I want to formalise a systematic, low-risk stock arbitrage programme that exploits pricing discrepancies across exchanges and closely related securities. My priority is capital preservation, so every tactic must revolve around a high win-rate edge, tight risk controls, and sensible diversification rather than sheer leverage or headline returns. Here is the framework I have in mind: • Inefficiency focus: pure arbitrage. I am not looking for momentum, mean-reversion, or discretionary overlays—only quantifiable mispricings that can be captured and neutralised quickly. • Instruments: listed equities and their derivatives or depository receipts; no crypto or FX legs at this stage. • Data: the engine must combine real-time feeds for execution decisions with a rich historical database for signal construction, parameter calibration, and walk-forward testing. You would be responsible for designing the strategy logic, coding it into a production-ready algorithm (Python is preferred, but I’m open to C++, Java, or a cloud-native stack if you can justify the latency profile), and demonstrating its robustness through statistically significant back-tests and forward simulations. Order-routing can point to Interactive Brokers, TradeStation, or another low-latency broker you already know well; just outline the connectivity layer in your proposal. Deliverables 1. Well-documented source code with modular risk controls (max position, max exposure per pair, real-time VaR monitoring). 2. A replicable research notebook or report detailing data cleaning, signal construction, slippage assumptions, and out-of-sample test results. 3. Deployment guide showing how to launch the strategy live, including scheduling, logging, and fail-safe shutdown procedures. Acceptance criteria • Minimum Sharpe of 2.0 and maximum drawdown under 3 % in your out-of-sample testing window. • At least 12 months of tick-level or second-level simulation to validate execution assumptions. • Code passes a dry-run on my machine with sample API keys and produces identical metrics to yours. If this brief aligns with your expertise in statistical arbitrage, market micro-structure, and high-integrity engineering, I look forward to seeing how you would tackle the challenge.