Masterarbeit, 2015
83 Seiten, Note: 1,5
This work focuses on developing trading strategies for government bonds. It introduces two approaches to yield curve prediction, an arbitrage-free model and a parametric estimation method. The performance of these methods is analyzed and compared in the context of US Treasury bonds. Additionally, the concept of portfolio optimization with respect to conditional value at risk is explained and two methods for its efficient implementation are presented. Finally, the study demonstrates how yield curve estimations can be integrated into portfolio optimization to generate trading strategies.
Government bonds, yield curve prediction, arbitrage-free model, Heath-Jarrow-Morton model, parametric estimation, dynamic Nelson-Siegel method, portfolio optimization, conditional value at risk, trading strategies, US Treasury bonds.
The work focuses on government bond markets, specifically using yield curve prediction models to develop arbitrage-free trading strategies.
It is an arbitrage-free yield modelling framework used to predict the evolution of interest rates and bond prices.
DNS is a parametric estimation method used to fit and forecast the yield curve, often compared to arbitrage-free models for performance.
CVaR is a risk measure that quantifies the tail risk of a portfolio, focusing on the average loss in extreme negative scenarios.
The performance of both models was tested and compared using US Treasury yield curve data.
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