Proposed project for Alchemy Inc FIN 3150 Fall 2019 Assignment 8 - Evaluating sensitivity to risk Part 1. Select two companies that have stock prices continuously available for November 2014 through...

1 answer below »
Please do it on excel


Proposed project for Alchemy Inc FIN 3150 Fall 2019 Assignment 8 - Evaluating sensitivity to risk Part 1. Select two companies that have stock prices continuously available for November 2014 through October 2019. Obtain monthly prices for each company (end of month) for that period. If you obtain prices from yahoo finance, you will get end of month prices if you request “monthly” prices even though the date indicates first of month. Use the adjusted closing price. If you use another source for stock prices, be sure you use the price on the last trading day of the month for the calculations in this part and adjust returns for stock splits and dividends For each stock, select one of the economic variables for which data is available in the “monthly” sheet in the file “assignment 8 data.xlsx”. (Use a different economic variable for each stock.) 1. Compute monthly returns for each stock and percentage changes for each selected variable. 2. Use a single variable regression to determine the sensitivity of each stock to the economic variable selected. Note: For construction spending or vehicle miles traveled, you will not be able to use all the stock returns. For these, use only returns for dates where there is a corresponding value for the percentage change in the underlying variable. Interpret the regression results for each stock and economic variable. That is, indicate the following for each stock and selected economic variable: 3. How a 1% change in the economic variable is expected to affect the value of the stock. 4. Whether the relationship between the economic variable and the stock is statistically significant (and explain how you make that determination). 5. Whether the stock’s natural risk associated with the economic variable is long or short. 6. How much stock return volatility can be eliminated if the risk associated with that economic variable is entirely eliminated. Part 2. Select two companies that have stock prices continuously available for November 3, 2014 through November 7, 2019. Obtain daily prices for each company for those dates. (You may use the same companies from part 1. For each stock, select one of the economic variables for which data is available in the “daily” sheet in the file “assignment 8 data.xlsx”. (Use a different economic variable for each stock.) 7. Compute daily returns for each stock and percentage changes for each selected variable. 8. Use a single variable regression to determine the sensitivity of each stock to the economic variable selected. Interpret the regression results for each stock and economic variable. That is, indicate the following for each stock and the selected economic variable: 9. How a 1% change in the economic variable is expected to affect the value of the stock. 10. Whether the relationship between the economic variable and the stock is statistically significant (and explain how you make that determination). 11. Whether the stock’s natural risk associated with the economic variable is long or short. 12. How much stock return volatility can be eliminated if the risk associated with that economic variable is entirely eliminated.
Answered Same DayNov 11, 2021

Answer To: Proposed project for Alchemy Inc FIN 3150 Fall 2019 Assignment 8 - Evaluating sensitivity to risk...

Kushal answered on Nov 14 2021
166 Votes
Exxon Monthly
    date (end of month)    PPI: Secondary smelting of aluminum    construction spending ($)    Changein Construction Spending    vehicle miles traveled (millions)    CPI personal computers and peripherals    U. of M. index of consumer sentiment
    2019-10                        95.7        2014-10-01    135.1    Exon Price    Adjusted Close Price    Price Change
    2019-09    101.9    116828    -1.92%        39.730    95.5        2014-11-01    134.7    31-Oct-2019    67.570000    -4%        SUMMARY OUTPUT
    2019-08    105.8    119109    0.17%    288116    40.056    93.2        2014-12-01    134.5    30-Sep-2019    70.610000    3%
    2019-07    108.6    118902    2.60%    294336    39.745    89.8        2015-01-01    133.2    31-Aug-2019    68.480000    -8%        Regression Statistics
    2019-06    111.8    115887    2.84%    279690    38.586    98.4        2015-02-01    131.4    31-Jul-2019    74.360000    -3%        Multiple R    0.0801967872
    2019-05    115.3    112691    5.53%    286395    39.339    98.2        2015-03-01    130.3    30-Jun-2019    76.630000    8%        R Square    0.0064315247
    2019-04    117.6    106786    7.13%    279148    39.603    100.0        2015-04-01    127.9    31-May-2019    70.770000    -12%        Adjusted R Square    -0.0113107695
    2019-03    118    99683    10.76%    270177    39.889    97.2        2015-05-01    126.1    30-Apr-2019    80.280000    -1%        Standard Error    0.0518526108
    2019-02    118.6    90000    1.38%    224137    39.649    98.4        2015-06-01    123.0    31-Mar-2019    80.800000    2%        Observations    58
    2019-01    120.9    88772    -6.96%    247149    40.044    93.8        2015-07-01    119.8    28-Feb-2019    79.030000    8%
    2018-12    122.5    95415    -10.48%    269706    40.110    91.2        2015-08-01    117.0    31-Jan-2019    73.280000    7%        ANOVA
    2018-11    126    106590    -7.31%    258574    39.841    98.3        2015-09-01    114.1    31-Dec-2018    68.190000    -14%            df    SS    MS    F    Significance F
    2018-10    127.3    115002    -3.33%    282230    40.573    97.5        2015-10-01    112.2    30-Nov-2018    79.500000    -0%        Regression    1    0.0009746427    0.0009746427    0.3624967894    0.5495529253
    2018-09    128.9    118968    -1.99%    263175    41.092    98.6
        2015-11-01    111.0    31-Oct-2018    79.680000    -6%        Residual    56    0.1505668218    0.0026886932
    2018-08    127.4    121385    -0.51%    285979    40.575    100.1        2015-12-01    110.3    30-Sep-2018    85.020000    6%        Total    57    0.1515414645
    2018-07    129.8    122010    1.92%    289390    40.230    96.2        2016-01-01    110.4    31-Aug-2018    80.170000    -2%
    2018-06    130.6    119712    3.01%    280583    40.986    97.9        2016-02-01    110.7    31-Jul-2018    81.510000    -1%            Coefficients    Standard Error    t Stat    P-value    Lower 95%    Upper 95%    Lower 95.0%    Upper 95.0%
    2018-05    130.7    116215    7.72%    283417    41.370    98.2        2016-03-01    111.5    30-Jun-2018    82.730000    2%        Intercept    -0.0033255451    0.0068380755    -0.4863276382    0.6286327172    -0.0170238565    0.0103727662    -0.0170238565    0.0103727662
    2018-04    128.4    107882    6.35%    272444    41.424    98.0        2016-04-01    111.4    31-May-2018    81.240000    4%        X Variable 1    0.0648320567    0.1076806621    0.6020770627    0.5495529253    -0.1508782302    0.2805423436    -0.1508782302    0.2805423436
    2018-03    126.9    101444    8.86%    269229    41.249    98.8        2016-05-01    111.3    30-Apr-2018    77.750000    4%
    2018-02    126    93191    4.20%    225146    41.278    101.4        2016-06-01    110.2    31-Mar-2018    74.610000    -1%
    2018-01    124.3    89433    -8.31%    243483    41.455    99.7        2016-07-01    109.3    28-Feb-2018    75.740000    -13%        3. Change
    2017-12    123    97535    -9.74%    267958    41.353    95.7        2016-08-01    109.4    31-Jan-2018    87.300000    4%        1% change in the construction spending will lead to 0.06483% change in the stock price
    2017-11    122.1    108061    -4.27%    258159    42.040    95.9        2016-09-01    109.5    31-Dec-2017    83.640000    0%
    2017-10    121.3    112886    -1.35%    278888    42.284    98.5        2016-10-01    109.0    30-Nov-2017    83.290000    -0%
    2017-09    119.3    114433    -1.88%    265212    42.190    100.7        2016-11-01    108.8    31-Oct-2017    83.350000    2%        4. Statistically Significant
    2017-08    117.1    116631    0.80%    282558    42.451    95.1        2016-12-01    109.1    30-Sep-2017    81.980000    7%
    2017-07    116.6    115703    0.58%    288566    42.973    96.8        2017-01-01    109.4    31-Aug-2017    76.330000    -5%        here due to very low R-squared value, and very high p values, we can see the stock price change and the economic variable is not statistically significant.
    2017-06    116.5    115035    4.56%    280290    42.561    93.4        2017-02-01    111.1    31-Jul-2017    80.040000    -1%
    2017-05    116.7    110017    7.47%    281264    42.361    95.0        2017-03-01    114.5    30-Jun-2017    80.730000    0%        5. Natural Risk
    2017-04    116.6    102367    4.16%    272864    42.896    97.1        2017-04-01    116.6    31-May-2017    80.500000    -1%        Due to the positive co-efficent , the natural risk associated with the vairable is long.
    2017-03    114.5    98283    11.11%    268343    42.818    97.0        2017-05-01    116.7    30-Apr-2017    81.650000    -0%
    2017-02    111.1    88459    2.34%    225644    43.369    96.9        2017-06-01    116.5    31-Mar-2017    82.010000    1%        6. Stock Volatility elimination
    2017-01    109.4    86433    -10.18%    242600    43.475    96.3        2017-07-01    116.6    28-Feb-2017    81.320000    -3%        Only 0.6% volatility of the stock can be eliminated based on the r-squared
    2016-12    109.1    96226    -8.74%    264778    43.377    98.5        2017-08-01    117.1    31-Jan-2017    83.890000    -7%
    2016-11    108.8    105436    -4.68%    255154    43.576    98.2        2017-09-01    119.3    31-Dec-2016    90.260000    3%
    2016-10    109    110613    -0.91%    275610    43.721    93.8        2017-10-01    121.3    30-Nov-2016    87.300000    5%
    2016-09    109.5    111628    -0.96%    262039    43.770    87.2        2017-11-01    122.1    31-Oct-2016    83.320000    -5%
    2016-08    109.4    112714    1.79%    279213    43.917    91.2        2017-12-01    123.0    30-Sep-2016    87.280000    0%
    2016-07    109.3    110734    -0.06%    285160    44.205    89.8        2018-01-01    124.3    31-Aug-2016    87.140000    -2%
    2016-06    110.2    110801    8.16%    276991    44.496    90.0        2018-02-01    126.0    31-Jul-2016    88.950000    -5%
    2016-05    111.3    102438    6.12%    277972    44.853    93.5        2018-03-01    126.9    30-Jun-2016    93.740000    5%
    2016-04    111.4    96532    5.00%    269653    45.282    94.7        2018-04-01    128.4    31-May-2016    89.020000    1%
    2016-03    111.5    91939    11.62%    265147    45.269    89.0        2018-05-01    130.7    30-Apr-2016    88.400000    6%
    2016-02    110.7    82367    3.00%    223011    45.249    91.0        2018-06-01    130.6    31-Mar-2016    83.590000    4%
    2016-01    110.4    79965    -9.23%    239679    45.424    91.7        2018-07-01    129.8    29-Feb-2016    80.150000    3%
    2015-12    110.3    88092    -7.57%    259424    45.997    92.0        2018-08-01    127.4    31-Jan-2016    77.850000    -0%
    2015-11    111    95306    -8.25%    248843    46.716    92.6        2018-09-01    128.9    31-Dec-2015    77.950000    -5%
    2015-10    112.2    103878    -2.33%    268469    47.094    91.3        2018-10-01    127.3    30-Nov-2015    81.660000    -1%
    2015-09    114.1    106359    -0.88%    255090    47.359    90.0        2018-11-01    126.0    31-Oct-2015    82.740000    11%
    2015-08    117    107303    0.88%    272209    47.132    87.2        2018-12-01    122.5    30-Sep-2015    74.350000    -1%
    2015-07    119.8    106370    0.74%    278372    47.892    91.9        2019-01-01    120.9    31-Aug-2015    75.240000    -5%
    2015-06    123    105593    8.55%    270574    48.164    93.1        2019-02-01    118.6    31-Jul-2015    79.210000    -5%
    2015-05    126.1    97280    7.32%    270839    48.667    96.1        2019-03-01    118.0    30-Jun-2015    83.200000    -2%
    2015-04    127.9    90647    9.32%    262817    49.047    90.7        2019-04-01    117.6    31-May-2015    85.200000    -2%
    2015-03    130.3    82916    12.39%    258017    48.772    95.9        2019-05-01    115.3    30-Apr-2015    87.370000    3%
    2015-02    131.4    73778    0.83%    217220    49.111    93.0        2019-06-01    111.8    31-Mar-2015    85.000000    -4%
    2015-01    133.2    73171    -8.97%    233498    48.913    95.4        2019-07-01    108.6    28-Feb-2015    88.540000    1%
    2014-12    134.5    80385    -7.03%    252271    49.089    98.1        2019-08-01    105.8    31-Jan-2015    87.420000    -5%
    2014-11    134.7    86464    -9.08%    241451    50.212    93.6        2019-09-01    101.9    31-Dec-2014    92.450000    2%
    2014-10    135.1    95095        265144    50.930    88.8                30-Nov-2014    90.540000
Chevron monthly
    date (end of month)    PPI: Secondary smelting of aluminum    construction spending ($)    Changein Construction Spending    vehicle miles traveled (millions)    CPI personal computers and peripherals    U. of M. index of consumer sentiment                Chevron Oil price    Adjusted Close Price    Price Change
    2019-10                        95.7        2014-10-01    135.1    31-Oct-2019    116.140000    -2%
    2019-09    101.9    116828    -1.92%        39.730    95.5        2014-11-01    134.7    30-Sep-2019    118.600000    1%        SUMMARY OUTPUT
    2019-08    105.8    119109    0.17%    288116    40.056    93.2        2014-12-01    134.5    31-Aug-2019    117.720000    -4%
    2019-07    108.6    118902    2.60%    294336    39.745    89.8        2015-01-01    133.2    31-Jul-2019    123.110000    -1%        Regression Statistics
    2019-06    111.8    115887    2.84%    279690    38.586    98.4        2015-02-01    131.4    30-Jun-2019    124.440000    9%        Multiple R    0.0803362536
    2019-05    115.3    112691    5.53%    286395    39.339    98.2        2015-03-01    130.3    31-May-2019    113.850000    -5%        R Square    0.0064539136
    2019-04    117.6    106786    7.13%    279148    39.603    100.0        2015-04-01    127.9    30-Apr-2019    120.060000    -3%        Adjusted R Square    -0.0109767194
    2019-03    118    99683    10.76%    270177    39.889    97.2        2015-05-01    126.1    31-Mar-2019    123.180000    3%        Standard Error    0.0568847532
    2019-02    118.6    90000    1.38%    224137    39.649    98.4        2015-06-01    123.0    28-Feb-2019    119.580000    4%        Observations    59
    2019-01    120.9    88772    -6.96%    247149    40.044    93.8        2015-07-01    119.8    31-Jan-2019    114.650000    5%
    2018-12    122.5    95415    -10.48%    269706    40.110    91.2        2015-08-01    117.0    31-Dec-2018    108.790000    -9%        ANOVA
    2018-11    126    106590    -7.31%    258574    39.841    98.3        2015-09-01    114.1    30-Nov-2018    118.940000    7%            df    SS    MS    F    Significance F
    2018-10    127.3    115002    -3.33%    282230    40.573    97.5        2015-10-01    112.2    31-Oct-2018    111.650000    -9%        Regression    1    0.0011981239    0.0011981239    0.3702627215    0.5452784195
    2018-09    128.9    118968    -1.99%    263175    41.092    98.6        2015-11-01    111.0    30-Sep-2018    122.280000    3%        Residual    57    0.1844448831    0.0032358751
    2018-08    127.4    121385    -0.51%    285979    40.575    100.1        2015-12-01    110.3    31-Aug-2018    118.460000    -6%        Total    58    0.1856430071
    2018-07    129.8    122010    1.92%    289390    40.230    96.2        2016-01-01    110.4    31-Jul-2018    126.270000    -0%
    2018-06    130.6    119712    3.01%    280583    40.986    97.9        2016-02-01    110.7    30-Jun-2018    126.430000    2%            Coefficients    Standard Error    t Stat    P-value    Lower 95%    Upper 95%    Lower 95.0%    Upper 95.0%
    2018-05    130.7    116215    7.72%    283417    41.370    98.2        2016-03-01    111.5    31-May-2018    124.300000    -1%        Intercept    0.0022583221    0.0074337988    0.3037911183    0.7623932354    -0.0126276033    0.0171442474    -0.0126276033    0.0171442474
    2018-04    128.4    107882    6.35%    272444    41.424    98.0        2016-04-01    111.4    30-Apr-2018    125.110000    10%        X Variable 1    0.0717862743    0.1179740312    0.6084921704    0.5452784195    -0.1644526482    0.3080251967    -0.1644526482    0.3080251967
    2018-03    126.9    101444    8.86%    269229    41.249    98.8        2016-05-01    111.3    31-Mar-2018    114.040000    2%
    2018-02    126    93191    4.20%    225146    41.278    101.4        2016-06-01    110.2    28-Feb-2018    111.920000    -11%
    2018-01    124.3    89433    -8.31%    243483    41.455    99.7        2016-07-01    109.3    31-Jan-2018    125.350000    0%
    2017-12    123    97535    -9.74%    267958    41.353    95.7        2016-08-01    109.4    31-Dec-2017    125.190000    5%        1% change in the construction spending will lead to 0.07% change in the stock price
    2017-11    122.1    108061    -4.27%    258159    42.040    95.9        2016-09-01    109.5    30-Nov-2017    118.990000    3%
    2017-10    121.3    112886    -1.35%    278888    42.284    98.5        2016-10-01    109.0    31-Oct-2017    115.890000    -1%
    2017-09    119.3    114433    -1.88%    265212    42.190    100.7        2016-11-01    108.8    30-Sep-2017    117.500000    9%        4. Statistically Significant
    2017-08    117.1    116631    0.80%    282558    42.451    95.1        2016-12-01    109.1    31-Aug-2017    107.620000    -1%
    2017-07    116.6    115703    0.58%    288566    42.973    96.8        2017-01-01    109.4    31-Jul-2017    109.190000    5%        here due to very low R-squared value, and very high p values, we can see the stock price change and the economic variable is not statistically significant.
    2017-06    116.5    115035    4.56%    280290    42.561    93.4        2017-02-01    111.1    30-Jun-2017    104.330000    1%
    2017-05    116.7    110017    7.47%    281264    42.361    95.0        2017-03-01    114.5    31-May-2017    103.480000    -3%        5. Natural Risk
    2017-04    116.6    102367    4.16%    272864    42.896    97.1        2017-04-01    116.6    30-Apr-2017    106.700000    -1%        Due to the positive co-efficent , the natural risk associated with the vairable is long.
    2017-03    114.5    98283    11.11%    268343    42.818    97.0        2017-05-01    116.7    31-Mar-2017    107.370000    -5%
    2017-02    111.1    88459    2.34%    225644    43.369    96.9        2017-06-01    116.5    28-Feb-2017    112.500000    1%        6. Stock Volatility elimination
    2017-01    109.4    86433    -10.18%    242600    43.475    96.3        2017-07-01    116.6    31-Jan-2017    111.350000    -5%        Only 0.6% volatility of the stock can be eliminated based on the r-squared
    2016-12    109.1    96226    -8.74%    264778    43.377    98.5        2017-08-01    117.1    31-Dec-2016    117.700000    6%
    2016-11    108.8    105436    -4.68%    255154    43.576    98.2        2017-09-01    119.3    30-Nov-2016    111.560000    7%
    2016-10    109    110613    -0.91%    275610    43.721    93.8        2017-10-01    121.3    31-Oct-2016    104.750000    2%
    2016-09    109.5    111628    -0.96%    262039    43.770    87.2        2017-11-01    122.1    30-Sep-2016    102.920000    2%
    2016-08    109.4    112714    1.79%    279213    43.917    91.2        2017-12-01    123.0    31-Aug-2016    100.580000    -2%
    2016-07    109.3    110734    -0.06%    285160    44.205    89.8        2018-01-01    124.3    31-Jul-2016    102.480000    -2%
    2016-06    110.2    110801    8.16%    276991    44.496    90.0        2018-02-01    126.0    30-Jun-2016    104.830000    4%
    2016-05    111.3    102438    6.12%    277972    44.853    93.5        2018-03-01    126.9    31-May-2016    101.000000    -1%
    2016-04    111.4    96532    5.00%    269653    45.282    94.7        2018-04-01    128.4    30-Apr-2016    102.180000    7%
    2016-03    111.5    91939    11.62%    265147    45.269    89.0        2018-05-01    130.7    31-Mar-2016    95.400000    14%
    2016-02    110.7    82367    3.00%    223011    45.249    91.0        2018-06-01    130.6    29-Feb-2016    83.440000    -4%
    2016-01    110.4    79965    -9.23%    239679    45.424    91.7        2018-07-01    129.8    31-Jan-2016    86.470000    -4%
    2015-12    110.3    88092    -7.57%    259424    45.997    92.0        2018-08-01    127.4    31-Dec-2015    89.960000    -1%
    2015-11    111    95306    -8.25%    248843    46.716    92.6        2018-09-01    128.9    30-Nov-2015    91.320000    0%
    2015-10    112.2    103878    -2.33%    268469    47.094    91.3        2018-10-01    127.3    31-Oct-2015    90.880000    15%
    2015-09    114.1    106359    -0.88%    255090    47.359    90.0        2018-11-01    126.0    30-Sep-2015    78.880000    -3%
    2015-08    117    107303    0.88%    272209    47.132    87.2        2018-12-01    122.5    31-Aug-2015    80.990000    -8%
    2015-07    119.8    106370    0.74%    278372    47.892    91.9        2019-01-01    120.9    31-Jul-2015    88.480000    -8%
    2015-06    123    105593    8.55%    270574    48.164    93.1        2019-02-01    118.6    30-Jun-2015    96.470000    -6%
    2015-05    126.1    97280    7.32%    270839    48.667    96.1        2019-03-01    118.0    31-May-2015    103.000000    -7%
    2015-04    127.9    90647    9.32%    262817    49.047    90.7        2019-04-01    117.6    30-Apr-2015    111.060000    6%
    2015-03    130.3    82916    12.39%    258017    48.772    95.9        2019-05-01    115.3    31-Mar-2015    104.980000    -2%
    2015-02    131.4    73778    0.83%    217220    49.111    93.0        2019-06-01    111.8    28-Feb-2015    106.680000    4%
    2015-01    133.2    73171    -8.97%    233498    48.913    95.4        2019-07-01    108.6    31-Jan-2015    102.530000    -9%
    2014-12    134.5    80385    -7.03%    252271    49.089    98.1        2019-08-01    105.8    31-Dec-2014    112.180000    3%
    2014-11    134.7    86464    -9.08%    241451    50.212    93.6        2019-09-01    101.9    30-Nov-2014    108.870000    ERROR:#DIV/0!
    2014-10    135.1    95095        265144    50.930    88.8
Chevron daily
        S&P 500 Index    yield on BBB bonds    exchange rate for £    Change    Volatility index    West Texas intermediate crude oil price    Chevron price    Change
    2019-11-07    3085.18    3.36%    1.2820    -0.1920    3.36        121.890000    2%            SUMMARY OUTPUT
    2019-11-06    3076.78    3.28%    1.5867    0.2318    3.28        119.900000    -2%
    2019-11-05    3074.62    3.32%    1.2881    -0.0016    3.32        121.940000    0%            Regression Statistics
    2019-11-04    3078.27    3.27%    1.2901    -0.0038    3.27    56.330    121.570000    5%            Multiple R    0.0400614134
    2019-11-01    3066.91    3.24%    1.2950    0.0009    3.24    56.040    116.210000    0%            R Square    0.0016049168
    2019-10-31    3037.56    3.22%    1.2939    0.0052    3.22    54.020    116.140000    -0%            Adjusted R Square    0.0008404489
    2019-10-30    3046.77    3.28%    1.2872    -0.0026    3.28    54.850    116.360000    -1%            Standard Error    0.0141071895
    2019-10-29    3036.89    3.30%    1.2905    0.0035    3.30    55.340    118.130000    -0%            Observations    1308
    2019-10-28    3039.42    3.31%    1.2860    0.0021    3.31    55.600    118.480000    -0%
    2019-10-25    3022.55    3.29%    1.2833    0.0018    3.29    56.520    118.670000    1%            ANOVA
    2019-10-24    3010.29    3.27%    1.2810    -0.0059    3.27    56.110    117.580000    -0%                df    SS    MS    F    Significance F
    2019-10-23    3004.52    3.27%    1.2886    -0.0048    3.27    55.900    117.980000    0%            Regression    1    0.0004178056    0.0004178056    2.0993907409    0.1475978997
    2019-10-22    2995.99    3.27%    1.2948    -0.0027    3.27    54.210    117.800000    1%            Residual    1306    0.2599107115    0.0001990128
    2019-10-21    3006.72    3.31%    1.2983    0.0061    3.31    53.280    116.610000    2%            Total    1307    0.2603285171
    2019-10-18    2986.20    3.28%    1.2904    0.0040    3.28    53.750    114.740000    -1%
    2019-10-17    2997.95    3.30%    1.2853    -0.0001    3.30    53.890    115.350000    0%                Coefficients    Standard Error    t Stat    P-value    Lower 95%    Upper 95%    Lower 95.0%    Upper 95.0%
    2019-10-16    2989.69    3.30%    1.2854    0.0092    3.30    53.420    115.110000    -1%            Intercept    0.0000511706    0.0003900903    0.1311762813    0.8956560619    -0.0007141015    0.0008164427    -0.0007141015    0.0008164427
    2019-10-15    2995.68    3.33%    1.2737    0.0043    3.33    52.810    116.310000    0%            X Variable 1    -0.0553355405    0.0381906911    -1.448927445    0.1475978997    -0.130257354    0.019586273    -0.130257354    0.019586273
    2019-10-14    2966.15    3.34%    1.2683    0.0000    3.34    53.570    116.180000    0%
    2019-10-11    2970.27    3.34%    1.2683    0.0243    3.34    54.760    116.150000    1%            3. Change
    2019-10-10    2938.13    3.29%    1.2382    0.0137    3.29    53.570    114.590000    1%            1% change in the exchange rate will lead to -0.553% change in the stock price
    2019-10-09    2919.40    3.24%    1.2215    0.0007    3.24    52.630    113.140000    1%
    2019-10-08    2893.06    3.20%    1.2206    -0.0094    3.20    52.640    111.710000    -1%
    2019-10-07    2938.79    3.21%    1.2322    0.0011    3.21    52.760    113.260000    -1%            4. Statistically Significant
    2019-10-04    2952.01    3.17%    1.2309    -0.0065    3.17    52.840    113.850000    1%
    2019-10-03    2910.63    3.19%    1.2390    0.0063    3.19    52.410    113.150000    1%            here due to very low R-squared value, and very high p values, we can see the stock price change and the economic variable is not statistically significant.
    2019-10-02    2887.61    3.24%    1.2313    0.0058    3.24    52.670    112.290000    -3%
    2019-10-01    2940.25    3.26%    1.2242    -0.0051    3.26    53.600    116.010000    -2%            5. Natural Risk
    2019-09-30    2976.74    3.30%    1.2305    -0.0006    3.30    54.090    118.600000    0%            Due to the negative co-efficent , the natural risk associated with the vairable is short.
    2019-09-27    2961.79    3.28%    1.2312    -0.0025    3.28    55.950    118.600000    -1%
    2019-09-26    2977.62    3.29%    1.2343    -0.0016    3.29    56.240    120.160000    -3%            6. Stock Volatility elimination
    2019-09-25    2984.87    3.33%    1.2363    -0.0090    3.33    56.380    123.510000    -0%            Only 0.1% volatility of the stock can be eliminated based on the r-squared...
SOLUTION.PDF

Answer To This Question Is Available To Download

Related Questions & Answers

More Questions »

Submit New Assignment

Copy and Paste Your Assignment Here