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Equity Risk Premium: Expectations Great and Small

This paper explores the Equity Risk Premium (ERP), defined as the difference between market returns and risk-free returns, particularly in the context of US equity markets from 1926 to 2002. It discusses the implications of ERP for actuaries, touching on its role in the Capital Asset Pricing Model (CAPM) and cost of capital estimates. Furthermore, it reviews the nuances of ERP, including different types, estimation methods, and historical data analysis, while addressing unresolved questions about the ERP puzzle and its predictions for future investment returns.

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Equity Risk Premium: Expectations Great and Small

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  1. Equity Risk Premium: Expectations Great and Small Richard A. Derrig and Elisha D. Orr Bowles Symposium April 2003

  2. Equity Risk Premium (ERP) • Definition: Difference between the market return and a risk-free return

  3. US Equity Risk Premia S&P 500 1926-2002 Source: Ibbotson Yearbook (2002) and December 2002 Market Report

  4. Why the ERP is Important for Actuaries ? • Universally accepted benchmark for pricing risk • Input into simple CAPM and Fama-French 3-factor model • Affects other cost of capital estimates and discount rates • Market value of liabilities

  5. Paper Objectives • Introduction to the ERP Puzzle • Types of ERP • Time Series Analysis • Catalogue ERP Puzzle Literature • Selection of an ERP • Summary

  6. ERP Puzzle • Mehra and Prescott (1985): • Anomalous results when historical realized ERP compared to asset pricing theory values • Otherwise, must assume risk aversion level outside of “reasonable” range • Led to literature to solve the “ERP puzzle”

  7. Literature to Solve the Puzzle • 1st thread (Behavioral Finance) • New models and assumptions to explain historical data • 2nd thread • Estimates of the ERP from standard economic models • Catalogue in Appendix B

  8. ERP Types • Geometric vs. arithmetic • Short vs. long investment horizon • Short vs. long run expectation • Unconditional vs. conditional • US vs. international market data • Data sources and periods • Real vs. nominal returns

  9. ERP using same historical data (1926-2002) Source: Ibbotson Yearbook (2002) and December 2002 Market Report

  10. Converting from Geometric to Arithmetic Returns • Formula: AR = GR + var/2, var, variance of the return process

  11. Time Series Analysis • Stationarity Assumption • Supported by ANOVA regressions • ARIMA model projects future years as average of data • No significant time trends • Mean of full Ibbotson series and subset (1960+) not statistically different

  12. Why Different Estimates ? • Historical • 1926-2002 • 1802-2001 (Earlier period) • Dividend Growth Model • Next Ten Years + Remainder of 75 Years • Historical ≠ Expected • Conditional versus Unconditional expectations

  13. Short-Horizon ERP bySub-periods Source: Siegel (1994)

  14. Catalogue of ERP Estimates • Social Security (1999, 2001) • Puzzle Research • Campbell and Shiller (2001) • Arnott and Ryan (2001), Arnott and Bernstein (2002) • Fama and French (2002) • Ibbotson and Chen (2003) • Constantinides (2002)

  15. Catalogue of ERP Estimates (Cont.) • Financial Analyst Estimates • Claus and Thomas (2001) • Harris and Marston (2001) • Surveys • CFOs, Graham and Harvey (2002) • Financial economists, Welch (2000 & 2001) • Behavioral Approach

  16. The Next 10 Years • Social Security • Lower return over next 10 years • Remainder of 75 years likely to be similar to historical returns • Campbell and Shiller • Current P/E and Div/P ratios far from mean • With mean reversion assumption, dismal forecast for next ten years • Market decrease since 1999 is -37.6% or -14.6% annual

  17. TIPSInflation-Indexed Treasury Securities Source: WSJ 2/24/2003

  18. Behavioral Finance • Benartzi and Thaler (1995) • Start with prospect theory • Loss Aversion • Add “mental accounting” • Myopic Loss Aversion

  19. Selecting an ERP • Rely on past data to forecast the future OR • Analyze the past and apply informed judgment as to future differences

  20. What You Need To Know About ERP Estimates • Range of estimates • Appendix B • Data and terminology • Underlying assumptions • Your independent analysis is required if estimate differs from historical average

  21. Where to Go From Here • Ibbotson and Chen (2003) • Appendix C • Fundamental components of the historical ERP • Change estimates based upon good judgment • The puzzle is not yet solved…

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