Are CDS spreads predictable during the Covid-19 pandemic? Forecasting based on SVM, GMDH, LSTM and Markov switching autoregression

This paper investigates the forecasting performance for credit default swap (CDS) spreads by Support Vector Machines (SVM), Group Method of Data Handling (GMDH), Long Short-Term Memory (LSTM) and Markov switching autoregression (MSA) for daily CDS spreads of the 513 leading US companies, in the period 2009–2020. The goal of this study is to test the forecasting performance of these methods before and during the Covid-19 pandemic and to check whether there are changes in the market efficiency. MSA outperforms all other methods most frequently. GMDH breaks the efficient market hypothesis more frequently (75%) than other methods. The change of the relative predictability during Covid-19 is small with some increase of the advantage of the investigated methods over a benchmark. We find that the market has been less efficient during Covid-19, however, there are no huge differences in prediction performances before and during the Covid-19 period. © 2022 Elsevier Ltd

Авторы
Vukovic D.B. 1, 2 , Romanyuk K.3 , Ivashchenko S.4, 5, 6 , Grigorieva E.M. 1, 7
Издательство
Elsevier Ltd
Язык
Английский
Статус
Опубликовано
Номер
116553
Том
194
Год
2022
Организации
  • 1 International Laboratory for Finance and Financial Markets, Faculty of Economics, People's Friendship University of Russia, (RUDN University), 117198, Miklukho-Maklaya str. 6, Moscow, Russian Federation
  • 2 Geographical Institute “Jovan Cvijic” SASA, Djure Jaksica 9, Belgrade, 11000, Serbia
  • 3 Higher School of Economics University, 101000, Myasnitskaya str. 6, Moscow, Russian Federation
  • 4 North-Western Main Branch of the Bank of Russia, 191038, Saint Petersburg Fontanka River Embankment, 68 (107016, Moscow, 12 Neglinnaya Street), Russian Federation
  • 5 Macroeconomic Analysis Division, Financial Research Institute, 127006, Moscow, Nastasyinsky Lane, 3, p. 2, Russian Federation
  • 6 Theoretical Economics Laboratory, The Institute of Regional Economy Studies (Russian Academy of Sciences), 190013, Saint Petersburg, Serpukhovskaya Street 36-38, Russian Federation
  • 7 Finance and Credit Department, Faculty of Economics, People's Friendship University of Russia (RUDN University), 117198, Miklukho-Maklaya str.6, Moscow, Russian Federation
Ключевые слова
CDS spreads; Covid-19; GMDH; LSTM; Markov switching autoregression; SVM
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