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Autonomous Trading Signal Generator

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

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