Exponentiating Quantitative Returns
Exp(Quant) researches and develops quantitative trading algorithms across equities, ETFs, commodities, bonds and currencies, from vanilla instruments to complex derivatives, grounded in financial theory and machine learning methodology.
Strategy R&D
Proprietary and academically grounded trading strategies across equities, ETFs, commodities, bonds and currencies.
Derivatives
From vanilla instruments to complex derivatives, including options market-structure research.
Machine learning
Deep learning, reinforcement learning and genetic algorithms, applied with statistical rigour.
Quantum finance
Quantum finance and quantum machine-learning methodology.
We publish what we find, including what didn't work. A signal we can kill cheaply in research is a loss an investor never has to carry.
Which way do alternative-data signals point?
58 backtests on insider flow, news sentiment and borrow fees. Two textbook assumptions turn out to be backwards.
Does alternative data improve a simple trend model?
A clean test of three free alt-data overlays on a single-name trend rule. The honest answer: no.
Alt-data signals at institutional scale
Scaling the same signals to 500 names and 18 test cells settles the question and closes the research line.