A hybrid Training Course for traders, investors & analysts
A 3-day course providing the necessary models and tools required for relative value trading in the fixed income markets. Taking place in-person in London and online.
Course Introduction
This 3-day course provides a comprehensive but concise overview over the models and tools required for successful relative value analysis in fixed income markets. Both statistical and financial models are covered and numerous hands-on exercises and case studies prepare participants to translate the theory into profitable trading strategies. The transition to new reference rates and its impact on swaps (spreads) is extensively addressed.
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Familiarity with common fixed income instruments and trades is a prerequisite, while advanced mathematical knowledge is not.
Who should attend: traders, fund managers, hedge funds, institutional investors and analysts.
"Very insightful, the right amount of theoretical backed up with market data. It has planted the seeds for many ideas to research in my day to day".
Lewis Gatrell, Portfolio Manager, Brightwell Pensions
Course Details
12-14 May 2025
Duration: 3 Days
Hybrid: Tower Hotel, London E1 and Online
Course Fee: £3400 + VAT
Course Outline
Day 1: Statistical Relative Value Models
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Introduction to Fixed Income Relative Value (RV) Analysis
• Concept of RV analysis
• Sources of RV opportunities
• The insights from RV analysis
• Applications of RV analysis: trading, hedging, asset selection, creating alpha
• RV models: statistical and financial models and their interaction
• Outline of the course
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Principal Component Analysis (PCA): Theory
• What is PCA and how does it help us?
• PCA versus other factor models
• Mathematics of PCA
• Gaining insights into market mechanisms through interpretation of the PCA results
• Decomposing a market into directional (beta) and non-directional (alpha) factors
• Using PCA to screen the market for trading opportunities
• Using PCA for asset selection
• Combining all these elements into a step-by-step guide for PCA-based analysis and trading
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Principal Component Analysis: Practice
• Using PCA for yield curve analysis
• Using PCA for swaption analysis
• Using PCA for hedging and asset selection
• Using PCA in other markets: stocks, FX, commodities
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Mean Reversion (MR): Theory
• What is mean reversion and how does it help us?
• Mathematics and model selection
• Calculating conditional expectations and probability densities
• Calculating Sharpe ratios
• Calculating first passage times
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Mean Reversion: Practice
• Which performance is likely over which horizon?
• Setting performance targets
• Setting stop loss levels
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Practical Case Study: Applying Statistical RV Models in a Trading Context
• Perform a PCA on the yield curve and find trading opportunities
• Run a mean reversion model to assess the performance potential and speed of these trades
Multi-Variate Ornstein-Uhlenbeck Process (MVOU)
• Combining MR and correlation between time series into a single model
• Intuition and Mathematics of MVOU
• Application 1: Butterfly analysis
• Application 2: Analysis of a portfolio of trades
Day 2: Asset Swaps, Basis Swaps, Default Swaps, and their Combinations
Overview
• Link and mutual influences between all swap markets worldwide
• Consequences for analytic approach and goals
• Roadmap for the day
Reference Rates
• The transition from LIBOR to OIS and SOFR
• Repo market and SOFR calculation
• A model for the spread between unsecured (LIBOR) and secured (repo) rates
Asset Swap Spreads (ASW)
• Model approach: ASW combine a funding and a credit swap
• Model the funding swap via the LIBOR-repo model
• Model the credit swap via adjusting CDS quotes
• Swap spread curves and driving factors of flattening/steepening
• Cyclicality of swap spreads
• Factors not covered in the model (yet): Haircuts, shadow cost of capital and impacts from other markets via the basis swap
Credit Default Swaps (CDS)
• FX component and other pricing issues
• Using adjusted CDS quotes for swap spread analysis and trading
• Other RV trades with CDS
Basis Swaps (BSW)
• Intra-currency basis swaps
• Cross-currency basis swaps
• Swapping bonds into a different currency
• Spreads versus USD SOFR as common yardstick for all global bonds
Combinations and Mutual Influences Between ASW, BSW and CDS
• The “arbitrage inequality” between ASW, BSW and CDS
• Trading this “arbitrage inequality” in practice
• The equilibrium between all global swap markets
Practical Case Study: The Mutual Influences of ASW, BSW and CDS in the JGB Market
Global Bond RV via SOFR Asset Swap Spreads
• Deficiencies of using swap spreads as rich/cheap indicator for bonds
• Mitigating these deficiencies for SOFR asset swap spreads
Other Influencing Factors
• Haircuts
• Regulatory constraints
• Shadow cost of (arbitrage) capital
• The limitations of swap spread models
Day 3: Analytic Tools and Framework for Bonds, Futures and Options
Fitted Curves for Bond Markets
• Goals: generation of constant maturity time series without structural breaks and of rich/cheap indicators for asset selection
• Functional forms
• External explanatory variables such as benchmark or CTD status
• Model setup
• Interpretation and application of results
• Comparision with SOFR asset swap spreads as rich/cheap indicators
An Analytic Process for Government Bond Markets
• Combining fitted curves, PCA and MR (or MVOU)
• Monitoring the market for trading opportunities
• Defining exposure
• Asset selection
• Execution optimisation
• Portfolio considerations
Bond Futures and their Delivery Option
• The importance of the delivery option
• Usual approach to price the delivery option and its problems
• A better approach to price the delivery option
• Applications: basis trades and calendar spreads/rolls
Swaption Trading Strategies
• Brief review of option pricing theory
• Classification of option trades
• Different exposures and goals of the different option trades
Swaption Trading Strategy 1: Conditional Curve Trades
• Single underlying: breakeven analysis, breakeven curves, link to macro models
• Multiple underlyings: conditional steepeners and butterflies
Swaption Trading Strategy 2: Implied Versus Realized Volatility
• Single underlying: delta hedging, calculation of realized volatility
• Multiple underlyings: implied vol curve versus realized vol curve
Swaption Trading Strategy 3: Implied Versus Implied Volatility
• Factor model for the swaption vol surface
• Practical pitfalls
Practical Case Study: Finding, Classifying and Analysing Swaption Trades on the USD Vol Surface
Course Trainer
Christian Schaller has 30 years of experience in Relative Value analysis. He played a key role in establishing the current analytic state-of-the-art in the areas of principal component analysis and basis swap modeling. He co-authored the books Fixed Income Relative Value Analysis – A practitioner’s guide to the Theory, Tools and Trades, Wiley, 2024 (2nd edition) and SOFR Futures and Options, Wiley, 2022.
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After earning a Ph.D. in Mathematics at the University of Bonn, Germany, in 1995, Christian learned the tools of the fixed income trade in the Relative Value team at Deutsche Bank, managed by Anshu Jain. As Global Head of Leveraged Investment Strategy at ABN AMRO, he used his skill to translate mathematical theory into profitable trading positions for the firm’s most demanding clients, including hedge funds, proprietary trading desks, central banks, and other financial institutions. Since 2004, he has advised investment banks on the development, training, and management of quantitative research teams through his Japan-based consulting firm Shinzenbi Ltd.
