ASSIGNMENT 2, FINANCIAL ECONOMETRICS SUMMER 2023
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ASSIGNMENT 2, FINANCIAL ECONOMETRICS SUMMER 2023
This assignment covers materials discussed in class. The report is due on 7/14. Submit it on Canvas. Follow the instructions, including the notes at the end of this document. Some of you may want to work individually. However, you can work in groups of up to three students.
1. Data
The analysis will use the time series listed below, attached to the assignment announcement. These series relate to bank financial performance, specifically credit card portfolio balances, and delinquencies.
a. DDCQ.csv (Delinquency Rate on Credit Card Loansfor U.S. Commercial Banks)
This series is seasonally adjusted, so it does not require seasonal modeling. The file has two columns used in the R code discussed below. The columns are CCDQ, the delinquency date, and CHGCCDQ, the one-period change (already differenced series) on the delinquency rate.
b. CCBAL.csv (Credit Card Balancefor U.S. Commercial Banks)
This series is not seasonally adjusted, so that it will require seasonal modeling. The series includes one column, CCBAL. The R code described below has steps to obtain the regular and seasonal differencing.
2. Spreadsheets and Code
The assignment will require Excel and R. You will use Excel exponential smoothing examples to produce CCDQ and CCBAL forecast estimates. You will then use R to generate ARIMA and SARIMA forecasts on the CCDQ and CCBAL series. The details of the attached Excel spreadsheets and R programs are as follows:
a. Excel: Holt.xlsx
• This spreadsheet contains an example of a quarterly forecast using the Holt exponential smoothing technique. You will modify the spreadsheet to accommodate the series used in this assignment .
b. Excel: Holt- Winters.xlsx
• This spreadsheet contains an example of a quarterly forecast using the Holt-Winters seasonal technique. You will modify the spreadsheet to accommodate the series used in this assignment .
a. R Code: CCDQ.R
• This program takes the CCDQ.csv series and runs an ARIMA model and related analyses. You will only have to modify the “setwd” based on your file location, and the program should produce the outputs smoothly. The analysis requirements are in the analysis section below.
b. R Code: CCBAL.R
• This program takes the CCBAL.csv series and runs a seasonal ARIMA (SARIMA) model and related analyses. You will only have to modify the “setwd” based on your file location, and the program should produce the outputs smoothly. The analysis requirements are in the analysis section below.
3. Analysis
As noted above, you will modify the Excel files and run the R code to produce linear and seasonal forecasts and related analyses. Once you obtain the predictions and associated outputs, you will describe the data and results and answer related questions. The analysis will involve the following:
a. Description of time series
• You will use the provided report template to paste charts of the CCDQ and CCBAL series and their differenced versions. You will also discuss the ADF, ACF, and PACF outputs.
b. Holt Exponential Smoothing and ARIMA Forecasts on the CCDQ series
• The assignment asks you to discuss the differences between the Holt exponential smoothing and ARIMA techniques. Also, you will discuss differences or similarities between the Holt exponential smoothing and ARIMA forecasts, explaining reasons for the difference or similarity between the two outputs.
c. Holt- Winters and SARIMAforecasts on the CCBAL series
• You will present a discussion similar to the one outlined above for the CCDQ forecasts. The analysis will include a description of the series and a comparison of the projections.
d. Chief Credit Officer’s Perspective
• You will assume the bank’s Chief Credit Officer role. Do high-level background research on the banks’ credit card lending business (trends, risk, expectations, etc.). Familiarize yourself with the state of the credit card lending market. Then, based on the knowledge you acquired, assess the direction and magnitude of the forecasts, discussing whether you would adjust the projections based on your perspective as a credit officer. Also, outline additional information to determine whether you need to restrict, maintain, or increase the banks’ lending volume.
4. Report
Summarize the outputs and analysis in a report following the template attached to the assignment. When you complete the analysis, save it as a pdf document. The template will have the following sections:
a. Cover
• Show the students’ names.
b. Time Series Charts
• Present relevant observations about the data series and related ADF, ACF, and PACF outputs. Use text and chart boxes based on the attached pre-formatted template.
c. Forecast Outputs
• Paste each series’s forecast outputs and discuss the results answering the questions on the report template. Use the text and chart boxes based on the attached pre-formatted template.
d. Discussion
• Use this section to discuss the results and answer the questions listed in the analysis section above. The specific questions will be on the report template.
e. Conclusion
• State what you think is the most important inference from the analysis.
Other Notes
• Assume you are preparing this report for presentation to a group of colleagues interested in the assignment topic. Use the template provided, keeping a professional report style.
• When discussing the results or answering the questions, be clear and organized. Clarity and organization will be a factor in the evaluation.
• Follow the pre-formatted style, using the text and chart boxes as requested. When you complete the report, save it in pdf format.
• Submit the report on Canvas, in pdf format. You only need to submit your pdf file. Do not submit CSV or R files.
• You can work in groups of up to three students. Submit only one report per group. If you work in groups, ensure all student names are on the report cover.
2023-07-11