HEDGEFUND.md


Agent-to-Agent Hedge Fund Strategy Coordination


Part of the protocols.md network


๐Ÿ“ˆ Draft v0.1 - Hedge fund coordination framework. RFC stage

โš ๏ธ CONCEPTUAL WHITE PAPER โ€” This is a theoretical specification exploring potential agent coordination protocols. No implementation exists.




Legal Disclaimers & Compliance First

NOT FINANCIAL ADVICE. NOT A LICENSED ENTITY. CONCEPT ONLY.

Critical Notices

  • This is NOT financial advice and should not be construed as such
  • No entity is operating under this specification - this is purely conceptual
  • Not a registered investment advisor (RIA), broker-dealer, or financial institution
  • No securities or investment services are being offered or provided
  • Compliance required with SEC, FINRA, CFTC, FCA, MiFID II, and all applicable regulations
  • KYC/AML mandatory for any hypothetical implementation
  • Accredited investor requirements must be verified where applicable
  • Securities laws vary by jurisdiction - full compliance required

This specification explores how future hedge funds might coordinate strategies while preserving privacy through zero-knowledge proofs. No operational technology exists.




Challenge

Hedge funds operate in isolation with limited ability to verify counterparty strategies, validate market hypotheses, or coordinate risk management without exposing proprietary models.


Solution โ€“ Privacy-Preserving Coordination Layer

GET https://hedgefund.md/discover { "participating_funds": 847, "verified_strategies": 12421, "zkproof_validations": 94720, "network_aum": "redacted", "avg_alpha": "redacted", "privacy_preserved": true }

One API for strategy verification and coordination โ€” without revealing identities, positions, or proprietary models.




Agent Benefits

  • Zero-Knowledge Strategy Verification โ€“ Prove strategy validity without revealing details
  • Anonymous Counterparty Discovery โ€“ Find complementary funds without identity disclosure
  • Risk Correlation Detection โ€“ Identify crowded trades without exposing positions
  • Alpha Signal Exchange โ€“ Share validated insights through cryptographic commitments
  • Regulatory Compliance โ€“ Built-in audit trails with privacy preservation



Core APIs

Anonymous Strategy Verification


POST /verify { "fund_id": "zkproof:fund_anonymous_4k2x", "strategy": { "type": "long_short_equity", "sector_focus": "zkproof:hash_7d4k2m", "backtest_sharpe": "zkproof:commit_9x3h", "max_drawdown": "zkproof:commit_2k8s" }, "proof": { "zksnark": "0x7d4k2m...", "validator_network": "distributed_verifiers" } } // Returns validation without revealing strategy { "verification_id": "verify_8h3k9x", "strategy_valid": true, "risk_parameters_verified": true, "backtests_authenticated": true, "fund_identity": "anonymous", "compliance_proof": "zkproof:audit_trail_3k7h" }



Agent Use Cases

Risk Correlation Detection


// Detect crowded trades without exposing positions const correlation = await fetch('https://hedgefund.md/risk-check', { method: 'POST', body: JSON.stringify({ portfolio_hash: 'zkproof:portfolio_9k3x', sector_exposure: 'zkproof:sector_4h2k', check_crowding: true }) }).then(res => res.json()); console.log(`Correlation risk: ${correlation.risk_level}`); console.log(`Similar exposure count: ${correlation.crowd_count}`); console.log(`Your identity: anonymous`); // Output: "Correlation risk: moderate" // Output: "Similar exposure count: 47 funds"

Alpha Signal Exchange

POST /signal-exchange { "signal": { "type": "mean_reversion_opportunity", "asset_class": "zkproof:asset_hash", "confidence": "zkproof:confidence_commit", "time_horizon": "3_7_days" }, "exchange": { "seeking": "volatility_arbitrage_signals", "commitment": "zkproof:reciprocal_signal" } } // Returns matched signal without revealing sources { "match_id": "match_7k4h3x", "signal_received": true, "counterparty": "anonymous", "validity_proof": "zkproof:verified_4k2x", "reputation_score": 0.89 }



Privacy Architecture

| Component | Technology | Purpose | |-----------|-----------|---------| | Identity | zkSNARKs + DIDs | Anonymous authentication | | Strategy Proofs | Zero-Knowledge Commitments | Verify without revealing | | Position Hashing | Homomorphic Encryption | Check correlation privately | | Signal Exchange | Secure Multi-Party Computation | Trade insights anonymously | | Audit Trail | zkProofs + Blockchain | Compliance without exposure |

All interactions preserve fund privacy through cryptographic proofs.




Why This Matters

  • Privacy-First coordination without exposing strategies
  • Risk Management through anonymous crowding detection
  • Alpha Discovery via cryptographically verified signals
  • Regulatory Compliance with built-in audit trails
  • Counterparty Validation without identity disclosure



Network Effects

Once hedgefund.md becomes standard:

  • Market Intelligence โ€“ Aggregate insights without centralization
  • Risk Reduction โ€“ Early warning of systemic correlations
  • Strategy Validation โ€“ Peer verification through zkProofs
  • Liquidity Discovery โ€“ Anonymous counterparty matching
  • Compliance Innovation โ€“ Privacy-preserving regulatory reporting



Zero-Knowledge Primitives

{ "cryptographic_tools": { "identity": "zkSNARKs + Decentralized_Identifiers", "commitments": "Pedersen_Commitments + Hash_Functions", "proofs": "Bulletproofs + STARKs", "computation": "Secure_Multi_Party_Computation", "encryption": "Homomorphic_Encryption", "signatures": "Ring_Signatures + Schnorr" }, "privacy_guarantees": { "identity": "anonymous", "positions": "never_revealed", "strategies": "verified_not_exposed", "signals": "cryptographically_committed", "compliance": "provably_auditable" } }



spec_version: 0.1.0-draft
published: 2025-10-06T14:22:17-07:00
status: exploratory
contact: proofmdorg [at] gmail [dot] com


hedgefund.md

ยฉ 2025 hedgefund.md authors ยท MIT License ยท Exploratory specification

DISCLAIMER: This specification is for educational and conceptual purposes only. It does not constitute financial, investment, legal, or tax advice. No securities, investment products, or financial services are being offered. Any hypothetical implementation would require proper licensing, registration, and compliance with all applicable securities laws and regulations.