineered stock fundamental features. These features are...
Predicting Profitability: Introducing PredictNow.Ai a Live Machine Learning Tool to Alpaca
What is PredictNow.Ai? PredictNow.ai is a no-code machine learning SaaS-based in Toronto, Canada that is primarily focused...
Conditional Parameter Optimization: Adapting Parameters to Changing Market Regimes
Every trader knows that there are market regimes that are favorable to their strategies, and other regimes...
The Amazing Efficacy of Cluster-based Feature Selection
One major impediment to widespread adoption of machine learning (ML) in investment management is their black-box nature:...
Experiments with GANs for Simulating Returns (Guest post)
By Akshay Nautiyal, Quantinsti Simulating returns using either the traditional closed-form equations or probabilistic models like Monte Carlo...
Is News Sentiment Still Adding Alpha?
By Ernest Chan and Roger Hunter Nowadays it is nearly impossible to step into a quant trading...
The most overlooked aspect of algorithmic trading
Many algorithmic traders justifiably worship the legends of our industry, people like Jim Simons, David Shaw, or Peter...
Loss aversion is not a behavioral bias
In his famous book “Thinking, Fast and Slow“, the Nobel laureate Daniel Kahneman described one common example...
