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Credit default swap (CDS) prediction model & trading strategy
| Nome: | Descrição: | Tamanho: | Formato: | |
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| 2.29 MB | Adobe PDF |
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This project focuses on the study of different explanatory models for the behavior of CDS security, such as Fixed-Effect Model, GLS Random-Effect Model, Pooled OLS and Quantile Regression Model.
After determining the best fitness model, trading strategies with long and short positions in CDS have been developed. Due to some specifications of CDS, I conclude that the quantile regression is the most efficient model to estimate the data. The P&L and Sharpe Ratio of the strategy are
analyzed using a backtesting analogy, where I conclude that, mainly for non-financial companies, the model allows traders to take advantage of and profit from arbitrages.
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Credit default swap Econometric prediction model Quantile regression Trading strategy