Due diligence, answered.

For external programs, we generally prefer to collaborate with managers who operate within established structures, such as a hedge fund vehicle, an Actively Managed Certificate (AMC), or an Exchange Traded Product (ETP). We seek a demonstrable, multi-year track record that can be validated through an audit by a reputable and qualified auditor.

While audits are strongly preferred, we recognize that they are not a mandatory requirement for smaller hedge funds under various regulatory regimes globally. In such cases, we accept official Net Asset Value (NAV) letters from an independent administrator. These letters must also confirm the manager's Assets Under Management (AUM).

An administrator acts as an independent third party responsible for calculating a fund's NAV, processing subscriptions and redemptions, and maintaining financial records. In some respects, an administrator's oversight can be highly effective because they often have weekly or monthly visibility into the fund's brokerage and bank accounts. This frequent monitoring provides an ongoing layer of verification, complementing the annual review typical of an audit.

Generally speaking, a larger AUM indicates a maturity of processes, sound decision-making frameworks, and proven risk management systems. It demonstrates that the manager has successfully navigated various market cycles and built an infrastructure capable of handling significant capital, which aligns with our focus on stability and long-term performance.

No. Much of the strongest alpha sits inside larger firms, without a standalone record.

No. We understand that significant alpha often resides outside traditional, standalone funds. There is an ecosystem of AI and quant-based portfolio managers and data scientists who have historically served only the most sophisticated global investors. These individuals often hail from top-tier hedge funds, proprietary trading firms, family offices, market makers, prime brokers, and investment banks. For instance, top-tier hedge funds often operate with numerous specialized trading teams (or "pods"). While these teams may generate exceptional returns, they do not possess a standalone, third-party audited track record. Many such teams manage substantial capital utilizing proprietary strategies that remain internal to their parent firms.

We audit the raw evidence ourselves: broker statements, timestamped trades and backtests.

We recognize that the true drivers of exceptional returns are often the data scientists and quantitative researchers behind the scenes, rather than the public-facing portfolio managers. We actively seek out these individuals to access unique sources of alpha. In the secretive world of quantitative finance, returns exceeding standard benchmarks are often the baseline. To validate the performance of these managers and data scientists, we employ our sophisticated AI R&D platform. We conduct our own rigorous audits of broker statements, timestamped trade data, and backtests. Leveraging PhD-level mathematical approaches and advanced AI/ML techniques, we validate that the generated alpha is genuine and not the result of curve-fitting, utilizing the same performance validation methodologies employed by the world's leading hedge funds.

References first, then often a live pilot on real capital.

When available, we require and verify broker and investor references. Furthermore, we often conduct an initial test of a portfolio manager's strategy using our own capital or capital from our most sophisticated investors who seek exposure to emerging talent and are willing to accept the associated risks in exchange for a first right of refusal. This is particularly relevant for strategies with limited capacity (e.g., High-Frequency Trading strategies that may only accommodate $5 million AUM but offer significant return potential). In these instances, we implement a 90 to 180-day pilot period utilizing real capital. This allows us to validate the strategy's live performance against its historical track record or backtest. We also thoroughly review the manager's blue-chip credentials and prior experience with established firms.

While no due diligence process is perfect, our AI-driven risk management engines are designed to monitor performance continuously and strive to identify potential issues or failures early, mitigating risk for our clients.