Forecasting Bitcoin volatility: A new insight from the threshold regression model

2021 ◽  
Author(s):  
Yaojie Zhang ◽  
Mengxi He ◽  
Danyan Wen ◽  
Yudong Wang
2020 ◽  
Vol 12 (3) ◽  
pp. 376-398 ◽  
Author(s):  
Takumi Saegusa ◽  
Tianzhou Ma ◽  
Gang Li ◽  
Ying Qing Chen ◽  
Mei-Ling Ting Lee

2020 ◽  
Vol 12 (19) ◽  
pp. 8198
Author(s):  
Yue Zhu ◽  
Ziyuan Sun ◽  
Ling Wang ◽  
Xiaoping Wang ◽  
Lu Zhang

The purpose of this research is to develop the subjective initiative and enhance the sense of independent innovation in the process of high-tech enterprises, so as to guarantee the sustainable development of innovation ability. Based on the relevant data of high-tech enterprises from 2012 to 2017, a threshold regression model was established to study the existence of innovative “incentive” catering behaviors in the process of identifying high-tech enterprises. First, the empirical test results support the hypothesis of innovative “incentives” catering behavior, identified by high-tech enterprises, with a threshold of 0.0370. The empirical results show that the one-size-fits-all objective identification standard will indeed encourage some companies to adopt catering behaviors. Next, the paper verifies that high-tech companies that do not adopt “incentive” catering behaviors will have higher innovation efficiencies. Moreover, the R&D investment and R&D subsidy of high-tech enterprises without catering behaviors will be higher. Finally, through a stepwise regression test, it was found that R&D investment and R&D subsidies play an intermediary role in the relationship between innovation “incentives” catering behavior and corporate innovation efficiency. High-tech enterprises affect the innovation efficiency of enterprises through the transmission mechanism of R&D investment and R&D subsidies.


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