VOL. XCIV, NO. 247

BOOK BREAKDOWN

NO ADVICE

Intermediate · 2011

What Works on Wall Street: A Guide to the Best-Performing Investment Strategies of All Time

by James P. O'Shaughnessy · Partly Dated

A data-driven, factor-investing playbook: test what has worked historically (value, momentum, size, yield, quality proxies), then implement diversified, rules-based multifactor portfolios with discipline and cost awareness.

Level

Intermediate

Strategies

4 types

Frameworks

5 frameworks

Rating

4.0

Target Audience

Ideal Reader

  • Investors who like evidence, ranking models, and systematic rebalancing
  • People building a quant/factor sleeve (even if the rest is index funds)
  • Anyone who wants a practical bridge from 'factors exist' to 'here’s how to run them'

May Not Suit

  • Readers who want a narrative stock-picking book with company stories
  • Investors unwilling to follow rules through long underperformance stretches
  • Anyone who cannot tolerate big drawdowns (factor portfolios can still drop hard)

Investor Fit

StrategyQuantitative · Value Investing · Growth Investing · Portfolio Management
Time HorizonLong-term (5+ years)
Asset FocusEquities
Math LevelAlgebra
PrerequisitesComfort with basic valuation ratios (P/E, P/S, P/B, EV-based multiples) · Basic portfolio concepts (diversification, rebalancing) · Willingness to implement systematic rules

Key Learnings

  • 1Many popular “rules” are noise; some have long-run edges (on a gross basis)
  • 2Single-factor signals rotate in and out of favor; composites can be more robust than one metric
  • 3Combining value + momentum is a recurring theme in best-performing strategies
  • 4Avoiding the most expensive, most loved “glamour” stocks matters a lot
  • 5Small-cap universes can amplify factor effects but also amplify trading costs and volatility
  • 6Implementation is the real moat: discipline, diversification, turnover control, and patience
  • 7Backtests can look clean; reality adds trading frictions, taxes, and capacity constraints
  • 8Even strong strategies can suffer very large drawdowns—survival and sticking power matter

Frameworks (5)

Formulas (9)

Case Studies (2)

market

Severe bear markets as live stress tests

Takeaway

The model isn’t only about average return; survivability and discipline through crisis regimes are part of the edge.

market

Momentum inversion during emotional bear markets

Takeaway

Momentum can flip in sharp drawdowns; volatility controls and diversification help, but don’t eliminate crash risk.

Mental Models

  • Factor premia: systematic sources of return (value, momentum, size, yield, quality proxies)
  • Ranking beats thresholds: sort by percentiles/deciles and buy the best bucket
  • Composite scoring reduces reliance on any single fragile signal
  • Multifactor hurdles beat single-factor ranking
  • Rebalancing as a structural edge (and behavioral discipline)
  • Expectations matter: what’s popular and expensive tends to disappoint

Key Terms

No glossary terms documented for this book.

Limitations & Caveats

Keep in mind

  • Backtest-heavy: results can be distorted by data snooping and by ignoring trading frictions
  • Implementation details matter more than most readers expect (costs, liquidity, taxes, capacity)
  • Primarily U.S. equity focused; global generalization is not automatic
  • Accounting and market structure evolve; some signals can weaken as they become crowded

Reading Guide

Priority Reading

  1. Factor performance surveys (value, momentum, size, yield)
  2. Multifactor model construction (why and how to combine signals)
  3. Trading frictions / implementation caveats
  4. Sector and universe breakdowns (large vs small)

Optional Sections

  • Very detailed tables once you understand the main conclusions (use as reference later)

Ratings

Rigor
5
Practicality
4
Readability
3
Originality
4
Signal To Noise
4
Longevity
4

Concept Tags

factor_investingmultifactorvaluemomentumrelative_strengthvalue_compositemomentum_compositeprice_to_salesshareholder_yieldebitda_evfree_cash_flow_yieldsmall_capsdecile_analysisbacktestingdata_snooping_biastrading_frictionsturnover

Ready to apply these frameworks?

See concepts from this book applied to real companies with moat scores and segment analysis.

View the moat stocks list

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