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Autonomous Trading Signal Generator
HardML System Design
Design an ML system that generates buy/sell/hold signals for equities trading.
Scenario: A quantitative hedge fund wants to generate trading signals from market data, news sentiment, and alternative data sources. The system must handle regime changes (bull/bear markets) and avoid overfitting to historical patterns.
Your Task: Design the signal generation pipeline.
Key Challenges:
- Non-stationary data (markets change regimes)
- Low signal-to-noise ratio in financial data
- Overfitting and look-ahead bias prevention
- Risk management and position sizing
- Multiple time horizons (intraday, daily, weekly)
Design Mode
📝 Your Design Approach
Describe your system design approach. Consider components, data flow, and key decisions.
🎯 Design Questions(Select all that apply)
Q1.Why is feature engineering particularly challenging for financial ML?
Q2.What is the correct way to backtest a trading strategy?
Q3.How should the system manage risk in its trading signals?
Q4.What model architecture is appropriate for generating trading signals?
0 of 4 questions answered