About the Client
A mid-sized hedge fund preparing to allocate capital to a third-party systematic equity strategy asked Nexus for fast, field-level validation. The fund’s investment committee liked the back tests, but needed confidence on three fronts: execution slippage in live markets, data and model robustness, and practical capacity before committing meaningful capital.
The Challenge
Opaque implementation risk
The strategy relied on proprietary signals and third-party data that weren’t easy to validate from the pitch book.
Execution & market-microstructure uncertainty
The fund worried that real-world trading costs and crowding could erode the advertised alpha.
Capacity and correlation concerns
There was limited visibility on how quickly the strategy could scale without performance decay, or how crowded the factor exposures already were.
Our Approach
Precision screening
We screened ~40 candidates and delivered a curated list of 25+ experts for the client to choose from: quant PMs, execution traders, sell-side electronic trading heads, data engineers at alternative data firms, and former prime-broker portfolio risk leads.
Structured interview design
Together with the client we built a short, role-specific discussion guide covering: data provenance, signal stability, expected implementation shortfall, slippage drivers, and capacity ceilings.
Manager & counterparty checks
We ran targeted conversations with former counterparties and ex-employees who had direct experience with the strategy or the underlying data vendor.
Micro-benchmarking and synthesis
We ran a quick comparison across similar systematic strategies (execution costs, typical bps slippage, and capacity ranges) and produced a one-page heatmap: model risk, execution risk, and scaling readiness—plus a short checklist the fund’s ops team could use during onboarding.
Results & Impact
Delivered in under two weeks, the engagement gave the fund clear, decision-ready intelligence:
- 25 expert interviews completed (screened 40+).
- Identified likely live-trade slippage of ~30–50 bps relative to backtests, driven by market impact and crowded intraday signals, an eye-opening figure the client used to reprice expected net alpha.
- Recommended a staged allocation (initially 30–40% of the planned size) with pre-set scale triggers tied to realized slippage and capacity metrics, this reduced short-term implementation risk and preserved optionality.
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