📖Benjamin Graham

Quantitative Analysis

🌿 Intermediate★★★★★

Investment analysis must be grounded in quantitative data and standardized tests, not subjective opinions.

💬

The analyst's conclusions must always rest upon figures and upon established tests and standards.

— "Security Analysis"，1934

🏠 Everyday Analogy

Just as a traditional Chinese medicine practitioner must observe, listen, inquire, and palpate rather than prescribe based on mere intuition, investment analysis requires examining financial statements, calculating ratios, and comparing historical data—not relying on rumors, gut feelings, or speculative trends. Only through quantitative metrics can an accurate "health check-up" be conducted for a company.

📖 Core Interpretation

Security analysis must be based on data and established criteria, rather than subjective judgment.
💎 Key Insight：Graham pioneered the discipline of security analysis by insisting on objective, reproducible methods. Opinions and narratives are seductive but unreliable. Build your investment process on verifiable numbers: earnings, book value, dividends, and debt ratios. What cannot be measured should not drive decisions.

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❓ Why It Matters

Quantitative analysis reduces bias and provides an objective basis for decision-making.

🎯 How to Practice

Learn financial analysis and utilize standard metrics such as the price-to-earnings ratio and price-to-book ratio.

🎙️ Master's Voice

The intelligent investor is a realist who sells to optimists and buys from pessimists.
Graham made fortunes buying during panics when pessimists sold at any price. He understood that emotional extremes created pricing extremes.

⚔️ Practical Guide

✅ Decision Checklist

  • Am I buying from pessimists?
  • Am I selling to optimists?
  • Is sentiment at an extreme?

📋 Action Steps

  1. Track sentiment indicators
  2. Buy when others are fearful
  3. Sell when others are greedy

🚨 Warning Signs

  • Buying with the crowd
  • Selling in panic
  • Following sentiment

⚠️ Common Pitfalls

✕Numbers Can Be Misleading
✕Understand the meaning behind the numbers.

📚 Case Studies

1
Pre-Crash Overvaluation (1929)
Graham’s quantitative screens revealed extreme overvaluation and weak earnings quality in many industrials before the 1929 crash.
✨ Outcome：Raised cash and reduced speculative holdings, limiting losses when the market collapsed.
2
Net-Net Bargains in Depression (1932)
During the Great Depression, Graham bought stocks trading below net current asset value, including undervalued industrials and utilities.
✨ Outcome：Many positions doubled or more as conditions normalized, validating deep value, balance-sheet-based quantitative methods.

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