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学者姓名：谢启伟
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Abstract ：
Current research on commercial bank credit risk mainly focuses on the risk of loans and advances without considering the treasury operations and off-balance-sheet credit business that also carry credit risk. Ignoring the correlation between diverse risk factors results in the biased integration of credit risk. In this work, we aggregate the credit risk of commercial banks based on three risk factors using a vine copula. Our empirical results show that banks that are not global systemically important banks are confronted with higher credit risk than global systemically important banks. In addition, the risk of loans-and-advances business is positively correlated with treasury operations risk and negatively correlated with off-balance-sheet credit business. While the risk of loans-and-advances business is significant, the risks of treasury operations and off-balance-sheet credit business still play an indispensable role in (and contain vital information about) credit risk. In addition, banking as a system can achieve lower credit risk, but this effect is weakened under the extreme lower-tail risk.
Keyword ：
commercial banks commercial banks risk integration risk integration credit risk credit risk risk dependency risk dependency vine copula vine copula
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| GB/T 7714 | Xie, Qiwei , Cheng, Lu , Li, Jingyu et al. The impact of treasury operations and off-balance-sheet credit business on commercial bank credit risk [J]. | JOURNAL OF RISK , 2023 , 25 (5) : 23-50 . |
| MLA | Xie, Qiwei et al. "The impact of treasury operations and off-balance-sheet credit business on commercial bank credit risk" . | JOURNAL OF RISK 25 . 5 (2023) : 23-50 . |
| APA | Xie, Qiwei , Cheng, Lu , Li, Jingyu , Zheng, Xiaolong . The impact of treasury operations and off-balance-sheet credit business on commercial bank credit risk . | JOURNAL OF RISK , 2023 , 25 (5) , 23-50 . |
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Abstract ：
The structural information detection of road conditions, which is adopted for improving driving comfort, patrol inspection, road maintenance, and accident rescue. In order to improve the trustworthiness of road condition detection, a real-time artificial intelligence road detection system based on binocular vision sensors is investigated in this article. The system is deployed on the low-power edge computing platform, which can upload the processing results to the cloud through the Internet-of-Things devices. The authors use binocular disparity information and image-based lightweight deep segmentation network to enhance the detection robustness and accuracy in the industrial Internet-of-Things application scenarios. Considering the small training dataset, a special data labeling regularization and training strategy have also been proposed for training this network. In addition, we employ multiframes feature matching and measurement data filtering to enhance the measurement accuracy. The experimental results demonstrate that our monocular-binocular fusion framework is robust and efficient.
Keyword ：
monocular-binocular fusion framework monocular-binocular fusion framework Task analysis Task analysis Cameras Cameras trustworthy road condition detection trustworthy road condition detection deep learning deep learning Image segmentation Image segmentation Deep learning Deep learning Field programmable gate arrays Field programmable gate arrays Computational modeling Computational modeling Binocular vision Binocular vision Roads Roads
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| GB/T 7714 | Xie, Qiwei , Hu, Xiyuan , Ren, Lei et al. A Binocular Vision Application in IoT: Realtime Trustworthy Road Condition Detection System in Passable Area [J]. | IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS , 2023 , 19 (1) : 973-983 . |
| MLA | Xie, Qiwei et al. "A Binocular Vision Application in IoT: Realtime Trustworthy Road Condition Detection System in Passable Area" . | IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS 19 . 1 (2023) : 973-983 . |
| APA | Xie, Qiwei , Hu, Xiyuan , Ren, Lei , Qi, Lianyong , Sun, Zhao . A Binocular Vision Application in IoT: Realtime Trustworthy Road Condition Detection System in Passable Area . | IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS , 2023 , 19 (1) , 973-983 . |
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The insurance industry plays a crucial role of the national financial system, and the operating efficiency of insurance companies has always been a significant subject of academic research. This study proposes a multiperiod DEA model to dynamically evaluate the operating efficiency of insurance companies, which not only overcomes the defect of the traditional DEA method ignoring the internal structure of decision-making units, but also extends the limitation of the leader-follower model in evaluating single-period efficiency. By analyzing the efficiency of seven listed insurance companies in China from 2009 to 2018, the following conclusions are drawn. The multiperiod DEA model demonstrates advantages over the leader-follower model. The profitability of insurance companies during the first five years is higher compared with the last five years. There is a significant correlation between premium financing efficiency and overall efficiency. Throughout both periods, the loss ratio, loss reserve ratio, and consumer price index (CPI) are always positively correlated with the efficiency of the insurer, while the gearing ratio is negatively related to the efficiency of the insurer. The correlation among gross domestic product (GDP), total insurance value, tradable financial assets, and corporate efficiency varies over time.
Keyword ：
insurance companies insurance companies multiple periods multiple periods DEA DEA leader-follower model leader-follower model
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| GB/T 7714 | Xie, Qiwei , Zhao, Mengfan , Li, Rong et al. Efficiency Evaluation of Insurance Companies From Multiperiod Perspective [J]. | IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS , 2023 . |
| MLA | Xie, Qiwei et al. "Efficiency Evaluation of Insurance Companies From Multiperiod Perspective" . | IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS (2023) . |
| APA | Xie, Qiwei , Zhao, Mengfan , Li, Rong , Li, Wen , Zheng, Xiaolong , Li, Yongjun et al. Efficiency Evaluation of Insurance Companies From Multiperiod Perspective . | IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS , 2023 . |
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Carbon trading is a vital market mechanism to achieve carbon emission reduction. The accurate prediction of the carbon price is conducive to the effective management and decision-making of the carbon trading market. However, existing research on carbon price forecasting has ignored the impacts of multiple factors on the carbon price, especially climate change. This study proposes a text-based framework for carbon price prediction that considers the impact of climate change. Textual online news is innovatively employed to construct a climate-related variable. The information is combined with other variables affecting the carbon price to forecast the carbon price, using a long short-term memory network and random forest model. The results demonstrate that the prediction accuracy of the carbon price in the Hubei and Guangdong carbon markets is enhanced by adding the textual variable that measures climate change. (c) 2022 Economic Society of Australia, Queensland. Published by Elsevier B.V. All rights reserved.
Keyword ：
Climate change Climate change Long short-term memory (LSTM) Long short-term memory (LSTM) Random forest (RF) Random forest (RF) Text mining Text mining Carbon price prediction Carbon price prediction
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| GB/T 7714 | Xie, Qiwei , Hao, Jingjing , Li, Jingyu et al. Carbon price prediction considering climate change: A text-based framework [J]. | ECONOMIC ANALYSIS AND POLICY , 2022 , 74 : 382-401 . |
| MLA | Xie, Qiwei et al. "Carbon price prediction considering climate change: A text-based framework" . | ECONOMIC ANALYSIS AND POLICY 74 (2022) : 382-401 . |
| APA | Xie, Qiwei , Hao, Jingjing , Li, Jingyu , Zheng, Xiaolong . Carbon price prediction considering climate change: A text-based framework . | ECONOMIC ANALYSIS AND POLICY , 2022 , 74 , 382-401 . |
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Abstract ：
PurposeThis study aims to systematically reveal the complex interaction between uncertainty and the international commodity market (CRB).Design/methodology/approachA composite uncertainty index and five categorical uncertainty indices, together with wavelet analysis and detrended cross-correlation analysis, were used. First, in the time-frequency domain, the coherency and lead-lag relationship between uncertainty and the commodity markets were investigated. Furthermore, the transmission direction of the cross-correlation over different lag periods and asymmetry in this cross-correlation under different trends were identified.FindingsFirst, there is significant coherency between uncertainties and CRB mainly in the short and medium terms, with natural disaster and public health uncertainties tending to lead CRB. Second, uncertainty impacts CRB more markedly over shorter lag periods, whereas the impact of CRB on uncertainty gradually increases with longer lag periods. Third, the cross-correlation is asymmetric and multifractal under different trends. Finally, from the perspective of lag periods and trends, the interaction of uncertainty with the Chinese commodity market is significantly different from its interaction with CRB.Originality/valueFirst, this study comprehensively constructs a composite uncertainty index based on five types of uncertainty. Second, this study provides a scientific perspective on examining the core and diverse interactions between uncertainty and CRB, as achieved by investigating the interactions of CRB with five categorical and composite uncertainties. Third, this study provides a new research framework to enable multiscale analysis of the complex interaction between uncertainty and the commodity markets.
Keyword ：
Wavelet analysis Wavelet analysis DCCA methods DCCA methods International commodity market International commodity market Uncertainty Uncertainty
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| GB/T 7714 | Liu, Chao , Zhang, Wei , Xie, Qiwei et al. Multiscale analysis of the complex interaction between uncertainty and the international commodity market [J]. | INTERNATIONAL JOURNAL OF EMERGING MARKETS , 2022 . |
| MLA | Liu, Chao et al. "Multiscale analysis of the complex interaction between uncertainty and the international commodity market" . | INTERNATIONAL JOURNAL OF EMERGING MARKETS (2022) . |
| APA | Liu, Chao , Zhang, Wei , Xie, Qiwei , Wang, Chao . Multiscale analysis of the complex interaction between uncertainty and the international commodity market . | INTERNATIONAL JOURNAL OF EMERGING MARKETS , 2022 . |
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As an important national initiative, China's public transport priority development strategy is conducive to the development of the public transport industry and urban economic construction. However, current public transport operation is inefficient due to the information asymmetry between the government and public transport enterprises, thereby inevitably generating losses. To address the issue of information asymmetry, this study designs a public transport subsidy allocation method from the perspective of incentives and discusses the allocation results using this method through a case study. The rationality of the proposed method and the scientificity and authenticity of the conclusions, are fully explained and demonstrated via the experimental simulation. Based on real published data of public transport enterprises, the proposed method can motivate public transport enterprises to improve their performance. In the case of reporting false data, the proposed method can motivate public transport enterprises to report accurate data.
Keyword ：
information asymmetry information asymmetry Resource management Resource management Subsidy allocation Subsidy allocation Behavioral sciences Behavioral sciences Costs Costs Nash non-cooperative game Nash non-cooperative game data envelopment analysis data envelopment analysis Industries Industries Government Government Data envelopment analysis Data envelopment analysis Games Games
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| GB/T 7714 | Xie, Qiwei , Wu, Xiao , Dai, Qianzhi et al. An Integrated Data Envelopment Analysis and Non-Cooperative Game Approach for Public Transportation Incentive Subsidy Allocation [J]. | IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS , 2022 , 23 (11) : 21515-21530 . |
| MLA | Xie, Qiwei et al. "An Integrated Data Envelopment Analysis and Non-Cooperative Game Approach for Public Transportation Incentive Subsidy Allocation" . | IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS 23 . 11 (2022) : 21515-21530 . |
| APA | Xie, Qiwei , Wu, Xiao , Dai, Qianzhi , Zheng, Xiaolong , Wang, Fei-Yue . An Integrated Data Envelopment Analysis and Non-Cooperative Game Approach for Public Transportation Incentive Subsidy Allocation . | IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS , 2022 , 23 (11) , 21515-21530 . |
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Abstract ：
This paper studies the carbon price fluctuation in China through the adaptive Fourier decomposition (AFD). Apart from the transient time-frequency distribution of the original AFD model, we also reconstruct the mono-components of this model to obtain the components in different time-frequency scales. Our empirical results based on the carbon price in Hubei Province demonstrate that there are three periods when the price fluctuates dramatically, mainly affected by the governmental policies about carbon emission and the development of clean energies, as well as the outbreak of COVID-19. Furthermore, the fluctuations of the price in the three identified periods are reflected in different scales. The comparison of the decomposition results and those of EMD and VIVID shows that the AFD performs best in absorbing the price's useful information extracted through all these methods. (C) 2021 The Authors. Published by Elsevier B.V.
Keyword ：
adaptive Fourier decomposition adaptive Fourier decomposition time-frequency domain time-frequency domain Carbon price Carbon price
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| GB/T 7714 | Li, Jingyu , Liu, Ranran , Xie, Qiwei . The price fluctuation in Chinese carbon emission trading market: New evidence from adaptive Fourier decomposition [J]. | 8TH INTERNATIONAL CONFERENCE ON INFORMATION TECHNOLOGY AND QUANTITATIVE MANAGEMENT (ITQM 2020 & 2021): DEVELOPING GLOBAL DIGITAL ECONOMY AFTER COVID-19 , 2022 , 199 : 1095-1102 . |
| MLA | Li, Jingyu et al. "The price fluctuation in Chinese carbon emission trading market: New evidence from adaptive Fourier decomposition" . | 8TH INTERNATIONAL CONFERENCE ON INFORMATION TECHNOLOGY AND QUANTITATIVE MANAGEMENT (ITQM 2020 & 2021): DEVELOPING GLOBAL DIGITAL ECONOMY AFTER COVID-19 199 (2022) : 1095-1102 . |
| APA | Li, Jingyu , Liu, Ranran , Xie, Qiwei . The price fluctuation in Chinese carbon emission trading market: New evidence from adaptive Fourier decomposition . | 8TH INTERNATIONAL CONFERENCE ON INFORMATION TECHNOLOGY AND QUANTITATIVE MANAGEMENT (ITQM 2020 & 2021): DEVELOPING GLOBAL DIGITAL ECONOMY AFTER COVID-19 , 2022 , 199 , 1095-1102 . |
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This study investigates the impact of the recent COVID-19 pandemic on the time-frequency volatility spillovers across the international crude oil market and Chinese major energy futures markets. In addition to the Chinese crude oil market, six other major energy futures markets in China are also considered. Volatility spillover networks are constructed based on the generalized forecast error variance decomposition in the frequency domain. The results demonstrate that the outbreak of COVID-19 strengthened the total volatility spillover across these markets. Interestingly, the volatility spillovers from the international crude oil market to China's markets were found to be overall strong in the long term and to have increased substantially during the pandemic. However, the spillovers across the domestic markets were found to dominate in the short term, even with the occurrence of the pandemic and crude oil price turbulence. The findings suggest that policymakers and investors should be cautious about the diverse impacts of the pandemic at multiple scales.
Keyword ：
Variance decomposition in frequency domain Variance decomposition in frequency domain COVID-19 COVID-19 Chinese energy futures markets Chinese energy futures markets Volatility spillover Volatility spillover
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| GB/T 7714 | Li, Jingyu , Liu, Ranran , Yao, Yanzhen et al. Time-frequency volatility spillovers across the international crude oil market and Chinese major energy futures markets: Evidence from COVID-19 [J]. | RESOURCES POLICY , 2022 , 77 . |
| MLA | Li, Jingyu et al. "Time-frequency volatility spillovers across the international crude oil market and Chinese major energy futures markets: Evidence from COVID-19" . | RESOURCES POLICY 77 (2022) . |
| APA | Li, Jingyu , Liu, Ranran , Yao, Yanzhen , Xie, Qiwei . Time-frequency volatility spillovers across the international crude oil market and Chinese major energy futures markets: Evidence from COVID-19 . | RESOURCES POLICY , 2022 , 77 . |
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Abstract ：
The endoplasmic reticulum (ER) is a contiguous and complicated membrane network in eukaryotic cells, and membrane contact sites (MCSs) between the ER and other organelles perform vital cellular functions, including lipid homeostasis, metabolite exchange, calcium level regulation, and organelle division. Here, we establish a whole pipeline to reconstruct all ER, mitochondria, lipid droplets, lysosomes, peroxisomes, and nuclei by automated tape-collecting ultramicrotome scanning electron microscopy (ATUM-SEM) and deep learning techniques, which generates an unprecedented 3D model for mapping liver samples. Furthermore, the morphology of various organelles and the MCSs between the ER and other organelles are systematically analyzed. We found that the ER presents with predominantly flat cisternae and is knitted tightly all throughout the intracellular space and around other organelles. In addition, the ER has a smaller volume-to-membrane surface area ratio than other organelles, which suggests that the ER could be more suited for functions that require a large membrane surface area. Our data also indicate that ER‒mitochondria contacts are particularly abundant, especially for branched mitochondria. Our study provides 3D reconstructions of various organelles in liver samples together with important fundamental information for biochemical and functional studies in the liver.
Keyword ：
3D reconstruction 3D reconstruction MCSs MCSs liver liver deep learning deep learning ER ER ATUM-SEM ATUM-SEM
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| GB/T 7714 | Jiang Yi , Li Linlin , Chen Xi et al. Three-dimensional ATUM-SEM reconstruction and analysis of hepatic endoplasmic reticulum‒organelle interactions. [J]. | Journal of molecular cell biology , 2021 . |
| MLA | Jiang Yi et al. "Three-dimensional ATUM-SEM reconstruction and analysis of hepatic endoplasmic reticulum‒organelle interactions." . | Journal of molecular cell biology (2021) . |
| APA | Jiang Yi , Li Linlin , Chen Xi , Liu Jiazheng , Yuan Jingbin , Xie Qiwei et al. Three-dimensional ATUM-SEM reconstruction and analysis of hepatic endoplasmic reticulum‒organelle interactions. . | Journal of molecular cell biology , 2021 . |
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Abstract ：
The majority of data envelopment analysis (DEA) models can be linearized via the classical Charnes-Cooper transformation. Nevertheless, this transformation does not apply to sum-of-fractional DEA efficiencies models, such as the secondary goal I (SG-I) cross efficiency model and the arithmetic mean two-stage network DEA model. To solve a sum-of-fractional DEA efficiencies model, we convert it into bilinear programming. Then, the obtained bilinear programming is relaxed to mixed-integer linear programming (MILP) by using a multiparametric disaggregation technique. We reveal the hidden mathematical structures of sum-of-fractional DEA efficiencies models, and propose corresponding discretization strategies to make the models more easily to be solved. Discretization of the multipliers of inputs or the DEA efficiencies in the objective function depends on the number of multipliers and decision-making units. The obtained MILP provides an upper bound for the solution and can be tightened as desired by adding binary variables. Finally, an algorithm based on MILP is developed to search for the global optimal solution. The effectiveness of the proposed method is verified by using it to solve the SG-I cross efficiency model and the arithmetic mean two-stage network DEA model. Results of the numerical applications show that the proposed approach can solve the SG-I cross efficiency model with 100 decision-making units, 3 inputs, and 3 outputs in 329.6 s. Moreover, the proposed approach obtains more accurate solutions in less time than the heuristic search procedure when solving the arithmetic mean two-stage network DEA model.
Keyword ：
Fractional programming Fractional programming Global optimal solution Global optimal solution Mixed-integer linear programming Mixed-integer linear programming Data envelopment analysis Data envelopment analysis
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| GB/T 7714 | Xie, Jianhui , Xie, Qiwei , Li, Yongjun et al. Solving data envelopment analysis models with sum-of-fractional objectives: a global optimal approach based on the multiparametric disaggregation technique [J]. | ANNALS OF OPERATIONS RESEARCH , 2021 , 304 (1-2) : 453-480 . |
| MLA | Xie, Jianhui et al. "Solving data envelopment analysis models with sum-of-fractional objectives: a global optimal approach based on the multiparametric disaggregation technique" . | ANNALS OF OPERATIONS RESEARCH 304 . 1-2 (2021) : 453-480 . |
| APA | Xie, Jianhui , Xie, Qiwei , Li, Yongjun , Liang, Liang . Solving data envelopment analysis models with sum-of-fractional objectives: a global optimal approach based on the multiparametric disaggregation technique . | ANNALS OF OPERATIONS RESEARCH , 2021 , 304 (1-2) , 453-480 . |
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