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2015 | OriginalPaper | Chapter

25. Market Segmentation and Pricing of Closed-End Country Funds: An Empirical Analysis

Author : Dilip K. Patro

Published in: Handbook of Financial Econometrics and Statistics

Publisher: Springer New York

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Abstract

This paper finds that for closed-end country funds, the international CAPM can be rejected for the underlying securities (NAVs) but not for the share prices. This finding indicates that country fund share prices are determined globally where as the NAVs reflect both global and local prices of risk. Cross-sectional variations in the discounts or premiums for country funds are explained by the differences in the risk exposures of the share prices and the NAVs. Finally, this paper shows that the share price and NAV returns exhibit predictable variation and country fund premiums vary over time due to time-varying risk premiums. The paper employs generalized method of moments (GMM) to estimate stochastic discount factors and examines if the price of risk of closed-end country fund shares and NAVs is identical. GMM is an econometric method that was a generalization of the method of moments developed by Hansen (Econometrica 50, 1029–1054, 1982). Essentially GMM finds the values of the parameters so that the sample moment conditions are satisfied as closely as possible.

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Hence forth both premiums and discounts are referred to as premiums. Therefore, a discount is treated as a negative premium.

In 1993, the World Bank defined an emerging market as a stock market in a developing country with a GNP per capita of $8,625 or less. This is the definition of an emerging market in this paper.

Although the evidence in favor of the domestic CAPM is ambiguous, many studies such as Cumby and Glen (1990) and Chang et al. (1995) do not reject the mean-variance efficiency of the world market index. Interestingly, although Cumby and Glen (1990) do not reject mean-variance efficiency of the world market index, they reject mean-variance efficiency of the US market index.

Stulz and Wasserfallen (1995) use the log-linear approximation of Campbell and Ammer to write the logarithm of the price of a stock as ln(P) = EΣηⁱ[(1 − η)d^t+j+1 − r^t+j+1] + θ, where η is a log-linear approximation parameter and r^t+j+1 is the return from t+j to t+j+1. Assuming that η is the same for prices and NAVs, and the relation holds period by period, the premium can be written as above.

Note that unlike here, Errunza et al. (1998) use returns on industry portfolios to proxy for the US market.

Ferson and Foerster (1994) show that an iterated GMM approach has superior finite sample properties. Therefore the iterated GMM approach is used in the estimations.

For such conditional representation, see, for example, Ferson and Schadt (1996).

See Cochrane (1996) for such specifications. Cochrane (1996) calls such models as “scaled factor models.” See Bansal et al. (1993) for a nonlinear specification of stochastic discount factors.

Unlike industrial initial public offerings (IPOs), closed-end fund IPOs are “overpriced” (Weiss 1989). Peavy (1990) finds that new funds show significant negative returns in the aftermarket. Hanley et al. (1996) argue that closed-end funds are marketed to a poorly informed public and document the presence of flippers – who sell them in the immediate aftermarket. They also document evidence in support of price stabilization in the first few days of trading. Therefore, the first 6 months (24 weeks) of data for each fund is excluded in the empirical analysis.

For some of the funds, such as the India growth fund, the prices and net asset values are as of Wednesday closing. This may lead to nonsynchronous prices and NAVs. However, as Bodurtha et al. (1995) and Hardouvelis et al. (1993) show, the effects of nonsynchronous trading are not pervasive and do not affect the analysis.

Assuming that the price returns and NAV returns are from two normal populations, the test statistic which is the ratio of the variances has an F distribution (if the two variances are estimated using the same sample size). The null hypothesis that the variance of price returns is greater than the variance of NAV returns is tested using this statistic at the 5 % level of significance.

For a set of linear restrictions, the Wald test statistic is given by $ \mathrm{W}=\left[\mathrm{R}\upbeta -\mathrm{r}\right]\prime \left[\mathsf{R}\ \mathsf{Var}\left(\upbeta \right)\ \mathrm{R}\prime \right]\left[\mathrm{R}\upbeta -\mathrm{r}\right] $, where β is the vector of estimated parameters and Rβ = r is the set of linear restrictions.

Risk exposures of the price and NAV returns were also estimated using regional indices in place of the local market indices for the funds from Europe, Latin America, and Asia. These results indicate that, out of the 12 European funds, only two funds’ price returns have significant risk exposure to the MSCI Europe index in the presence of the MSCI world index. Also, out of the seven Latin American funds, all seven price returns and six NAV returns have significant exposure to the Latin American index. Also, out of the 11 Asian funds, nine price returns and eight NAV returns have significant risk exposures to the Asian index.

Other studies such as Cumby and Glen (1990) fail to reject the mean-variance efficiency of the MSCI world market portfolio for national indices of developed markets. Also, Chang et al. (1995) fail to reject the mean-variance efficiency of the MSCI world market index for a sample of developed as well as emerging market indices.

Cochrane (1996) shows that iterated GMM estimates behave badly when there are too many moment conditions (37 in his case).

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Title: Market Segmentation and Pricing of Closed-End Country Funds: An Empirical Analysis
Author: Dilip K. Patro
Publisher: Springer New York
Book: Handbook of Financial Econometrics and Statistics
Print ISBN: 978-1-4614-7749-5

Electronic ISBN: 978-1-4614-7750-1

Copyright Year: 2015
DOI: https://doi.org/10.1007/978-1-4614-7750-1_25