Discover SQT Strategy
The core of SQT’s strategy relies on Particle Swarm Optimization (PSO), an algorithm inspired by collective intelligence in nature. In financial markets, PSO enables SQT to explore a vast space of portfolio weight combinations and efficiently converge toward robust allocations that balance return and risk.
Each “particle” represents a potential portfolio, and through iterative interaction with the swarm, it gradually moves closer to the most stable and effective solution. This method is particularly valuable in non-linear and noisy market environments where traditional optimization techniques often fall short.
SQT’s Approach
to Portfolio Construction
Our approach combines:
- Diverse data inputs
- Systematic feature engineering
- Stochastic simulations
This allows SQT to produce allocations that remain resilient across market regimes.
Risk Management
at SQT
Risk management is embedded throughout the process:
- Exposure and liquidity checks before trade execution
- Volatility targeting and drawdown controls during live trading
- Continuous monitoring and performance attribution after execution
By integrating swarm intelligence into portfolio construction, SQT’s strategy captures attractive opportunities while maintaining a disciplined and consistent risk profile over time.
Each “particle” represents a potential portfolio, and through iterative interaction with the swarm, it gradually moves closer to the most stable and effective solution. This method is particularly valuable in non-linear and noisy market environments where traditional optimization techniques often fall short.
