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Modeling the Volatility of US Bond Yields

Discover how the US bond yields behave using descriptive statistics and advanced modeling.

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10 Tasks1,500 XP

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Project Description

In this project, we will explore the volatility structure of US Government Bond Yields. Essentially all financial assets exhibit a phenomenon called volatility clustering where low and high volatility regimes follow each other. The alternating volatility regimes are a focus for risk management and investment decisions. We will use the well-known GARCH (Generalized AutoRegressive Conditional Heteroskedasticity) method to explore the statistical properties of financial time series data.

This project assumes background knowledge on time series analysis, GARCH modeling, plotting and uses packages xts and rugarch.

The historical yield data are published by the US Federal Reserve Data Releases and imported from Quandl, https://www.quandl.com/data/FED/SVENY,

Project Tasks

  1. 1
    Volatility changes over time
  2. 2
    Plotting the evolution of bond yields
  3. 3
    Make the difference
  4. 4
    The US yields are no exceptions, but maturity matters
  5. 5
    Let's dive into some statistics
  6. 6
    GARCH in action
  7. 7
    Fitting the 20-year maturity
  8. 8
    What about the distributions? (Part 1)
  9. 9
    What about the distributions? (Part 2)
  10. 10
    A final quiz

Technologies

R R

Topics

Data VisualizationApplied Finance
József Soltész HeadshotJózsef Soltész

Manager at KPMG

József Soltész, CFA, FRM is a banking expert specialized in market and liquidity risks. He loves to find the underlying story hidden in the data and emphasizes sharing the knowledge. In his day-to-day work, he analyzes the risk management activities and risk models of banks using SQL, VBA, and R.
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