Chapter

V Institutional Investor Behavior and the Pricing of Developing Country Stocks

Author(s):
International Monetary Fund
Published Date:
September 1995
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In the aftermath of the Mexican crisis, selling pressures were experienced across a broad range of developing country securities markets. One possible explanation for this development stems from the behavior of institutional investors. In particular, these investors appear to have come to treat developing country securities as a separate asset class. Thus, there is the potential for a shift in investor sentiment regarding the asset class to affect all securities in the class, without fully reflecting the economic fundamentals determining expected returns in individual developing country markets.

A Model of Investor Asset Pricing Behavior in Developing Country Stock Markets

In making portfolio choices, individuals allocate their funds to various assets on the basis of relative expected returns and the relative riskiness of all available assets. Risk-neutral investors shift their portfolios toward assets with the highest expected returns, driving up the price of these assets (reducing the expected return) until the expected returns of all available assets are equal. When investors are risk averse, however, they require a higher return to hold assets that are risky relative to the world portfolio (where the world portfolio comprises all equity assets). Reflecting this relationship, standard finance models for equities predict that, after investors have allocated their portfolios, all remaining expected returns in excess of the riskless rate should be a function of the riskiness of each asset’s return and of the sensitivity of the asset to returns on the world portfolio. Events in the aftermath of the Mexican devaluation tend to conflict with the predictions of these models.

To the extent that the crash of the Mexican stock market reflected news solely about Mexican fundamentals, it would have been expected to have had only a very small impact on the world portfolio, since Mexico represents less than 2 percent of global stock market capitalization. With only a small impact on the world portfolio, the impact of the Mexican crash on other developing country stock markets would have been expected to be insignificant. The decline in other developing country stock market prices, particularly within Latin America, in response to the Mexican crash suggests that investors do not analyze these markets solely in the context of global risk factors.

One possible explanation for the spillover effects observed is that investors, seeking to diversify their portfolios globally, treat developing country equities as a separate asset class, first deciding what share of their total portfolio to invest in this asset class, then allocating their funds across developing country markets. The across-the-board, short-term liquidation of developing country equity holdings in the wake of the Mexican devaluation suggests that there was not sufficient differentiation among developing country equity markets based on the risks in individual markets. Investors appeared to have interpreted the Mexican devaluation as an indicator of possible declines in returns in other developing country stock markets, despite the lack of evidence of a common shock to underlying asset fundamentals in all developing country markets.

Asset Pricing If Developing Country Equity Markets Are Treated as a Separate Asset Class

According to the capital asset pricing model (CAPM), a representative investor is expected to hold a portfolio of risky assets identical to the world portfolio.29 The investor would deviate from holding the market portfolio only if by doing so he could improve the efficiency of his individual portfolio (that is, improve his expected return without accepting additional risk). As such, the only factor that should affect the investor’s demand for a particular asset is the sensitivity of that asset’s return to the expected return on the world portfolio.30 This relationship can be expressed as

where rj, t is the return on market j and rw, t is the return on the world portfolio at time t.31 Therefore, if developing country equity markets are part of the global market, the expected return in any given market should be proportional to that market’s covariance with the world portfolio. Higher expected returns in any market would be exploited by investors who would shift funds into that market until the excess returns are eliminated.

The composition of institutional investor portfolios, however, suggests that investors do not determine their holdings solely on the basis of each developing country equity’s relationship to the world portfolio, independent of other factors. In particular, investors have not allocated as much of their portfolios to developing country equities as the CAPM would have suggested based on historical return patterns. Over the period from December 1988 to December 1992, investors could have substantially improved the efficiency of their portfolios, increasing returns without accepting additional risk, by increasing their holdings of developing country equities.32

The low proportion of developing country equities in investor portfolios suggests that investors intentionally limit their developing country holdings to a lower share than potentially optimal. Because many developing country markets are very illiquid, only a few investors could achieve an apparently optimal portfolio allocation between developing and industrial country equities. If all portfolio managers tried to shift simultaneously into developing country equities, stock prices would be quickly driven up, and expected returns driven down, thus reducing the optimal portfolio share of developing country equities. As such, the portfolio share invested in developing country equities may be optimal once liquidity problems are considered. Alternatively, the underallocation of assets to developing country stocks might simply indicate that the realized returns on these securities were much better than expected. However, it is quite possible that investors believe that developing country equities are subject to larger shifts in investor sentiment (than are equities in mature markets) and other classwide risks and, as such, are riskier as a class than the variance of their individual returns might suggest. Moreover, restrictions on institutional investor behavior may contribute to investors’ treating developing country equities as a separate asset class. Dedicated developing country mutual funds are forced to keep the vast majority of their assets in developing country securities at all times, whereas broadly based mutual funds are limited in the proportion of fund assets that can be invested in developing country securities by the portfolio allocation guidelines outlined in their prospectuses.

The standard one-factor asset pricing model represented by equation (1) can be modified to reflect this behavior and to test the proposition that developing country securities are treated as a separate asset class. Accordingly, the expected return in a given developing country equity market would be a function of its covariance with both the expected return on the world portfolio and the expected return on a broad portfolio of developing country stocks:

where rj, t is the return in market j, rw, t is the return on the world portfolio, and rem, t is the return on a portfolio of developing country stocks at time t. The coefficient βem represents the covariance between expected returns in market j and the expected return on a developing country equity portfolio, where the return an investor would require to hold the assets in market j—as opposed to holding the developing country market portfolio—would be an increasing function of that covariance.33 If investors select each asset only on the basis of its relation to the world portfolio, βem should not be significantly different from zero. Any significant βem would be consistent with investors treating developing country equities as a separate class, allocating within that class according to market j’s relationship with returns on the developing country portfolio.34

Estimates of the Asset Pricing Model

Ordinary least-squares (OLS) estimates of the two-factor model of equation (2) indicate that the addition of the developing country market portfolio substantially improves the explanation of returns in individual developing country equity markets relative to the standard CAPM specified in equation (1).35 In weekly data covering the period January 1989 to April 1995, the one-factor CAPM specification can be rejected in favor of the two-factor specification for 8 of 13 markets, including the largest and most liquid of the developing country equity markets (Taiwan Province of China, Malaysia, Mexico, and Brazil) (Table 12).36 The estimated two-factor equations explain up to 63 percent of returns in individual markets, with explanatory power highest in some of the largest and most liquid markets (Malaysia, Mexico, Taiwan Province of China, and Thailand). Explanatory power is very low, however, in markets that are either legally or practically closed to foreign investors (Colombia, India, and Venezuela). Argentina is an interesting exception where the equation has little explanatory power despite the presence of substantial foreign investment. The coefficient on the developing country portfolio is statistically significant in eight markets.37 The coefficient on the world portfolio is significant in 5 of the 13 markets.38

Table 12.Two-Factor Model for 13 Emerging Markets1
MarketWeekly DataMonthly Data
βw (t-statistic)βem (t-statistic)Adj. R2F1,305 (p-value)βw (t-statistic)βem (t-statistic)Adj. R2F1.67 (p-value)
Argentina-0.120.25-0.0030.84-0.320.12-0.0280.03
(0.29)(0.80)(0.36)(0.38)(0.18)(0.85)
Brazil0.261.330.16144.040.251.710.23618.45
(0.86)(5.49)(—)(0.43)(3.95)(—)
Chile-0.080.300.04314.97-0.130.520.0858.03
(0.68)(4.04)(—)(0.50)(3.59)(0.01)
Colombia-0.030.090.0020.71-0.220.05-0.0250.03
(0.30)(0.87)(0.40)(0.52)(0.22)(0.86)
India-0.190.180.0042.70-0.350.10-0.0120.22
(1-12)(1.68)(0.10)(1.17)(0.48)(0.64)
Jordan0.130.090.0141.770.300.010.0210.01
(1.84)(0.95)(0.18)(1.41)(0.11)(0.92)
Korea0.160.430.11928.790.700.290.2334.06
(1.25)(5.43)(—)(3.07)(2.63)(0.05)
Mexico0.320.530.15933.810.040.740.17714.10
(2.44)(4.48)(—)(0.18)(3.96)(—)
Malaysia0.580.410.31343.590.470.390.30111.77
(6.41)(5.10)(—)(2.98)(4.17)(—)
Philippines0.020.631.650.730.490.2246.77
(0.09)(2.39)(0.20)(2.13)(2.35)(0.01)
Taiwan Province of China-0.251.840.627468.25-0.191.680.55078.18
(2.25)(17.19)(—)(-0.85)(8.87)(—)
Thailand0.310.650.20449.400.380.380.0954.05
(1.93)(4.56)(—)(1.22)(1.94)(0.05)
Venezuela-0.27-0.010.0070.01-0.26-0.440.0181.92
(1.11)(0.07)(0.93)(0.58)(-1.31)(0.17)
Sources: IFC Emerging Markets Data Base; Financial Times; and IMF staff estimates.

The existence of region-specific developing country mutual funds also suggests that investors may be managing portfolios on a regional basis. The sharper and more sustained drop in Latin American stock markets after the Mexican devaluation, compared with Asian markets, lends support to this observation. Similarly, Latin American markets were substantially correlated among themselves in the months following the Mexican devaluation but were far less correlated with Asian markets. Perceived common macroeconomic characteristics across Asian and Latin American economies, respectively, support investors’ tendencies to classify markets by region.

If investors made their portfolio allocation decisions by region and considered the relative returns among individual markets only as a second step, then returns in Latin American markets would be a function only of other Latin American markets and not of markets outside the region; the same could be expected to hold among developing country equity markets in Asia. More specifically, returns in Argentina would be a function of their covariance with returns on a portfolio of Latin American equities, but they would not depend on their covariance with returns on a portfolio of developing Asian market equities. For Argentina, βLatAm would be statistically significant and βAsia would be zero:

where rLatAm, t is the return on a Latin American portfolio (proxied by the IFC Global Latin America Return Index) and rAsia, t is the return on an Asian portfolio (proxied by the IFC Global Asia Return Index).39 In OLS estimates of equation (3) for 13 markets over the period January 1989 to April 1995, the results are varied (Table 13).40 The regional portfolio has explanatory power only for returns in Brazil, Chile. Malaysia, and Taiwan Province of China. How-ever, for Mexico and Korea, the IFC Composite portfolio has explanatory power beyond the regional term; the Latin American portfolio return is not statistically significant in explaining Mexican returns, which would be consistent with the view that investors treat Mexican securities as a benchmark for other Latin American country securities.

Table 13.Four-Factor Model For 13 Emerging Markets1
Marketβw (t-statistic)βem (t-statistic)βAsia (t-statistic)βLatAm (t-statistic)Adj. R2 (t-statistic)
Weekly data
Argentina-0.281.12-1.110.470.052
(-0.68)(0.64)(0.92)(0.81)
Brazil-0.11-0.550.422.050.672
(-0.60)(0.61)(0.61)(10.22)
Chile-0.140.030.030.340.151
(-1.26)(0.09)(0.10)(3.05)
Colombia-0.051.26-0.95-0.220.007
(-0.44)(2.39))(2.30)(1.90)
India-0.18-0.510.570.10-0.004
(1.01)(0.83)(1.21)(0.67)
Jordan0.150.48-0.25-0.18-0.026
(2.06)(1.31)(0.99)(1.86)
Korea0.18-0.871.070.210.149
(1.49)(1.96)(3.04)(1.77)
Mexico0.202.11-1.530.120.403
(1.70)(3.12)(-2.97)(0.79)
Malaysia0.60-0.610.850.150.341
(6.39)(1.46)(2.70)(1.46)
Philippines0.02-1.031.260.440.005
(0.05)(-0.76)(1.11)(0.83)
Taiwan Province of China-0.140.381.42-0.120.741
(1.66)(0.96)(4.59)(1.32)
Thailand0.330.280.340.206
(2.03)(0.52)(0.81)(0.02)
Venezuela-0.311.38-1.16-0.190.012
(1.25)(1.95)(2.18)(1.08)
Sources: Financial Times; IFC Emerging Markets Data Base; and IMF staff estimates.

Impact of the Trading Behavior of Institutional Investors on Developing Country Stock Prices

The treatment of developing country securities as a distinct asset class (as discussed above) reflects the rules-based approaches to portfolio allocation generally followed by institutional investors. According to these approaches, institutional investors allocate funds to developing country securities on the basis of fundamental economic factors determining asset returns, as well as other considerations, such as the liquidity of the asset markets and the desire to diversify overall portfolios internationally. As a result, the trading behavior of institutional investors could be another source of inefficiency in developing country financial markets, since these investors at times could push market prices out of line with underlying economic fundamentals.41 If institutional investors were to experience a widespread shift in sentiment away from developing country markets, they could create significant short-run asset price deviations away from fundamentals. Normally, other investors in the markets who tend to trade on the basis of economic fundamentals (commonly referred to in the economic literature as arbitrage traders) would be expected to offset this behavior by buying assets that they viewed as being undervalued.

With the possibility of further shifts in sentiment against the assets, however, the arbitrage traders face the risk that prices will fall even further before eventually returning to a level justified by economic fundamentals. The potential losses to the arbitragers, should they be forced to liquidate when prices are low. May limit their willingness to counteract large shifts in investor sentiment. In this way, the risks stemming from the behavior of institutional investors could create the possibility for self-fulfilling shifts in investor sentiment away from developing country securities—investors sell their portfolio of developing country assets because they expect prices to decline, and prices decline because investors sell.42

Moreover, if institutional investors use past performance of developing country stock markets as a major factor in their investment decisions, shifts in investor sentiment can lead to significant asset price over-shooting. Institutional investors seeking to diversify their portfolios might have little information other than past performance to evaluate the risk/return characteristics of developing country markets. In these circumstances, a decrease in demand for developing country stocks that pushes prices down could trigger further sales as more investors are influenced by the lower returns.43 Rather than counteracting movements in prices away from fundamentals, informed arbitragers might find it advantageous to go along with shifts in market sentiment in the short run even if they know these shifts to be counter to fundamentals (De Long and others (1990)).

The extent to which arbitrage traders might accommodate or reinforce trading behavior that pushes prices away from economic fundamentals will depend on how certain they are of the fundamentals and how long they expect such trading behavior to persist. The distinctly different experiences of Latin American and Asian stock markets in the wake of the Mexican devaluation illustrate this point. In Mexico and other major Latin American countries, arbitragers may have reinforced the sell-off of stocks prompted by shifts in investor sentiment both because of changes in economic fundamentals in these countries, as a consequence of the Mexican devaluation, and because of increased uncertainty about country fundamentals. In contrast, the sell-off may not have been as persistent in Asian stock markets because arbitrage traders’ views regarding economic fundamentals in these countries were not significantly affected by events in Mexico. Thus, these traders moved rather quickly to offset the selling generated by a shift in sentiment against developing country securities. In fact, sentiment may have subsequently shifted in favor of Asian markets, given their stronger performance relative to other developing countries.

Testing for Destabilizing Behavior

To evaluate whether institutional investors may have had a destabilizing influence on developing country stock markets, changes in the behavior of stock prices in these markets are examined between two periods—the first, from 1989 through 1991, when developing country stock markets were undergoing liberalization and the markets were being opened to foreign investors; and the second, from 1992 through the first quarter of 1995, broadly corresponding to the period when institutional investors began to significantly expand their holdings of developing country securities (Chart 11).44

Chart 11.Total Returns in Developing Country Stock Markets

(IFC weekly U.S. dollar Investable Total Return Indices, December 1988 = 100)

Source: International Finance Corporation (IFC), Emerging Markets Data Base.

The test of market stability used is the variance ratio test. It operates on the simple proposition that a stock price should reflect all available information about fundamentals and, under certain conditions, will follow a random walk (that is, the current price will be the best forecast of future prices).45 In the case of a random walk, actual future prices of a stock will remain, on average, within a range that widens linearly over time. Therefore, the variance of the rate of return will increase proportionately with the length of the period the asset is held; if σT is the variance of the rate of return when an asset is held for T weeks and σ1 is the variance when the asset is held one week, then

If instead this ratio is greater than unity, price increases today would signal further price increases in the future (the variance of the rate of return will increase nonlinearly with the length of the period the asset is held). This is equivalent to saying that the variance ratio measures the autocorrelation of rates of return—whether the expected future rate of return is positively (or negatively) related to past rates of return.46 The change in the variance ratios between the two periods for which they are calculated will reflect the change in the degree of autocorrelation of rates of return, allowing inferences to be drawn about the effect of institutional investors on stock price behavior.

Variance Ratio Estimates for Developing Country Stock Markets

If institutional investors have had a stabilizing influence on developing country stock prices, the variance ratio would be expected to decline between the first period (1989-91) and the second period (1992-95), when institutional investors played a larger role in these markets. The opposite, however, appears to have been the case (Table 14), at least for developing country equities as a whole and for Latin American and Asian stock markets taken together on a regional basis. Estimates presented in Table 14 show variance ratios based on a 16-week holding period; and the asymptotic t-statistics are shown to indicate whether the variance ratio is statistically different from unity.47 For the composite indices (the overall, the Asia, and Latin America indices), variance ratios are not significantly different from unity for the period 1989-91. However, the variance ratios increase profoundly for the period after 1991.48 Moreover, there is no sign that the autocorrelation decreases even after allowing for an initial period of learning by new investors; Table 14 shows that variance ratios on the three composite indices are larger for a subperiod beginning in 1994 than for the 1992-93 subperiod.

Table 14.Variance Ratio Test of Weekly Stock Market Returns1
Total Return IndexWeight in Index21989-911992-95 (Q1)1992-94 (Q1)1994: Q2-1995: Q11989-95 (Q1)
Composite1001.083.743.225.202.15
(0.17)(7.69)(5.04)(7.51)(3.88)
Latin America49.71.132.582.483.631.86
(0.33)(4.10)(3.36)(4.73)(3.01)
Argentina4.50.831.611.921.290.92
(-0.38)(1.58)(1.98)(0.43)(-0.19)
Brazil15.91.111.020.872.191.08
(0.25)(0.05)(-0.33)(2.09)(0.26)
Chile2.21.721.411.901.371.65
(2.06)(1.05)(1.97)(0.55)(2.49)
Colombia1.81.991.661.780.642.29
(1.34)(1.75)(1.75)(-0.61)(3.07)
Mexico23.91.682.832.003.832.67
(1.71)(4.01)(2.39)(4.64)(4.90)
Venezuela0.52.200.931.100.541.88
(2.50)(-0.20)(0.24)(-0.66)(2.95)
Asia42.91.332.011.652.301.52
(0.67)(2.49)(1.23)(2.20)(1.50)
Indonesia2.41.611.731.910.801.96
(1.29)(2.12)(2.35)(-0.36)(3.28)
Malaysia22.80.961.431.151.641.13
(-0.09)(1.06)(0.27)(1.11)(0.41)
Pakistan0.91.281.681.801.332.02
(0.43)(1.71)(1.67)(0.54)(2.66)
Philippines3.52.151.431.501.101.79
(3.31)(1.18)(1.11)(0.18)(3.12)
Thailand4.81.381.551.401.591.37
(0.68)(1.48)(0.87)(1.07)(1.00)
Taiwan Province of China2.51.391.531.811.071.25
(0.68)(1.30)(1.71)(0.13)(0.74)
Other
Greece1.52.191.091.240.491.81
(3.21)(0.23)(0.52)(-0.91)(2.83)
Jordan0.20.561.221.120.280.74
(-1.06)(0.49)(0.22)(-1.34)(-0.84)
Portugal1.61.621.591.691.101.51
(1.55)(1.74)(1.74)(0.15)(1.88)
Turkey3.51.941.551.270.541.56
(2.25)(1.14)(0.46)(-0.73)(1.72)
U.S. stock market31.120.470.340.750.87
(0.33)(1.57)(1.67)(0.41)(0.47)
Sources: IFC; Standard and Poor’s; and IMF staff estimates.

An important fact that emerges from the table is that, of the 16 individual country estimates, only the variance ratios for Mexico and Indonesia (and to a lesser extent those for Argentina, Brazil, and Chile) are sufficiently greater than unity in the period 1992-95. In addition, the estimates of the variance ratio on individual markets are less than the estimates on the composite indices in all cases.49 This result is striking because if each composite index simply reflected arbitrary groupings of individual assets, the composites would be expected to show less autocorrelation than each of the individual indices. The results, however, imply that the composites themselves have an importance beyond the sum of their components. This result appears to provide additional confirmation for the argument that institutional investors treat developing country stocks as a separate asset class.

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