Introduction

StablecoinStabilityTracker is a high-performance C++ application designed to monitor major stablecoins (USDT, DAI, USDC), analyze multiple risk signals (volatility, on-chain metrics, sentiment, TVL), and detect potential depeg events in real-time. The system fetches data from REST and WebSocket APIs, applies historical pattern matching, computes a composite risk score, and issues alerts when predefined thresholds are crossed.

Features

• Real-time data ingestion from multiple sources (CoinGecko, Etherscan, custom sentiment API)
• Asynchronous fetchers for low-latency performance
• Historical pattern matching against known depeg events
• Composite risk scoring using weighted signals
• Configurable thresholds and confidence levels
• Structured logging and persistent output to JSON, CSV, and text files

Prerequisites

• C++17 compatible compiler (e.g., GCC 9+, Clang 10+)
• CMake 3.15 or higher
• Internet access for API calls
• Optional: Redis or Kafka for future scaling (not required out-of-the-box)

Installation

1. Create build directory

   mkdir build && cd build

2. Configure and build

   cmake ..
   make -j$(nproc)

3. Or

   ./build/StablecoinStabilityTracker

Configuration

Configuration files are located in the config/ directory:

• config.json: API keys, endpoints, and global settings
• setting.cfg: Threshold values for risk alerts, confidence levels, and logging preferences

Example config.json:

{
  "coingecko_api": "https://api.coingecko.com/api/v3",
  "etherscan_api_key": "YOUR_KEY",
  "sentiment_endpoint": "https://api.sentiment.io/v1/score",
  "analysis_window_days": 30
}

Project Structure

StablecoinStabilityTracker/
├── build/                    # Compiled binaries
├── config/
│   ├── config.json
│   └── setting.cfg
├── data/
│   ├── history/              # Historical JSON data per coin
│   └── final_report.txt      # Summary report
├── include/                  # Header files
│   ├── alerting/
│   ├── analytics/
│   ├── core/
│   ├── data/
│   ├── monitoring/
│   ├── prediction_engine/
│   ├── third_party/
│   └── utils/
├── logs/                     # Application logs
│   └── alerts.log
├── output/                   # Generated alerts and performance CSV
│   ├── alerts.json
│   └── performance.csv
├── src/                      # Source code
│   ├── alerting/
│   ├── analytics/
│   ├── core/
│   ├── data_ingestion/
│   ├── monitoring/
│   ├── prediction_engine/
│   ├── utils/
│   └── main.cpp
├── tests/                    # Unit tests
├── CMakeLists.txt
└── README.md                 # This documentation

Module Descriptions

Data Ingestion

• api_client.hpp/cpp: Base class for REST clients
• coingecko_client: Fetches historical and current prices
• defi_client (etherscan_client, sentiment_client, websocket_handler): Fetches on-chain metrics, sentiment scores, and live ticks
• data_normalizer: Standardizes data formats across sources

Analytics

• pattern_engine: Implements historical depeg pattern matching
• pattern_matcher: Searches for event signatures in time series data

Prediction Engine

• risk_scorer: Computes weighted risk score from volatility, on-chain, sentiment, TVL
• model_interface: Defines the scoring algorithm

Alerting

• threshold_watcher: Compares risk score against configured thresholds
• notification_dispatcher: Logs or sends alerts when a depeg risk is detected

Core & Utilities

• config_manager: Loads and validates configuration files
• thread_pool: Manages asynchronous tasks
• logger & perf_logger: Structured and performance logging
• time_series: Data structures for time-indexed price points

Monitoring

• alert_router: Routes alerts to different outputs (JSON, logs)

Running the Project

From the build/ directory, run:

./StablecoinStabilityTracker

You should see output similar to:

=== Stablecoin Stability Tracker (Configurable) ===
[INFO] -------- Analyzing USDT --------
[INFO] ...
[FINAL REPORT] Written to ./data/final_report.txt

Logging & Output

• logs/alerts.log: Rolling log of alerts and analysis steps
• output/alerts.json: JSON-formatted alerts with timestamp and risk details
• output/performance.csv: Aggregated metrics for backtesting and performance analysis
• data/final_report.txt: Human-readable summary of the latest analysis run

Testing

Unit tests are implemented using GoogleTest. To run tests:

cd build
ctest --output-on-failure

Future Improvements

• Integrate Redis or Kafka for scalable ingestion
• Add real-time dashboard with Grafana
• Support additional stablecoins and on-chain signals
• Implement email/Slack notifications
• Enhance error handling and retry logic