Core Concepts of Quantitative Investing
Quantitative investing is about turning investment decisions into quantifiable rules, using data and models to guide trading. Its core belief is: Data is more reliable than gut feeling. Visit our Strategy Center to explore quantitative stock selection solutions.
Three Core Principles of Quantitative Investing
- Data-Driven: Make decisions with data, not feelings or tips
- Systematic: Only execute when clear rules exist; no rules, no trading
- Backtest Verification: Validate strategies with historical data instead of blind faith
Basic Framework of Quantitative Investing
Layer 1: Data Collection
| Data Type | Examples |
|---|---|
| Price Data | Open, Close, High, Low |
| Volume Data | Daily volume, volume change rate |
| Fundamental Data | P/E, EPS, ROE, Debt Ratio |
| Technical Indicators | MACD, RSI, Bollinger Bands, ATR |
Layer 2: Factor Design
Factors are quantifiable characteristics that affect stock performance:
| Factor Type | Examples | Use Case |
|---|---|---|
| Momentum Factor | Past 6-month return | Trend following |
| Value Factor | Low P/E, Low P/B | Value investing |
| Quality Factor | High ROE, Low debt | Select quality companies |
| Volatility Factor | Low volatility | Risk control |
Layer 3: Strategy Development
Turn factor combinations into executable trading rules:
If (Momentum Factor > 0) AND (Value Factor < Industry Average) AND (Quality Factor > 15%):
Buy
If (Momentum Factor < 0) OR (Stop-loss triggered):
Sell
Layer 4: Backtest Verification
Use historical data to test strategy performance. See Backtesting Basics for more details.
Layer 5: Live Execution
Put verified strategies into practice:
- Start with small capital
- Observe differences between live and backtest results
- Continuously optimize the strategy
Key Performance Metrics
| Metric | Calculation | Target Value |
|---|---|---|
| Annualized Return | Annualized total return | > 10% |
| Maximum Drawdown (MDD) | Historical maximum loss | < 20% |
| Sharpe Ratio | (Return - Risk-free rate) / Volatility | > 1.0 |
| Win Rate | Winning trades / Total trades | 40-60% |
| Profit/Loss Ratio | Average win / Average loss | > 2:1 |
For more risk metrics, refer to Drawdown Management Strategy.
Advantages of Quantitative Investing
| Advantage | Description |
|---|---|
| Objectivity | Let data speak, free from emotional interference |
| Verifiability | Backtests can prove strategy effectiveness |
| Efficiency | Automate processing of large amounts of data |
| Replicability | Good strategies can be reused |
| Controllable Risk | Quantitative models can precisely manage risk exposure |
How to Start Quantitative Investing?
Beginner Stage
- Learn basic technical indicators (MACD, RSI, Moving Averages)
- Build simple screening criteria (e.g., Stock Screener)
- Execute trades manually according to rules
Intermediate Stage
- Learn backtesting methods
- Design your own multi-factor model
- Use quantitative platforms to assist decision-making
Advanced Stage
- Build an automated trading system
- Use machine learning to optimize factor weights
- Manage multi-strategy portfolios
Common Misconceptions
Misconception 1: "Quantitative Investing = Algorithmic Trading"
The core of quantitative investing is rule-based thinking, not code. You can absolutely execute quantitative strategies manually.
Misconception 2: "Quantitative Investing Requires Advanced Math"
Basic quantitative strategies only need addition, subtraction, multiplication, and division. What really matters is writing down your trading logic clearly.
Misconception 3: "Quantitative Strategies Never Lose Money"
Quantitative strategies also have losing periods. Their advantage isnt avoiding losses, but knowing why you lost and being able to systematically improve.
Summary
The core value of quantitative investing:
- From Subjective to Objective -- Replace feelings with data
- From Chaos to System -- Follow clear rules
- From Guesswork to Verification -- Prove strategy effectiveness through backtesting
- From Emotion to Calm -- Rules curb emotional interference, and use the Stock Radar for data-driven decisions
Remember: The essence of quantitative investing is not complex math, but making investment decisions using scientific methods. Start with systematic trading and gradually build your quantitative system.