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							Measuring the Beta using
 Historical Stock Prices




           2039
In this slide set

   The beta coefficient
   The linear regression approach to beta
    measurement using historical return data
    –   Normalizing the data
    –   Normalized holding period returns
    –   Running the regression using MS Excel
    –   Relevant regression statistics and their
        interpretation
    –   Different regression charts
The Beta Coefficient

   Under the theory of the Capital Asset Pricing Model total risk is
    partitioned into two parts:
     –   Systematic risk
     –   Unsystematic risk
                        Total Risk of the Investment



                  Systematic Risk       Unsystematic Risk

   Systematic risk is the only relevant risk to the diversified
    investor
   The beta coefficient measures systematic risk
The Term – “Relevant Risk”
   What does the term “relevant risk” mean in the context of the CAPM?
     – It is generally assumed that all investors are wealth maximizing
       risk averse people
     – It is also assumed that the markets where these people trade are
       highly efficient
     – In a highly efficient market, the prices of all the securities adjust
       instantly to cause the expected return of the investment to equal
       the required return
     – When E(r) = R(r) then the market price of the stock equals its
       inherent worth (intrinsic value)
     – In this perfect world, the R(r) then will justly and appropriately
       compensate the investor only for the risk that they perceive as
       relevant…hence investors are only rewarded for systematic
       risk…risk that can be diversified away IS…and prices and returns
       reflect ONLY systematic risk.
The Proportion of Total Risk that is
Systematic

   Each investor varies in the percentage of total risk that is
    systematic
   Some stocks have virtually no systematic risk.
     –   Such stocks are not influenced by the health of the economy in
         general…their financial results are predominantly influenced by
         company-specific factors
     –   An example is cigarette companies…people consume cigarettes
         because they are addicted…so it doesn‟t matter whether the
         economy is healthy or not…they just continue to smoke
   Some stocks have a high proportion of their total risk that is
    systematic
     –   Returns on these stocks are strongly influenced by the health of
         the economy
     –   Durable goods manufacturers tend to have a high degree of
         systematic risk
The Regression Approach to
Measuring the Beta

 •   You need to gather historical data about the stock and the market
 •   You can use annual data, monthly data, weekly data or daily data.
 •   You need at least thirty (30) observations of historical data.
 •   Hopefully, the period over which you study the historical returns of the
     stock is representative of the normal condition of the firm and its
     relationship to the market.
 •   If the firm has changed fundamentally since these data were produced
     (for example, they have merged with another firm or have divested
     itself of a major subsidiary) there is good reason to believe that future
     returns will not reflect the past…and this approach to beta estimation
     SHOULD NOT be used….rather, use the ex ante approach.
 Historical Beta Estimation

     In this example, we have determined the quarterly returns on the stock and the
     market and using Excel…ran a regression to produce the accompanying chart.

Period   HPR(Stock) HPR(TSE 300)
1990.1          -0.04      0.012
                                          Characteristic Line (Regression)
                                                       0.3
1990.2          -0.16      -0.07




                                            Returns on Stock
1990.3           0.32       0.12                                           0.2
1990.4           0.16       0.08
1991.1          -0.22      -0.11                                           0.1
1991.2           0.15       0.16
1991.3           0.28       0.13                                            0
1991.4           0.19       0.07                               -0.5              0         0.5
1992.1          -0.16      -0.04                                          -0.1
1992.2           0.08       0.16
                                                                          -0.2
1992.3          -0.03      -0.11
1992.4           0.34       0.25                                      Returns on TSE 300
    Characteristic Line

   The characteristic line is a regression line that represents the
    relationship between the returns on the stock and the returns on the
    market over a period of time.
   The slope of the Characteristic Line is the Beta Coefficient
   The degree to which the characteristic line explains the variability in the
    dependent variable (returns on the stock) is measured by the
    coefficient of determination. (also known as the R2 (r-squared or
    coefficient of determination)).
   If the coefficient of determination equals 1.00, this would mean that all
    of the points of observation would lie on the line. This would mean that
    the characteristic line would explain 100% of the variability of the
    dependent variable.
   The alpha is the vertical intercept of the regression (characteristic line).
    Many stock analysts search out stocks with high alphas.
Characteristic Line for Imperial
Tobacco
                        Characteristic
      Returns on
                        Line for Imperial
      Imperial
                        Tobacco
      Tobacco %

                                • High alpha
                                • R-square is
                                  very low
                                • Beta is
                                  irrelevant



                             Returns on
                             the Market %
                             (TSE 300)
High R2

   An R2 that approaches 1.00 (or 100%) indicates that the
    characteristic (regression) line explains virtually all of the
    variability in the dependent variable.
   This means that virtually of the risk of the security is
    „systematic‟.
   This also means that the regression model has a strong
    predictive ability. … if you can predict what the market will
    do…then you can predict the returns on the stock itself with a
    great deal of accuracy.
Characteristic Line General Motors

                        Characteristic
      Returns on
                        Line for GM
      Imperial
      Tobacco %         (high R2)

                               • Positive alpha
                               • R-square is
                                 very high
                               • Beta is
                                 positive and
                                 close to 1.0


                             Returns on
                             the Market %
                             (TSE 300)
An unusual Characteristic Line

      Returns on a   Characteristic Line for a stock
      Stock %        that will provide excellent
                     portfolio diversification
                                              • Positive alpha
                     (high R2)
                                              • R-square is
                                                very high
                                              • Beta is
                                                negative and <
                                                1.0


                                          Returns on
                                          the Market %
                                          (TSE 300)
Diversifiable Risk
(non-systematic risk)



   Examples of this type of risk include:
     –   a single company strike
     –   a spectacular innovation discovered through the company‟s R&D
         program
     –   equipment failure for that one company
     –   management competence or management incompetence for that
         particular firm
     –   a jet carrying the senior management team of the firm crashes
     –   the patented formula for a new drug discovered by the firm.
   Obviously, diversifiable risk is that unique factor that influences
    only the one firm.
OK – lets go back and look at raw data
gathering and data normalization

   A common source for stock of information is Yahoo.com
   You will also need to go to the library a use the TSE Review (a
    monthly periodical)
   You want data for at least 30 months.
   For each month you will need:
     –   Ending stock price
     –   Number of shares outstanding for the stock
     –   Dividend per share paid during the month for the stock
     –   Ending value of the market indicator series you plan to use (ie.
         TSE 300 composite index)
Demonstration Through Example


              The following slides will
              be based on Alcan
              Aluminum (AL.TO)
Five Year Stock Price Chart for AL.TO
Spreadsheet Data From Yahoo

Process:
  –   Go to http://ca.finance.yahoo.com
  –   Use the symbol lookup function to search for the
      company you are interested in studying
  –   Use the historical quotes button…and get 30
      months of historical data
  –   Use the download in spreadsheet format feature
      to save the data to your harddrive
Spreadsheet Data From Yahoo

The raw downloaded data should look like this:

Date         Open      High       Low       Close      Volume
  01-May-02     57.46       62.39     56.61     59.22    753874
   01-Apr-02      62.9      63.61     56.25       57.9   879210
   01-Mar-02      64.9      66.81     61.68     63.03    974368
   01-Feb-02    61.65       65.67     58.75     64.86    836373
   02-Jan-02    57.15       62.37     54.93     61.85    989030
   03-Dec-01      56.6      60.49      55.2     57.15    833280
   01-Nov-01        49      58.02     47.08     56.69    779509
Spreadsheet Data From Yahoo

The raw downloaded data should look like this:

   Date        Open       High        Low        Close   Volume
  01-May-02     57.46       62.39      56.61       59.22  753874
   01-Apr-02     62.9       63.61      56.25        57.9  879210


                                                         Volume of
                Opening price per share, the           trading done
The day,        highest price per share during the      in the stock
month and       month, the lowest price per share      on the TSE in
year            achieved during the month and the      the month in
                closing price per share at the end      numbers of
                of the month                             board lots
Spreadsheet Data From Yahoo

From Yahoo, the only information you can use is the
  closing price per share and the date. Just delete the
  other columns.

                Date        Close
               01-May-02      59.22
                01-Apr-02      57.9
               01-Mar-02      63.03
               01-Feb-02      64.86
                02-Jan-02     61.85
Acquiring the Additional Information
You Need

In addition to the closing price of the stock on a per share basis,
   you will need to find out how many shares were outstanding at
   the end of the month and whether any dividends were paid
   during the month.

You will also want to find the end-of-the-month value of the
  S&P/TSX Total Return Composite Index (look in the green
  pages)

You will find all of this in The TSE Review periodicals (HG
  5160.T6T6) found on the second floor of the library.
Raw Company Data

                                 Closing Price    Cash
                    Issued         for Alcan    Dividends
     Date           Capital          AL.TO      per Share
    01-May-02      321,400,589           $59.22      $0.00
     01-Apr-02     321,400,589           $57.90      $0.15
    01-Mar-02      321,400,589           $63.03      $0.00
    01-Feb-02      321,400,589           $64.86      $0.00
     02-Jan-02     160,700,295         $123.70       $0.30
    01-Dec-01      160,700,295         $119.30       $0.00
   Number of shares doubled and share price fell in half
   – this is indicative of a 2 for 1 stock split.
 Normalizing the Raw Company Data

                           Closing      Cash
               Issued      Price for Dividends Adjustment Normalized Normalized
   Date        Capital      Alcan     per Share  Factor     Stock Price  Dividend
01-May-02    321,400,589       $59.22      $0.00       1.00       $59.22       $0.00
 01-Apr-02   321,400,589       $57.90      $0.15       1.00       $57.90       $0.15
01-Mar-02    321,400,589       $63.03      $0.00       1.00       $63.03       $0.00
01-Feb-02    321,400,589       $64.86      $0.00       1.00       $64.86       $0.00
 02-Jan-02   160,700,295     $123.70       $0.30       0.50       $61.85       $0.15
01-Dec-01    145,000,500     $111.40       $0.00       0.45       $50.26       $0.00




             The adjustment factor is just the value in the issued
             capital cell dividend by 321,400,589.
Calculating the HPR on the stock from
the normalized data


             Normalized     Normalized
   Date      Stock Price     Dividend      HPR
                                                            ( P  P0 )  D1
                                                    HPR 
01-May-02          $59.22          $0.00    2.28%              1
 01-Apr-02         $57.90          $0.15   -7.90%
01-Mar-02          $63.03          $0.00   -2.82%
                                                                  P0
01-Feb-02          $64.86          $0.00    4.87%
 02-Jan-02         $61.85          $0.15   23.36%
01-Dec-01          $50.26          $0.00



       Use $59.22 as the ending price, $57.90 as the
       beginning price and during the month of May, no
       dividend was declared.
Now Put the data from the S&P/TSX
Total Return Composite Index in


                                                   Ending
             Normalized Normalized                   TSX
   Date      Stock Price  Dividend        HPR       Value
01-May-02          $59.22       $0.00      2.28%   16911.33
 01-Apr-02         $57.90       $0.15     -7.90%   16903.36
01-Mar-02          $63.03       $0.00     -2.82%   17308.41
01-Feb-02          $64.86       $0.00      4.87%   16801.82
 02-Jan-02         $61.85       $0.15     23.36%   16908.11
01-Dec-01          $50.26       $0.00              16881.75

       You will find the Total Return S&P/TSX Composite
       Index values in TSE Review found in the library.
Now Calculate the HPR on the Market
Index


                                                     Ending
             Normalized Normalized                     TSX     HPR on
   Date      Stock Price  Dividend          HPR       Value   the TSX
01-May-02          $59.22       $0.00        2.28%   16911.33    0.05%
 01-Apr-02         $57.90       $0.15       -7.90%   16903.36   -2.34%
01-Mar-02          $63.03       $0.00       -2.82%   17308.41    3.02%
01-Feb-02          $64.86       $0.00        4.87%   16801.82   -0.63%
 02-Jan-02         $61.85       $0.15       23.36%   16908.11    0.16%
01-Dec-01          $50.26       $0.00                16881.75

       Again, you simply use the HPR formula using the
       ending values for the total return composite index.
Regression In Excel

   If you haven‟t already…go to the tools
    menu…down to add-ins and check off the
    VBA Analysis Pac
   When you go back to the tools menu, you
    should now find the Data Analysis bar, under
    that find regression, define your dependent
    and independent variable ranges, your
    output range and run the regression.
Now Use the Regression Function in
Excel to regress the returns of the
stock against the returns of the market

 SUMMARY OUTPUT

        Regression Statistics
 Multiple R              0.05300947
 R Square                    0.00281         R-square = coefficient of
 Adjusted R Square       -0.2464875
 Standard Error          5.79609628
                                             determination
 Observations                      6

 ANOVA
                            df         SS        MS            F      Significance F
 Regression                       1 0.3786694 0.37866937   0.011271689 0.920560274
 Residual                         4 134.37893 33.5947321
 Total                            5  134.7576

                       CoefficientsStandard Error t Stat    P-value     Lower 95%      Upper 95% Lower 95.0%Upper 95.0%
 Intercept              59.3420816 2.8980481 20.4765686     3.3593E-05 51.29579335     67.38836984 51.2957934 67.38837
 X Variable 1           3.55278937 33.463777 0.10616821    0.920560274 -89.35774428    96.46332302 -89.3577443 96.46332



                                       Alpha
                Beta
Finalize Your Chart

   You can use the charting feature in Excel to
    create a scatter plot of the points and to put a
    line of best fit (the characteristic line) through
    the points.
   Finally, you will want to interpret the Beta (X-
    coefficient) the alpha (vertical intercept) and
    the coefficient of determination.
The Beta


   Obviously the beta (X-coefficient) can simply
    be read from the regression output.
   You will want to interpret it in the context of
    the firms, its products and the likely
    relationship that they hold with the health of
    the overall market.

						
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