Repository Article

·2021 OPEN ACCESS

Recent Innovation in Benchmark Rates (BMR): Evidence from Influential Factors on Turkish Lira Overnight Reference Interest Rate with Machine Learning Algorithms

Özer Depren YTU , Mustafa Tevfik Kartal YTU , Serpil Kılıç Depren YTU

SSRN Electronic Journal

Abstract

Some countries have announced national benchmark rates while some others have been working on the recent trend in which the London Interbank Offered Rate (LIBOR) will be retired at the end of 2021. Considering that Turkey announced the Turkish Lira Overnight Reference Interest Rate (TLREF), this study examines the determinants of TLREF. In this context, three global determinants, five country-level macroeconomic determinants, and COVID-19 pandemic are considered by using daily data between December 28, 2018 and December 31, 2020 by performing machine learning algorithms and Ordinary Least Square. The empirical results show that (i) the most significant determinant is the amount of securities bought by Central Bank; (ii) country-level macroeconomic factors have a higher impact whereas global factors are less important, and the pandemic does not have a significant effect; (iii) Random Forest is the most accurate prediction model. Taking actions by considering the findings of the study, can be beneficial to support economic growth by achieving low-level benchmark rates.

Keywords

Turkish Interest rate Benchmark (surveying) Context (archaeology) Lira Libor Random forest Economics Econometrics Machine learning Monetary economics Computer science Exchange rate Geography

Subject Areas

Monetary Policy and Economic Impact ·General Economics, Econometrics and Finance ·Social Sciences
Market Dynamics and Volatility ·Economics and Econometrics ·Social Sciences
Energy, Environment, Economic Growth ·Economics and Econometrics ·Social Sciences