Algo Trading Risk Engine

A quantitative trading desk was executing thousands of trades per second and needed a way to monitor their Value-at-Risk (VaR) and 'Greeks' in real-time. During periods of high market volatility, their existing risk reports were too slow, creating a danger of exceeding exchange-mandated risk limits.

A single breach could lead to massive fines or loss of trading privileges. They needed a 'systemic kill-switch' that could respond faster than a human trader could click a button.

I developed a specialized Risk Engine using a hybrid of C++ for computation-heavy Greeks calculations and Python for data orchestration and visualization. The system consumes live market data feeds and recalculated the entire portfolio's risk profile on every tick.

I implemented a high-performance dashboard that uses 'Traffic Light' signaling to warn traders when they are approaching risk thresholds. The engine also features an automated 'Kill Switch' that can halt specific algos if they exceed pre-defined loss limits.

I also integrated a 'Stress Test' simulator that allows the risk team to 'shock' the portfolio with historical scenarios (like the 2008 crash) to see how it would perform in extreme conditions, all in real-time.