Capital Asset Pricing Model Calculator (CAPM)

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Capital Asset Pricing Model Calculator (CAPM)

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To calculate current expected return of any specific security, Capital Asset Pricing Model (CAPM) calculator helps to determine it well. – PowerPoint PPT presentation

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Title: Capital Asset Pricing Model Calculator (CAPM)


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Capital Asset Pricing Model Calculator (CAPM)
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  • The valuation of the capital asset pricing model
    uses a variation of discounted cash flows.
    However, there are varied ways to measure the
    investment beta co efficient. The formula is
  • Kc     Rf     beta x ( Km - Rf )
  • where
  • Kc is the risk-adjusted discount rate (also known
    as the Cost of Capital) Rf is the rate of a
    "risk-free" investment, i.e. cash Km is the
    return rate of a market benchmark, like the SP
    500.

3
Risk and the Capital Asset Pricing Model Formula
  • In order to understand the capital asset pricing
    model calculator one needs to have an
    understanding of risk on investment.  
  • Typically, Applicant securities carry a risk of
    depreciation which is equal to a loss of
    investment to the investor.
  • Generally, some securities have more risk than
    others as compared to the additional risk.
  • The risk involved when evaluating a particular
    stock is accounted for in the capital asset
    pricing model formula with beta.  
  • Beta is the adequate term used to measure the
    capital asset pricing model formula to evaluate
    the risk involved with investing in a particular
    stock relative to the risk of the market.  
  • The beta of the market would be 1. An individual
    security with a beta of 1.5 would be as
    proportionally riskier than the market and
    inversely, a beta of .5 would have less risk than
    the market.

4
Alternative Capital Asset Pricing Model Formula
  • When regression analysis is applied to the
    capital asset pricing model based on prior
    returns, the formula will be shown as above.
    Alpha is considered to be the risk-free rate and
    epsilon is considered to be the error in the
    regression.
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