M1L01: Introduction

1. Fundamental Trading Concepts

  • Objective:

    • Long position: Buy low, sell high
      Profit = Selling Price - Buying Price

    • Short position: Sell high (borrowed), buy low to return
      Profit (short)= Sell Price − Buy-to-Cover Price

2. Information Edge

  • Everyone has access to public data:

    • Financial statements (income statement, balance sheet, cash flow).

    • Technical charts.

  • Key idea: It’s not about having unique data, it’s about:

    • Better interpretation

    • Unique combinations of indicators

3. Data Mining Financial Signals

  • Researchers tested 2.1 million combinations of financial indicators.

  • Most useful predictors:

    • Advertising Expense

      • Indicates management confidence

      • Example: If a firm increases ad spending while maintaining margins, it may forecast strong future sales.

    • Cash Flow from Operations (CFO)

      • More reliable than earnings (less subject to manipulation).

      • Look at:


  • Return on Advertising Spend (ROAS) (used in marketing-focused analysis):

4. Alternative Data for Market Edge

  • Satellite imagery: Count cars in parking lots to estimate sales volume.

  • Credit card data: Real-time tracking of consumer spending behavior.

  • Historical comparison:

    • Charles Dow (1800s): Tracked railcar traffic to measure industrial output.

    • Warren Buffett's "desert island indicator":

      • Railcar Loadings ∝ Future Economic Activity

5. Behavioral Patterns in Retail

  • Seasonal sales behavior:

    • Drop in traffic after holidays

    • Spring boost due to promotions

  • Store traffic as proxy for sales:
    Estimated Sales≈Avg Spend per Visitor×Number of Cars (Visitors)

6. Speaking with Management: Limited Usefulness

  • Regulation FD (Fair Disclosure):

    • Prohibits companies from disclosing material info selectively.

    • Conversations with management are allowed, but not useful for inside info.

✅ Key Takeaways

  • Best investors don’t rely on secret data—they:

    • Use common data differently.

    • Discover statistical edges through testing.

    • Look beyond traditional indicators using creative thinking.

  • Formula-based and empirical insight gives a durable edge if applied consistently.