Platform
StrategyQuantX — the teaching engine
We use StrategyQuantX as the platform students research on. It gives us strategy generation, backtesting, robustness and walk-forward analysis, and portfolio assembly in one reproducible workflow — the machinery behind every stage of our demo-first pipeline.
Tutee discount
Use code IMEDUCATIONSG10 at checkout for 10% off StrategyQuantX.
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Strategy generation
Build strategies from building blocks or let the engine search the strategy space. We teach students to read what it produces — not to trust it.
Backtesting engine
Tick-accurate backtesting across long histories with modelling of spreads, slippage, and commissions. The first place an idea meets reality.
Robustness testing
Monte Carlo, walk-forward, and parameter sensitivity analysis. The core of our 'does the edge survive?' stage.
Portfolio assembly
Combine strategies into a portfolio and study correlation and combined drawdown. Diversification is a result, not an assumption.
Workflow & automation
Repeatable research pipelines from data to deployable strategy. The scaffolding that makes the work reproducible.
How it fits the curriculum
Each applied-math module lands on a concrete StrategyQuantX exercise: a time-series module becomes a walk-forward study; an optimisation module becomes a portfolio weighting problem; a statistics module becomes a robustness test. The platform is where the math becomes a strategy.
A tool, not an oracle
StrategyQuantX can generate strategies that look good and fail live. We teach students to treat its output as a hypothesis to test on a demo account — never as a finished answer.