Avramov, D. T. Chordia, and A. Goyal, 2006, “The Impact of Trades on Daily Volatility,” Review of Financial Studies, Vol. 19, pp. 1241-277.
Bhattacharya, U., and N. Galpin, 2010, “The Global Rise of the Value-Weighted Portfolio,” Journal of Financial and Quantitative Analysis, forthcoming.
Chan, K., and A. Hameed, 2006, “Stock Price Synchronicity and Analyst Coverage in Emerging Markets,” Journal of Financial Economics, Vol. 80, pp. 115-47.
Chen, H., G. Noronha, and V. Singal, 2004, “The Price Response to S&P 500 Index Additions and Deletions: Evidence of Asymmetry and a New Explanation,” Journal of Finance, Vol. 59, pp. 1901-929.
Coakley, J., P. Kougoulis, and P. Nankervis, 2008, “The MSCI-Canada Index Rebalancing and Excess Comovement,” Applied Financial Economics, Vol. 18, pp. 1277-287.
De Nicolo, G., L. Laeven, and K. Ueda, 2008, “Corporate Governance Quality: Trends and Real Effects,” Journal of Financial Intermediation, Vol. 17, pp. 407-38.
Denis, D. J. Mcconnell, A. Ovtchinnikov, and Y. Yu, 2003, “S&P Index Additions and Earnings Expectations,” Journal of Finance, Vol. 58, pp. 1821-840.
Djankov, S., C. McLiesh, and A. Shleifer, 2007, “Private Credit in 129 Countries,” Journal of Financial Economics, Vol. 84, pp. 299-329.
Eliott, W., B. Van Ness, M. Walker, and R. Warr, 2006, “What Drives the S&P Inclusion Effect? An Analytical Survey,” Financial Management, Vol. 35, pp. 31-48.
Ferreira, M., and P. Matos, 2008, “The Colors of Investors’ Money: The Role of Institutional Investors around the World,” Journal of Financial Economics, Vol. 88, pp. 499–533.
Giannetti, M., and L. Laeven, 2009, “Pension Reform, Ownership Structure, and Corporate Governance: Evidence from Sweden,” Review of Financial Studies, Vol. 22, pp. 4091-127.
Gompers, P., and A. Metrick, 2001, “Institutional Investors and Equity Prices,” Quarterly Journal of Economics, Vol. 116, pp. 229-59.
Greenwood, R., 2008, “Excess Comovement and Stock Returns; Evidence from Cross-sectional Variation in Nikkei 225 Weights” Review of Financial Studies, Vol. 21, pp. 1153-186.
Greenwood, R., and N. Sosner, 2007, “Trading Patterns and Excess Comovement of Stock Returns,” Financial Analysts Journal, Vol. 63, pp. 69-81.
Grout, P., W. Megginson, and A. Zalewska, 2009, “One Half-Billion Shareholders and Counting—Determinants of Individual Share Ownership around the World,” unpublished manuscript, University of Oklahoma.
Harford, J., and A. Kaul, 2005, “Correlated Order Flow: Pervasiveness, Sources and Pricing Effects,” Journal of Financial and Quantitative Analysis, Vol. 40, pp. 29-55.
Harris, L., and E. Gurel, 1986, “Price and Volume Effects Associated with Changes in the S&P 500 List: New Evidence for the Existence of Price Pressures,” Journal of Finance, Vol. 41, pp. 815-29.
Hegde, S., and J. McDermott, 2003, “The Liquidity Effects of Revisions to the S&P 500 Index: An Empirical Analysis,” Journal of Financial Markets, Vol. 6, pp. 413–459.
Jin, L., and S. Myers, 2006, “R2 around the World: New Theory and New Tests,” Journal of Financial Economics, Vol. 79, pp. 257–92.
Kamara, A, X. Lou, and R. Sadka, 2008, “The Divergence of Liquidity Commonality in the Cross-section of Stocks,” Journal of Financial Economics, Vol. 89, pp. 444–66.
Kang, J. K., and R. Stulz, 1997, “Why Is There a Home Bias? An Analysis of Foreign Portfolio Equity Ownership in Japan,” Journal of Financial Economics, Vol. 46, pp. 3-28.
Kaul, A., V. Mehrotra, and R. Morck, 2000, “Demand Curves for Stocks Do Slope Down: New Evidence from an Index Weights Adjustment,” Journal of Finance, Vol. 55, pp. 893-912.
Kaul, A., V. Mehrotra, and C. Stefanescu, 2008, “Do Stock Exchanges Corral Investors into Herding?” unpublished manuscript, University of Alberta.
Morck, R., B. Yeung, and W. Yu, 2000, “The Information Content of Stock Markets: Why Do Emerging Markets Have Synchronous Stock Price Movements?” Journal of Financial Economics, Vol. 58, pp. 215-60.
Zun, S., 2008, “Clustered Institutional Holdings and Stock Comovement,” unpublished manuscript, University of California, Irvine.
We thank Doron Avramov, Eugene Kandel, Luc Laeven, Shiki Levi, Randall Morck, seminar participants at the IMF, Korea University, and the University of Alberta and two anonymous referees for very helpful comments and suggestions. We would also like to thank Zeynep Elif Aksoy and Mohsan Bilal for extensive and excellent research assistance and to Gregorio Impavido for sharing data on institutional investors. This project was initiated while Yishay Yafeh was Resident Scholar at the IMF Research Department and their hospitality is gratefully acknowledged. Yafeh also acknowledges financial support from the Krueger Center at the Hebrew University School of Business.
The two phenomena are obviously related; however, we are not aware of any study documenting the extent to which the stock price response to the announcement of inclusion in an index is related to the subsequent increase in comovement. Data constraints (and in particular, unknown announcement dates) for most countries in our sample prevent us from pursuing this direction in the present study.
The assumption that index inclusions contain no information is standard in the literature, although studies such as Denis et al. (2003) or Cai (2007) challenge it. However, Kaul et al. (2000) and Boyer (2008) provide convincing evidence that changes in the structure of stock indices elicit changes in stock prices without conveying new information.
This idea is related to earlier work by Pindyck and Rotemberg (1993) who examine if stocks co-move in response to macroeconomic news.
The two BSW comovement theories are not exhaustive of course; other possible reductions in market frictions and trading inefficiencies may accompany index inclusion and lead to increased comovement. Some technical factors could also account for this phenomenon. We explore some of these below.
De Nicolo, Laeven and Ueda (2008) for example, report declines in the degree of stock price synchronicity for most countries in recent years, which they view as suggestive evidence of better incorporation of information.
One interpretation of this is that, in some countries, analysts generate aggregate (rather than firm-specific) information (e.g., Chan and Hameed, 2006) and this aggregate information is incorporated more quickly into the prices of index-included stocks, resulting in increased comovement.
See also a short study by Coakley et al. (2008) documenting changes in comovement following inclusion in (deletion from) the MSCI Canada index.
Data constraints prevent further broadening of the sample both across countries and over time. For many stock markets, data are not available on index composition, especially in early years. Sometimes, the number of stocks included over the sample period is too small for country analysis. In some countries, stocks appear to be included and excluded multiple times within a short period, so that the calculation of pre- and post-inclusion statistics is impossible.
One example is India where, because of data availability constraints, we use the NIFTY index whereas the largest exchange traded funds (and probably institutional investors) may track the MSCI India index. If the NIFTY is not the most natural or popular “habitat” for investors in India, then our tests would be biased against finding post-inclusion increases in comovement. We do find, however, that the weight of an index in total market capitalization has no clear association with the increase in comovement, suggesting that there is no systematic bias due to the overall coverage of the index we use. In passing, we note that the popular MSCI indices are published by Morgan Stanley and are not official publications of any stock exchange. Therefore, changes in the composition of these indices are not as widely announced as changes in the composition of “official” indices.
Some studies, including BSW, estimate also bivariate betas between the added firm’s stock returns and those of the main index and of non-index stocks (e.g., non-S&P 500 returns in the US). This is not feasible for most countries in our sample (except the financial centers of the US, UK and Japan) because the “non-index” component of the stock market is typically small and data on non-index returns are often not available. Another feature of some studies is the use of index exclusions (deletions) data; we discuss this issue briefly towards the end of the paper.
Under the null hypothesis that, following inclusion in an index neither beta nor R2 should change, and assuming that the sign of the change in comovement in the entire sample has a binomial distribution with a “success” probability of ½, the expected number of countries with a positive change in comovement is 20, with a variance (standard deviation) of 10 (3.16). The null hypothesis of no change in comovement is then rejected for the daily beta and both the daily and weekly R2 at a 95% confidence level; for the weekly beta the level of confidence is slightly lower.
Interestingly, unlike previous studies, the index inclusion effects in the US are manifest in an increase in R2 and turnover, but not in an increase in beta. When we break down the sample period, we observe an increase in the daily beta following inclusions in the first half of the sample (up to 2005) but not in subsequent years (except for a small increase in 2009). These differences, however, are less pronounced in weekly data. One possible explanation could be that firms added to the S&P index in recent years had high pre-inclusion betas, an issue we return to below. It is too early to tell whether the patterns we observe for the US are due to the specific properties of the sample we use or whether they signify a longer-lasting change.
In untabulated specifications, we find some evidence of higher index inclusion effects in financial systems which belong to the common law tradition, perhaps because of the larger presence of index-prone financial institutions in these markets, an effect we explore below more specifically.
For example, global ETF assets have gone up from about $74 billion in 2000 to $1036 billion in 2010 (BlackRock, v2010).
We examine, for example, the meeting protocols of the investment committee of one Israeli institutional investor and find them consistent with the view that a large portion of the assets are allocated to firms in major indices, either directly or through exchange traded funds; the protocols clearly indicate also that the overall investment results are evaluated against benchmark indices. Further anecdotal support can be drawn from the time when Israel’s stock market was reclassified and included in indices of developed (rather than emerging) markets. The shift was extensively covered in the financial press for its possible effects on changes in demand for Israeli stocks by foreign institutional investors (e.g., a special report published by Bank HaPoalim, Israel’s second largest bank, on March 21, 2010).
Information on the extent of index-based investment is not available even for the most sophisticated markets, largely due to the difficulty in defining index-following. Moreover, even information on the value of all exchange traded funds following a particular index is not available on a consistent basis for all countries and indices. Information on the presence of institutional investors in equity markets is also, surprisingly, incomplete. Ferreira and Matos (2008) generate a worldwide data set of holdings by various types of institutional investors; we do not use their data, however, because their figures for some of our main countries (e.g., Australia, Japan) seem very implausible.
The coefficients are also positive, significant and very similar in magnitude when using the change in weekly beta as the dependent variable. They remain positive, but less statistically significant, when the dependent variable is the daily or weekly change in R2. Bhattacharya and Galpin (2010) try to derive measures of the prevalence of what they call “value-weighted” investment across countries, although they readily admit that their estimates for countries other than the US are very imprecise. When we use their measures instead of the measures of institutional investor presence, we find positive coefficients as well but a much lower level of significance.
It is possible that the demand-based view of comovement also predicts a smaller increase in comovement at sufficiently low frequencies because of arbitrage across non-fundamentals-based stock prices. If this is the case, this test cannot distinguish between the two views. BSW write that both the demand-based view and the information-diffusion view “predict that the shifts in beta after inclusion should become weaker at sufficiently low frequencies. Since we expect noise trader sentiment to revert eventually, and even slowly diffusing information to be incorporated eventually, lower-frequency returns, and therefore also lower frequency patterns of comovement, will be more closely tied to fundamentals” (p. 296).
Interestingly, institutional investors and indexing may generate comovement not only through the channels of the demand-based view but also by generating added liquidity: Kamara et al. (2008) find that institutional investors increase what they call the “liquidity beta” (i.e., when institutional investors are present, firm-specific liquidity tends to co-move with average liquidity).
As in the original Vijh (1994) paper, we exclude the two cases where pre-inclusion liquidity is higher than the market average and post-inclusion liquidity is lower, or vice versa, because the theoretical predictions about them are ambiguous.
An early study by Blume (1975) proposes possible mechanical reasons for the convergence of betas to one over time, not necessarily in the context of inclusion in an index.
For instance, if beta is negative and becomes more negative upon exclusion from an index, R2 may well increase (i.e. move in the opposite direction from beta), but these cases are rare in the sample.