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Outputs (4)

Dynamics and Determinants of Credit Risk Discovery: Evidence from CDS and Stock Markets (2017)
Journal Article
Chau, F., Han, C., & Shi, S. (2018). Dynamics and Determinants of Credit Risk Discovery: Evidence from CDS and Stock Markets. International Review of Financial Analysis, 55, 156-169. https://doi.org/10.1016/j.irfa.2017.11.004

This paper investigates the dynamics and drivers of credit risk discovery between stock and CDS markets in the US. Our research is distinguished from the existing literature in three aspects: 1) we employ an improved method to measure the information... Read More about Dynamics and Determinants of Credit Risk Discovery: Evidence from CDS and Stock Markets.

Deep Learning Networks for Stock Market Analysis and Prediction: Methodology, Data Representations, and Case Studies (2017)
Journal Article
Chong, E., Han, C., & Park, F. (2017). Deep Learning Networks for Stock Market Analysis and Prediction: Methodology, Data Representations, and Case Studies. Expert Systems with Applications, 83, 187-205. https://doi.org/10.1016/j.eswa.2017.04.030

We offer a systematic analysis of the use of deep learning networks for stock market analysis and prediction. Its ability to extract features from a large set of raw data without relying on prior knowledge of predictors makes deep learning potentiall... Read More about Deep Learning Networks for Stock Market Analysis and Prediction: Methodology, Data Representations, and Case Studies.

Partial Structural Break Identi fication (2017)
Journal Article
Han, C., & Taamouti, A. (2017). Partial Structural Break Identi fication. Oxford Bulletin of Economics and Statistics, 79(2), 145-164. https://doi.org/10.1111/obes.12153

We propose an extension of the existing information criterion-based structural break identification approaches. The extended approach helps identify both pure structural change (break) and partial structural change (break). A pure structural change r... Read More about Partial Structural Break Identi fication.

A Geometric Treatment of Time-Varying Volatilities (2017)
Journal Article
Han, C., Park, F. C., & Kang, J. (2017). A Geometric Treatment of Time-Varying Volatilities. Review of Quantitative Finance and Accounting, 49(4), 1121-1141. https://doi.org/10.1007/s11156-017-0618-0

In this article, we propose a new framework for addressing multivariate time-varying volatilities. By employing methods of differential geometry, our model respects the geometric structure of the covariance space, i.e., symmetry and positive definite... Read More about A Geometric Treatment of Time-Varying Volatilities.