scholarly journals Rolling window selection for out-of-sample forecasting with time-varying parameters

2017 ◽  
Vol 196 (1) ◽  
pp. 55-67 ◽  
Author(s):  
Atsushi Inoue ◽  
Lu Jin ◽  
Barbara Rossi
Mathematics ◽  
2021 ◽  
Vol 9 (19) ◽  
pp. 2423
Author(s):  
Nikita Moiseev ◽  
Aleksander Sorokin ◽  
Natalya Zvezdina ◽  
Alexey Mikhaylov ◽  
Lyubov Khomyakova ◽  
...  

The research paper is devoted to developing a mathematical approach for dealing with time-varying parameters in rolling window logit models for credit risk assessment. Forecasting coefficients yields a better model accuracy than a trivial approach of using computed past statistics parameters for the next time period. In this paper, a new method of dealing with time-varying parameters of scoring models is proposed, which is aimed at computing the default probability of a borrower. It was empirically shown that in a continuously changing economic environment factors’ influence on a target variable is also changing. Therefore, forecasting coefficients yields a better financial result than simply applying parameters obtained by accumulated statistics over past time periods. The paper develops a new theoretical approach, incorporating a combination of the ARIMA class model, the DCC-GARCH model and the state–space model, which is more accurate, than using only the ARIMA model. Rigorous simulation testing is provided to confirm the efficiency of the proposed method.


2015 ◽  
Vol 9 (6) ◽  
pp. 568
Author(s):  
Ahmad Al-Jarrah ◽  
Mohammad Ababneh ◽  
Suleiman Bani Hani ◽  
Khalid Al-Widyan

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