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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: G24 G33 C25 O16 (search for similar items in EconPapers)
Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:eee:empfin:v:48:y:2018:i:c:p:19-35

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Journal of Empirical Finance is currently edited by R. T. Baillie, F. C. Palm, Th. J. Vermaelen and C. C. P. Wolff

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