Quantitative Methods, Financial Data & Programming

  1. F1

    Probability

    The uncertainty layer. What a probability is and what a distribution describes.

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      Topic 01

      Randomness

      Topic 02

      Uncertainty: A Known Shape or an Unknown One

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  2. F2

    Statistics and Inference

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      Topic 01

      Population and Sample: What You Have Versus What You Want to Know

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      Topic 01

      Arithmetic Mean

      Topic 02

      Geometric Mean: Which One Compounds

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      Topic 01

      Statistical Significance

      Topic 02

      Economic Significance

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      Topic 01

      Confidence Interval

      Topic 02

      Prediction Interval: Two Questions

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  3. F3

    Correlation and Regression

    The first relationship. Fitting a line, and everything that makes the fit a lie.

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      Topic 01

      Regression

      Topic 02

      Classification: Size or Label

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  4. F8

    Backtesting and Research Integrity

    Testing a rule on history without fooling yourself. The integrity layer.

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      Topic 01

      Backtest

      Topic 02

      Live Performance: One Rule, Two Records

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  5. F9

    Data Quality and Structure

    What breaks before any method is applied. Missing values, outliers, survivorship and structure.

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      Topic 01

      Structured Data

      Topic 02

      Unstructured Data: What Each Answers

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      Topic 01

      Missing Data

      Topic 02

      Zero: An Empty Cell Against a Real Nothing

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      Topic 01

      Data Validation

      Topic 02

      Data Cleaning: Finding Against Fixing

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  6. F10

    Programming for Finance

    The working toolkit, narrowed to what a finance analyst does rather than what a developer knows.

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      Topic 01

      API

      Topic 02

      CSV File: One Record, Two Deliveries

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