Lessons
- CFA Level 2: Fixed Income Part 1 – Introduction
- Principles of Credit Analysis
- High Yield Corporate Debt (aka Junk bonds)
- Analyzing Credit of Asset Backed Securities
- Analyzing Credit of Municipal Bonds
- Sovereign Debt
- Three Shapes of the Yield Curve
- Parallel and Non-parallel Shifts in Yield Curve
- Factors Driving Treasury Investment Returns and Bond Price Risk
- Yield Curve Construction with Treasuries
- LIBOR Swap Rate Curve
- Theories of the Term Structure of Interest Rates
- Key Rate Duration
- How to Calculate Interest Rate Volatility?
- Benchmark Yield Spreads
- Valuing an Option Embedded Bond using Binomial Interest Rate Tree
- How to Price Convertible Bonds?
Parallel and Non-parallel Shifts in Yield Curve
Parallel Shift
Rates across the maturity spectrum change by a constant amount and the slope of the yield curve remains consistent.
Non-Parallel Shifts
- Twist: The slope of the yield curve becomes flatter (the spread between short and long term yields narrows) or steeper (the spread between short and long term yields widens).
- Butterfly: Change to the curvature of the yield curve.
**Positive butterfly:** The yield curve goes loses some of its "hump" and becomes straighter. **Negative butterfly:** The yield curve takes on more of a hump and ceases to look similar to a straight line.
Data Science in Finance: 9-Book Bundle
Master R and Python for financial data science with our comprehensive bundle of 9 ebooks.
What's Included:
- Getting Started with R
- R Programming for Data Science
- Data Visualization with R
- Financial Time Series Analysis with R
- Quantitative Trading Strategies with R
- Derivatives with R
- Credit Risk Modelling With R
- Python for Data Science
- Machine Learning in Finance using Python
Each book includes PDFs, explanations, instructions, data files, and R code for all examples.
Get the Bundle for $39 (Regular $57)JOIN 30,000 DATA PROFESSIONALS
Free Guides - Getting Started with R and Python
Enter your name and email address below and we will email you the guides for R programming and Python.
