Elie Vascres
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Personal R&D

Binance Signals Platform

Algorithmic signals and execution for Binance Futures

2025 – 2026

PythonFastAPIReactWebSocketDockerTelegram API
Private — access restricted
Binance Signals Platform interface
Overview

A system that watches the Binance Futures market in real time, generates trading signals, and can act on them — automatically, with a manual confirmation step, or in a safe simulated mode.

Challenge

I wanted a signal system that does not just generate ideas, but also manages risk properly and keeps working even when part of the system fails.

Solution

I built a real-time data pipeline over WebSocket, an analysis engine that scores the market on four factors and detects the current market regime, and a risk engine shared by all three execution modes: paper, manual (confirmed through Telegram), and live.

My contribution

I designed and built the full system: the data ingestion, the analysis and signal logic, the risk engine, the three execution modes, the Telegram bot, and the monitoring.

Key features
  • Real-time market data over WebSocket
  • A four-factor analysis engine with market regime detection
  • Stop-loss and take-profit levels based on market volatility (ATR)
  • Three execution modes: paper, Telegram-confirmed manual, and live
  • A shared risk engine with circuit breakers for all three modes
  • Backtesting without lookahead bias
  • Chaos testing against simulated failures
  • A private dashboard, gated behind a bearer-token login
Architecture
Technical details

Market data flows in through WebSocket, gets normalized, and feeds the analysis engine. Every signal passes through the same risk engine, whichever execution mode is active. The system logs latency at each step and redacts secrets automatically from its logs.

How it was built

I tested each part in isolation first — data, then signals, then risk, then execution — then ran the full system in paper mode before trusting it with small amounts of real money.

Where it stands today

The system passed over 669 automated tests and a round of chaos testing (simulated outages and sudden price crashes) without failing unsafely. The engineering meets a high bar — whether to risk real capital with it at scale is a separate decision I haven't made yet.