Quantitative Strategy Sandbox (PBOT)

High-Frequency Statistical Execution Engine

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Project Overview

PBOT is a headless execution engine developed to stress-test high-frequency statistical strategies (Martingale, Trend-Following, and Mean Reversion) against real-time WebSocket-driven data. It transitions manual trading concepts into a programmatic, emotionless execution environment.

The Logic

Designed with a "Mechanical Engineering" approach to risk, the system prioritizes Systemic Gating. Instead of constant execution, the engine remains idle until specific statistical "exhaustion" thresholds are met, significantly increasing the probability of successful entries.

Technical Architecture

• Language: Python 3.x
• Automation Engine: Selenium (Optimized for sub-100ms latency)
• GUI Framework: Tkinter (Custom dashboard for real-time parameter tuning)
• Data Parsing: BeautifulSoup4 & JSON Normalization
• Real-Time Monitoring: Custom WebDriverWait logic for WebSocket event tracking

Key Features

• Conditional Gating Algorithm: Implements "Programmatic Patience"—executing only when specific trend-exhaustion criteria (e.g., consecutive loss streaks) are met.
• Real-Time Risk Management: Automated stop-loss triggers and stake-sequencing based on live balance fluctuations.
• State-Machine Architecture: Robust session persistence and error-handling to manage network volatility and authentication.
• Live Dashboard: A custom-built Tkinter interface allows the user to adjust risk parameters (Stake, Thresholds, Target ROI) on the fly.

Installation & Setup

git clone [https://github.com/egbertdev/PBOT-Strategy-Sandbox.git](https://github.com/egbertdev/PBOT-Strategy-Sandbox.git)
cd PBOT-Strategy-Sandbox
2. Install Dependencies
Bash
pip install selenium beautifulsoup4
3. Run the Engine
Bash
python main.py
Author: Egbert Joel Abok

Focus: Quantitative Automation & Systems Logic