Our Approach

We employ the best practices of the scientific method and cutting-edge statistical and machine learning modeling to develop our market-neutral Quantitative Algorithms.
Each of our Algorithms shares the same philosophy and undergoes an extensive six-stage Life Cycle before presenting it to the public.
This ensures that we aren't exposed to any unnecessary risk and uphold the consistency and reliability of all our Algorithms.
Life Cycle of Quantitative Algorithm


Strategy Concept

Everything starts with an idea. At this stage, we brainstorm and identify trading opportunities by analyzing market inefficiencies, statistical patterns, and economic theories. The objective is to develop a clear hypothesis or rationale for why the strategy should succeed, defining all the essential parameters and expected returns.



At this stage, the conceptual idea is converted into a structured model with clearly defined rules, parameters, and objectives. Quantitative techniques such as statistical analysis and machine learning algorithms are employed to create the strategy framework, and preliminary tests are conducted.



Following the preliminary tests, the strategy is backtested against multi-year historical market data to evaluate its performance. The results provide us with a deep understanding of how the strategy would have performed in the past, enabling us to fine-tune parameters and ensure that the strategy is sound and not overfitted.



In this phase, the strategy is tested in a more realistic environment that includes market conditions not present in historical data, such as transaction costs, slippage, market impact, latency, and various other market scenarios. This stage gives us the opportunity to validate the strategy under near-live conditions and optimize it even further.


Pilot Test

During the Pilot Phase, the strategy is deployed on a small scale in live market conditions without committing significant capital. This phase allows us to closely monitor the strategy's performance, executions, and operational issues and address potential problems before full-scale deployment.



Once confirmed that Pilot Test performance is aligned with the expectations, the strategy is fully implemented, and the new algorithm is introduced to the public. Our clients are invited to invest in this innovative product with confidence.

Revision Date 26 May, 2024 10:36