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A decomposition of portfolio momentum returns
Conflicting explanations on price momentum effects is a potential source of confusion, as they have different implications for portfolio strategy. JAMES SEFTON and ALAN SCOWCROFT believe that price return momentum is driven largely by industry momentum.
he extensive literature on price momentum effects is a potential source of confusion for portfolio managers, as conflicting explanations give rise to different implications for portfolio strategy. Is momentum a stock level phenomenon or is it subsumed by industry or style effects? What are the performance implications of imposing sector or style neutrality? How does price momentum impact estimates of tracking errors or Sharpe ratios?In a value weighted large-cap universe, such as the Global MSCI, we found that price return momentum is driven largely by industry momentum; it does not appear to be explained by individual stock momentum. Further, this return continuation is not a result of either cross-sectional dispersion in industry mean returns, or by varying industry exposure to systematic risk. In small-cap universes stock-specific effects assume greater importance.
Over both our sample periods - January 1992 to March 2003 and January 1980 to March 2003 - value investors would have reduced risk by imposing sector neutrality while growth managers could have profited from both a growth strategy and a momentum strategy by relaxing any sector constraints; though the effects are stronger over the more recent past. In practice, any group of companies sharing a common characteristic has the potential to exhibit price momentum effects. Such a characteristic could be as simple as industry or country or more generally any characteristic that investors expect to affect performance. Controlling the risk in any portfolio therefore requires monitoring style exposure.
UNDERSTANDING MOMENTUM
Although there is broad consensus over the size and duration of any pricing momentum effects, there is no consensus over what is driving them. Whether these violations of market efficiency can be given a behavioural explanation or whether they are due to the rational response of investors to real market constraints is far from clear. There is also no consensus on whether these momentum effects can be found only at a stock level or whether they are pervasive at the industry, country or style levels. The key issues for portfolio strategy are the implications for both alpha generation and risk control.RISK
The implications for risk control are potentially far reaching. The presence of short-term price momentum violates the assumption that each period is independent and as a consequence, the true annual variance and tracking variance of returns would be potentially far greater than 12 times the monthly variance. Scowcroft and Sefton (1999) showed that the presence of short-term price momentum could lead to annual tracking error forecasts being understated by as much as 50%; Gardner, Bowie, Brooks and Cumberworth (2000) made a similar point. If, as appears to be the case in our study, momentum is largely an industry phenomenon then exposure to additional momentum risk can be limited by running an industry neutral fund. If this is not desirable for investment reasons, at least exposure can be monitored easily from the size of any industry tilts.
More generally, any style could exhibit strong momentum if the desired characteristic is currently being ‘priced’ in the market. Such a characteristic could be due to industry momentum but it could be due to any characteristic that investors expect to affect performance. Controlling the risk in any portfolio therefore requires monitoring style exposure too.R ETURN
Momentum has obvious implications for alpha generation. If momentum is largely an industry phenomenon then sector rotation strategies could potentially be designed to capture this alpha at the industry level. However, risk models will underestimate the true risk of these strategies, and so care must be taken in assessing their performance with risk-based measures such as Sharpe ratios.
Further, if momentum is generally an industry phenomenon and inversely correlated to value, value strategies can reduce their risk by constraining the weights to be industry neutral, Asness (1997). More generally, value managers could improve their risk-adjusted performance by constraining their portfolios to be neutral to non-value factors. Similarly, growth is likely to be positively correlated with momentum, and so the imposition of industry neutrality would have a detrimental impact on the performance of growth managers.
DO INDUSTRIES DRIVE MOMENTUM?
There is consensus over the size and duration of these momentum pricing anomalies, but there is no such consensus over what is driving these excess returns. In particular, whether these momentum effects can only be found at the stock level or whether they can be found at the industry or country level too; are the causes specific to the firm or are they common across the industry or country?
The answer has profound importance for portfolio construction. If momentum is an industry phenomenon then fund managers trying to play momentum will need only to take small industry tilts in their portfolios. It does not make sense to run a sector-neutral momentum strategy. Further, they will probably give more weight to strategist views on the likely future industry prospects. For value fund managers it
means that by running sector-neutral portfolios they can reduce their exposure to risk from being inevitably underweight momentum.Alternatively, if price momentum can be found only at the stock level, these recommendations are almost reversed. Momentum managers must pay more attention to news from the analysts on future individual stock prospects and will be able to run lower-risk sectorneutral portfolios. Value managers will need to pay more attention to exposure to momentum so as not to be caught by these medium-term market movements.
THE EVIDENCE FOR INDUSTRY MOMENTUM
Moskowitz and Grinblatt (1999) argued that medium-term momentum profits are driven mainly by an implicit sector-rotation strategy. To demonstrate this, O’Neal (2000) and Swinkels (2002) show that a sector-rotation or sector-momentum strategy generates similar profits to a momentum strategy at the stock level. In the following table, we present similar results for the MSCI global universe. For every period, we rank the 10 MSCI sectors on their performance in the previous J months. The winning portfolio is then the market-cap weighted portfolio of all stocks in the best two performing sectors, and the losing portfolio is a market-cap weighted portfolio of all stocks in the worst two. As earlier, we hold the self-financing portfolio, that is long the winners and short the losers for the following K months. The table then records the average percentage monthly return to these self-financing portfolios over our sample period.
Our shorter data sample, 1992 to 2003, includes the period of the technology bubble, which started in mid 1998 and burst in 2000. An obvious question, is how much of our profits are generated by a momentum play on this bubble? In the second panel of table 1, we repeat the exercise but this time we omit all stocks from the information technology sector from our sample. This omission does reduce profits by about 25% to 50%. However, this also implies that more than 50% of the profits, amounting to an excess return of more than 6% annually, comes from rotation in and out of other sectors. For comparison, in the bottom panel we record the profits to these sector rotation strategies over the longer period 1980 to 2003. These profits are of similar magnitude to those in the
second panel. Therefore, although present, the profits to these sectorrotation strategies were lower in the 1980s than in the 1990s. However, momentum profits were also lower on average over this longer period; in fact, profits to the sector rotation strategy are of the same order as the profits to the portfolio-momentum strategies over this period.
The evidence for country momentum Richards (1997) found some evidence that country rotation – momentum strategies can deliver a small excess profit over the medium term. In the previous section, we estimated the returns to sector rotation strategies and in this section we repeat the experiment but for countries instead. Thus in every month, we rank the 20 countries in our universe on their performance in the previous J months. The winning portfolio is then the market-cap weighted portfolio of all stocks in the best four performing countries, and the losing portfolio is a market-cap weighted portfolio of all stocks in the worst four. The construction process then proceeds as before. Table 2 records the results of these experiments.
Over the period of 1992-2003 and for formation and holding periods of six to 12 months, the excess return to these country rotation strategies are of the order 0.65% per month or about 7.5% annually. In the second panel of table 2 we investigate the proportion of this profit that can attributed to a play on the three smallest countries in our sample: Singapore, Hong Kong and South Korea, during the Asian Crisis of mid 1997 to early 1999. We rerun the experiment having removed all stocks from these countries from our sample. This reduces profits by about 50%. In the bottom panel, we record the profits to country rotation strategies over the longer period of 1980 to 2003. These profits are of similar magnitude to those in the second panel, suggesting that profits to country-rotation strategies were lower over the 1980s than over the 1990s.
WHAT CAUSES RETURN MOMENTUM?
Explaining the momentum pricing anomaly has become one of the principal battlefields between the behaviourists and the rationalists.
The behaviourists almost exclusively focus on the mechanism by which new information, or news, diffuses into prices, if investors are prone to exhibiting various psychological biases. Daniel, Hirshleifer and Subrahmanyam (1998) consider the asymmetries induced by self-attribution bias; the tendency of investors to attribute positive outcomes to skill, and dismiss negative outcomes as bad luck. Selfattribution bias can induce both medium-term momentum, and long-term price overreaction. For following a decision to buy, an investor exhibiting this bias is far more likely to later buy more of the stock should he receive further good news than he is likely to sell if he receives bad news. This asymmetry causes prices to rise too far in the short term, and correct themselves later.
By contrast, Barberis, Shleifer and Vishny’s investors exhibit conservatism. This makes them slow to update their priors in the event of good (bad) news. Therefore, prices do not adjust completely to any new information. Given this, it is more likely that further news will also be positive (negative) and prices will then adjust some more later. This induces short-term return continuation too.
Both mechanisms could induce momentum at the industry level or the stock level. For, if investors focus on industry signals for large-cap firms and firm-specific news for small-cap firms (a form of representativeness bias), then return continuation will be at the industry level for large-cap and at the stock level for small-cap.
The rationalists focus, not on psychological biases, but on how minimally rational investors reacting to unpredictable changes in market conditions could induce these pricing anomalies. Although there is no single paper that has managed to model the medium term momentum effect satisfactorily, there are some promising avenues of research. Empirically, O’Neal (2000) found the winning industries performed well when the default risk premium on high-yield bonds fell. A fall in this premium is suggestive of improving market conditions. Lo and MacKinlay (1999) found that the majority of the momentum effect can be attributed to positive cross auto-covariances and not to simple cross-correlations. By this they mean, that when one stock does well, it is the tendency for similar stocks to do well later, rather than that specific stock, that causes the above average return to these momentum portfolios. These empirical observations are therefore suggestive that as market conditions improve, news slowly diffuses into the prices of similar stocks or stocks in the same industry; after all, industrial classification is just a way of grouping similar stocks. These empirical observations therefore link well with Berk, Green and Naik (1999) who show theoretically that changes in a firm’s growth opportunities, which are related to their systematic risk, can generate medium-term momentum in returns.
James Sefton - Career highlights:
James Sefton is principal scientist at Winton Capital Management and professor of economics at Imperial College’s Tanaka Business School, a CFA Program Partner, and a senior visiting fellow at the National Institute of Economic and Social Research. As an economist, he has led a variety of projects including one to compile the first set of UK Generational Accounts (which now forms the basis of HM Treasury’s annual Long Term Fiscal Sustainability Report), one funded by the Department of Work and Pensions investigating the impact of the means-testing of pension benefits on early retirement and another to build an equilibrium asset allocation model for the HM Revenue and Customs. As an equity analyst, he runs the MBA financial management course at Imperial and was head of global quantitative research at UBS until June 2007. He specialises in understanding asset pricing anomalies and associated equity investment strategies. He has published widely in areas as varied as computable general equilibrium modelling, national accounting, portfolio management and econometrics.