Who we are and why we do what we do.
The co-founders Jeremy Sosabowski and Wei Teo are both experts in experimental physics, mathematics and algorithms but were (and still are) somewhat intellectually perplexed with the world’s obsession of using past data for future extrapolation purposes; even more so when there is little or no past data available for events such as elections, referendums or other ‘never seen before’ events.
Prediction methodologies and calibration from past events are the foundation for most models used in today’s financial services industry including portfolio diversification (Markovitz), option pricing (Black–Scholes), interest rate evolution (Black–Karasinski) and tail risk impact probabilities (VaR and others).
Needless to say that occasionally things can and do go very wrong and not just in global financial markets. The irony is not lost on the AlgoDynamix team and its ever increasing client base that most financial models stop working when they are needed the most. AlgoDynamix is redressing these fundamental flaws using its analytic engine based on deep data from primary data sources (the world’s global financial exchanges) and its proprietary unsupervised machine learning algorithms. In most cases existing models and methodologies are augmented and enhanced using one or more of our forecasting analytics products.
Browse our products
AlgoDynamix currently offers three product services which differ depending on your needs. Find out more here.