Summary of Programme:

During the programme, my teammate and I developed a Python-based ETF arbitrage strategy, modelling the price divergence between the ETF market price and its theoretical NAV as a mean-reverting process. The strategy incorporated adaptive statistical thresholds, position-aware entry logic, and dual exit conditions to manage inventory risk effectively.

Through conversations with Goldman Sachs’ quantitative researchers and traders, I gained first-hand insight into how mathematical frameworks — from stochastic processes to statistical inference — are continuously applied and refined in real-world trading environments.

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