Assessing Market Quality and Price Impact: Executing a Portfolio Manager’s Investment Decisions

This case study presents a dynamic, hands-on trading simulation where students step into the role of junior traders at Q-Cumber Capital, a fictional investment firm. Tasked with assisting a Senior Portfolio Manager (represented by the instructor), students are challenged to refine execution strategies and provide data-driven insights on market quality and trade timing. Previously, junior traders at the firm helped assess market conditions by analyzing limit order book snapshots to compute liquidity proxies before trade execution. However, a recent shift at Q-Cumber Capital has restricted the Portfolio Manager's access to real-time limit order books. Now, students must rely on historical trade-and-quote (TAQ) data to evaluate ex-post market quality, measuring the impact of large orders on price movements and liquidity conditions. The case places students in a realistic trading environment where they must not only conduct financial computations but also synthesize data to form actionable recommendations. It strengthens technical competencies such as market microstructure analysis, advanced Excel modeling, and data visualization, while also sharpening decision-making skills in a high-frequency trading context. By bridging theoretical concepts with applied learning, the case enhances students' ability to navigate execution challenges in financial markets.