Executive Summary
CashStra is a comprehensive automated trading strategy platform that uses technical analysis indicators (RSI, MACD, volume-based signals) to generate and execute trading signals across multiple asset classes: stocks, ETFs, and cryptocurrencies. It provides real-time monitoring, backtesting capabilities, portfolio management, and a web dashboard for analysis.
The platform is built for research and education—enabling systematic exploration of algorithmic trading strategies while emphasizing risk management, performance tracking, and transparent signal generation.
Key Features
Automated Signal Generation
RSI, MACD, and volume-based technical analysis generate trading signals automatically. Configurable thresholds and cooldown periods prevent overtrading.
Multi-Asset Support
Monitors stocks (large cap, growth tech, small cap), ETFs, and cryptocurrencies. Supports 30+ assets across different market segments.
Risk Management
Position sizing, cooldown periods, portfolio limits, and trade risk fractions prevent overexposure and manage drawdown.
Real-time Execution
Automatic trade execution based on generated signals, with manual override options for fine control.
Performance Tracking
Win rates, P&L analysis, drawdown monitoring, and signal outcome scoring provide comprehensive performance metrics.
Web Dashboard
Streamlit-based interface for live signal monitoring, portfolio management, historical analysis, and trading insights.
What It Does
Signal Generation Engine
CashStra continuously monitors configured assets, applying technical analysis indicators to identify trading opportunities. RSI thresholds detect oversold/overbought conditions. MACD identifies momentum shifts. Volume analysis confirms signal strength. The system generates buy/sell signals automatically, with configurable parameters for sensitivity and cooldown periods.
Automated Execution
When signals are generated, the platform can execute trades automatically based on configured risk parameters. Position sizing uses a trade risk fraction (default 10% of portfolio). Cooldown periods prevent rapid-fire trading on volatile signals. Portfolio limits ensure diversification and prevent concentration risk.
Analytics & Monitoring
Every signal is tracked with outcome scoring—did the trade profit or lose? The system maintains performance metrics: win rates, average returns, best returns, drawdown tracking. Real-time portfolio analytics show current holdings, cash balance, unrealized gains/losses, and total portfolio value over time.
Web Dashboard
The Streamlit dashboard provides multiple views: live signals with real-time market data, signal history with filterable performance analysis, portfolio management with current holdings and P&L, analytics with equity curves and performance charts, and trading insights with volatility analysis and risk metrics.
Supported Assets
CashStra monitors a diverse set of assets across multiple categories:
- Large Cap Stocks: AAPL, GOOGL, MSFT, AMZN, META
- Growth Tech: TSLA, NVDA, PLTR, ROKU, SNAP
- ETFs: SPY, QQQ, ARKK, SOXL, TQQQ
- Energy & Finance: XOM, JPM, BAC, WFC
- Volatile Small Cap: AMC, GME, CLOV, SPCE, RIOT, MARA, COIN, HOOD
- Cryptocurrencies: BTC-USD, ETH-USD, DOGE-USD
Performance Metrics
The platform tracks comprehensive performance data. Recent metrics include:
- Total Signals Tracked: 2,868+
- Win Rate: 16.6%
- Average Return: 0.040%
- Best Return: 6.37%
- System Uptime: 99.9%
These metrics demonstrate the platform's capability to generate and track signals systematically, providing data for strategy refinement and performance analysis.
Architecture
CashStra follows a modular architecture with clear separation of concerns:
- Core Layer: Configuration, constants, and exception handling
- Data Layer: Market data fetching (yfinance), storage (SQLAlchemy), and models
- Strategy Layer: Signal generation, technical analysis, and signal tracking
- Trading Layer: Trade execution, portfolio management, and position tracking
- Monitoring Layer: Analytics, health checks, performance tracking, and reporting
- Utils Layer: Caching, circuit breakers, and utility functions
Research & Education Focus
CashStra is built for research and educational purposes. It provides a complete platform for exploring algorithmic trading strategies, understanding how technical indicators perform in practice, and analyzing systematic trading approaches. The transparent signal generation, comprehensive tracking, and detailed analytics make it valuable for learning and experimentation.
Educational Value:
- Understand how technical analysis indicators work in practice
- Explore systematic trading strategies with real market data
- Learn about risk management and portfolio construction
- Analyze performance patterns and strategy effectiveness
- Experiment with different parameters and configurations
What This Explores
CashStra enables systematic exploration of algorithmic trading questions:
- How do technical indicators perform across different asset classes?
- What win rates and return profiles emerge from systematic strategies?
- How do risk management parameters affect performance?
- Can automated signal generation outperform manual trading approaches?
- What patterns emerge in signal performance over time?
Status
This page is a public concept note—shared for discussion and posterity. CashStra is an active platform for algorithmic trading research and education. The codebase is open source (MIT License) and available for exploration, contribution, and educational use.