Key Takeaways
- • validityBase launches blockchain-backed track record validation: Founded by Dan Averbukh and Greg Kapoustin, the firm addresses a critical pain point for hedge fund allocators—determining whether reported returns are legitimate or subject to selection bias, survivorship bias, or data-mining artifacts.
- • Problem originates from due diligence blind spots: Averbukh and Kapoustin, formerly running Clerkenwell Asset Management (a systematic arbitrage fund), struggled to validate pitches from algorithm developers and strategy vendors—unable to confirm whether presented results excluded worst-case trading days or represented cherry-picked performance from multiple backtested iterations.
- • Verifiable predictive data as competitive differentiator: validityBase enables fund managers to create auditable archives of predictive signals and trading data, allowing allocators to independently verify that reported performance matches actual executed positions and investment decisions.
- • Addresses institutional investor skepticism: The solution targets the persistent gap between track record claims and investor confidence, particularly relevant for emerging managers and algorithmic traders whose returns often appear "too good to be true" without independent corroboration.
Summary
validityBase has emerged to solve a fundamental credibility problem in hedge fund capital raising: validating whether exceptional track records are genuinely achievable or artifacts of selection bias and data manipulation. Founded by Dan Averbukh and Greg Kapoustin—former principals of Clerkenwell Asset Management, a systematic arbitrage fund specializing in market dislocations and frontier technologies—the firm leverages blockchain-backed technology to create immutable records of predictive signals and trading performance.
The founders' motivation stems from direct experience evaluating strategy pitches. As Clerkenwell grew, Averbukh and Kapoustin received numerous proposals from algorithm developers and quantitative traders claiming exceptional returns. However, they faced an intractable validation problem: confirming whether the presented results excluded worst-case trading days, represented survivorship-biased performance, or reflected one successful iteration among thousands of backtested variations. "How are we to know if the worst day of trading isn't there, or if somebody ran 1,000 different versions of their strategy, and they're showing us the one that worked?" Averbukh noted. This inability to confirm the credibility of pitches prevented them from confidently marketing strategies to their own investors.
For institutional allocators, this challenge is pervasive. While most track record figures are genuine, a material subset involves either optimistic assumptions or selective presentation. validityBase addresses this by enabling fund managers to create verifiable archives of their predictive data—essentially time-stamping signals and investment decisions in a manner that permits third-party audit. This transparency mechanism allows allocators to independently assess whether reported performance corresponds to actual executed positions and market conditions.
The service is particularly relevant for emerging managers and systematic traders, whose returns often appear improbably strong without independent corroboration. By establishing blockchain-backed proof of strategy performance, managers can differentiate themselves in a competitive capital-raising environment while simultaneously providing investors the confidence necessary to commit capital to non-traditional or newly launched vehicles.
The founders' motivation stems from direct experience evaluating strategy pitches. As Clerkenwell grew, Averbukh and Kapoustin received numerous proposals from algorithm developers and quantitative traders claiming exceptional returns. However, they faced an intractable validation problem: confirming whether the presented results excluded worst-case trading days, represented survivorship-biased performance, or reflected one successful iteration among thousands of backtested variations. "How are we to know if the worst day of trading isn't there, or if somebody ran 1,000 different versions of their strategy, and they're showing us the one that worked?" Averbukh noted. This inability to confirm the credibility of pitches prevented them from confidently marketing strategies to their own investors.
For institutional allocators, this challenge is pervasive. While most track record figures are genuine, a material subset involves either optimistic assumptions or selective presentation. validityBase addresses this by enabling fund managers to create verifiable archives of their predictive data—essentially time-stamping signals and investment decisions in a manner that permits third-party audit. This transparency mechanism allows allocators to independently assess whether reported performance corresponds to actual executed positions and market conditions.
The service is particularly relevant for emerging managers and systematic traders, whose returns often appear improbably strong without independent corroboration. By establishing blockchain-backed proof of strategy performance, managers can differentiate themselves in a competitive capital-raising environment while simultaneously providing investors the confidence necessary to commit capital to non-traditional or newly launched vehicles.
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