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Bootstrapping a Treasury Yield Curve
Vinay Bharath
Vinay Bharath
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Bootstrapping a Treasury Yield Curve

Master the method to derive precise interest rates for different maturities by leveraging financial modelling techniques.

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Mondays
 at
5:00
P.M.
 ET /
2:00
P.M.
PT
8 weeks, 2-3 hours per week
Expert
No experience required
No experience required
Some experience required
Degree and experience required

Description

In this Finance Modeling Project, you'll step into the shoes of a Quantitative Analyst and construct a Treasury Yield Curve from scratch. Under the supervision of an experienced industry expert, you'll analyze market data and implement a mathematical model in Python to estimate term structures of interest rates. You'll become familiar with industry tools and methodologies for data manipulation and bootstrapping techniques for yield curve construction. All this will provide invaluable hands-on experience crucial for entry-level roles in finance, where proficiency in quantitative modeling and data analysis is highly valued.

Session timeline

  • Applications open
    September 5, 2024
  • Application deadline
    September 19, 2024
  • Project start date
    Week of July 8, 2024
    Week of
    October 7, 2024
  • Project end date
    Week of

What you will learn

  • Deepen your understanding of fixed income concepts such as par rates, coupons, yield-to-maturity, gaining insights into bond valuation.
  • Develop proficiency in Python programming, including data manipulation, statistical analysis and visualization using libraries such as Pandas, NumPy and Matplotlib.
  • Gain knowledge of financial market data sources and APIs for accessing and retrieving relevant financial data for analysis.
  • Get hands on experience in applying financial modeling techniques for yield curve construction and interpolation.

Project workshops

1
Introductions & setting up Jupyter notebook
2
Fixed Income Concepts
3
Yield to Maturity
4
Fetching Data
5
Bootstrapping basics
6
Bootstrapping hands-on
7
Compare model with real data
8
Conclusion & further reading

Prerequisites

  • Experience with Python (loops, conditions, functions, libraries, simple algorithms). Knowledge of Jupyter notebook is a plus.
  • Understanding of financial concepts like compound interest, coupon rate, par values etc.
  • Familiarity with statistical techniques such as interpolation, regression and curve fitting.

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About the expert

Hi everyone! My name is Vinay and I’m originally from India and did my Master's in Financial Engineering from NYU. I currently work as an Associate for an Asset Management company in Boston helping to build tools that analyze how our investment ideas affect client portfolios.

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