International CAPM (ICAPM) - Beyond Extended CAPM

  • The ICAPM attempts to explain the required return on a risky asset, measured in its own local currency.

  • ICAPM assumption divergences from Extended CAPM

  • The market basket for goods used in calculating CPI does not need to be the same goods, in the same percentages.

  • Purchasing Power Parity does not always prevail.

  • Theoretically, the ICAPM should offer investors sufficient returns for taking on systemic/market risk of returns on the world market of investible securities, measured in the same currency as the one in which the asset's return is attempted to be measured.

R ADC = rDC + (βAWM * (R WMDC - rDC)) + (γ ADC,1/LC × SRP 1/LC) + … + (γ ADC,i/LC × SRP i/LC)

  • R ADC = Expected/required return measured in an investor's domestic currency for a foreign risky asset denominated in its own local currency

  • rDC = Risk free rate in the investor's country

  • βAWM = Sensitivity of the risky asset's returns to changes in world market portfolio returns, when both are measured in the investor's domestic currency

  • (R WMDC - rDC) = World market risk premium measured in the investor's domestic currency

  • γ ADC,i/LC = Currency exposure of the risky asset, measuring the sensitivity of the risky asset's returns, measured in the investor's domestic currency, to changes in the value of the asset's local currency against the kth currency represented in the world market portfolio

  • SRP i/LC = Foreign currency risk premium; risk compensation to the investor for the risk that the value of the asset's local currency against the ith currency in the world market portfolio might be different from its expected value.

  • The foreign currency risk premium is the difference between the expected future spot exchange rate and the current forward exchange rate, divided by the current spot rate.

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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.