Skip to content

Stefan071/AutoTrader

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

2 Commits
 
 
 
 

Repository files navigation

AutoTrader

A try a at coding with Jules and Gemini to create an automatic trader / bot trader for a stock exchange like DEGIRO.

AutoTrader Framework A high-frequency, autonomous algorithmic trading system designed for deterministic execution, strict risk management, and sub-millisecond latency.

Architecture Overview The AutoTrader framework utilizes a microservices-inspired, event-driven architecture to isolate critical execution threads from slower network or rendering processes. The system leverages a polyglot codebase to maximize efficiency:

C++ / Java Core: Handles the computationally intensive Level 2 (L2) Central Limit Order Book (CLOB) reconstruction and Risk Management engine.

Python Analytics & GUI: Manages historical data processing, Volume-Weighted Average Price (VWAP) calculations, and the asynchronous visualization layer.

Redpanda / Kafka: Manages event streams for future Natural Language Processing (NLP) sentiment analysis integrations.

Data Processing Hierarchy The execution logic strictly adheres to the following data priority:

Real-Time Price Action: Ingested via persistent WebSocket connections for immediate execution triggers.

L2 Order Book Depth: Processed in C++ using Red-Black Trees to calculate instantaneous Depth VWAP, mitigating slippage on block orders.

Historical Data: Utilized for backtesting, mean-reversion baselines, and establishing volatility metrics (e.g., Average True Range).

Asynchronous News Sentiment: A decoupled stream processing pipeline for forward-looking volatility indicators.

Risk Management Constraints Capital preservation is mathematically enforced at the execution layer. The framework utilizes a Fractional Kelly Criterion (Quarter-Kelly) to dynamically scale position sizes based on the strategy's historical win probability and reward-to-risk ratio. Hard-coded circuit breakers prevent maximum daily drawdown breaches.

Visualization The GUI is entirely decoupled from the execution threads. It utilizes the lightweight-charts-python library to render TradingView-style HTML5 Canvas charts, streaming live telemetry data via inter-process communication without blocking the trading algorithms.

Security Directive Do not hardcode API credentials. All exchange keys and cryptographic secrets must be injected via secure environment variables (.env). Connections to brokerages must enforce TLS and cryptographic payload signing.

About

A try a at coding with Jules and Gemini to create an automatic trader / bot trader for a stock exchange like DEGIRO.

Resources

License

Stars

0 stars

Watchers

0 watching

Forks

Releases

No releases published

Packages

 
 
 

Contributors