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Finance IIA: Portfolio Theory Part 3,4 & 5 (FTX3044F) $7.35
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Finance IIA: Portfolio Theory Part 3,4 & 5 (FTX3044F)

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Notes cover content on Parts 3,4& 5 of Portfolio Theory: Index models, asset pricing (the CAPM and APT), and market efficiency and behavioural finance.

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  • June 6, 2023
  • 41
  • 2022/2023
  • Class notes
  • Ailie charteris
  • All classes
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Single-Factor Model

Building a Single-Factor Model:

• Rate of return:




• Some securities are more sensitive to shocks to the macroeconomy than others.
Thus, we assign each rm a sensitivity coe cient to the common market factor
denoted β (beta).
• Thus the return on a stock in any period is as follows:




• Because the market factor and rm-speci c factor are uncorrelated, the variance
of the returns can be written as follows:




fi fi fiffi

,• What if we want to combine securities together in a portfolio?
- Firm speci c surprises are uncorrelated meaning that the only source of
covariance between any pair of securities is their common dependence on the
market factor.
- Therefore, the covariance between two rms’ returns depends on the
sensitivity of each to the market, as measured by their betas:




The Single-Index Model (SIM)

The Equation of the SIM:
• To make the single factor model operative, we identify the market factor as a
broad market index because it a ects the returns on all stocks which gives us
the single-index model (SIM).
• The single-index model does not have a theoretical foundation, it is simply a
way to describe the typical relationship between market returns and the returns
on a particular security.
• The excess returns on the market (the market risk premium) are given as: RM
= rM – rf and the associated risk is denoted as σM.

• The excess returns of the security are denoted as: Ri = ri – rf

• To obtain the single-index model, we regress the historical excess returns of
security i on the historical excess returns of the index for period t:




fi ff fi

,Expected return-beta relationship:




Variance for security i:




If we want to combine securities together:

, Portfolio return:




Portfolio Variance:




E ects of diversi cation on the variance:




• where: ^2( ) is the average of the rm-speci c variances.
• Because the average unsystematic risk is independent of n, when n gets large,
^2( p) becomes negligible and rm speci c risk is diversi ed away.

Residual standard deviation: rm speci c residual deviation: ^2( p). Firm
speci c risk will be low or 0 if the business is fully diversi ed




𝜎 ff 𝑒fi 𝜎

𝑒 fi fi fi fi fi fi fi fifi 𝜎 𝑒

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