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  • Sharpe a 26-year-old researcher at the RAND Corporation was also a Ph.D. candidate at the University of California , he searched for topic of dissertation and H. Markowiz advised him a portfolio choice problem. His dissertation was then published under the name “Capital Asset Prices: a theory of market equilibrium under conditions of risk” in Journal of finance #19 1964 Two things are: Henry Markovitz work: "Portfolio Selection" first published in 1952 and updated in 1959—that presented a so-called efficient frontier of optimal investment. Essence of the work: Portfolio has expected return and risk. Expected return is related to the expected return of the securities, but risk is more complicated. Risk is related to the risks of the individual components as well as the correlations. You can put estimates of risk/return correlation into a computer and find efficient portfolios. In this way, you can get more return for a given risk and less risk for a given return, and that's efficiency a la Markowitz. James Tobin, who in “Liquidity Preference as behaviour towards risk” 1958 paper said if you hold risky securities and are able to borrow—buying stocks on margin—or lend—buying risk-free assets— and you do so at the same rate, then the efficient frontier is a single portfolio of risky securities plus borrowing and lending, and that dominates any other combination. Tobin's Separation Theorem says you can separate the problem into first finding that optimal combination of risky securities and then deciding whether to lend or borrow, depending on your attitude toward risk. It then showed that if there's only one portfolio plus borrowing and lending, it's got to be the market.
  • Mean-variance matters due to: The individual investor views the outcome of any investment in probabilistic terms; that is, he thinks of the possible results in terms of some probability distribution, thus he is willing to act on the basis of only two parameters of this distribution – its expected value and standard deviation.
  • The prices of capital assets Typically the expected return, standard deviation values associated with single assets will lie below the capital market line, reflecting the inefficiency of undiversified holdings. Moreover such points may be scattered throughout the feasible region, with no consistent relationship between their expected return and total risk. However there will be a consistent relationship between their expected returns and the systematic risk. Beta becomes the predicted response of expected return on a security to changes in the expected return on market portfolio. Then given the predicted risk on the market portfolio, the systematic portion of the predicted risk of each asset can be determined. Assets, which are more responsive to changes in expected market return, will have higher expected returns than those, which are less responsive. Diversification enables the investor to escape all but the risk resulting from swings in the economic activity, as this type of risk remains even in efficient combinations. And, since all other types can be avoided by diversification, only the responsiveness of an asset’s rate of return to the level of economic activity is relevant its risk. Prices will adjust until there is a linear relationship between magnitude of such responsiveness and expected return. (SML equation should hold).
  • Financial markets are integrated if financial assets with the same risk characteristics have identical expected returns, irrespective of the market to which they belong . The widespread use of domestic market indices as a proxy for the true market portfolio assumes that markets are internationally segmented . The discount rate should fall when markets become integrated ... Investors can transfer some part of country-specific risks to foreign investors, while taking some foreign risk in exchange Each country‘s cost of capital is reduced by making risk diversifiable that would not be otherwise diversifiable Skewness – the chance of an unexpected large positive or negative movement in returns. Kurtosis – the likelihood of big returns – positive or negative. Downside risk is estimated amount of money one can lose if buys stock. (usually expressed in % terms)
  • Above factors increase volatility of investment returns in emerging markets. Thus we get confirmation that in Emerging markets asset return distribution possesses fatter tails.
  • “ This additional premium represents the compensation an investor receives for taking on the considerable risks of the emerging markets that is not explained by beta alone.”
  • Interpretation: - The sovereign yield spread is the yield on a U.S. dollar bond that a country offers versus a U.S. Treasury bond of the same maturity - The spread represents an ex-ante assessment of a „country risk premium“ which reflects the credit worthiness of the government This model is only useful if you have the sovereign yield spread. Problem with the Goldman Integrated model: - Even adding this yield spread delivers a cost of capital that is unreasonably low in many countries (beta is still close to zero) - While you can get the yield spread in 136 countries with the EHV method, you can only get risk premiums for those countries with equity market s
  • Produces unreasonably high measures of the cost of capital for many international markets!
  • The Erb, Harvey and Viskanta (JPM, 1995) model • The model is intuitive and can be used in 136 countries, i.e., also in countries without equity markets • Fits developed and emerging markets the „reward for risk“ is worldwide

presentation_EM_CAPM.ppt presentation_EM_CAPM.ppt Presentation Transcript

  • Emerging markets Expected returns in Emerging Markets. Is CAPM alive? Prepared by: Tchekounaeva Ioulia
  • Presentation Outline
    • When and where did the CAPM arise?
    • Major assumptions of the classical CAPM.
    • Implications of the classical CAPM
    • Why classical CAPM cannot be applied to Emerging markets?
    • What additional factors to consider when pricing stocks in Emerging markets.
    • Suggested models for Emerging markets.
  • When and where did the CAPM arise?
    • 1960 William F. Sharpe
    • The CAPM comes out of two theories :
      • Henry Markowitz
      • James Tobin
    • Eugene Fama gave it a name now widely spread CAPM
  • Major assumptions of the classical CAPM.
    • Markowitz Mean-Variance Model
    • Investor is risk averse
    • One period world
    • Investors maximize expected utility of end-of-period wealth
    • Either (a) quadratic utility (all that matters is expected wealth & variance), or (b) holding period returns are “normally” distributed
    • Assumptions to get a general equilibrium risk-return relationship
    • Risk-free security exists, everyone can invest in this or borrow at this risk-free rate
    • Perfect capital markets:
      • No frictions to trading (commissions, taxes, price impacts, can buy fractional shares, continuous time trading)
      • Costless access to information (everybody will have same information)
  • Implications of the classical CAPM
    • The market portfolio will be mean-variance efficient
    • All efficient portfolios will be equivalent to investment in the market portfolio plus, possibly, lending or borrowing at a risk-free rate
    • There will be a linear relationship between expected return and beta.
  • Why classical CAPM cannot be applied to Emerging markets?
    • Assumption of normally distributed asset returns
    • Perfect market integration - markets that are "emerging" would seem, by definition, to be imperfect in their integration
    • CAPM is limited to Mean -Variance analysis, thus beta is based upon standard deviations (volatility). However Skewness and Kurtosis are more apparent in historical emerging markets' return data, suggesting greater downside risk.
    • As a result we get that:
    • CAPM underestimates the discount rate for emerging markets.
  • What additional factors to consider in Emerging markets .
    • The stage of emerging market development:
      • Existence of stock market, number of stocks traded and liquidity
      • Banking Infrastructure
      • Tax structure
    • The degree of emerging market’s integration into the global market
    • Particular risks associated with operations on this emerging market
  • Suggested models for Emerging markets
    • To incorporate all additional factors affecting the return in emerging markets, one should use multi-factor model.
    • According to Sharpe’s work “Capital Asset prices with and without Negative Holdings” 1990:
    • Early approaches to portfolio selection assumed that returns were generated according to somewhat similar to:
    • i.e. single factor model – special case of later developments of multi-factor models:
  • Suggested models for Emerging markets
      • The Ibbotson model
      • Ibbotson approach combines the CAPM’s prediction with prediction based on past performance
      • Steps:
        • Calculate world risk premium = U.S. risk premium divided by the beta versus the MSCI world (=7.8%)
        • Estimate country beta versus world index
        • Multiply this beta times world risk premium
        • Add in 0.5 times the ‘intercept’ from the initial regression
  • Suggested models for Emerging markets
    • Goldman Sachs Integrated model
    • This model is widely used by McKinsey, Salomon and many others
    • Addresses the problem that the CAPM gives a discount rate too low for many emerging and otherwise segmented stock markets
    • Solution: Add the sovereign yield spread
    • Steps:
      • Estimate market beta on the S&P 500
      • Beta times historical U.S. premium
      • Add sovereign yield spread plus the risk free
  • Suggested models for Emerging markets
    • The Goldman Segmented model
    • Approach: Modified beta = standard deviation of local market return in U.S. dollars divided by standard deviation of the U.S. market return
    • Steps:
      • Cost of capital is the modified beta times the historical U.S. premium
      • Add sovereign yield spread to get adjusted cost of capital
  • Suggested models for Emerging markets
    • The country risk rating model
    • Assumption: Credit rating is a good ex-ante measure of risk
    • Many factors influence a country‘s credit rating:
      • Political risk
      • Economic risk
      • Financial risk
      • Nation‘s industrial portfolio
    • Fit the cross-sectional regression model:
      • Average return = a 1 + a 2 ´Log(CCR) + e , where Log(CCR) is the natural logarithm of the Country Credit Rating
  • Sources of Information
    • Sharp: “Capital Asset Prices: a theory of market equilibrium under conditions of risk” Journal of finance 1964
    • Sharpe: “Capital Asset Prices with and without Negative holdings” Journal of Finance June 1991
    • “ Revisiting The CAPM” interview of W. Sharpe to The Dow Jones Asset Management May/June 1998
    • http://www.duke. edu /~ charvey
    • Dr. Wolfgang Drobetz Presentation “ Cost of capital in global markets ” April 2002 University of Basel.