Annotated Bibliography of Selected Momentum Research Papers

 

 

1)       Jegadeesh, N. and Titman, S. “Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency.” Journal of Finance 48 (1993).

Summary:  Generally get the credit for “discovering” momentum in academia.   They show that simple relative strength strategies that rank stocks based on their past 3-12 month cumulative raw returns predict relative performance over the next 3-12 months.  That is, recent (3-12 month) relative winners will continue to be relative winners over the next 3-12 months and recent relative losers will continue to be relative losers over the next 3-12 months.  After 12 months, the effect disappears.  They also showed you couldn't explain these results with the CAPM or other known risk factors (at the time).  They concluded that "underreaction to firm-specific information" was a likely cause for this phenomenon, known to be later called the momentum effect.

2)      Asness, C.S. “Variables that Explain Stock Returns.” Ph.D. Dissertation, University of Chicago (1994).
Summary:  As part of Cliff's dissertation, he wrote a chapter entitled "The Power of Past Stock Returns to Explain Future Stock Returns."  The paper found much of the same evidence as in Jegadeesh and Titman (1993)(see above) and also similarly concluded that state of the art risk models could not explain the results.  The paper went on to show that over the long-term winners and losers revert; with winners underperforming 3 to 5 years out and losers outperforming the market.  In effect, long-term winners became growth stocks who underperformed and long-term losers became value stocks who subsequently outperformed.  This was one of the first papers highlighting that momentum and value may be related and operate over different time horizons.

 

3)       Fama, E.F. and French, K.R. “Multifactor Explanations of Asset Pricing Anomalies.” Journal of Finance 51 (1996).
Summary:  Studied all the so-called market anomalies in a unified framework to see how much of them were redundant, by comparing them to the Fama-French three factor model consisting of a market index, a size factor, and a value factor.  Found that the only anomaly to survive and not be captured by the size effect and value effect was momentum.  In fact, momentum still remains the largest discrepancy to the Fama-French model.

 

4)       Chan, Louis K.C., Narasimhan Jegadeesh, and Josef Lakonishok “Momentum  Strategies.”  Journal of Finance 51, no. 5 pp. 1681-1713 (1996).
Summary:  Study the evidence and overlap between price and earnings momentum and find that while they are correlated (about 0.60), there is evidence that an investor can benefit from both price and earnings momentum.  A stronger momentum signal is given when both prices and earnings are moving in the same direction.

 

5)       Asness, C.S. “The Interaction Between Value and Momentum Strategies.” Financial Analysts Journal, March/April (1997).

Summary:  First to really explore the relation between value and momentum strategies as well as their interaction.  Value tends to be strongest among low-momentum (loser) stocks and weakest among high-momentum (winner) stocks. Momentum strategies work in general but are even more effective among high-growth stocks.

6)       Carhart, M. “On Persistence in Mutual Fund Performance.” Journal of Finance 53 (1997).

Summary:  First to think about momentum as a benchmarked style or factor to explain returns.  Augmented the three factor Fama-French model with a fourth factor based on momentum and used this model to evaluate mutual fund performance.  The momentum factor made a large contribution to the explanatory power of the model.  Also, use of a momentum factor indicates that momentum stocks are correlated with each other. 

After Fama and French (1996) and Carhart (1997), the standard of any asset pricing study is to now adjust for size, value, and momentum.

 

7)       Asness, C.S., Liew, J. and Stevens, R. “Parallels Between the Cross-sectional Predictability of Stock and Country Returns.” Journal of Portfolio Management 23 (1997).

Summary:  Found that using momentum strategies across country indices also works well.  There is momentum in returns even at the country level.  Some of the momentum at the country level is driven by currencies (hence, there is currency momentum as well), but even absent currency effects there is substantial momentum among country equity indices.

 

8)       Rouwenhorst, K.G. “International Momentum Strategies.” Journal of Finance 53 (1998).
Summary:  Found that stock momentum was just as present in European markets as it is in the U.S.

 

9)       Rouwenhorst, K.G. “Local Return Factors and Turnover in Emerging Stock Markets.” Journal of Finance 54 (1999).

Summary:  Found that stock momentum was also very strong in emerging markets.

First set of behavioral theories for momentum surface:

 

10)    Daniel, K., Hirshleifer, D., Subrahmanyam, A., "Investor psychology and security market under- and over-reactions." Journal of Finance 53, 1839–1886, (1998).

Summary:  Behavioral model where an investor exhibits overconfidence and self-attribution bias that causes delayed overreaction to information in markets, which produces momentum in the short-run and reversals (a.k.a. the value effect) in the long-run.

 

11)    Barberis, N., Shleifer, A., Vishny, R. "A Model of Investor Sentiment." Journal of Financial Economics 49, 307–343, (1998).
Summary:  Behavioral model where an investor extrapolates trends that cause momentum in markets for a short period of time that eventually reverse.

12)    Hong, H., Stein, J.C. "A unified theory of underreaction, momentum trading, and overreaction in asset markets." Journal of Finance 54, 2143–2184, (1999).
Summary:  Behavioral model where investors underreact to information causing momentum that arbitrageurs try to exploit and eventually cause reversals.

 

13)   Moskowitz, T.J., Grinblatt, M.  "Do Industries Explain Momentum?"  Journal of Finance 54,1249–1290, (1999).

Summary:  Found momentum works extremely well among industry and sector portfolios.  Furthermore, the tremendous industry momentum contributes a lot to the momentum effect in stock returns, particularly among large-cap stocks.  Also found that industry momentum works more quickly and at shorter horizons than regular stock momentum.

14)   Asness, C.S., Burt Porter, and Ross Stevens, "Predicting Stock Returns Using Industry-Relative Firm Characteristics", working paper AQR Capital, (2000).
Summary:  Further break down the inter and intra-industry components of momentum, finding that both a strong industry and within-industry momentum effect is present.  Combining both features can enhance an overall momentum strategy.  Also found these effects to reside even among the most liquid stocks.


15)   Grundy, B. F. and Martin, S.R. “Understanding the Nature of the Risks and the Source of the Rewards to Momentum Investing.” Review of Financial Studies 14 (2001).

Summary:  Recognized and analyzed that buying relative winners and selling losers naturally exposes you to more market beta when the market is doing well and to less market exposure when the market recently did poorly.  This effect, however, only deepens the puzzle associated with momentum as momentum generates even more excess returns after adjusting for the temporal shift in beta.  Also analyzed industry effects and found they were more important for large cap stock momentum and much less so for small cap stock momentum.  Finally, looked at trading costs and concluded costs would have to be large to wipe out the profits associated with momentum trading.

 

16)   Hong, H., Lim, T., Stein, J.C. "Bad news travels slowly: size, analyst coverage, and the profitability of momentum strategies." Journal of Finance 55, 265–296, (1999).

Summary:  Found that momentum is strongest among small cap stocks (excluding micro cap) and low analyst covered stocks.  Also found these effects to be more potent for losers than winners.  Slow reaction to information seems to be stronger when it is bad news and in particular among stocks that are small, risky, and poorly covered by analysts.  These are precisely the stocks where the efficiency of information is likely to be weakest.

 

17)   Lee, C., Swaminathan, B. "Price momentum and trading volume." Journal of Finance 55, 2017–2070, (2000).

Summary:  Found that momentum is strongest among stocks with high turnover and that these stocks also experience greater subsequent reversals in the long-run.  Momentum is strongest where most trading activity is taking place.

 

18)   Jegadeesh, N., Titman, S. “Profitability of Momentum Strategies: An Evaluation of Alternative Explanations.” Journal of Finance 56 (2001).

Summary:  Provided out of sample evidence that momentum worked just as well in the decade following its original sample of study.  Evaluated various explanations for momentum and concluded that risk-based or trading cost stories cannot explain why momentum works and that behavioral stories are more promising.

19)    Grinblatt, M., T.J. Moskowitz.  “Predicting Stock Price Movements from Past Returns: The Role of Consistency and Tax-Loss Selling,” Journal of Financial Economics Vol.71 No. 3, 541-579. (2004)
Summary:  Found that momentum contains a strong seasonal at the turn-of-the year that is related to tax-motivated trading.  Momentum is strongest in December and weakest in January, primarily driven by the losers performing terribly in December and reasonably well in January.  These effects are magnified when capital gains tax rates increase from year-to-year.  Also find that the consistency of the past return matters, where consistent winners over the last year outperform inconsistent winners who may have only had on or two lucky months over the past year.  Also provided out of sample evidence on the performance of momentum outside of its initial sample of study.  Momentum appeared to work just as well in the out of sample period as it did in its original sample.

20)    Griffin, J., Ji, S. and Martin, S. “Global Momentum Strategies: A Portfolio Perspective.” Journal of Portfolio Management (2005).
Summary:  Examined price and earnings momentum within 40 different international stock markets. Momentum seems to be a phenomenon present in almost every market, providing a rich out of sample test.

 

21)   Hvidkjaer, S. "A Trade-Based Analysis of Momentum. “A Trade-based Analysis of Momentum.” Review of Financial Studies 19, no. 2, 457–491, (2006).

Summary:  Found that using momentum strategies across country indices also works well.  There is momentum in returns even at the country level.  Some of the momentum at the country level is driven by currencies (hence, there is currency momentum as well), but even absent currency effects there is substantial momentum among country equity indices.

 

22)    Grinblatt, M. and Han, B. “Prospect Theory, Mental Accounting, and Momentum.” Journal of Financial Economics (2005).
Summary:  Tested a specific behavioral theory called the disposition effect and its influence on momentum in markets. The disposition effect is the tendency for investors to hang on to losers too long and sell winners too quickly, thus causing good news to be incorporated slowly into past winners and bad news to be incorporated into past losers more slowly.  Testing this idea using volume and return data, they find that it the disposition effect may drive a substantial component of stock momentum.

 

23)   Frazzini, A. “The Disposition Effect and Underreaction to News.” Journal of Finance, 61 (2006).

Summary:  Tested the disposition effect and its influence on momentum using mutual fund manager positions and trades where one can estimate reasonably well the average capital gain and loss overhang of all managers in each stock.  Using this data, the study found that stocks more prone to the dispostion effect drove a great deal of the momentum anomaly.

 

24)    Fama, E.F. and French, K.R. “Dissecting Anomalies.” Journal of Finance 63 (2008).
Summary
:  An update to their 1996 paper on anomalies, Fama and French start out by noting that "momentum is pervasive."  They find that momentum is one of the few effects that has withstood the test of time and cannot be captured by their three factor model of size, value, and the general market.

25)   Asness, C.S., Moskowitz, T.J. and Pedersen, L.H. “Value and Momentum Everywhere.” National Bureau of Economic Research Working Paper (2009).

Summary:  Found that momentum (and value) are present in eight different international markets and asset classes that include four national equity markets of individual stocks, country index futures, commodities, government bonds across countries, and currencies.  The out of sample evidence on momentum in eight vastly different asset classes and markets and in the period fifteen years after the original studies indicates that random chance or data mining is not a concern with regard to momentum.  Moreover, the study also shows that the momentum strategies in these different markets and asset classes are highly correlated, suggesting there exists some common theme or source to momentum.  On the other hand, there are still large diversification benefits to be gained by combining momentum strategies across these markets and asset classes.

The opinions and views expressed in the above research papers and/or articles do not necessarily reflect those of AQR Capital Management LLC. These views may not be relied on as investment advice. Additionally, any references to specific company securities should not be construed as a recommendation or investment advice.