Moskowitz–Grinblatt: Industry Momentum

#The Paper at a Glance

Title: Do Industries Explain Momentum? Authors: Tobias J. Moskowitz, Mark Grinblatt Published: Journal of Finance, 1999

By the late 1990s, the momentum effect documented by Jegadeesh and Titman (1993) had been tested across countries, asset classes, and sample periods. It was robust. But an important question remained: where does the signal actually come from? Are the right stocks simply members of hot industries, or is there genuine idiosyncratic momentum that operates regardless of industry membership?

Moskowitz and Grinblatt answered that question with a careful decomposition. Their result reshaped how practitioners think about momentum and about factor-neutral portfolio construction.

#What the Paper Found

Industry-Sorted Portfolios

The authors first formed portfolios based on lagged industry returns. They sorted industries (not stocks) on past 6-12 month performance, bought the top-ranking industries, shorted the bottom-ranking industries, and held for 1 to 12 months. The long-short spread was economically and statistically significant. Winner industries kept winning, and loser industries kept losing.

Stock-Level Decomposition

They then decomposed the standard Jegadeesh-Titman momentum return into two pieces: the return attributable to industry membership, and the residual attributable to within-industry stock selection. The industry component dominated. Once they stripped out industry returns, the residual individual-stock momentum was much smaller and, at some horizons, no longer statistically significant.

Implementation Simplicity

Industry momentum was easier to implement than stock-level momentum. With roughly 20 to 50 industry portfolios instead of thousands of individual names, transaction costs were lower, turnover was lower, and capacity was higher. For practitioners running real money, this was a material advantage.

Cross-Sectional Scope

The result was robust across the full cross-section of NYSE and NASDAQ stocks through the sample window, and it held in sub-periods. Industry persistence was strongest at horizons of 1 to 6 months, consistent with the short-to-medium term continuation that Jegadeesh and Titman had documented in individual stocks.

Not a Risk Explanation

A natural challenge was that industry momentum might simply reflect time-varying industry risk premia. The authors addressed this directly. Controlling for standard factor exposures — market, size, book-to-market — did not eliminate industry momentum. Whatever it was, it was not merely compensation for known factor risks.

#The Math (Lite)

The decomposition intuition is straightforward. The return on stock i can be written as the return on its industry plus a residual:

r_i,t = r_industry(i),t + epsilon_i,t

The Jegadeesh-Titman momentum signal ranks stocks by cumulative past returns. That ranking implicitly sorts on both the industry and the residual component. Moskowitz and Grinblatt separated them.

Form two signals:

signal_industry_momentum = cumulative past return of the stock's industry
signal_residual_momentum = cumulative past return of the stock minus the cumulative past industry return

Then regress future returns on both signals. The industry signal received the larger loading; the residual signal shrank toward zero once the industry signal was included. In portfolio terms:

R_standard_momentum = R_industry_momentum + R_residual_momentum

and empirically R_industry_momentum captures most of the standard momentum premium.

#How Blank Capital Research Uses This

We weight momentum at 25% of our composite score, alongside five other factors:

Moskowitz-Grinblatt directly shapes our implementation choices in two ways. First, we measure cross-sectional momentum relative to industry peers whenever possible. A stock with a strong absolute 12-month return that merely matches its industry average is not getting credit for a true stock-specific signal. Second, we place explicit sector and industry caps on the final portfolio so that the momentum component does not silently concentrate us in whatever sector is currently hot. Investors who fail to do this can find themselves with a "momentum" portfolio that is really a thinly-disguised long-technology, short-utility bet.

The Quality (30%) and Stability (10%) factors also indirectly neutralize some unwanted industry drift, because they respond to company-specific profitability and earnings volatility rather than to sector-level price action.

#Practitioner Watch-Outs

• Industry definition matters. GICS industry codes, Fama-French industries, SIC codes, and modern data-driven clusterings produce meaningfully different results. Pick a definition and stick with it; backtest both crisp and fuzzy versions.
• Concentration risk is real. A pure industry-momentum portfolio can accidentally bet heavily on a small number of industries. Impose per-industry caps.
• Turnover and transaction costs. Industry momentum has lower turnover than stock momentum, but still meaningful turnover. Estimate costs realistically; many backtests are implicitly long-short with zero slippage.
• Macro regime dependence. Industry momentum has struggled during sharp regime transitions, such as the 2009 rebound and the 2022 style reversal.
• Survivorship and listing changes. Industry membership changes over time as firms reclassify. Map industry codes consistently across the sample.

#See It in Action

• Momentum screener →
• Top momentum stocks →
• Momentum factor page →

#Further Reading

• Moskowitz, T. J., and Grinblatt, M. (1999). "Do Industries Explain Momentum?" Journal of Finance.
• Jegadeesh, N., and Titman, S. (1993). "Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency." Journal of Finance.
• Grundy, B. D., and Martin, J. S. (2001). "Understanding the Nature of the Risks and the Source of the Rewards to Momentum Investing." Review of Financial Studies.
• Asness, C. S., Moskowitz, T. J., and Pedersen, L. H. (2013). "Value and Momentum Everywhere." Journal of Finance.

#Related Factor Explainers

• Jegadeesh & Titman (1993) — Momentum
• Asness: Value-Momentum Everywhere
• Novy-Marx — Gross Profitability
• Carhart Four-Factor