EODHD Academy

Statistics for Market Data

The statistics a price series actually obeys — returns rather than prices, fat tails, volatility that clusters, correlations that flip, averages too noisy to trust — measured on the API's own data, with the pitfalls that turn a correct formula into a wrong number.

4 units · 16 lessons · 65 min read · plus hands-on practice, at your pace

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Why does every analysis start by throwing the prices away?

Returns, Not Prices · 3 min read · practitioner

Start the first lesson

Unit 1 Returns, Not Prices

  1. Why does every analysis start by throwing the prices away? 3 min
  2. What does a day in the S&P 500 look like, statistically? 5 min
  3. How often does a five-sigma day happen, really? 4 min
  4. Why does volatility arrive in clusters? 4 min
Practice Check · Unit 1 A short check · cannot be failed Start

Unit 2 What a Sample Can Say

  1. How many years does it take to know a market's average return? 4 min
  2. What does a t-statistic of 3 mean, and why did finance raise the bar? 4 min
  3. Why does a regression on prices lie? 4 min
  4. What did the dataset forget, and what did it know too early? 4 min
Practice Check · Unit 2 A short check · cannot be failed Start

Unit 3 Dependence

  1. When did stocks and bonds stop moving apart? 4 min
  2. How do two unrelated series come to look related? 4 min
  3. What is the number behind a beta of 1.2? 4 min
  4. Why do correlations rise exactly when you need them low? 4 min
Practice Check · Unit 3 A short check · cannot be failed Start

Unit 4 With the API

  1. Which mistakes turn a correct formula into a wrong return? 5 min
  2. How likely is a −20% year? 4 min
  3. Why does the same question have three answers on the same day? 4 min
  4. Statistics for Market Data checkpoint — the number, with its window 4 min
Practice Check · Unit 4 A short check · cannot be failed Start

Last Course exam

One exam, the whole course Unlocks when you have read all 16 lessons

Passing it earns the course certificate.