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Capital Asset Pricing Process Analysis

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There are a lot of items that go into buying and investing in a company. One of the hardest decisions for a shareholder is deciding if the investment is going to be profitable. Once a shareholder decides to buy or invest in an organization the next step would be deciding how much to pay or invest. Another hard decision is if the investment that was made goes bad can you get out of this obligation. Throughout the course of the paper I will illustrate some of the items that assist with this decision process. The items that are covered in this paper are the cost of equity, the cost of debt, and the weighted average cost of capital. All three of these items assist in the decision process. Most companies use Capital Asset Pricing Model (CAPM), which is a model that is utilized to calculate the required rate of return. The main reason for utilizing this model is that the rate of return injuctively authorized by equity investors will be a function of the jeopardy of the equity where risk is quantified by a variable beta (McGladrey & Pullen, 2010). The equation used to deduce the Cost of Equity (CoE) = Risk-Free Rate of Return + (the market risk premium – Risk-Free Rate of Return) x beta coefficient (unsystematic risk) (Investopia, 2016). Re = Rf + β (Rm - Rf) Rf = 2.32% β = 0.95 Rm = 13.96% Re = 2.32% + 0.95 (11.72% - …show more content…

In this essay, the author

  • Explains how the cost of equity, debt, and weighted average costs of capital assist in the decision process.
  • Explains that most companies use capital asset pricing model (capm), which is a model that is utilized to calculate the required rate of return.
  • Explains that amazon.com inc's interest expense (positive number) was $459 mil and its total book value of debt (d) is $13336 mil.
  • Explains that the weighted average cost of capital (wacc) is the rate that a company is expected to pay to all its security holders to finance its assets.
  • Explains the cost of debt finance, wdebt 6.96%, and the income tax rate, t 36.0.
  • Explains the importance and value of weighted average cost of capital (wacc) as a financial tool for companies and investors.

One of the key rates used to figure out the CoD is the current market rate Amazon (AMZN) is paying on its debt. If AMZN is not paying market rates then one should be estimated (Investopedia, 2016). Because companies like AMZN profit from tax deductions obtainable on interest paid, the net CoD is the interest paid minus tax savings resulting from the tax-deductible interest payment (Investopedia, 2016). As of Dec. 2015, Amazon.com Inc 's interest expense (positive number) was $459 Mil. Its total Book Value of Debt (D) is $13336 Mil (GuruFocus,

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    • Explains that a callable bond, which can be bought back by the issuer before its maturity, can reduce the cost of debt when the interest rate decreases.
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    • Explains that this cost reflects the opportunity cost the company incurs when it decides to retain its earnings.
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    Berk, J., & DeMarzo, P. (2011). Corporate finance: The core, second edition. (2nd ed.). Boston, MA: Prentice Hall.

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    • Compares hd and lowes total debt (short term & long term) plus available cash versus hd.
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    So this raises the question what is the CAPM model useful for and how effective is it when estimating cost of capital? Scholars such as Perold (2004) have answered this question through testing and analysis, they have found that even if the model does not give us an accurate real world result in estimating todays cost of capital, it can aid us in predicting future investor behaviour. I would agree with this conclusion of CAPM and Perold’s view on its effectiveness when estimating cost of capital and explaining performance of investment portfolios when given incorrect variables. However, on this note I do not argue that CAPM is theoretically incorrect but from a investors point of view it is questionable, scholars such as Levy (2010) have also stated this within their research of CAPM backing up their argument with thorough testing and analysis within his journal ‘The CAPM is alive and

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    • Explains that they will compare and contrast the effectives of capital asset pricing model (capm), arbitrage pricing theory, and the fama-french three factor model when estimating capital costs and explaining portfolio performance.
    • Explains that today's widely used capm model was originally developed by sharpe (1964) in order to explain how capital markets set share prices.
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    • Explains that the capm model is still practical if we are given incorrect variables. guermat argues in his journal that we can still use it.
    • Concludes that capm is not theoretically incorrect but from an investors point of view it is questionable.
    • Explains that scholars zhi da, re-jin guo, and ravi jagannathan have proposed certain adjustments of capm to increase its efficiency when estimating cost of capital.
    • Explains that the arbritrage pricing theory (apt) was introduced by ross in 1976 as alternative option to capm.
    • Explains that a fundamental weakness of apt is that of price approximation. shanken (1982) argues that the pricing of portfolios is of more significance rather than individual assets.
    • Explains that the measurement of certain financial variables is another drawback for apt in terms of its accuracy when estimating cost of capital and explaining investment portfolios.
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    • Explains capital asset pricing model (capm) is an ex ante concept, built on the portfolio theory established by markowitz. it enhances the understanding of elements of asset prices, specifically the linear relationship between risk and return.
    • Opines that capm is a useful model for determining asset investments despite all the evidence against it.
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    • Argues that capm is an inadequate and misleading model with several shortcomings that make it unacceptable by various academics.
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    • Defines day return r at as the percentage return that would be earned by an investor who bought the stock at the end of a particular day/month t-1 and sold it.
    • Explains that rt is the rate of return during the period (t-1,t) and the price at time t.
    • Explains that a continuously compounded return is the appropriate return measure, and not discretely.
    • Explains that the research study consists of four sections based on information set of return predictability.
    • Explains that sort-term return predictability includes both non-parametric and parametric approaches to test the weak form of stock market efficiency.
    • Explains that non-parametric stock market efficiency tests: both run test and autocorrelation function will be discussed in 5.2.1.
    • Explains that a parametric stock market efficiency test: arima model will be discussed in the 5.2.2 section.
    • Explains how the daily and weekly kse 100 indices data sets are used to find return predictability through market efficiency tests.
    • Explains n is the total number of price changes, and ni are the numbers of prices of each sign.
    • Explains that, for a purely white noise process the autocorrelation at various lags hover around zero.
    • Summarizes box and jenkins' four-stage univariate box-jenkins process for selecting a good model.
    • Explains that the simplest ways to state autoregressive of order one ar (1) model may also be estimated as:
    • Explains that the model looks like the markov first order autoregressive model. if 1, rt becomes non stationary series, a unit root problem occurs in the returns.
    • Explains that the most widely used model of serial correlation is the first-order autoregressive model.
    • Explains that the value of r at time t depends on its value in the previous time period and a random term; the r values are expressed as deviations from their mean value.
    • Explains that rt follows a random walk model with drift because the presence of its constant parameter, pare the parameters of autoregressive coefficients and ut is an uncorrelated random error term.
    • Explains that moving average process of order q is created by a weighted average of random error term and written its equation as:
    • Explains that moving average process is simply a linear combination of white noise error term.
    • Explains the success of the widely accepted arima models in forecasting, which is more authentic than other econometric models.
    • Explains that the run test is a non-parametric test whereby the number of successive positive and negative returns is tabularized and compared against its sampling distribution under the random walk hypothesis.
    • Explains how to find out the number of runs (consider the signs of prices whether positive, negative or no change).
    • Explains the autocorrelation function test, which evaluates the correlation between the current and lagged observations of the time series of stock returns.
    • Explains that k =0, 0 =1, since both covariance and variance are measured in the same units of measurement, the graph is known as the correlogram.
    • Explains that forecasting return volatility is a crucial and thought-provoking financial problem that has garnered attention.
    • Explains that the identification stage uses two graphical devices to estimate the correlation between the observations within a single data series.
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    • Explains that there are ‘p’ autoregressive terms and ‘q’ moving average terms. the intercept parameter is related to the mean of rt and the errors are assumed to be uncorrelated random variables with zero mean and constant variance.
    • Explains that is an intercept term and is assumed to be uncorrelated random variables, an unknown parameter of autoregressive model and a moving average process.
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