Quantitative Equity Portfolio Management

Equity Models and Valuation

  1. Andrew Alford PhD1,
  2. Robert Jones CFA2,
  3. Terence Lim PhD, CFA3

Published Online: 15 DEC 2012

DOI: 10.1002/9781118182635.efm0048

Encyclopedia of Financial Models

Encyclopedia of Financial Models

How to Cite

Alford, A., Jones, R. and Lim, T. 2012. Quantitative Equity Portfolio Management. Encyclopedia of Financial Models. .

Author Information

  1. 1

    Managing Director, Quantitative Investment Strategies, Goldman Sachs Asset Management

  2. 2

    Chairman, Arwen Advisors and Chairman and CIO, System Two Advisors

  3. 3

    CEO, Arwen Advisors

Publication History

  1. Published Online: 15 DEC 2012


Equity portfolio management has evolved considerably since the 1950s. Portfolio theories and asset pricing models, in conjunction with new data sources and powerful computers, have revolutionized the way investors select stocks and create portfolios. Consequently, what was once mostly an art is increasingly becoming a science: Loose rules of thumb are being replaced by rigorous research and complex implementation. While greatly expanding the frontiers of finance, these advances have not necessarily made it any easier for portfolio managers to outperform the market. The two approaches to equity portfolio management are the traditional approach and the quantitative approach. Despite the contrasting of these two approaches by their advocates, they actually share many traits such as applying economic reasoning to identify a small set of key drivers of equity values, using observable data to quantify these key drivers, using expert judgment to develop ways to map these key drivers into the final stock-selection decision, and evaluating their performance over time. The difference in the two approaches is how they perform these tasks.


  • traditional approach;
  • quantitative approach;
  • forecasts;
  • stock returns;
  • risks;
  • transaction costs;
  • signals;
  • equilibrium expected returns;
  • factor risk model;
  • risk budgeting;
  • tracking error;
  • active return;
  • information ratio;
  • efficient portfolio;
  • optimized portfolio;
  • rule-based portfolio;
  • Growth/Value;
  • Post-earnings-announcement drift;
  • Short-term price reversal;
  • Intermediate-term price momentum;
  • Earnings quality;
  • Stock repurchases;
  • Analyst earnings estimates and stock recommendations