Return seasonalities in government bonds and macroeconomic risk

Mikutowski, Mateusz; Karathanasopoulos, Andreas; Zaremba, Adam

doi:10.1016/j.econlet.2019.01.012

Cited by 5 publications

(3 citation statements)

References 6 publications

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“…First, our research could ease the financial burden of the central government, promote the development of the capital market, overcome the tendency of using foreign capital in local currency and help the government to study and formulate a scientific and reasonable issuance scale and mode (Dove, 2016;Eichler and Plaga, 2017). Second, it can avoid the occurrence of speculative events and reduce the economic losses caused by default in the process of municipal bond issuance (Clarke and Lu, 2017;Ehrmann and Fratzscher, 2017;Mikutowski et al, 2019).…”

Section: Introductionmentioning

confidence: 97%

“…Our research has the following implications: First, our research could ease the financial burden of the central government, promote the development of the capital market, overcome the tendency of using foreign capital in local currency and help the government to study and formulate a scientific and reasonable issuance scale and mode (Dove, 2016; Eichler and Plaga, 2017). Second, it can avoid the occurrence of speculative events and reduce the economic losses caused by default in the process of municipal bond issuance (Clarke and Lu, 2017; Ehrmann and Fratzscher, 2017; Mikutowski et al , 2019). Third, this research could help local governments to plan the financing scale reasonably, avoid credit risks caused by excessive issuance of debt, provide scientific data support for the establishment of debt default bankruptcy mechanism and crisis management mechanism, as well as provide objective and fair reference materials for investors (Câmara et al , 2012; Gennaioli et al , 2018; Piljak and Swinkels, 2017).…”

Section: Introductionmentioning

confidence: 99%

“…Second, it can avoid the occurrence of speculative events and reduce the economic losses caused by default in the process of municipal bond issuance (Clarke and Lu, 2017; Ehrmann and Fratzscher, 2017; Mikutowski et al , 2019).…”

Section: Introductionmentioning

confidence: 99%

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A prediction model for the secure issuance scale of Chinese local government bonds

Jia

et al. 2020

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Purpose The purpose of this paper is to calculate the local guaranteed fiscal revenue with the local fiscal revenue of 31 provinces, and predict their guaranteed fiscal revenue in 2018 with the artificial neural network (ANN). Design/methodology/approach The principal components analysis (PCA), particle swarm optimization (PSO) and extreme learning machine (ELM) model was designed to produce the inputs of KMV model. Then the KMV model was used for obtaining the default probabilities under different issuance scales. Data were collected from Wind Database. MATLAB 2018b and SPSS 22 were used in the field of modeling and results analysis. Findings This study’s findings show that PCA–PSO–ELM proposed in this research has the highest accuracy in terms of the prediction compared with ELM, back propagation neural network and auto regression. And PCA–PSO–ELM–KMV model can calculate the secure issuance scale of local government bonds effectively. Practical implications The sustainability forecast in this study can help local governments effectively control the scale of debt issuance, strengthen the budget management of local debt and establish the corresponding risk warning mechanism, which could make local governments maintain good credit ratings. Originality/value This study sheds new light on helping local governments avoid financial risks effectively, and it is conducive to establish a debt repayment reserve system for local governments and the proper arrangement for stock debt.

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