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### objective
env: Windows
deadline 23/12
### CAUTION
Do not include any code not written by you in your
project. You are NOT allowed to import any Python libraries in your solution except the
modules namely os (https://docs.python.org/3/library/os.html), sys
(https://docs.python.org/3/library/sys.html) and csv (https://docs.python.org/3/library/csv.html). If
cheating is found or the import requirement is violated, you will receive a zero mark.
### Deliverable
You have to include your student name and ID in your source code and name your project solution as
“XXXXXXXX_project.py” (where XXXXXXXX is your 8-digit student ID). Please remember to
upload your source code solution to Moodle by the submission deadline.
### drill down
Functions
Given the file of stock prices, you are asked to develop a Python program to process the data by
designing appropriate functions. At minimum you need to implement and call the following three
functions:
• get_data_list(csv_file_name)
This function has one parameter, namely csv_file_name. When the function is called, you
need to pass along a CSV file name which is used inside the function to open and read the CSV
file. After reading each row, it will be split into a list. The list will then be appended into a main
list (a list of lists), namely data_list. The data_list will be returned at the end of the
function.
2
• get_monthly_averages(data_list)
This function has one parameter, namely data_list. You need to pass the data_list
generated by the get_data_list() function as the argument to this function and then
calculate the monthly average prices of the stock. The average monthly prices are calculated in
the following way. Suppose the volume and adjusted closing price of a trading day are V1 and C1,
respectively. The total sale of that day equals V1 x C1. Now, suppose the volume and adjusted
closing price of another trading day are V2 and C2, respectively. The average of these two trading
days is the sum of the total sales divided by the total volume:
Average price = (V1 x C1 + V2 x C2) / (V1 + V2)
To average a whole month, you need to add up the total sales (V1 x C1 + V2 x C2 + ... +
Vn x Cn) for each day and divide it by the sum of all volumes (V1 + V2 + ... + Vn) where n
is the number of trading days in the month.
A tuple with 2 items, including the date (year and month only) and the average for that month,
will be generated for each month. The tuple for each month will be appended to a main list,
namely monthly_averages_list. The monthly_averages_list will be returned at
the end of the function.
• get_moving_averages(monthly_averages_list)
This function has one parameter, namely monthly_averages_list. You need to pass the
monthly_averages_list generated by get_monthly_averages() as the argument
to this function and then calculate the 5-month exponential moving average (EMA) stock prices.
In general, the EMA for a particular month can be calculated by the following formula:
EMA = (Monthly average price – previous month’s EMA) x smoothing constant
+ previous month’s EMA
where
smoothing constant = 2 / (number of time periods in months + 1)
3
For example, the following table shows the stock prices between Oct 2020 and Apr 2021:
Month Monthly Average Price
Oct 2020 14
Nov 2020 13
Dec 2020 14
Jan 2021 12
Feb 2021 13
Mar 2021 12
Apr 2021 11
The initial 5-month EMA for Feb 2021 can be calculated by the simple average formula, as
shown below:
5-month EMA for Feb 2021 = (14 + 13 + 14 + 12 + 13) / 5 = 13.2
The 5-month EMA for Mar 2021 can be calculated by the EMA formula, as shown below:
5-month EMA for Mar 2021 = (Monthly average price – previous month’s EMA) x
smoothing constant + previous month’s EMA
= (12 – 13.2) x (2 / 6) + 13.2
= 12.8
The 5-month EMA for Apr 2021 can be calculated by the EMA formula, as shown below:
5-month EMA for Apr 2021 = (Monthly average price – previous month’s EMA) x
smoothing constant + previous month’s EMA
= (11 – 12.8) x (2 / 6) + 12.8
= 12.2
The resulting 5-month EMA stock prices are shown below:
Month Average Price 5-month EMA Price
Oct 2020 14 -
Nov 2020 13 -
Dec 2020 14 -
Jan 2021 12 -
Feb 2021 13 13.2
Mar 2021 12 12.8
Apr 2021 11 12.2
4
A tuple with 2 items, including the date (year and month only) and the 5-month EMA price for
that month, will be generated for each month except the first 4 months. Each tuple will be
appended to a main list, namely moving_averages_list. The
moving_averages_list will be returned at the end of the function.
Program Input and Output
At the outset, your program needs to ask the user for a CSV file name:
Based on the entered CSV file name, a corresponding output text file (e.g. “Google_output.txt”
for this case) will be generated. In the output file, you are eventually required to print the best month
(with the highest EMA price) and the worst month (with the lowest EMA price) for the stock. You
need to first print a header line for the stock, and then print a date (MM-YYYY), a comma followed by
a moving average price (in 2 decimal places) on another line. You must follow the output format as
shown below (please note the values are not true, which are for reference only)
IV. Evaluation Criteria (40% of Overall Course Assessment)
The project will be graded using the following criteria:
• 15% - Correctness of program execution and output data
• 10% - Modularization (e.g. dividing the program functionality into different functions)
• 5% - Error handling
• 5% - Consistent style (e.g., capitalization, indenting, etc.)
• 5% - Appropriate comments