58 lines
1.9 KiB
Python
58 lines
1.9 KiB
Python
from __future__ import annotations
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"""Toy two-venue ArbSphere demo.
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This module wires two toy adapters (price feed and broker) from two venues
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and demonstrates a minimal federated compute step using the existing ADMM-lite
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coordinator API.
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"""
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import time
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from typing import List
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from arbsphere.primitives import LocalArbProblem, SharedSignals
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from arbsphere.coordinator import admm_lite_step
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from arbsphere.adapters.price_feed_adapter import PriceFeedAdapter
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from arbsphere.adapters.broker_adapter import BrokerAdapter
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def run_demo() -> None:
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# Define two toy venues with simple, deterministic budgets
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lp1 = LocalArbProblem(asset_pair=("AAPL", "MSFT"), target_mispricing=0.5, liquidity_budget=1000.0, latency_budget=5.0)
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lp2 = LocalArbProblem(asset_pair=("GOOG", "AMZN"), target_mispricing=0.7, liquidity_budget=800.0, latency_budget=6.0)
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shared = SharedSignals(
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deltas=[0.1, -0.05],
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cross_venue_corr=0.25,
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liquidity_availability={"venue-1": 0.8, "venue-2": 0.75},
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latency_proxy=0.9,
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)
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# Step 1: compute a delta (toy) via admm_lite_step
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delta = admm_lite_step([lp1, lp2], shared)
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print("Generated PlanDelta:")
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print(delta)
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# Step 2: route using toy broker adapters (two venues)
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broker_a = BrokerAdapter(venue_name="venue-1")
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broker_b = BrokerAdapter(venue_name="venue-2")
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# Create simple per-venue plan deltas; in a real system this would be split by venue
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plan_for_venue_a = {"legs": delta.legs, "total_size": delta.total_size}
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plan_for_venue_b = {"legs": delta.legs, "total_size": delta.total_size}
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broker_a.route(plan_for_venue_a)
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broker_b.route(plan_for_venue_b)
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print("Venue-1 execution history:", broker_a.history())
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print("Venue-2 execution history:", broker_b.history())
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def main() -> None:
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print("Starting ArbSphere two-venue demo...")
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run_demo()
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if __name__ == "__main__":
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main()
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