Domestic CAPM and Extended CAPM

Domestic CAPM

  • An efficient market allows investors to diversify away company/security specific risk and have exposure solely to the market risk.

  • The Capital Asset Pricing Model (CAPM) as previously discussed was considered purely from an investor's domestic point of view.

  • Domestic CAPM: Theoretic technique for an investor that can be used to price market/systemic risk exposure of assets denominated in his/her own currency.

  • Domestic CAPM: Local Currency of Asset = Domestic Currency of the Investor

  • The domestic CAPM can only price local market risk.

  • Internationally, the domestic CAPM fails to consider:

  • Global market risks. Ex: Only the U.S. market risk is important in pricing Wal-Mart common equity shares.

  • Exchange rate risk.

Extending Domestic CAPM

Extended CAPM: Extends domestic CAPM to pricing systemic risk adjusted security returns to a world market portfolio of investible assets.

**Domestic CAPM formula:

E(RiLC) = RFLC + βiLC[E(RMLC) - RFLC]**

  • E(RiLC) = Domestic return for global asset "i", as measured in the asset's local currency
  • RFLC = Risk-free rate of return in the investor's domestic currency
  • E(RMLC = Expected return of the domestic market portfolio, used in calculating the domestic market risk premium, where the domestic currency is the local currency for the market.
  • βiLC = The asset's beta, its sensitivity to domestic market returns, where the investor's domestic currency is the local currency

**Extended CAPM formula:

RiDC = RFDC + βiDC[E(RWDC) - RFDC]**

  • RiDC = Return for risky global asset "i" measured in investor's domestic currency
  • RFDC = Global risk-free asset's rate of return in the investor's domestic currency.
  • RWDC = Return on world market of investible assets in the investor's domestic currency; used in calculating the world market risk premium in the investor's domestic currency.
  • βiDC = The global asset's beta, its sensitivity to world market returns, in the investor's domestic currency

Assumptions Needed to Justify an Extended CAPM

  • Consumer price index for all nations is composed of a like basket of goods and services.

  • Capital markets across all nations are integrated, so the model's real risk free rate is the same for all global investors.

  • Asset returns have systemic risk exposure to the world market portfolio, a cap weighted portfolio of all risky assets on planet earth.

  • Purchasing Power Parity (PPP) is persistent.

  • PPP implies that when an investor observes a change in his/her global asset's price in terms of domestic currency, the only difference in price change for an investor in the same asset residing in another country relates to the difference in expected inflation rates of the two countries where the investors reside.

  • PPP thus implies no real exchange rate risk

  • Modeling under the assumptions of the Extended CAPM still fails to compensate investors for exchange rate risk.

  • PPP may rarely hold under empirical analysis.

  • The next section explores changes to the real exchange rate.

Data Science in Finance: 9-Book Bundle

Data Science in Finance Book Bundle

Master R and Python for financial data science with our comprehensive bundle of 9 ebooks.

What's Included:

  • Getting Started with R
  • R Programming for Data Science
  • Data Visualization with R
  • Financial Time Series Analysis with R
  • Quantitative Trading Strategies with R
  • Derivatives with R
  • Credit Risk Modelling With R
  • Python for Data Science
  • Machine Learning in Finance using Python

Each book includes PDFs, explanations, instructions, data files, and R code for all examples.

Get the Bundle for $39 (Regular $57)
JOIN 30,000 DATA PROFESSIONALS

Free Guides - Getting Started with R and Python

Enter your name and email address below and we will email you the guides for R programming and Python.

Data Science in Finance: 9-Book Bundle

Data Science in Finance Book Bundle

Master R and Python for financial data science with our comprehensive bundle of 9 ebooks.

What's Included:

  • Getting Started with R
  • R Programming for Data Science
  • Data Visualization with R
  • Financial Time Series Analysis with R
  • Quantitative Trading Strategies with R
  • Derivatives with R
  • Credit Risk Modelling With R
  • Python for Data Science
  • Machine Learning in Finance using Python

Each book comes with PDFs, detailed explanations, step-by-step instructions, data files, and complete downloadable R code for all examples.