D Financial Market Indicators

This module delves into key financial market indicators such as interest rates, stock market indices, commodity prices, yield curves, and credit spreads. It provides a detailed exploration of how these indicators are measured, the data sources used, and their importance in assessing the financial markets’ performance and stability.

D.1 Overview

Outlined below are the chapters contained in this module:

  • Chapter 11: “Financial Market Indicators” delves into topics such as interest rates, stock market metrics, and indicators of financial stability.

Additionally, the following DataCamp course supplements the chapter mentioned above:

  • Introduction to Data Visualization with ggplot2: This course introduces the principles of effective data visualization using the ggplot2 package in R, covering foundational plotting concepts and enabling you to create professional exploratory graphics.

The module culminates in the creation of a data report:

  • Data Report on Yield Curves: This tests your ability in analyzing yield curves and their forecasting potential for macroeconomic indicators.

D.2 Learning Objectives

Upon completing this module, students will be able to:

  1. Understand and identify key financial market indicators.
  2. Locate and interpret data sources relevant to these measures.
  3. Utilize R to effectively visualize financial market data.
  4. Draw insights from these visualizations and understand their implications.

D.3 Learning Activities & Assessments

Throughout this module, you’ll engage in the following activities:

  • Textbook Engagement: Read the textbook chapter 11 and reproduce the content provided. Input the code from the chapters into RStudio and verify that your results match the chapter outputs.

  • DataCamp Training: Work through the Introduction to Data Visualization with ggplot2 course on DataCamp. While progressing through the courses, keep an R script handy and apply the learned functions to any of the datasets introduced in this module. This preserves the new functions of the course and potentially offers new insights from the chosen dataset.

  • Data Report Creation: To consolidate your learning, craft a Data Report on Yield Curves using R Markdown. Your report should clearly display data, provide meaningful analyses, and embody the module’s content.

Your assessment will be based on:

  • DataCamp Course Completion: Finish the designated DataCamp courses for this module. Your grade is based on course completion; thus, you receive full credit by completing all chapters and obtaining a minimum of 75% XPs (experience points) by the deadline. Hence, while the Take Hint and Show Answer options reduce your XPs, they won’t affect your module grade if you stay above the 75% threshold.

  • Data Report Evaluation: The quality of the data report is central to module assessment. It should be professional, suitable for clients, and reflect the module’s content. Ensure you adhere to the data report instructions.

For further guidance on maximizing your textbook and DataCamp experience, consult the Textbook Engagement and Learn R with DataCamp sections. For specifications on the data report’s format and content, consult the Data Report Instructions and the subsequent section below.

D.4 Data Report on Yield Curves

Analyze the yield curves from your birth date alongside the most recent one. Plot both curves, and if data isn’t available for your birth date (either due to a pre-1990 birth or a non-trading day), use the next available trading day’s data. Utilize insights from Chapter 11 to interpret the curve shapes and compare them against macroeconomic indicators of the respective periods. If you’re unfamiliar with yield curves, consider further research, starting with the U.S. Treasury website where you sourced your data.

As preparation for this assignment, please work through the module chapters and DataCamp courses listed under the overview section above. Ensure your report adheres to the guidelines detailed in Data Report Instructions, which dictates the creation of two versions: official and internal. Upon completion, submit both versions on Blackboard.