Modelling market implied ratings using LASSO variable selection techniques

Georgios Sermpinis, Serafeim Tsoukas and Ping Zhang

Journal of Empirical Finance, 2018, vol. 48, issue C, 19-35

Abstract: Making accurate predictions of corporate credit ratings is a crucial issue to both investors and rating agencies. In this paper, we investigate the determinants of market implied credit ratings in relation to financial factors, market-driven indicators and macroeconomic predictors. Applying a variable selection technique, the least absolute shrinkage and selection operator (LASSO), we document substantial predictive ability. In addition, when we compare our LASSO-selected models with the benchmark ordered probit model, we find that the former models have superior predictive power and outperform the latter model in all out-of-sample predictions.

Keywords: Market implied ratings; LASSO; Financial ratios; Forecasting (search for similar items in EconPapers)
JEL-codes: C25 G24 G33 O16 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (17)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:empfin:v:48:y:2018:i:c:p:19-35

DOI: 10.1016/j.jempfin.2018.05.001

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