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In academic affiliation with Carnegie Mellon University
Institute of Algorithmic Tradingand Applied Computational Finance

Practitioner course in systematic investing

Factor Investing

How equity factors are defined, built and tested: value, momentum, size, quality and low volatility, the construction of long-short factor portfolios, combining factors, and the multiple-testing problem that hides behind hundreds of published factors.

Factor investing replaces stock picking with rules. Instead of judging companies one by one, a factor investor ranks every stock in a universe on a characteristic, such as its price relative to book value, and holds the ones that rank best. The approach underlies a large share of quantitative equity management.

Which factors have the strongest evidence?

Value, momentum, size, profitability and low volatility are the most studied. Each has decades of published evidence and each has had long periods of poor returns, value most notably after 2007. The course sets out the evidence for each factor and the competing explanations for why it might persist.

Why are so many published factors false?

Researchers have tested hundreds of characteristics, and some will look significant by chance. Harvey, Liu and Zhu argued that a new factor should clear a much higher statistical bar than the usual one because of this. You will apply that kind of correction to your own results.

Who is this course for?

Quant equity analysts, portfolio managers and investors who want to understand or build factor strategies. It counts toward the Certificate in Systematic Investing and the Certificate in Quantitative Portfolio Management.

What you will be able to do

  • Define the main equity factors and the evidence behind each.
  • Build long-short factor portfolios from company data.
  • Measure factor returns, exposures and correlations.
  • Combine factors into a multi-factor portfolio and control turnover.
  • Apply multiple-testing corrections when judging a new factor.

Syllabus, module by module

  1. What a factor is

    Characteristics that explain differences in returns; risk and behavioural explanations.

  2. The main factors

    Value, momentum, size, quality, profitability and low volatility, with their evidence.

  3. Building factor portfolios

    Sorting, ranking, weighting, rebalancing and handling sectors.

  4. Data

    Point-in-time fundamentals, reporting lags and survivorship bias.

  5. Combining factors

    Signal blending versus portfolio blending, correlations and turnover.

  6. The factor zoo

    Hundreds of published factors, Harvey, Liu and Zhu, and higher hurdles for new ones.

  7. Project lab

    Supervised work on the assessed factor project.

How the certificate is earned

An assessed project: you construct three factors from company data, test them with costs, combine them into a portfolio, and submit the code with a report. On a pass you receive the Course certificate in Factor Investing, issued by the Institute with a verification code. Read how certification works.

Before you start

Working Python with pandas, regression, and the material of The Capital Asset Pricing Model.

This course counts toward

Questions applicants ask

What is factor investing?

Building portfolios that tilt towards stock characteristics that have been linked to higher returns over long periods, such as cheapness, recent strength or high profitability, using fixed rules rather than individual stock picks.

What is the difference between factor investing and smart beta?

Smart beta is the name commonly used for long-only index funds that tilt towards factors. Factor investing also covers the long-short portfolios used in research and by hedge funds. The course builds both.

$690 24 hours