ML algorithms Research
In finance world, the “name of the game” these days is machine learning (ML) - Marcos Prado.
aiquants Research
Perspective
Machine learning takes the form of algorithms that are basically able to learn on their own certain patterns, relationships etc. from raw data. The algorithms used can of course be applied in different financial areas, not only in algorithmic trading but also in predicting the direction of market movements. Some of the common ones used are:

  • ML algorithms for unsupervised learning (such as k-means clustering)
  • Supervised learning (such as DNN classifiers).

The financial sector is undergoing significant restructuring. Banks, hedge funds, and fintech are automating their investments by integrating machine learning and deep learning algorithms into their decision-making process.

Areas of research interest
  • Supervised learning
  • Unsupervised learning


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Our solutions
AI consulting
Python and its ecosystem of powerful packages is the technology platform of choice for algorithmic trading.

ML consulting
In recent years, we have seen how machine learning has gained popularity in solving traditional business problems.

DNNs (Deep Neural Networks)
[T]hey were silly enough to think you can look at the past to predict the future, The Economist.