Using Diverse Local Optima for Setting Kernel Parameters in Support Vector Regression: Forecasting Emerging Market Credit Spreads (2024)
Working Paper
Anderson, G., & Audzeyeva, A. (2024). Using Diverse Local Optima for Setting Kernel Parameters in Support Vector Regression: Forecasting Emerging Market Credit Spreads

We propose a novel approach for determining support vector regression (SVR) kernel parameters in the presence of multiple local optima. In contrast to existing approaches focusing on identifying a single "best" tuning parameter setting, an impractica... Read More about Using Diverse Local Optima for Setting Kernel Parameters in Support Vector Regression: Forecasting Emerging Market Credit Spreads.

On the Prediction of Emerging Market Sovereign Credit Spreads (2015)
Journal Article
Audzeyeva, A., & Fuertes, A. (2015). On the Prediction of Emerging Market Sovereign Credit Spreads. https://doi.org/10.2139/ssrn.2649216

This paper examines the quarter-ahead out-of-sample predictability of Brazil, Mexico, the Philippines and Turkey credit spreads before and after the Lehman Brothers' default. A model based on the country-specific credit spread curve factors predicts... Read More about On the Prediction of Emerging Market Sovereign Credit Spreads.

Emerging Market Sovereign Credit Spreads: In-Sample and Out-of-Sample Predictability (2015)
Journal Article
Audzeyeva, A., & Fuertes, A. (2015). Emerging Market Sovereign Credit Spreads: In-Sample and Out-of-Sample Predictability. https://doi.org/10.2139/ssrn.2649216

This paper investigates the quarter-ahead predictability of Brazil, Mexico, Philippines and Turkey credit spreads for short and long maturity bonds during two separate periods preceding and following the Lehman Brothers' default. A model based on the... Read More about Emerging Market Sovereign Credit Spreads: In-Sample and Out-of-Sample Predictability.