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					Project Proposal (instalment I)

Course Code: MGT 13082-0104

Course Name: Statistics for Management

Professor Name: V. Yu

Date: 01 November 2004
In submitting this work for grading, I (we) confirm:

      that the work is original, and due credit is given to others where appropriate;

      acceptance and acknowledgement that assignments found to be plagiarized in
       any way will be subject to sanctions under the University’s Code of Behaviour on
       Academic Matters

In the case of group assignments, we furthermore confirm:

      that all have contributed substantially and proportionally to each group
       assignment;

      that all have sufficient familiarity with the entire contents of the group assignment
       so as to be able to sign off on them as original work;

       Number of Group Members Submitting this Assignment: 5

Signature(s)                                     Name                  Student Number

                                                 B. Vakili             961349110

                                                 D. Taranovsky         009877201

                                                 X. Lu                 990536283

                                                 R. Kulathu            993896325

                                                 K. Hawkins            993894817


                    Note that unsigned assignments will not be graded.
                         Project Proposal (Installment I)
Descriptive Project Title:
Analysis of extraneous variables influencing Exxon-Mobil share price movement.


1. Summary

   1.1. Description of the problem:

       Our statistical study involves an application of portfolio management by an investment

       firm. In general, when considering new ventures, investment firms need to acquire as

       much knowledge and data in regards to the industry of interest.         Investors are also

       keenly aware of venture risks, and so they take measures to collect data and acquire

       knowledge to aid them. Understanding the trends and factors affecting an industry of

       investment interest provides an investor with a better knowledge of its inherent risks and

       how to take advantage of them in order to create profitable returns.



       The industry of interest for the purposes of this project is the oil producing industry. We

       regard this from the perspective of Investment Managers who are determining whether

       or not to include an oil producer in their investment portfolio.   Our project will describe

       how these Investment Managers will collect statistical information in order to analyze if

       an investment in an oil producing corporation will produce returns in the long term. Our

       Investment Managers are interested in the Exxon Mobil Corporation.



       Exxon Mobil Corporation is engaged in the energy and petrochemical business. Through

       its divisions and affiliated companies, Exxon Mobil operates or markets products in the

       United States and approximately 200 other countries and territories. The Company's

       principal business is energy, involving exploration for, and production of, crude oil and

       natural gas, manufacture of petroleum products and transportation and sale of crude oil,

       natural gas and petroleum products. Exxon Mobil is also a manufacturer and marketer of

       basic petrochemicals, including olefins, aromatics, polyethylene and polypropylene
       plastics and a variety of specialty products. In addition, the Company has interests in

       electric power generation facilities.



       Our Investment Managers are trying to predict whether or not there is a correlation

       between the Exxon-Mobil’s historical share prices against a series of extraneous variables

       over 90 days (short-term) and 60 months (long-term).         These extraneous variables

       include:

                 Crude oil prices (Insert type of oil)

                 General market performance (DOW Jones Index)

                 Exchange Rate of Saudi Arabia

                 Average daily temperature (Toronto)

                 Share Trade Volume

                 Consumer Price Index (?)

   By observing any trends or effects of the above variables on Exxon Mobil’s share price, the

   Investment Bankers will be able to make proposals on how and when to use their funds to

   buy and sell shares of Exxon Mobil.



   1.2. Managerial and Statistical questions:

MQ1.   How does the share price of Exxon Mobil generally behave over time?

Process              Closing of share trade price (end of the day)
Statistical Unit     Month or Day
Variables            Share price
Parameters           Mean, mode, median, standard deviation, variance, range, minimum and
                     maximum


   1.1. Determine each of the above parameters for Exxon Mobil’s share price.

   1.2. Does the share price follow a normal distribution?

MQ2.   Is the company’s share price affected by any extraneous variables?

   2.1. Is there a linear relationship (or any relationship) between the Exxon Mobil share price
   and the crude oil price per barrel?

Process            Closing of share trade price (end of day)
Statistical Unit   Month or Day
Variables          Y - Share price (response variable)
                   X - Crude oil price per barrel (factor variable)
Parameters         Correlation and covariance between X and Y
                   Regression coefficients about the fitted line
                   Standard deviation of residuals about the fitted line


   2.2. Is there a linear relationship (or any relationship) between the Exxon Mobil share price

   and the exchange rate of major oil producing nations?

Process            Closing of share trade price (end of day)
Statistical Unit   Month or Day
Variables          Y - Share price (response variable)
                   X – Exchange rate of Saudi Arabian rial to US dollar (factor variable)
Parameters         Correlation and covariance between X and Y
                   Regression coefficients about the fitted line
                   Standard deviation of residuals about the fitted line


MQ3.   Do market conditions affect trade volume?

   3.1. Is there a linear relationship (or any relationship) between the Dow Jones Index and the

   trade volume for Exxon Mobil shares?

Process            Closing of share trading (end of day)
Statistical Unit   Month or Day
Variables          Y – Trade volume (response variable)
                   X – Dow Jones Index (factor variable)
Parameters         Correlation and covariance between X and Y
                   Regression coefficients about the fitted line
                   Standard deviation of residuals about the fitted line


   3.2. Is there a linear relationship (or any relationship) between the share price of Exxon Mobil

   shares and the Consumer Price Index?

Process            Closing of share trading (end of day)
Statistical Unit   Month or Day
Variables          Y – Share price (response variable)
                   X – Consumer Price Index (factor variable)
Parameters         Correlation and covariance between X and Y
                   Regression coefficients about the fitted line
                   Standard deviation of residuals about the fitted line
MQ4.    Does Exxon Mobil’s stock appreciate in value over time?

    4.1. Has the average stock price for Exxon Mobil being continually rising in the long run?

MQ5.    Does Exxon Mobil’s stock rise and fall during foreseeable time periods?

    5.1. Using visual inspection, does a scatter-plot of the Exxon Mobil share price indicate any

    pattern?

MQ6.    Do extremes in temperature have an effect on trading activity for oil?

    6.1. What are the minimum and maximum temperatures in New York City.

    6.2. Is there a linear relationship (or any relationship) between the share price of Exxon Mobil

    shares and the temperature in New York?

Process             Closing of share trade price (end of day)
Statistical Unit    Month or Day
Variables           Y - Share price (response variable)
                    X – Temperature in New York (factor variable)
Parameters          Correlation and covariance between X and Y
                    Regression coefficients about the fitted line
                    Standard deviation of residuals about the fitted line
                    Minimum and maximum temperatures in New York City


MQ7.    Should the Investment Managers add Exxon Mobil to their portfolios?

(what kind of statistical question to put here?)



    1.3. Practical use of study:

    This study is intended to aid Investment Managers in making a strategic decision on whether

    to invest in Exxon Mobil shares. By investigating and modeling any share trading patterns,

    the Investment Mangers would be able to determine when to buy and sell Exxon Mobil

    shares and thus improve portfolio performance. Any proposed models would only work if the

    investigation took into account major external factors (such as the barrel price of oil and

    exchange rates).

    1.4. Current knowledge about the managerial questions:

    There is an expectation that there will be a definitive relationship between the barrel price of

    oil and the share price of Exxon Mobil. One would expect the market for oil producer shares
   to react immediately to any major changes in oil quantities (for example due to OPEC

   restrictions). It is also expected that the stock market performance in general will have a

   strong effect on Exxon Mobil’s share price.     Exxon Mobil is only one of the hundreds of

   companies being traded on the New York Stock Exchange. It should not be surprising if the

   overall performance of the stock exchange in general was reflected in the share price of a

   single company.



   There is an expectation of a weak to moderate correlation between exchange rates and the

   stock price of Exxon Mobil. Saudi Arabia was chosen as the country of interest since it is the

   largest oil-rich nation in the world. Exxon Mobil purchases a vast amount of its oil from Saudi

   Arabia, and so the exchange rate between the American and Saudi Arabian currencies may

   be a factor. There will probably be no immediate relationship between the temperature in

   New York City and the share price of Exxon Mobil. However, there is some expectation that

   season changes (e.g. summer versus winter) will cause the share price to be affected due to

   changes in demand for oil-based transportation products.



   Although attempts can be made to model the relationships between extraneous variables and

   the stock market, stock prices in general are inherently difficult to forecast. There are many

   background variables that could affect this study and share purchasing behavior itself is

   difficult to predict.   Additionally, the impact of major socio-economic events must be

   considered. These events can include September 11 terrorist attacks, the U.S. elections,

   OPEC restrictions, the invasion of Iraq, general tension in the middle east, as well as labor

   issues in Venezuela. Such events could cause artifacts or outliers in our analysis. For MQ1,

   there is an expectation that Exxon Mobil’s share price has been climbing up in the past 5

   years. Any price fluctuations would yield relatively small deviations about resulting regression

   line.

2. Statistical Details
2.1. Time series vs. cross-sectional study:

    Our investigation involves only the use of time-series studies. The process of interest is

    the closing of share trading of Exxon-Mobil’s shares each day. The statistical unit is a

    day for short-term studies and conversely a month for long-term studies.



    In other units, our study uses:

       The US dollar for share price and crude oil barrel price

       A single trade for Exxon Mobil’s trade volume

       A degree Celsius for New York temperature



    Since the study is focused on the stock behavior of Exxon Mobil, we have chosen New

    York as our physical location (the New York Stock Exchange in particular). Most of our

    statistical variables are quite general in nature, with the exception of temperature.

2.2. Variables to be measured:

    These variables to be measured include:

       Crude oil prices as shown in NYMEX (Insert type of oil)

       General market performance indicated by Don Jones Index

       Industry performance indicated by Dow Jones Energy Index

       Exchange Rate between Saudi Arabia Riyal and US dollar

       Average daily temperature (New York)

       Consumer Price Index

(how do we name variables?)

(how is this different from section 1.2?)



2.3. Statistical aspects of interest:

-   (how is this different from section 1.2?)
3. Data collection plans

    3.1. Description of the sample:

    The data samples are taken on monthly basis for the last 5 years. The closing share prices

    for Exxon Mobil and DOW Jones Index are taken from the Yahoo Finance web site 1. Data for

    crude oil price is taken from US Department of Energy web site 2 and data for gasoline price is

    taken from US Department of Labor web site3. Average New York temperatures are taken

    from the World Meteorological Organization web site.

    (need to indicate source for consumer price index here)

    (why do we mention gasoline price here?       Are we intending to include it as one of our

    variables?)

    (sample size? i.e. we need a flat number like 40 or 50)

    (how are we going to do RANDOM sampling?)

    3.2. Operational definitions:

        The symbok XOM is the Exxon Mobil ticker.

        General market performance is indicated by the Dow Jones US Market Index.

        Crude Oil refers to Nymex Light Sweet Crude Oil. Crude Oil price is based on the New

        York Mercantile trading prices.

        Industry performance indicated by Dow Jones Energy Index.

    (why are we using the Dow Jones Energy Index)

        Exchange Rate between Saudi Arabia Riyal and US dollar




1
  http://finance.yahoo.com/
2
  http://www.eia.doe.gov/emeu/international/prices.html
3
  http://www.bls.gov/cpi/home.htm
   3.3. Data collection details:

         Data is collected from commercial web sites.

   3.4. Critique of data collection plans:

         Since data is collected from world wide web, there is no guarantee as to the correctness

         of the data. Furthermore monthly data is chosen for the project may tend to smooth out

         any deviation that occurred in the individual month. The assumption is that the available

         online data will, in general, be representative of the market conditions.

   3.5. Fictional data:

   Table 1.0 given below shows the sample data for this project.

            US City Average per         XOM          XOM         DOW           DOW
  Date             gallon               Close       Volume       Close        Volume       NY Temp F
 Jan-98             1.186               59.31       3925175     7906.5        6673605                40.00
 Feb-98             1.137               63.75       3182663     8545.72       6437384                40.60
 Mar-98             1.097               67.62       3430595     8799.81       6542963                45.40


4. Data Analysis Plans

   4.1. Graphical summaries:

   Figure given below shows the price movement for Exxon Mobil stock.
                         Stock Price
       Ja
          n-
                                            100




                    0
                   10
                        20
                        30
                             40
                             50
                                  60
                                  70
                                  80
                                       90

             98
        Ju
           l-9
               8
       Ja
          n-
             99
        Ju
           l-9
               9
       Ja
          n-
             00
        Ju
           l-0
               0
       Ja
          n-
             01
        Ju
           l-0
               1
       Ja
Date

          n-
             02
        Ju
           l-0
               2
                                                  Exxon Mobil Stock Price




       Ja
          n-
             03
        Ju
           l-0
               3
       Ja
          n-
             04
        Ju
           l-0
               4
   4.2. Descriptive summaries:

   The collected data will be in time series format. Data samples are taken on a monthly basis.

   Time series plots of individual parameters as well as Exxon Mobil stock price will be

   presented.

5. Data Collection (Sources)

   Monthly data samples of Exxon Mobil share prices and Dow Jones Index are collected from

   Yahoo Finance web site. Nymex Crude Oil price and consumption are collected from US

   department of energy web site. Average gasoline price is collected from US department of

   labor web site.




6. Appendixes


   Appendix A – Sample of values (mock-up)
            Imperial Oil           Cushing, OK Europe      Exchange Rate
Date        Share Price TSX Close WTI Spot     Brent Spot USD-1      EUR          VEB
2-Jul-04          62.47   8,487.30       38.37       35.36      1.32       1.63      0.0007
5-Jul-04          62.23   8,486.00                   35.73      1.33       1.63      0.0007
6-Jul-04          62.83   8,465.40       39.56       36.47      1.33       1.63      0.0007
7-Jul-04          63.19   8,481.90       39.18       35.62      1.32       1.63      0.0007
8-Jul-04          63.38   8,420.40       40.27       37.13      1.32       1.63      0.0007
9-Jul-04          63.44   8,473.20       39.90       37.58      1.32       1.64      0.0007
12-Jul-04         62.69   8,422.20       39.30       37.73      1.32       1.64      0.0007
13-Jul-04         62.13   8,452.60       39.55       36.68      1.32       1.63      0.0007
14-Jul-04         63.22   8,458.30       40.98       37.51      1.32       1.64      0.0007
15-Jul-04         62.30   8,397.30       40.70       38.41      1.32       1.64      0.0007
16-Jul-04         62.19   8,350.50       41.10       38.49      1.31       1.63      0.0007
19-Jul-04         62.78   8,414.80       41.55       39.07      1.31       1.63      0.0007
20-Jul-04         62.42   8,418.50       40.86       38.96      1.31       1.62      0.0007
21-Jul-04         63.13   8,454.20       40.63       38.48      1.32       1.62      0.0007
22-Jul-04         62.51   8,398.00       41.51       39.16      1.32       1.61      0.0007
23-Jul-04         62.22   8,383.30       41.82       39.59      1.32       1.60      0.0007
26-Jul-04         62.28   8,314.50       41.45       39.75      1.33       1.62      0.0007
27-Jul-04         62.34   8,294.40       41.83       40.09      1.33       1.61      0.0007
28-Jul-04         63.99   8,356.30       42.81       41.08      1.33       1.60      0.0007
29-Jul-04         64.52   8,443.20       42.69       40.93      1.33       1.60      0.0007
30-Jul-04         65.57   8,458.10       43.72       41.47      1.33       1.60      0.0007
3-Aug-04          65.44   8,464.10       44.13       41.82      1.32       1.59      0.0007
4-Aug-04          63.74   8,363.00       42.73       41.75      1.31       1.59      0.0007
5-Aug-04          63.52   8,267.90       44.39       42.49      1.32       1.59      0.0007
6-Aug-04          62.38   8,176.70       43.95       42.63      1.31       1.61      0.0007
9-Aug-04          62.08   8,183.40       44.86       43.21      1.32       1.61      0.0007
10-Aug-04         61.74   8,231.30       44.51       42.50      1.32       1.62      0.0007
11-Aug-04         61.61   8,168.20       44.72       42.45      1.32       1.62      0.0007
12-Aug-04         61.36   8,132.30       45.52       43.50      1.33       1.63      0.0007
13-Aug-04         61.91   8,172.60       46.61       44.13      1.31       1.62      0.0007
16-Aug-04         62.73   8,241.50       46.02       44.35      1.31       1.61      0.0007
17-Aug-04         61.81   8,232.20       46.75       44.05      1.31       1.61      0.0007
18-Aug-04         61.48   8,223.00       47.36       44.12      1.30       1.61      0.0007
19-Aug-04         62.58   8,293.90       48.66       44.84      1.30       1.60      0.0007
20-Aug-04         62.38   8,335.60       47.60       45.46      1.30       1.60      0.0007
23-Aug-04         60.93   8,315.50       46.00       44.39      1.31       1.59      0.0007
24-Aug-04         60.21   8,316.40       45.68       42.99      1.31       1.58      0.0007
25-Aug-04         60.23   8,371.40       43.83       42.39      1.31       1.58      0.0007
26-Aug-04         60.80   8,331.30       43.06       40.65      1.31       1.59      0.0007
27-Aug-04         61.56   8,334.30       43.11       40.72      1.31       1.58      0.0007
30-Aug-04         61.00   8,309.00       42.32       40.78      1.32       1.59      0.0007
31-Aug-04         61.55   8,377.00       42.23       39.80      1.31       1.60      0.0007
1-Sep-04          62.00   8,410.10       43.89       40.96      1.31       1.59      0.0007
2-Sep-04          62.43   8,388.90       44.04       42.39      1.30       1.58      0.0007
3-Sep-04          62.45   8,344.40       43.94       41.07      1.30       1.57      0.0007
7-Sep-04          62.20   8,369.40       43.18       40.19      1.29       1.56      0.0007
8-Sep-04          61.98   8,354.80       42.77       39.91      1.29       1.57      0.0007
9-Sep-04          62.09   8,394.00       44.53       41.45      1.29       1.57      0.0007
10-Sep-04         60.75   8,368.60       42.84       41.03      1.29       1.58      0.0007
13-Sep-04         61.91   8,513.40       43.86       40.63      1.30       1.59      0.0007
14-Sep-04         62.00   8,492.60       44.62       41.34      1.29       1.58      0.0007
15-Sep-04         62.62   8,467.00       43.83       42.03      1.30       1.58      0.0007
16-Sep-04         62.75   8,493.40       44.03       40.68      1.29       1.57      0.0007
17-Sep-04         63.00   8,529.90       45.63       43.08      1.30       1.58      0.0007
20-Sep-04         63.21   8,539.80       46.33       43.60      1.29       1.58      0.0007
21-Sep-04         64.45   8,642.90       47.11       44.56      1.29       1.58      0.0007
22-Sep-04         64.31   8,586.10       48.41       45.66      1.28       1.57      0.0007
23-Sep-04         63.55   8,591.70       48.37       46.53      1.28       1.57      0.0007
24-Sep-04         63.79   8,588.40       48.86       46.13      1.28       1.56      0.0007
27-Sep-04         63.62   8,498.00       49.56       46.87      1.27       1.57      0.0007
28-Sep-04         65.40   8,617.20       49.76       47.52      1.27       1.57      0.0007
29-Sep-04         65.08   8,634.10       49.53       46.54      1.27       1.57      0.0007
30-Sep-04         65.48   8,668.30       49.56       47.76      1.26       1.57      0.0007
1-Oct-04          66.12   8,747.10       50.16       46.86      1.26       1.57      0.0007
4-Oct-04          66.07   8,812.90       49.85       46.99      1.27       1.56      0.0007
5-Oct-04          66.69   8,797.00       51.08       47.10      1.26       1.55      0.0007
6-Oct-04          67.85   8,871.90       51.98       47.95      1.26       1.55      0.0007
7-Oct-04          68.00   8,825.40       52.56       48.98      1.26       1.54      0.0007
8-Oct-04          67.70   8,814.90       53.40       49.41      1.25       1.55      0.0007
12-Oct-04         68.29   8,785.90       53.49       51.28      1.26       1.55      0.0007
13-Oct-04         67.50   8,729.60       53.86       50.42      1.26       1.55      0.0007
14-Oct-04         68.20   8,745.60       54.69       51.31      1.26       1.55      0.0007
15-Oct-04         68.91   8,788.90       54.89       51.02      1.25       1.56      0.0007
18-Oct-04         68.36   8,788.90       53.59       49.16      1.26       1.57      0.0007
19-Oct-04         69.45   8,720.50       53.28       49.21      1.26       1.57      0.0007
20-Oct-04         70.70   8,788.10       54.93       50.78      1.25       1.57      0.0006
21-Oct-04         71.74   8,846.70       54.51       51.06      1.24       1.57      0.0006




    Appendix B - Graphs (mock-up)
   Final Page




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