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(a)
To determine:
To set the spreadsheet and to calculate the 26 week moving average of the index
Introduction:
For a stock price, the moving average is the average stock price over a certain given time interval. This interval however gets updated with time. In case of a 50 day moving average, the average price is tracked over the prior 50 days.
Answer to Problem 23PS
The 26 week moving average of the index is calculated and is presented in the explanation.
Explanation of Solution
Given Information:
Value of the index in the same period beginning should be kept as 100 and For each week it is updated by multiplying the level of previous week by (1+
The data was downloaded from the given website.
The weekly returns are converted to weekly index values. Here 100 is used as the base for the week before the first week of the set of data. From this, the 26 week moving average of S&P 500 is calculated.
| Week | S&P rate |
| 2013.01 | 1.64 |
| 2013.02 | 0.17 |
| 2013.03 | -0.82 |
| 2013.04 | 0.85 |
| 2013.05 | 0.59 |
| 2013.06 | -0.21 |
| 2013.07 | 0.12 |
| 2013.08 | 1.19 |
| 2013.09 | -3.27 |
| 2013.1 | -1.00 |
| 2013.11 | -0.03 |
| 2013.12 | 3.25 |
| 2013.13 | -0.23 |
| 2013.14 | -0.47 |
| 2013.15 | 0.47 |
| 2013.16 | -2.97 |
| 2013.17 | -0.91 |
| 2013.18 | 0.07 |
| 2013.19 | -0.20 |
| 2013.2 | 2.77 |
| 2013.21 | 0.11 |
| 2013.22 | 1.21 |
| 2013.23 | -0.27 |
| 2013.24 | 0.19 |
| 2013.25 | -0.85 |
| 2013.26 | -1.02 |
| 2013.27 | -0.92 |
| 2013.28 | -1.57 |
| 2013.29 | 1.72 |
| 2013.3 | -3.60 |
| 2013.31 | 0.32 |
| 2013.32 | 3.07 |
| 2013.33 | 0.88 |
| 2013.34 | 0.59 |
| 2013.35 | 0.85 |
| 2013.36 | 0.50 |
| 2013.37 | -1.49 |
| 2013.38 | 1.96 |
| 2013.39 | -1.00 |
| 2013.4 | -1.11 |
| 2013.41 | -1.13 |
| 2013.42 | 2.91 |
| 2013.43 | 3.61 |
| 2013.44 | 1.29 |
| 2013.45 | -0.86 |
| 2013.46 | 0.79 |
| 2013.47 | 0.76 |
| 2013.48 | 0.06 |
| 2013.49 | 0.57 |
| 2013.5 | 1.11 |
| 2013.51 | 0.08 |
| 2013.52 | -2.01 |
| 2014.01 | -0.17 |
| 2014.02 | -1.24 |
| 2014.03 | 0.56 |
| 2014.04 | 2.38 |
| 2014.05 | 0.45 |
| 2014.06 | -0.32 |
| 2014.07 | 0.87 |
| 2014.08 | 1.07 |
| 2014.09 | -1.91 |
| 2014.1 | -1.15 |
| 2014.11 | -1.18 |
| 2014.12 | 0.25 |
| 2014.13 | 0.48 |
| 2014.14 | -3.26 |
| 2014.15 | 1.24 |
| 2014.16 | 0.16 |
| 2014.17 | 1.15 |
| 2014.18 | -1.17 |
| 2014.19 | 2.93 |
| 2014.2 | 0.96 |
| 2014.21 | -0.09 |
| 2014.22 | 0.05 |
| 2014.23 | 1.37 |
| 2014.24 | -1.96 |
| 2014.25 | 0.46 |
| 2014.26 | 1.49 |
| 2014.27 | 1.26 |
| 2014.28 | 0.57 |
| 2014.29 | 0.16 |
| 2014.3 | -0.69 |
| 2014.31 | 0.14 |
| 2014.32 | -0.47 |
| 2014.33 | -1.39 |
| 2014.34 | 1.24 |
| 2014.35 | 1.91 |
| 2014.36 | -0.46 |
| 2014.37 | -1.67 |
| 2014.38 | 1.32 |
| 2014.39 | -2.79 |
| 2014.4 | -0.78 |
| 2014.41 | -0.45 |
| 2014.42 | 1.41 |
| 2014.43 | 1.93 |
| 2014.44 | 1.35 |
| 2014.45 | 1.10 |
| 2014.46 | 1.60 |
| 2014.47 | -0.22 |
| 2014.48 | -0.41 |
| 2014.49 | 0.55 |
| 2014.5 | 0.31 |
| 2014.51 | -1.77 |
| 2014.52 | 3.15 |
| 2015.01 | 0.19 |
| 2015.02 | -2.10 |
| 2015.03 | 2.04 |
| 2015.04 | -1.76 |
| 2015.05 | 0.29 |
| 2015.06 | 1.72 |
| 2015.07 | 0.47 |
| 2015.08 | -0.50 |
| 2015.09 | -0.13 |
| 2015.1 | 1.99 |
| 2015.11 | -0.32 |
| 2015.12 | -0.29 |
| 2015.13 | -0.23 |
| 2015.14 | -0.64 |
| 2015.15 | 1.90 |
| 2015.16 | 0.24 |
| 2015.17 | 0.80 |
| 2015.18 | -2.48 |
| 2015.19 | -1.66 |
| 2015.2 | 1.01 |
| 2015.21 | 0.48 |
| 2015.22 | -2.83 |
| 2015.23 | -0.12 |
| 2015.24 | -0.17 |
| 2015.25 | 2.29 |
| 2015.26 | -0.53 |
| 2015.27 | -2.44 |
| 2015.28 | 0.34 |
| 2015.29 | 3.25 |
| 2015.3 | 0.17 |
| 2015.31 | -0.93 |
| 2015.32 | 2.89 |
| 2015.33 | -0.67 |
| 2015.34 | 1.23 |
| 2015.35 | -0.86 |
| 2015.36 | 1.73 |
| 2015.37 | -0.38 |
| 2015.38 | 1.61 |
| 2015.39 | 1.08 |
| 2015.4 | 1.20 |
| 2015.41 | 0.15 |
| 2015.42 | 0.78 |
| 2015.43 | -1.00 |
| 2015.44 | 1.25 |
| 2015.45 | 1.58 |
| 2015.46 | -0.05 |
| 2015.47 | -0.09 |
| 2015.48 | 0.85 |
| 2015.49 | 0.65 |
| 2015.5 | -1.11 |
| 2015.51 | 0.62 |
| 2015.52 | -0.76 |
| 2016.01 | 1.92 |
| 2016.02 | -0.29 |
| 2016.03 | -0.48 |
| 2016.04 | 1.88 |
| 2016.05 | -0.60 |
| 2016.06 | 1.24 |
| 2016.07 | -0.29 |
| 2016.08 | -4.57 |
| 2016.09 | 1.52 |
| 2016.1 | -1.21 |
| 2016.11 | 3.51 |
| 2016.12 | -0.97 |
| 2016.13 | 1.58 |
| 2016.14 | 0.74 |
| 2016.15 | 2.27 |
| 2016.16 | 0.61 |
| 2016.17 | 0.93 |
| 2016.18 | -0.03 |
| 2016.19 | 1.16 |
| 2016.2 | -0.61 |
| 2016.21 | 1.57 |
| 2016.22 | -1.97 |
| 2016.23 | 1.78 |
| 2016.24 | -1.64 |
| 2016.25 | -0.08 |
| 2016.26 | 1.70 |
| 2016.27 | 1.22 |
| 2016.28 | -0.87 |
| 2016.29 | -5.46 |
| 2016.3 | -0.90 |
| 2016.31 | 0.63 |
| 2016.32 | 0.00 |
| 2016.33 | 2.51 |
| 2016.34 | -0.50 |
| 2016.35 | -1.03 |
| 2016.36 | 1.94 |
| 2016.37 | 2.55 |
| 2016.38 | 0.40 |
| 2016.39 | 2.14 |
| 2016.4 | 0.31 |
| 2016.41 | -4.26 |
| 2016.42 | 2.63 |
| 2016.43 | -1.57 |
| 2016.44 | -4.01 |
| 2016.45 | 0.45 |
| 2016.46 | -1.14 |
| 2016.47 | 3.15 |
| 2016.48 | 1.52 |
| 2016.49 | -2.48 |
| 2016.5 | 1.18 |
| 2016.51 | -0.56 |
| 2016.52 | -4.06 |
| 2017.01 | -0.82 |
| 2017.02 | -5.77 |
| 2017.03 | 0.75 |
| 2017.04 | 4.91 |
| 2017.05 | -4.67 |
| 2017.06 | 1.56 |
| 2017.07 | 0.35 |
| 2017.08 | -1.32 |
| 2017.09 | -3.08 |
| 2017.1 | -0.07 |
| 2017.11 | 2.41 |
| 2017.12 | -0.43 |
| 2017.13 | 4.09 |
| 2017.14 | -2.56 |
| 2017.15 | 3.82 |
| 2017.16 | 0.81 |
| 2017.17 | 1.37 |
| 2017.18 | -1.85 |
| 2017.19 | 2.70 |
| 2017.2 | -3.52 |
| 2017.21 | 1.96 |
| 2017.22 | -2.89 |
| 2017.23 | -0.11 |
| 2017.24 | -2.87 |
| 2017.25 | -3.08 |
| 2017.26 | -0.96 |
| 2017.27 | -1.95 |
| 2017.28 | 1.72 |
| 2017.29 | -0.40 |
| 2017.3 | 0.55 |
| 2017.31 | 2.54 |
| 2017.32 | 0.62 |
| 2017.33 | -0.40 |
| 2017.34 | -0.66 |
| 2017.35 | -3.40 |
| 2017.36 | 1.35 |
| 2017.37 | -0.99 |
| 2017.38 | -2.63 |
| 2017.39 | -8.70 |
| 2017.4 | -19.79 |
| 2017.41 | 5.33 |
| 2017.42 | -6.63 |
| 2017.43 | 11.25 |
| 2017.44 | -3.07 |
| 2017.45 | -7.71 |
| 2017.46 | -8.19 |
| 2017.47 | 13.29 |
| 2017.48 | -2.39 |
| 2017.49 | 1.20 |
| 2017.5 | -0.09 |
| 2017.51 | -1.17 |
| 2017.52 | 6.66 |
The graph shows the 26 week moving average with the help of average of index prices over 5 year period.
(b)
To determine:
To determine the instances where the moving average is crossed from below and the number of week after which the index increases following a cross-through.
Introduction:
For a stock price, the moving average is the average stock price over a certain given time interval. This interval however gets updated with time. In case of a 50 day moving average, the average price is tracked over the prior 50 days.
Answer to Problem 23PS
As per the data, 15 times the index moves below the moving average.
Explanation of Solution
Given Information:
The data is available in the given website.
From the data it is clear that there are 15 instances when the S&P index goes below the moving average. It is seen that 8 times the index goes up in weeks succeeding the cross-through. The index diminishes 7 times in weeks following a cross-through.
(c)
To determine:
To determine the instances where the index crosses through the moving average from above and the number of weeks in which the index increases following a cross-through and decreases following the cross-through.
Introduction:
For a stock price, the moving average is the average stock price over a certain given time interval. This interval however gets updated with time. In case of a 50 day moving average, the average price is tracked over the prior 50 days.
Answer to Problem 23PS
As per the data, 16 times the index moves below the moving average.
Explanation of Solution
Given Information:
The data is available in the given website.
From the data it is clear that there are 16 instances when the S&P index goes above the moving average. It is seen that 10 times the index goes up in weeks succeeding the cross-through. The index diminishes 6 times in weeks following a cross-through.
(d)
To determine:
To determine how well the moving average rule functions in identifying the selling or buying opportunities.
Introduction:
For a stock price, the moving average is the average stock price over a certain given time interval. This interval however gets updated with time. In case of a 50 day moving average, the average price is tracked over the prior 50 days.
Answer to Problem 23PS
This data does not help in predicting the sell or buy opportunities.
Explanation of Solution
Given Information:
The data is available in the given website.
The data which is available and the related calculations that are made do not help in obtaining the rule of relative strength which is needed to identify the buy or sell opportunities. So, this rule will not be applicable in this scenario.
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Chapter 12 Solutions
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