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⚡ ABITDA

Autonomous Options Agent Test Harness & Institutional Risk Desk

Alpaca Paper Broker Options Tier 3 Harness Score Verification Suite FastMCP Native

The standard benchmarking harness and fiduciary safety gate for autonomous options trading agents.
Stress-testing AI candidates against historical Black Swan shocks, enforcing analytical Black-Scholes Greeks invariants, and routing certified orders to Alpaca.

OverviewArchitectureStress HarnessAgent CommitteeMCP ServerQuickstartAlpaca Compliance


🚨 The Problem: Trading Bots vs. Agent Harness

Most submissions in AI finance build retail trading bots:

  [LLM Prompt] ──▶ "Market looks bullish today" ──▶ [Unhedged Call/Put] ──▶ 💥 Portfolio Blowup

In options trading, unhedged or naive LLM bots are financial disasters waiting to happen. When implied volatility explodes or spot gaps down 3%, naked delta exposure triggers catastrophic margin liquidations.

ABITDA is NOT just another trading bot.
It is an autonomous evaluation harness and fiduciary safety layer (analogous to SWE-bench or Gymnasium for quantitative finance). It solves the #1 unsolved question in algorithmic agent systems:

"How do you objectively benchmark, stress-test against Black Swans, and mathematically gate ANY autonomous AI agent before handing it broker options margin authority?"


🏛️ System Architecture

flowchart TB
    subgraph AGENT_LAYER["1. Pluggable Candidate Agents"]
        direction LR
        A1["Committee Desk<br/>(Macro, Tech, Alpha, Risk)"] 
        A2["Vibe Desk<br/>(NLP Intent Structuring)"]
        A3["External Agents<br/>(Claude / Gemini / Custom)"]
    end

    subgraph HARNESS_LAYER["2. ABITDA Evaluation & Stress Crucible"]
        direction TB
        H["Harness Evaluator<br/>(harness/evaluator.py)"]
        S["Historical Crises (5 Scenarios):<br/>• Aug 5 2024 Yen Crash (VIX 65)<br/>• March 2023 SVB Run<br/>• Feb 2018 Volmageddon<br/>• 1987 Flash Crash<br/>• Calm Bull Grind"]
        H <--> S
        SC["Fiduciary Scorecard<br/>Sharpe • Max DD • Greeks Breaches<br/>Grade A+ to F Certification"]
        H --> SC
    end

    subgraph RISK_GATE["3. Mathematical Greeks Backstop & Guardian"]
        direction TB
        G["Portfolio Greeks Firewall<br/>Net Delta: |Δ| ≤ 0.25<br/>Net Vega: ν ≤ $150.00<br/>Zero Naked Options Wings"]
        GD["Fiduciary Guardian<br/>• Regime-Flip Emergency Exit<br/>• Statistical Win-Rate Lock"]
        G --- GD
    end

    subgraph EXECUTION_LAYER["4. Institutional Broker & Interfaces"]
        direction LR
        ALP["Alpaca Paper Broker<br/>PA382FDPI5IO | $100,000 | Tier 3"]
        MCP["FastMCP Server<br/>(Claude Desktop / Cursor)"]
        WEB["Bloomberg React Terminal<br/>+ Streamlit Cloud Desk"]
    end

    AGENT_LAYER --> HARNESS_LAYER
    HARNESS_LAYER -->|Grade A Certified| RISK_GATE
    RISK_GATE -->|Greeks Approved| EXECUTION_LAYER
    RISK_GATE -.->|Breach Detected| VETO["🚨 VETO: Trade Intercepted & Logged"]

💎 The 4 Core Pillars of ABITDA

1. Standardized Pluggable Agent Protocol (harness/protocol.py)

Any autonomous agent implements the clean, standardized AgentProtocol interface:

from harness.protocol import AgentProtocol, AgentAction

class InstitutionalAgent(AgentProtocol):
    @property
    def name(self) -> str:
        return "DeepVol-Trader-v1"
        
    def propose_trade(self, telemetry: Dict[str, Any], book_greeks: Dict[str, float]) -> AgentAction:
        # LLM reasoning, multi-agent committee, or quantitative signals
        return AgentAction(action_type="OPEN", strategy="IRON_CONDOR", confidence=0.88, legs=[...])

Ships with 4 pre-calibrated agent adapters:

  • CommitteeAgentAdapter: 4-agent consensus floor desk (Macro, Technical, Alpha, Risk).
  • VibeAgentAdapter: Natural language sentiment structurer converting macro prompts into defined-risk spreads.
  • NaiveMomentumAgent: Unhedged directional baseline (used as a control subject).
  • PassiveThetaFarmer: Unchecked credit seller ignoring macro volatility spikes.

2. Historical Black Swan Stress Matrix (harness/scenarios.py)

Agents are subjected to 5 calibrated market crises to test true tail-risk survivability:

Scenario ID Historical Event Spot Shock VIX Spike IV Percentile Market Dynamic
aug5_2024 August 5, 2024 Yen Crash -3.00% +65.0% 99.5% Global liquidity squeeze, massive vol expansion
volmageddon_2018 February 2018 Volmageddon -4.10% +115.0% 100.0% Short-volatility product collapse, skew inversion
svb_march_2023 SVB Banking Run March 2023 -1.80% +22.0% 78.0% Regional banking liquidity freeze, systemic fear
flash_crash_1987 1987 Flash Crash Shock -20.50% +150.0% 100.0% Liquidity vacuum, circuit-breaker cascade
calm_bull_grind 2023 Low-Vol Grind (Control) +0.25% -4.0% 12.0% Benchmark regime for orderly theta harvesting

3. Fiduciary Scorecard & Objective Grading (harness/evaluator.py)

Every decision is audited against closed-form Black-Scholes Greeks calculus:

  • Portfolio Delta Neutrality Limit: Aggregate book Delta strictly bounded within |Δ| ≤ 0.25.
  • Portfolio Vega Volatility Limit: Aggregate book Vega exposure capped at ν ≤ $150.00.
  • Zero Naked Options: Strictly defined-risk structures only (Credit Spreads, Iron Condors).
  • Fiduciary Certification:
    • 🏆 Grade A+ (Score ≥ 95): 0 Greeks breaches, Max Drawdown < 4.0%, Survival Rate 100%.
    • 🥈 Grade A (Score ≥ 85): 0 catastrophic violations, approved for Alpaca execution.
    • Grade F (Score < 50): Unhedged tail-risk or margin blowout ➔ Execution Vetoed.

Head-to-Head Benchmark Results

========================================================================================
   ABITDA BENCHMARK LEADERBOARD (Scenario: Aug 5, 2024 Yen Carry Trade Crash)
========================================================================================
 Rank | Agent Architecture       | Grade | Score | Survival | Max DD  | Greek Breaches
----------------------------------------------------------------------------------------
  #1  | ABITDA Committee Desk    |  A+   | 96.5  |  100.0%  |  -1.8%  | 0 Breaches
  #2  | ABITDA Vibe Architect    |  A    | 88.0  |  100.0%  |  -3.2%  | 0 Breaches
  #3  | Passive Theta Farmer     |  D    | 52.0  |   40.0%  | -18.4%  | 4 Breaches
  #4  | Naive Momentum Bot       |  F    | 24.0  |    0.0%  | -42.8%  | 9 Breaches (LIQUIDATED)
========================================================================================

4. Mathematical Risk Backstops & Fiduciary Guardian (risk/)

Between any candidate agent and the live broker sits ABITDA's dual risk firewall:

  1. Marginal Greeks Gatekeeper (risk/portfolio_greeks_gate.py):
    Simulates the proposed trade added to the current book. If the marginal delta or vega would breach portfolio thresholds, the trade is immediately vetoed before reaching Alpaca.
  2. Regime-Flip Early Liquidation:
    If real-time macro VIX spikes >12% mid-trade, open short spreads are automatically closed for a minor scratch (-1.2%), preventing -45% gamma blowouts.
  3. Statistical Win-Rate Guardian:
    Tracks rolling trade performance. If realized win rate degrades below the statistical binomial edge (70%), the platform autonomously locks trading authority to preserve fiduciary capital.

👥 Multi-Agent Floor Committee

Inspired by institutional trading floors and academic multi-agent architectures (TauricResearch/TradingAgents):

                     ┌──────────────────────────────────────────────┐
                     │          FLOOR COMMITTEE DELIBERATION        │
                     └──────────────────────────────────────────────┘
                                            │
               ┌────────────────────────────┼────────────────────────────┐
               ▼                            ▼                            ▼
      ┌─────────────────┐          ┌─────────────────┐          ┌─────────────────┐
      │  MACRO ANALYST  │          │ TECHNICAL SCOUT │          │  ALPHA TRADER   │
      │ Realized Vol,   │          │ Bollinger Bands,│          │ Strike & Expiry │
      │ VIX Skew & Term │          │ RSI Momentum &  │          │ Selection with  │
      │ Structure       │          │ Key Support/Res │          │ Credit Maximizer│
      └────────┬────────┘          └────────┬────────┘          └────────┬────────┘
               │                            │                            │
               └────────────────────────────┼────────────────────────────┘
                                            ▼
                               ┌─────────────────────────┐
                               │      RISK GOVERNOR      │
                               │  Veto Power • Greeks    │
                               │  Delta/Vega Compliance  │
                               └────────────┬────────────┘
                                            ▼
                               [ CONSENSUS PLAYBOOK ]

🔌 Model Context Protocol (FastMCP) Server

ABITDA natively integrates Anthropic & Google's Model Context Protocol (MCP) via mcp_server.py. Any external agent or developer tool (Claude Desktop, Cursor, Gemini CLI) can interface with the harness:

{
  "mcpServers": {
    "abitda-options-harness": {
      "command": "python",
      "args": ["-m", "mcp_server"]
    }
  }
}

Exposed MCP Tools:

  • get_market_regime: Real-time VIX, realized volatility, and IV percentile clustering.
  • audit_portfolio_greeks: Live Black-Scholes Delta, Gamma, Vega, and Theta breakdown.
  • run_autonomous_cycle: Executes 5-step consensus trading cycle on Alpaca Paper.
  • replay_black_swan_event: Evaluates candidate agents against historical shocks.
  • get_guardian_status: Fiduciary self-suspension state and circuit-breaker telemetry.

💻 Web Platforms & Institutional Interfaces

ABITDA provides two synchronized, production interfaces:

1. Institutional Bloomberg-Style React Desk (frontend/)

  • Live ReAct Step Stream: Real-time visibility into agent reasoning, tool calls, and observations.
  • Interactive Greeks Risk Panel: Net book Delta, Gamma, Vega, and Theta meters with regulatory caps.
  • Harness Benchmarking Hub: Select any historical crisis, run candidate agents, and inspect comparative PnL curves.
  • Committee Deliberation Room: Bar-by-bar debate logs between Macro, Technical, Alpha, and Risk Governor.
  • Vibe Desk NLP Structurer: Converts natural language ideas ("hedge against rate decision volatility") into defined-risk options legs.

2. Streamlit Cloud / Railway Desk (ui/dashboard.py)

  • Interactive Plotly Black-Scholes options payoff curves with live slider adjustments.
  • Built-in "Ask the Desk Quant" Copilot powered by Gemini 3.6 Flash.
  • 5 One-Click Live Demo Triggers for judges to instantly test edge-cases.

⚡ Quickstart & Verification

1. Clone & Install

git clone https://github.com/RABNEER/ThetaHawk.git
cd ThetaHawk
pip install -e .

2. Run the 9-Point Automated Verification Suite

Verify all systems, broker connections, analytical engines, and harness scenarios:

python test_suite.py
======================================================================
   ABITDA AUTOMATED VERIFICATION & HARNESS SUITE
======================================================================
 ✓  Alpaca Broker Connection           [PASS]  Account PA382FDPI5IO | Tier 3 Active
 ✓  Black-Scholes Greeks Engine        [PASS]  Exact analytical precision
 ✓  Market Telemetry Reader            [PASS]  VIX: 14.19, IV %ile: 2.6%
 ✓  Regime Agent & Strategy Selector   [PASS]  TRENDING -> BULL_PUT_SPREAD
 ✓  Portfolio Greeks Gate (Gap 1)      [PASS]  Compliant trade PASS + breach VETO verified
 ✓  Regime-Flip Early Exit (Gap 2)     [PASS]  Immediate defensive liquidation verified
 ✓  Self-Awareness Lock (Gap 3)        [PASS]  Statistical edge decay suspension verified
 ✓  Agentic ReAct Co-Pilot             [PASS]  13 visible cognitive steps generated
 ✓  Abitda Agent Test Harness          [PASS]  Grade A+ vs Grade F benchmarked
======================================================================
   FINAL TEST RESULTS: 9/9 CHECKS PASSED (100% OPERATIONAL)
======================================================================

3. Run via CLI

# Evaluate the multi-agent committee on the August 5, 2024 Yen Crash
abitda evaluate --agent committee --scenario aug5_2024

# Convene the 4-agent Floor Committee deliberation for SPY
abitda committee --symbol SPY

# Generate the Institutional Desk Briefing Dossier
abitda report --symbol SPY

# Launch the FastMCP Server
python mcp_server.py

4. Run the Web Platform Locally

# Terminal 1: Backend API & Static Server
python server.py

# Terminal 2 (Optional Dev Mode): React Vite Desk
cd frontend && npm run dev

Open http://localhost:8000 in your browser.


🏆 Alpaca Hackathon Compliance Matrix

Hackathon Requirement ABITDA Implementation Status
Dedicated Alpaca Paper Account Account ID: PA382FDPI5IO ($100,000 Starting Equity) COMPLIANT
Approved Options Trading Tier Level 3 (Credit Spreads, Debit Spreads, Iron Condors, Defined Risk) COMPLIANT
Options-Focused Strategy Black-Scholes Greeks engine, delta-neutral spreads, dynamic volatility sizing COMPLIANT
Multi-Agent Architecture 4-Agent Floor Committee (Macro, Greeks, Volatility, Fiduciary) + Vibe Desk COMPLIANT
Fiduciary Risk Management Portfolio Greeks limits ( Δ
Stress-Testing & Benchmarking 5 Historical Crisis Scenarios (Yen Crash, SVB, Volmageddon, Flash Crash, Calm Grind) COMPLIANT
Model Context Protocol (MCP) Native FastMCP Server (mcp_server.py) with 5 institutional quant tools COMPLIANT
Public Codebase & Tests Open-source GitHub repository with passing automated verification suites COMPLIANT

📦 PyPI Package & Publishing

abitda is packaged as an institutional Python package:

# Install via pip
pip install abitda

# Verify installation & launch CLI
abitda --help

# Run Black Swan benchmark against Yen Carry Crash
abitda --benchmark --agent committee --scenario aug5_2024

Publishing to PyPI

# 1. Build source distribution and wheel
python -m build

# 2. Check distribution integrity with twine
twine check dist/*

# 3. Upload to TestPyPI (optional test)
twine upload --repository testpypi dist/*

# 4. Upload to Production PyPI
twine upload dist/*

📖 Developer & Agent Integration Guide

Want to benchmark your own custom trading agent (LangChain, AutoGen, CrewAI, or rule-based) against Abitda's Black Swan crucibles?

👉 Read the Full Harness Integration Guide


📂 Repository Organization

├── abitda.py                   # Top-level SDK module
├── main.py                     # CLI entrypoint for harness & desk
├── mcp_server.py               # FastMCP Server exposing harness tools
├── server.py                   # High-performance FastAPI backend + static React server
├── test_suite.py               # 9/9 End-to-end automated verification suite
├── extreme_test_suite.py       # Stress, chaos & adversarial fuzzing suite
├── pyproject.toml              # PyPI package build configuration
├── setup.py                    # Package metadata & entry points
├── SUBMISSION.md               # Official Hackathon Submission Dossier & Demo Script
├── HARNESS_SCORECARD.md        # Full benchmark scorecards across historical crises
├── DESK_BRIEFING.md            # Generated institutional quant daily risk dossier
├── docs/
│   └── HARNESS_INTEGRATION_GUIDE.md # Comprehensive external agent integration guide
├── harness/                    # 🛡️ THE AGENT TEST HARNESS SUITE
│   ├── protocol.py             # Standardized AgentProtocol & 4 pre-built adapters
│   ├── scenarios.py            # 5 Historical Black Swan market shock scenarios
│   └── evaluator.py            # Fiduciary grading engine & leaderboard compiler
├── agents/                     # 👥 MULTI-AGENT ARCHITECTURE
│   ├── committee.py            # 4-Agent Floor Committee (Macro, Greeks, Volatility, Fiduciary)
│   ├── vibe_desk.py            # NLP Sentiment Structurer
│   ├── copilot_agent.py        # Conversational ReAct Desk Copilot
│   └── regime_agent.py         # Macro regime classification & strategy selector
├── risk/                       # ⚖️ MATHEMATICAL RISK FIREWALL
│   ├── portfolio_greeks_gate.py# Analytical Black-Scholes Delta & Vega limit gate
│   ├── hard_backstops.py       # Capital allocation and daily drawdown breakers
│   ├── self_suspension.py      # Statistical win-rate self-suspension engine
│   └── regime_flip_exit.py     # Tail-risk emergency liquidation monitor
├── data/                       # 📈 MARKET DATA & TELEMETRY
│   ├── market_reader.py        # VIX, IV percentile, and realized volatility reader
│   ├── greeks_engine.py        # Closed-form Black-Scholes calculus & spread Greeks
│   └── stress_test.py          # 1987 Black Swan scenario simulation engine
├── execution/                  # 🚀 BROKER ORDER ROUTING
│   └── alpaca_client.py        # Alpaca Paper API client with safety guards
├── memory/                     # 💾 AUDIT & LEDGER
│   └── trade_logger.py         # SQLite3 immutable audit trail & ledger
└── frontend/                   # 🖥️ INSTITUTIONAL REACT TERMINAL
    ├── src/components/         # LiveTradingChart, GreeksRiskMeter, BenchmarkComparisonChart
    └── src/App.tsx             # Multi-page sidebar institutional console
Built with mathematical rigor for the Alpaca AI Trading Agents Hackathon.

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