We use machines to master logical ideas
Our machines generate risk mitigated trading algorithms to hunt down trading signals. Their input is data, their output is alpha.
Harvest Granular Price Data
We have a global compute platform to store and process per second price point data from stock market Indices. Once stored, that data is fed into a trading simulator that utilises millions of data points to mitigate risk and calculate probability. Our algorithms give no credence to the price direction of the markets.
Back Test Trading Algorithms
Our trading simulator allows us to implement trading formulas across vast periods of time with per second accuracy and infinite signalling. We are constantly evolving our input formulas. We utilise signal based machine learning to add refinements and back test infinite algorithm variations at the click of a button.
Mitigate Risk via Signal Analysis
More data provides clearer signals through back testing. As we process data we may witness scenarios that require micro level adjustments to our algorithms. This could result in the modification of micro parameters already codified, or the coding of new signals and algorithms for our simulators to back test.
Apply Algorithms to Live Trading
Once installed, new directives are simulated across quantitative time frames before real world testing. We use regulated trading platforms to execute automated algorithmic trades and compare them to simulations. This is an integral part of our approach to ensure accuracy and enhance our trading edge.
Individual investors can apply to join the QUOTRON investment platform
A single trade at absolute QUANTS is the product of people and machines in collaboration. The lines between research, technology and trading are intentionally porous in both simulated and live trading environments. Our algorithmic proficiency depends on a blend of stylised machine learning, sophisticated mathematics and large scale data analysis.