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CN2.DEVBUKYA NARESH
WORKS/PROJECTS/CRYPTO PLATFORM
PAPER OPERATIONAL
08

AUTONOMOUS DIGITAL-ASSET TRADING & RESEARCH PLATFORM (PYTHON)

CRYPTO PLATFORM

Market state should be modeled once, across scales — the authoritative engine owns state, risk and execution, and clients consume its contracts rather than their own calculations.

An institutional-grade autonomous cryptocurrency trading platform: a single Python 3.12 backend models market structure across a continuous 7-timeframe ladder and five overlapping observation sets, freezes research under a SHA-256 contract, enforces fail-closed risk governance, and serves identical state contracts to an institutional web workstation and a native Android client over REST and WebSocket.

CANDIDATE RECORDS

9,608

HISTORICAL RESEARCH — PHASE Q.2 BASELINE

EXPECTANCY · CONF ≥ 0.60

+0.8885R

BACKTEST SIMULATION — NOT LIVE PERFORMANCE

PROFIT FACTOR · CONF ≥ 0.60

4.918

BACKTEST SIMULATION — NOT LIVE PERFORMANCE

02 / THE PROBLEM

PROBLEM STATEMENT 01

Strategies developed in notebooks are rewritten for execution in another language, introducing unmodeled latency and divergence between research behavior and live behavior.

PROBLEM STATEMENT 02

Single-timeframe strategies ignore macro structural trend and higher-timeframe liquidity pools, which surfaces as false breakouts.

PROBLEM STATEMENT 03

Client-computed state lets two views of the same market disagree about risk.

03 / WHY I BUILT IT

ENGINEERING MOTIVATION & OBJECTIVES

I engineered CRYPTO PLATFORM to address core architectural challenges in autonomous digital-asset trading & research platform (python).

Market state should be modeled once, across scales — the authoritative engine owns state, risk and execution, and clients consume its contracts rather than their own calculations.

04 / ARCHITECTURE

MODULAR STATE MACHINE & PIPELINE FLOW

  1. 01

    INGESTION

    Binance public feeds, timestamp-verified

    • Tick validation against UTC
    • 7-timeframe candle engine
  2. 02

    STATE ENGINE

    Swings, breaks, zones and phase

    • CHOCH / BOS · FVG · order blocks
    • 5 overlapping observation sets
  3. 03

    DECISION ENGINE

    Frozen contract, confidence gating

    • Contract SHA-256 8fbc923a…
    • Confidence ≥ 0.50 to proceed
  4. 04

    RISK GOVERNOR

    Pre-trade capital controls

    • ≥ 4.0R destination floor
    • ≤ 1.0% trade · ≤ 3.0% heat
  5. 05

    CAPITAL GATE

    Fail-closed live authorization

    • Real capital $0.00
    • Live order submission disabled
  6. 06

    SERVER & CLIENTS

    One state contract, two clients

    • 21 REST endpoints · WebSocket
    • Web workstation · Android
LAYER 01

INGESTION

Binance public feeds, timestamp-verified

  • Tick validation against UTC
  • 7-timeframe candle engine
LAYER 02

STATE ENGINE

Swings, breaks, zones and phase

  • CHOCH / BOS · FVG · order blocks
  • 5 overlapping observation sets
LAYER 03

DECISION ENGINE

Frozen contract, confidence gating

  • Contract SHA-256 8fbc923a…
  • Confidence ≥ 0.50 to proceed
LAYER 04

RISK GOVERNOR

Pre-trade capital controls

  • ≥ 4.0R destination floor
  • ≤ 1.0% trade · ≤ 3.0% heat
LAYER 05

CAPITAL GATE

Fail-closed live authorization

  • Real capital $0.00
  • Live order submission disabled
LAYER 06

SERVER & CLIENTS

One state contract, two clients

  • 21 REST endpoints · WebSocket
  • Web workstation · Android

05 / KEY CAPABILITIES

CORE ENGINES & SYSTEM MODULES

◆INGESTION

Binance public feeds, timestamp-verified: Tick validation against UTC, 7-timeframe candle engine

◆STATE ENGINE

Swings, breaks, zones and phase: CHOCH / BOS · FVG · order blocks, 5 overlapping observation sets

◆DECISION ENGINE

Frozen contract, confidence gating: Contract SHA-256 8fbc923a…, Confidence ≥ 0.50 to proceed

◆RISK GOVERNOR

Pre-trade capital controls: ≥ 4.0R destination floor, ≤ 1.0% trade · ≤ 3.0% heat

◆CAPITAL GATE

Fail-closed live authorization: Real capital $0.00, Live order submission disabled

◆SERVER & CLIENTS

One state contract, two clients: 21 REST endpoints · WebSocket, Web workstation · Android

06 / TECHNOLOGY STACK

LANGUAGES, PROTOCOLS & RUNTIME INFRASTRUCTURE

Python 3.12 · aiohttpSQLite WAL persistenceKotlin · Jetpack ComposeGitHub Actions CI

07 / ENGINEERING CHALLENGES

BOTTLENECK INVESTIGATION & RESOLUTION

CHALLENGE 01

Strategies developed in notebooks are rewritten for execution in another language, introducing unmodeled latency and divergence between research behavior and live behavior.

IMPLEMENTED SOLUTION

Keep 100% of market state generation, risk validation and execution logic in one authoritative Python engine; the web workstation and Android client are stateless projections over shared REST and WebSocket contracts.

CHALLENGE 02

Single-timeframe strategies ignore macro structural trend and higher-timeframe liquidity pools, which surfaces as false breakouts.

IMPLEMENTED SOLUTION

Model structure once on a continuous closed-bar 7-timeframe ladder and observe it through five overlapping three-timeframe sets — state updates only on closed candles, entries execute at next bar open.

CHALLENGE 03

Client-computed state lets two views of the same market disagree about risk.

IMPLEMENTED SOLUTION

Freeze alpha models and risk boundaries under a SHA-256 research contract, validate every candidate against a ≥ 4.0R destination floor with ≤ 1.0% per-trade risk and ≤ 3.0% portfolio heat, and pin real capital to $0.00 behind a fail-closed gate.

08 / DEVELOPMENT JOURNEY

EVOLUTIONARY PHASES & MILESTONES

PHASE 1

Problem Formulation

Strategies developed in notebooks are rewritten for execution in another language, introducing unmodeled latency and divergence between research behavior and live behavior.

PHASE 2

Architectural Construction

Keep 100% of market state generation, risk validation and execution logic in one authoritative Python engine; the web workstation and Android client are stateless projections over shared REST and WebSocket contracts.

PHASE 3

Validation & Testing

The full pytest suite — unit, integration and invariant regression — runs in GitHub Actions alongside repository secret scanning.

09 / CASE STUDIES

EMPIRICAL SCENARIO INVESTIGATIONS

CASE 01

CRYPTO PLATFORM Technical Investigation

An institutional-grade autonomous cryptocurrency trading platform: a single Python 3.12 backend models market structure across a continuous 7-timeframe ladder and five overlapping observation sets, freezes research under a SHA-256 contract, enforces fail-closed risk governance, and serves identical state contracts to an institutional web workstation and a native Android client over REST and WebSocket.

VERIFIED OUTCOME

CI passes 300/300 Python tests with 9,608/9,608 tick-invariant replay confirmed on every run.

10 / EVIDENCE & RESULTS

VERIFIED TEST SUITES, BENCHMARKS & HONEST LIMITATIONS

EMPIRICAL FINDINGS
  • ✓CI passes 300/300 Python tests with 9,608/9,608 tick-invariant replay confirmed on every run.
  • ✓Historical research baseline over 9,608 mapped candidate records across BTC, ETH, SOL and BNB (July 2020 onward): the confidence ≥ 0.60 cohort reports +0.8885R expectancy and 4.918 profit factor as backtested figures.
  • ✓The published Phase Q.2 analysis reports the model pruning 80.18% of baseline losses (3,907 of 4,873).
  • ✓Paper simulation is operational with 10 bps taker fees, 4 bps slippage and adverse-first intrabar stop collision.
HONEST LIMITATIONS
  • !All expectancy, profit-factor and win-rate figures are historical backtest simulations; live exchange execution is intentionally disabled and real capital is pinned to $0.00.
  • !Evaluations cover high-liquidity assets (BTC, ETH, SOL, BNB) — other pairs may behave differently, and modeled slippage can be exceeded in liquidity gaps.
  • !Cloud staging is configured but not provisioned; the Android release APK builds with R8 but is debug-signed, so store distribution is incomplete.

11 / SCREENSHOTS & VISUALISATIONS

SYSTEM TOPOLOGY & INSTRUMENTATION SCHEMATICS

System Topology & Flow

SCHEMATIC

Architectural topology of CRYPTO PLATFORM.

[LIVE SYSTEM TOPOLOGY · TELEMETRY INLINE]