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Predicting default probabilities and implementing trading strategies for emerging markets bond portfolios

机译：预测新兴市场债券投资组合的违约概率并实施交易策略

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摘要

In this paper, we address two main issues: the computation of default probability implicit in emerging markets bond prices and the impact on portfolio risks and returns of expected changes in default probability. Using a reduced-form model, weekly estimates of default probabilities for U.S. Dollar denominated Global bonds of 12 emerging markets are extrapolated for the sample period 1997-2001. The estimation of a logit type econometric model shows that weekly changes of the default probabilities can be explained by means of some capital markets factors. Recursively estimating the logit model using rolling windows of data, out-of-sample forecasts for the dynamics of default probabilities are generated and used to form portfolios of bonds. The practical application provides interesting results, both in terms of testing the ability of a naive trading strategy based on model forecasts to outperform a "customized benchmark", and in terms of the model ability to actively manage the portfolio risk (evaluated in terms of VaR) with respect to a constant proportion allocation.
机译：在本文中，我们解决了两个主要问题：新兴市场债券价格中隐含的违约概率的计算以及违约概率的预期变化对投资组合风险和收益的影响。使用简化形式的模型，以1997-2001年为样本期，推断了12个新兴市场以美元计价的全球债券的违约概率的每周估计。对数型计量经济学模型的估计表明，违约概率的每周变化可以通过一些资本市场因素来解释。使用滚动数据窗口递归估计logit模型，将生成默认违约率动态的样本外预测，并将其用于形成债券投资组合。实际应用程序提供了有趣的结果，既可以测试基于模型预测的幼稚交易策略的性能胜过“定制基准”，也可以通过模型有效管理投资组合风险的能力（以VaR评估） ）的比例分配。

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