An alternative approach to breaking down total risk (i.e. the total variance of (excess) returns and COE)) consists in, …rst, estimating the cross-sectional variance of stock (excess) returns in a given country at time t (Section 3.4) to capture the systematic component of stock (excess) return volatility, and, second, to divide the latter by the average total stock risk. Table 11 presents some descriptive statistics of these two measures, i.e. total and systematic risk. Recall that these are 12-month rolling window standard deviations. Figures 36 to 39 in the appendix plot the evolution of those variances by country, over the period 1996-2005. Table 12 compares the R-squared obtained from Black- CAPM regressions as discussed in Section 4.3 with the share of systematic risk in total risk measured according to the methodology laid out in Section 3.4.
Total Risk (Vt) Systematic Risk (Vew)
Mean Median Std Dev Mean Median Std Dev
Argentina 0.24 0.22 0.07 0.16 0.14 0.08 Brazil 0.32 0.31 0.08 0.18 0.16 0.08 Chile 0.16 0.16 0.03 0.08 0.08 0.03 Colombia 0.14 0.16 0.07 0.07 0.07 0.05 Mexico 0.18 0.17 0.03 0.10 0.09 0.03 Peru 0.20 0.19 0.06 0.09 0.07 0.05 Venezuela 0.23 0.23 0.04 0.14 0.14 0.06 Country
Table 11: Standard Deviations on Total Returns by country for the whole sample period: 1997-2004.
Table 1247 shows that, on average, systematic risk accounts for 30% of the
total variance in (excess) returns. This …gure is actually close to the average R-squared -32%- we have got from the best Black-CAPM econometric speci…- cations. Also, consistent with the …ndings from the Black-CAPM regressions, the share of systematic risk increases in the cases of Argentina and Venezuela, this time to 41% and 37%, respectively.
4 7Note that Column 1 in table 12 is the result of dividing the square of the …gures in column
4 by the square of the …gures in column 1 in table 11.
Country Systematic Risk / Total Risk Overall average R2 Argentina 0.41 0.44 Brazil 0.33 0.23 Chile 0.28 0.32 Colombia 0.25 0.40 Mexico 0.30 0.44 Peru 0.21 0.29 Venezuela 0.37 0.41
Table 12: Alternative Systematic Risk Measures. Overall averages for the whole sample period: 1997-2004
It is interesting to note that the country displaying the lowest R-squared in Black-CAPM regressions (23%), Brazil, has nevertheless the higher absolute systematic standard deviation with a value of 18.22% (see Table 4.4) . Brazil has also the largest absolute total variance measure. In relative terms, Brazil’s systematic risk share (33%) is not the highest and has a comparable level to that of Mexico(29%) or Chile(28%).
5
Conclusions
This paper provides a unique dataset of comparable COE estimates for Latin America. The dataset includes 921 …rms listed in 7 stock markets (Argentina, Brazil, Chile, Colombia, Mexico, Peru and Venezuela) and looks at the inter- temporal (1997-2004), cross-country and cross-sectoral dimensions of COE.
In order to obtain homogeneous (and robust) CAPM-COE estimates for these Latin American publicly-traded …rms, we introduce a number of method- ological considerations, some of which are "innovative" in the literature of emerging-market stock pricing (test of real market integration or "home bias e¤ect" in stock princing, an alternative method to price sovereign spreads into COE, adjustment for illiquidity, beta robustness and instability, treatment of negative COE estimates and weighting strategies; see Section 3.3),
Our main results can be summarized as follows:
1. Risk-adjusted returns on Latin American stocks are signi…cantly lower than those observed in developed countries. However, Latin American COE estimates (CAPM required returns) are much higher than those in mature markets, reaching an annualized regional average of 24.06% (in US dollars).
2. These results are mainly explained by the underlying extreme uncertainty in Latin American stock markets, in turn related to periods of heightened macroeconomic volatility.
3. Despite the recent increase in …nancial globalization, we …nd a lack of real market integration ("home bias e¤ect") in the case of Latin American
stocks. Therefore, COE estimates should be derived from domestic CAPM speci…cations instead of international versions.Notwithstanding the impli- cations of the latter, we found that "home bias" in stock pricing is slightly decreasing over time.
4. In line with Markowitz’s predictions, there is a clear-cut risk-return (stan- dard deviation-mean) positive trade-o¤ in COE estimates. This is not surprising because a strong relationship between returns and local port- folio risk should be expected when markets are segmented. As a result, the riskiest stock markets (Venezuela and Argentina) are also those asso- ciated with higher average COE estimates, while Chile (the Latin Amer- ican "paradigm" in terms of capital market development and stability) exhibits the lowest risk/return values. The positive risk-return trade-o¤ is also reported across-sectors, with Oil & Gas, Telecommunications and Construction displaying the highest COE means and standard deviations and Pension Funds and Agriculture & Fishing the lowest.
5. Latin American COE estimates are not generally pro-cyclical, which comes in sharp contradiction with the theoretical insights in the literature on de- veloped countries. This is because GDP growth is negatively correlated with sovereign spreads which are an important component of total …nanc- ing costs in emerging markets. If sovereign spread GDP-elasticities are higher in absolute value than those of local market (excess) returns, COE estimates can even be counter-cyclical (e.g. Argentina or Colombia). Put di¤erently, when there is a recession in Latin American countries, the re- duction in the local market premium is o¤set by a rise in the sovereign spread, yielding a-cyclical COE estimates.
6. Using two di¤erent measures of variance decomposition we …nd that indi- vidual returns, and hence COE are mainly driven by idiosyncratic shocks (even in Venezuela or Argentina, the countries with the largest shares of systematic risk in total risk). Consequently, CAPM-COE estimates should be cautiously interpreted because 60% to 70% of the total variance is not explained by the model. In a context of low probability of complete diversi…cation, this may lead to signi…cant misspricing errors.
Our main results may shed light on the causes of Latin American stock market underdevelopment.
On the demand side, excessive systematic risk reduces the risk-adjusted re- turn on Latin American stocks below the level of developed markets. Therefore, why should risk-averse investors hold Latin American stocks in their portfolios if they o¤er relatively small risk-adjusted returns?.
On the supply side, excessive macroeconomic volatility drives high and a- cyclical COE estimates. Then, why should Latin American private sector man-
agers tap stock markets to raise equity …nance if COE estimates are neither low nor ‡exible?.
In the light of the foregoing results, a policy concern should be to dampen the excessive macroeconomic volatility -typically associated with country risk- observed in some Latin American countries studied in this paper, thereby re- ducing the systematic component of risk and ultimately COE. This would make more advantageous for investors to hold Latin American stocks as their risk- adjusted returns would increase and for …rms to raise cheaper equity …nance as COE might fall. Lower COE is a necessary condition for higher investment, sustained long-term growth and poverty-reduction enhancing.
As said before, however, systematic risk in the context of our Black (domes- tic) CAPM regressions only accounts for 30% to 40% of total risk, i.e. it only explains less than half of COE. Other potential sources of systematic risk deal- ing with size (capitalization) and book to market value ratios (Fama and French 1992, 1996 and 1997) or …rm-speci…c variables (idiosyncratic risk not priced in Black-CAPM COE estimates) or both could help explain the remaining 60% to 70% of total variability in COE. An ongoing extension of this research project is looking into the latter potential sources of misspricing.
References
[1] Adler, M., and Dumas, B. (1983), "International Portfolio Selection and Corporation Finance: A Synthesis". Journal of Finance, 38, 925-984. [2] Alexander, G.J. and N. L. Chervany (1980), “On the Estimation and Sta-
bility of Beta,”Journal of Financial and Quantitative Analysis, Vol 15, pp. 123-137.
[3] Altman, E.I., B. Jacquillet, and M. Levasseur (1974), “Comparative Analy- sis of Risk Measures: France and the United States,” Journal of Finance, Vol. 29, 1974, pp. 1495-1511.
[4] Baesel, J.B. (1974), “On the Assessment of Risk: Some Further Consider- ations,” Journal of Finance, Vol. 29, pp. 1491-1494.
[5] Banz, R.W. (1981), “The Relationship Between Return and Market Value of Common Stocks.” Journal of Financial Economics, 9:1, pp. 3-18. [6] Barber, B. M., and T. Odean (2000),"Trading is hazardous to your wealth:
The common stock investment performance of individual investors". Jour- nal of Finance, 55, 773-806.
[7] Barnes, M. and Lopez, J. (2005), "Alternative Measures of the Federal Re- serve Banks’Cost of Equity Capital", Federal Reserve Bank of San Fran- cisco, Working Paper Series, WP 2005-06, San Francisco.
[8] Bennet, J. and Sias, R. (2004), "Why has Firm-Speci…c Risk Increased over Time?". Manuscript, Washington State University: Washington D.C. [9] Black, F. (1972), "Capital Market Equilibrium with Restricted Borrowing".
Journal of Business, 45, pp. 444-55.12.
[10] Black, F., Jensen, M., and Scholes, M. (1972), "The Capital Asset Pric- ing Model: Some Empirical Findings" in Studies in the Theory of Capital Markets, ed. By M. C. Jensen. New York: Praeger
[11] Basu, S. (1977), “Investment Performance of Common Stocks in Relation to Their Price-Earnings Ratios: A Test of the E¢ cient Market Hypothesis.”. Journal of Finance, 12:3, pp. 129-56.
[12] Bhandari, L. C. (1988). “Debt/Equity Ratio and Expected Common Stock Returns: Empirical Evidence”.Journal of Finance, 43:2, pp. 507-28. [13] Bekaert, G., and Harvey, C. R.,(1995) "Time-Varying World Market Inte-
gration," Journal of Finance 50, pp. 403-4.
[14] Bekaert, G., and Harvey, C. R.. (1997a) "Emerging Equity Market Volatil- ity", Journal of Financial. Economics, 43 , 29-77.
[15] Bekaert, G., and Harvey, C. R. (2000) "Foreign Speculators and Emerging Equity Markets", Journal of Finance Vol. 55(2), pp. 565-613.
[16] Bekaert, G., and Harvey, C. R. (2003), “Emerging Markets Finance”, Jour- nal of Empirical Finance, 10, 3-56.
[17] Bekaert, G. & Urias, M. S, (1996). "Diversi…cation, Integration and Emerg- ing Market Closed-End Funds", Journal of Finance, American Finance As- sociation, vol. 51(3), pages 835-69.
[18] Benartzi, S., and R. H. Thaler (2001), "Naïve diversi…cation strategies in de…ned contribution saving plans". American Economic Review 91, 79-98. [19] Boabang, F. (1996), "An adjustment procedure for predicting betas when thin trading is present: Canadian evidence". Journal of Business Finance and Accounting, 23:1333-1355.
[20] Breeden, D. T. (1979), “An intertemporal asset pricing model with sto- chastic consumption and investment opportunities”. Journal of Financial Economics, 7 (1979) 265-296.
[21] Bruner, R., K. Eades, R. Harris, and R. Higgins (1998), "Best
practices in estimating the cost of capital: Survey and syn-
thesis". Financial Practice and Education, Spring/Summer, 13-28.
http://207.36.165.114/JAF/fpess982.pdf.
[22] Caballero, R. J., (2000), "Macroeconomics Volatility In Latin America: A View And Three Case Studies". MIT Department of Economics Working Paper No. 00-10. http://ssrn.com/abstract=233226.
[23] Cao, C., Simin, T. and Zhao, J. (2005), "Do Growth Options Explain the Trend in Idiosyncratic Risk?". Manuscript, Department of Finance at the Pennsylvania State University.
[24] Carrera, J., Feliz, M. and Panigo, D. (1998), "Cuanto se asemejan las economias de Argentina y Brazil. Una comparacion de las regularidades empiricas desde 1980". Economica, XLV, 4, pp 93-163.
[25] Constantinides, G. M., and Du¢ e, D. (1996), "Asset pricing with heteroge- nous consumers", Journal of Political Economy, 104, 219-240.
[26] Damodaran, A. (2002), Investment Valuation. John Wiley and Sons, New York, second Edition.
[27] Daves, P., Ehrhardt, M. and Kunkel, R. (2000), "Estimating systematic risk: The choice of return interval and estimation period", Journal of Fi- nancial and Strategic Decisions, Volume 13, Number 1, Spring.
[28] De la Torre, A. and Schmukler, S. (2004), "Whither Latin American Capital Markets?", Latin American and Caribbean Region, World Bank: Washing- ton D.C.
[29] Dimson E and Marsh P. (1983), "The stability of UK risk measures and the problem of thin trading". Journal of Finance, 38:753-783.
[30] Druck, P. and Morón E. (2001), "The Twin Risks in the Dollarization Debate: Country and Devaluation Risks", manuscript.Sextas Jornadas de Economía Monetaria e Internacional, La Plata, 10 y 11 de mayo.
[31] Dumas, B. and Solnik, B. (1993), "The World Price of Foreign Exchange Risk" NBER Working Paper 4459.
[32] Erb, C., H. Campbell and Viskanta, T. (1995), "Country risk and global equity selection", Journal of Portfolio Management, 21, Winter, 74_83. [33] Fama, E. F. (1996), “Multifactor Portfolio E¢ ciency and Multifactor Asset
Pricing.”. Journal of Financial and Quantitative Analysis, 31:4, pp. 441- 465.
[34] Fama, E. F. and K. R. French (1992), “The Cross-Section of Expected Stock Returns”. Journal of Finance, 47:2, pp. 427-465.
[35] Fama, E. F. and K. R. French (1997), “Industry costs of equity.” Journal of Financial Economics, 43, 153–193.
[36] Fama, E. F and K. R. French, (1998), "Value versus Growth: The Interna- tional Evidence", Journal of Finance, v53, 1975-1999.
[37] Fama, E. F. and K. R. French (2004), “The Capital Asset Pricing Model: Theory and Evidence”. Manuscript.
[38] Fama, E. F. and J. MacBeth (1973), "Risk, return and equilibrium: Em- pirical tests", Journal of Political Economy, 81, 607-636.
[39] Fernandes, N. (2004), "Market Integration and International Asset Alloca- tion", manuscript, Universidade Catolica Portuguesa, May.
[40] Ferson, W. and Jagannathan, R. (1996), "Econometric Evaluation of Asset Pricing Models", Research Department Sta¤ Report 2006, Federal Reserve Bank of Minneapolis, Minneapolis.
[41] Fornero, R. (2002), "Valuacion de empresas en mercados …nancieros emer- gentes. Riesgo de negocio y tasa de actualizacion", manuscript. Universidad Nacional de Cuyo, Marzo.
[42] Galli, M. and Pereiro, L.E. (2000), “La Determinación del
Costo del Capital en la Valuación de Empresas de Capi-
tal Cerrado: una Guía Práctica”. Manuscript, UTDT IAEF.
http://www.utdt.edu/departamentos/empresarial/cif/pdfs-wp/wpcif- 042000.pdf.
[43] Godfrey, S., and R. Espinosa (1996), “A Practical Approach to calculating Costs of Equity for Investments in Emerging Markets,”Journal of Applied Corporate Finance, Fall, 80-89.
[44] Goetzmann, W. N., and A. Kumar (2001), Equity portfolio diversi…cation, Yale ICF Working paper No. 00-59.
[45] Gonedes, N.J. (1973), “Evidence on the Information Content of Accounting Numbers: Accounting-Based and Market-Based Estimates of systematic Risk,”Journal of Financial and Quantitative Analysis, Vol. 8, pp. 407-433. [46] Goyal, A. and Santa Clara, P. (2003)," Idiosyncratic Risk Matters!". Jour-
nal of Finance, VOL. LVIII, No3. June. 975-1007.
[47] Gordon, J. R. and Gordon, M. J., (1997), "The Finite Horizon Expected Return Model" Financial Analysts Journal, vol. 53, no. 3 (May/June):52- 61
[48] Grandes, M., Peter, M. and Pinaud, M. (2003) “The Currency Premium and Local-currency Denominated Debt Costs in South Africa”, OECD De- velopment Centre Working Paper 230
[49] Grootveld, H., and Salomons, R. (2002) "The Equity Risk Premium: Emerging versus Developed Markets" . University of Groningen SOM Working Paper No. 02E45.
[50] Greene, W. H. (2000), Econometric Analysis, 4th ed., Upper Sadle River, NJ, Prentice-Hall.
[51] Hail, L. and Leuz, C. (2004), International Di¤erences in the Cost of Equity Capital: Do Legal Institutions and Securities Regulation Matter?, manu- script, Institute for Accounting and Control, University of Zurich, May. [52] Hansen, L. (1982), "Large sample properties of generalized method of mo-
ments estimators", Econometrica 50, 1029–1054.
[53] Harvey, C.R. (1991), “The World price of Covariance Risk”, Journal of Finance, 46, 111-157.
[54] Harvey, C. R., (1995), "Predictable Risk and Returns in Emerging Mar- kets", Review of Financial Studies, Oxford University Press for Society for Financial Studies, vol. 8(3), pages 773-816.
[55] Hauptman, L. and Stefano N. (1997), "The Cost of Equity in Latin Amer- ica: The eternal doubt", Credit Swisse First Boston, Equity Research, May 20.
[56] Henry, P. B. , (2003). "Capital Account Liberalization, The Cost of Capital, and Economic Growth", American Economic Review, 93(2), May, pp. 91- 96.
[57] Kothari, S., J. Shanken and R. Sloan (1995), “Another look at the cross- section of expected returns.” Journal Finance, 50, 185–224.
[58] Koedijk, K.G and Van Dijk, M.A. (2002), “The Cost of Capital of Cross- Listed Firms” Erasmus University Rotterdam Working Paper
[59] Harris, M., and A. Raviv (1991), "The Theory of Capital Structure," Jour- nal of Finance 46, March 1991, pp. 297-355.
[60] Lam, K. (1999), "Some evidence on the distribution of beta in Hong Kong". Applied Financial Economics, 10:251-262.
[61] Lally, M. (1998), "An examination of Blume and Vasicek betas". Financial Review, 33:183-198.
[62] Lettau, M. and Ludvigson, S. (2002), "Time-varying riskpremia and the cost of capital: An alternative implication of the Q theory of investment". Journal of Monetary Economics, 49: 31–66
[63] Levy, H. (1978), "Equilibrium in an Imperfect Market: A Constraint in the Number of Securities in the Portfolio". The American Economic Review, Vol. 68. No. 4 (Sept., 1978). 643-658.
[64] Lintner, J. (1965), “The Valuation of Risk Assets and the Selection of Risky Investments in Stock Portfolios and Capital Budgets.”Review of Economics and Statistics, 47:1, 13-37.
[65] Mayers, D. (1976), "Nonmarketable assets, market segmentation, and the level of asset prices". Journal of Financial and Quantitative Analysis, 11, 1–12.
[66] Mariscal, J. and Lee, R. (1993), The valuation of Mexican stocks: An ex- tension of the capital asset pricing model, Goldman Sachs, New York. [67] Markowitz, H. (1952), “Portfolio Selection.” Journal of Finance, 7:1, pp.
77-99.
[68] Markowitz, H. (1959), "Portfolio Selection: E¢ cient Diversi…cation of In- vestments". Cowles Foundation Monograph No. 16. New York: John Wiley & Sons, Inc.
[69] Merton, R. C. (1973), “An Intertemporal Capital Asset Pricing Model.” Econometrica. 41:5, pp. 867-887.
[70] Merton, R. C. (1974), "On the pricing of corporate debt: The risk structure of interest rates". Journal of Finance, 29, 449-470.
[71] Mishra, D. R. and O’Brien, T. J., (2001). “A Comparison of Cost of Equity Estimates of Local and Global CAPMs”. Financial Review, 36, 27-48. [72] Mishra, D. R. and O’Brien, T. J., (2004). "Risk and Ex Ante Cost of Equity
Estimates of Emerging Market Firms" Working Paper Series.
[73] Rodriguez Pardina, M. (2005), "La Determinación del Costo de Capital en América Latina. Un Estudio Comparativo de Casos", manuscript. Instituto de Economía, Universidad Argentina de la Empresa (UADE), Septiembre. [74] Roenfeldt, R.L. (1978), G.L. Griepentrof, and C.C. P‡aun, “Further Evi- dence on the Stationarity of Beta Coe¢ cients,” Journal of Financial and Quantitative Analysis, Vol. 13, pp. 117-121.
[75] Roll, R.. (1977), “A Critique of the Asset Pricing Theory’s Tests’ Part I: On Past and Potential Testability of the Theory.” Journal of Financial Economics, 4:2, pp. 129-176.
[76] Rosenberg, B., K. Reid, and R. Lanstein (1985), “Persuasive Evidence of Market Ine¢ ciency.” Journal of Portfolio Management, 11, pp. 9-17. [77] Ross, S. A. (1976), “The Arbitrage Theory of Capital Asset Pricing.”.
Journal of Economic Theory, 13:3, pp. 341-360.
[78] Rouwenhorst, G. K. (1999), "Local Return Factors and Turnover in Emerg- ing Stock Markets," Journal of Finance, American Finance Association, vol. 54(4), pages 1439-1464.
[79] Scholes M and Williams J. (1977), "Estimating betas from non-synchronous data". Journal of Financial Economics, 5:309-328.
[80] Sercu P. (1980), "A Generalization of the International Asset Pricing Model". Revue de l’Association Française de Finance, 1(1), 91-135 [81] Sharpe, W. F. (1964), “Capital Asset Prices: A Theory of Market Equilib-
rium under Conditions of Risk”. Journal of Finance, 19:3, pp. 425-442. [82] Smith, K.V. (1980), “The E¤ect of Intervaling on Estimating Parameters
of the Capital Asset Pricing Model,”Journal of Financial and Quantitative Analysis, Vol. 13, pp. 313-332.
[83] Solnik, B. (1974), "The international Pricing of risk: An Empirical Inves- tigation of the World Capital Market Structure." Journal of Finance, 29. 48-54
[84] Stattman, Dennis. (1980), “Book Values and Stock Returns.”The Chicago MBA: A Journal of Selected Papers, 4, pp.25-45.
[85] Stulz, Rene, (1981), "A model of international asset pricing". Journal of Financial Economics, 9,. 383-406. Page 37. 34.
[86] Stulz, R., (1995a), "The cost of capital in internationally integrated mar- kets: The case of Nestlé". European Financial Management, 1, March, 11-22.
[87] Stulz, R., (1995b), "Globalization of capital markets and the cost of capital: The case of Nestlé". Journal of Applied Corporate Finance, Fall, 30-38. [88] Stulz, René M., (1999), "Globalization of Equity Capital Markets and the
Cost of Capital". NBER Working Papers 7021.
[89] Tanzi, V. (1992), "Structural Factors and Tax Revenue in Developing Coun- tries: A Decade of Evidence". In Goldin, I. and Winters, A. (eds.), Open Economies: Structural Adjustment and Agriculture. New York: Cambridge University Press, pp. 267-89.
[90] Vasicek, O. (1973), “A note on using cross-sectional information in Bayesian estimation of security betas.”. Journal of Finance, 28, 1233–1239.
[91] Wong Dávila, J.C., (2003) “What drives stock re-
turns in Latin America? An analysis of the pe-
riod 1995-2000”, Working Paper, http://www.wiwi.uni-
frankfurt.de/kolleg/alumni/wong/latin_stock_returns.
[92] Zellner, A. (1962), "An E¢ cient Method of Estimating Seemingly Unre- lated Regressions and Tests for Aggregation Bias". Journal of the American Statistical Association, 57, 348-36.
6
Appendix
0 0,05 0,1 0,15 0,2 0,25 0,3 0,35 0,4 0 0,05 0,1 0,15 0,2 0,25 Total Trading Volume as Percentage ofGDP (Liquidity Measure) Percentage of Observati ons Without Trad e (I liquidity M ea sure) Argentina 0 0,05 0,1 0,15 0,2 0,25 0,3 0 0,05 0,1 0,15 0,2 0,25
Total Trading Volume as Percentage of GDP (Liquidity Measure) P er ce nt age of Obse rvat ions W ith o ut Tra d e (I liqu id it y M easur e) Brazil 0 0,05 0,1 0,15 0,2 0,25 0 0,05 0,1 0,15 0,2 Total Trading Volume as Percentage of GDP
(Liquidity Measure) P ercen ta g e o f O b serva tio n s W ith o u t T ra d e (Iliq u id ity Mea su re) Chile 0 0,02 0,04 0,06 0,08 0,1 0,12 0,14 0,16 0 0,05 0,1 0,15 0,2 0,25
Total Trading Volume as Percentage of GDP (Liquidity Measure) P ercentage of Obse rv ations Without Trade (Iliq uidity Measure ) Mexico 0 0,1 0,2 0,3 0,4 0,5 0 0,02 0,04 0,06 0,08 Total Trading Volume as Percentage of GDP
(Liquidity Measure) Percen tage of O b ser vation s Wi th ou t T rad e (I liqu id ity Measu re) Peru 0 0,05 0,1 0,15 0,2 0,25 0,3 0,35 0,4 0,00 0,01 0,01 0,02 0,02
Total Trading Volume as Percentage of GDP (Liquidity Measure) Perc en ta g e o f O b se rvat io n s W ith o u t Tr ade (Iliqui dity M ea sure ) Colombia 0 0,1 0,2 0,3 0,4 0,5 0,00 0,02 0,04 0,06
Total Trading Volume as Percentage of GDP (Liquidity Measure) Percen tage of Ob serv ation s With out Trad e (Iliqu id ity Measu re)
Venezuela, Rep. Bol.
Figure 14: Liquidity Measures Comparison (1997-2004)
Stock Market Index (1) (2) (3) (4) (5) (6) (7) (8) MERVAL Argentina (1) 1.00 BOVESPA Brazil (2) 0.27* 1.00 IPSA Chile (3) 0.37* 0.45* 1.00 IGBC Colombia (4) 0.22* 0.05 0.18* 1.00 IPyC Mexico (5) 0.45* 0.41* 0.49* 0.14 1.00 IGBVL Peru (6) 0.23* 0.24* 0.35* 0.23* 0.44* 1.00 IBC Venezuela (7) 0.27* 0.21* 0.22* 0.25* 0.24* 0.13 1.00 DOW JONES USA (8)
0.27* 0.44* 0.47* 0.12 0.47* 0.16* 0.21* 1.00
Table 13: Stock Market correlation matrix (1990-2004). Note:* stands for
significant autocorrelation coefficients at 0.05.
0 2 4 6 8 10 Ke rn el De nsi ty -.5 0 .5
USD Monthly Total Returns DOWN JONES US MERVAL Argentina IBC Venezuela IGBC Colombia 0 2 4 6 8 10 Ke rn el D en si ty -.5 0 .5
USD Monthly Total Returns BOVESPA Brazil IPSA Chile IGBVL Peru IPyC Mexico
Figure 15: Gaussian Kernel Densities of Total Returns by Country (1990-2004)
Figure 16: Beta estimates by sector in Argentina from 1996-I to 2004-IV
Figure 17: Beta estimates by sector in Brazil from 1996-I to 2004-IV
Figure 18: Beta estimates by sector in Chile from 1996-I to 2004-IV
Figure 19: Beta estimates by sector in Colombia from 1996-I to 2004-IV
Figure 20: Beta estimates by sector in Mexico from 1996-I to 2004-IV
Figure 21: Beta estimates by sector in Peru from 1996-I to 2004-IV
Figure 22: Beta estimates by sector in Venezuela from 1996-I to 2004-IV
0 0.1 0.2 0.3 0.4 0.5 0.6
Jan-97 Mar-98 May-99 Jul-00 Sep-01 Nov-02 Jan-04
AR BR CL CO
MX PE VE
Critical value for rejection
Figure 23: Average Wald test p-values by country (using traded shares as weights in the GMM econometric specification) for the null H0: Global returns and RER returns do not explain individual
stock total returns
Figure 24: 12-month moving averages Black’s model COE estimates for Argentina
Figure 25: 12-month moving averages Black’s model COE estimates for Brazil
Figure 26: 12-month moving averages Black’s model COE estimates for Chile
Figure 27: 12-month moving averages Black’s model COE estimates for Colombia
Figure 28: 12-month moving averages Black’s model COE estimates for Mexico
Figure 29: 12-month moving averages Black’s model COE estimates for Peru
Figure 30: 12-month moving averages Black’s model COE estimates for Venezuela
Argentina 0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.00 0.20 0.40 0.60 0.80 1.00 1.20 COE std by sector (1997-2004) A verage COE by sec tor (19 97-20 04) Steal & Metal Transportation & Storage Telecommunications Textiles