Orlando Gemes: Market Efficiency, Dirty Data, and Pricing Beyond Black Scholes | Blushing Quants #8

Episode 8 with Orlando explores where market models work and where they fail, especially in credit markets where pricing is less observable, and data is often dirty. We cover how to find edge through data cleaning, why end-of-day pricing can mislead risk systems, and how to think about VaR and stress testing when liquidity shifts. We also discuss the limits of the Black-Scholes model for long-dated or far-from-the-money options, how Orlando builds a meritocratic research team, and what it takes to scale from an emerging fund to an institutional one.

 

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