Fixed Income Relative Value Trading

This two-day course provides a comprehensive and concise overview of the models and tools required for relative value trading in the fixed income markets. The application of the relative value toolkit in an actual trading context is particularly emphasized with practical exercises and case studies enabling participants to translate theory into effective trading strategies. Familiarity with common fixed income instruments and Excel is assumed although in-depth mathematical knowledge is not required. Delegates are equipped with PCs.

November 14 to November 15, 2017
Duration: Two days (9.00am to 5.00pm)
Location: The Tower Hotel – London, UK
Trainer: Christian Schaller
Course fee: £1890 + VAT – Register online

DAY 1: Statistical Relative Value Models

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

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

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

Mean Reversion: 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

Mean Reversion: Practice

+ Which performance is likely over which horizon?
+ Setting performance targets
+ Setting stop loss levels

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

DAY 2: Swaps, Options and their Combinations

Asset swap spreads (ASW)

+ Model approach: Link between ASW and LIBOR-repo spreads + A model for pricing ASW
+ Driving factors of ASW
+ Making the pricing model for ASW work in practice

Basis swaps (BSW)

+ Intra-currency basis swaps
+ Cross-currency basis swaps
+ Swapping bonds into a different currency
+ Assessing the relative value between bonds in different currencies
+ The mutual influences between ASW and BSW

Credit default swaps (CDS) for government bonds

+ FX component and other pricing issues
+ The "arbitrage inequality" between ASW, BSW and CDS
+ Trading this "arbitrage inequality" in practice

Practical case study 1

+ The mutual influences of ASW, BSW and CDS in the JGB market

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