Pub Date : 1900-01-01DOI: 10.4108/eai.18-11-2022.2326937
Rubing Chen, Suheng Ji, Kexin Lyu, Yiqing Zhou
{"title":"Performance Analysis of Different Investment Decision Models in Terms of Analytical Evaluation","authors":"Rubing Chen, Suheng Ji, Kexin Lyu, Yiqing Zhou","doi":"10.4108/eai.18-11-2022.2326937","DOIUrl":"https://doi.org/10.4108/eai.18-11-2022.2326937","url":null,"abstract":"","PeriodicalId":436941,"journal":{"name":"Proceedings of the 4th International Conference on Economic Management and Model Engineering, ICEMME 2022, November 18-20, 2022, Nanjing, China","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128774049","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.4108/eai.18-11-2022.2326778
Cuiying Pan, Haiyun Liang, Daxing Zhong
{"title":"The Linkage Relationship Between Commercial Insurance Performance and New Urbanization","authors":"Cuiying Pan, Haiyun Liang, Daxing Zhong","doi":"10.4108/eai.18-11-2022.2326778","DOIUrl":"https://doi.org/10.4108/eai.18-11-2022.2326778","url":null,"abstract":"","PeriodicalId":436941,"journal":{"name":"Proceedings of the 4th International Conference on Economic Management and Model Engineering, ICEMME 2022, November 18-20, 2022, Nanjing, China","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128799801","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.4108/eai.18-11-2022.2326756
Di Gang, Yuan Wang, Qian Zhi
. Based on the data compiled from scientific and technological statistics of colleges and universities in 2015-2019, this paper measures the transformation efficiency of the scientific and technological achievements of Double First-Class initiative colleges and universities from the micro and macro perspectives. The micro part uses the panel data fixed effect method to carry on the regression analysis to the input-output data of the science and engineering double first-class university and the ordinary university, determines the regression coefficient. Based on the DEA-Malmquist method, the macro part calculates the efficiency and dynamic changes of scientific and technological achievements between "211 and provincial co-construction colleges and universities "and ordinary colleges and universities in 2015-2019. The results show that double-class universities have obvious advantages over ordinary universities in pure technological innovation. Still, the social benefits of ordinary universities are better than those of double-class universities. Based on the research results, this paper puts forward some policy suggestions to optimize the resource allocation system of higher education and promote the close combination of higher education development with technological innovation and industrial structure transformation.
{"title":"Comparative Analysis on the Efficiency of Science and Technology Innovation in Chinese Universities Based on DEA_Malmquist and Regression Analysis","authors":"Di Gang, Yuan Wang, Qian Zhi","doi":"10.4108/eai.18-11-2022.2326756","DOIUrl":"https://doi.org/10.4108/eai.18-11-2022.2326756","url":null,"abstract":". Based on the data compiled from scientific and technological statistics of colleges and universities in 2015-2019, this paper measures the transformation efficiency of the scientific and technological achievements of Double First-Class initiative colleges and universities from the micro and macro perspectives. The micro part uses the panel data fixed effect method to carry on the regression analysis to the input-output data of the science and engineering double first-class university and the ordinary university, determines the regression coefficient. Based on the DEA-Malmquist method, the macro part calculates the efficiency and dynamic changes of scientific and technological achievements between \"211 and provincial co-construction colleges and universities \"and ordinary colleges and universities in 2015-2019. The results show that double-class universities have obvious advantages over ordinary universities in pure technological innovation. Still, the social benefits of ordinary universities are better than those of double-class universities. Based on the research results, this paper puts forward some policy suggestions to optimize the resource allocation system of higher education and promote the close combination of higher education development with technological innovation and industrial structure transformation.","PeriodicalId":436941,"journal":{"name":"Proceedings of the 4th International Conference on Economic Management and Model Engineering, ICEMME 2022, November 18-20, 2022, Nanjing, China","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126612338","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.4108/eai.18-11-2022.2327121
Z. Liu
— Portfolio management is a financial operation which aims at maximizing the return or optimizing the Sharpe Ratio. One widely used portfolio management strategy, Mean-Variance Optimization, also known as Modern Portfolio Theory, mainly profits by focusing on finding out the expected return and variance of stocks based on historical data to maximize Sharpe Ratio. Yet, it is not easy and accurate to simply predict future return and variance based on a formula. So, in this paper, two Models-free framework, Sharpe Ratio reward based Deep Q-Network (DQN-S) and Return reward (DQN-R) are proposed to overcome the limitations above. Deep Q-learning was employed to train a neural network to manage a stock portfolio of 10 stocks. Stock price was defined as environment of NN, weight of portfolio was defined as action of neural network agent, and reward was indicated to train the model. Traditional portfolio allocation strategy Mean Variance Optimization (MVO) and Naïve Portfolio Allocation (NPA) were also introduced as benchmark to evaluate the performance of reinforcement learning. Moreover, the extensiveness of DQN-S was discussed. The result shows that the MVO is dominating the NPA with a 5% higher annual return and 0.5 higher of Sharpe ratio, although the MDD is slightly higher, indicating the superiority of Sharpe Ratio oriented strategy.
{"title":"Reinforcement Learning in Portfolio Management with Sharpe Ratio Rewarding Based Framework","authors":"Z. Liu","doi":"10.4108/eai.18-11-2022.2327121","DOIUrl":"https://doi.org/10.4108/eai.18-11-2022.2327121","url":null,"abstract":"— Portfolio management is a financial operation which aims at maximizing the return or optimizing the Sharpe Ratio. One widely used portfolio management strategy, Mean-Variance Optimization, also known as Modern Portfolio Theory, mainly profits by focusing on finding out the expected return and variance of stocks based on historical data to maximize Sharpe Ratio. Yet, it is not easy and accurate to simply predict future return and variance based on a formula. So, in this paper, two Models-free framework, Sharpe Ratio reward based Deep Q-Network (DQN-S) and Return reward (DQN-R) are proposed to overcome the limitations above. Deep Q-learning was employed to train a neural network to manage a stock portfolio of 10 stocks. Stock price was defined as environment of NN, weight of portfolio was defined as action of neural network agent, and reward was indicated to train the model. Traditional portfolio allocation strategy Mean Variance Optimization (MVO) and Naïve Portfolio Allocation (NPA) were also introduced as benchmark to evaluate the performance of reinforcement learning. Moreover, the extensiveness of DQN-S was discussed. The result shows that the MVO is dominating the NPA with a 5% higher annual return and 0.5 higher of Sharpe ratio, although the MDD is slightly higher, indicating the superiority of Sharpe Ratio oriented strategy.","PeriodicalId":436941,"journal":{"name":"Proceedings of the 4th International Conference on Economic Management and Model Engineering, ICEMME 2022, November 18-20, 2022, Nanjing, China","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126848672","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.4108/eai.18-11-2022.2326787
Y. Mao, Suling Chen
{"title":"Analysis of the Impact of New Coronary Pneumonia on China's Economy","authors":"Y. Mao, Suling Chen","doi":"10.4108/eai.18-11-2022.2326787","DOIUrl":"https://doi.org/10.4108/eai.18-11-2022.2326787","url":null,"abstract":"","PeriodicalId":436941,"journal":{"name":"Proceedings of the 4th International Conference on Economic Management and Model Engineering, ICEMME 2022, November 18-20, 2022, Nanjing, China","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123300430","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.4108/eai.18-11-2022.2327167
C. Wang, Min Fang, Xiang Huang, Jianing Dong
: Located in northwestern China, Xinjiang is an extremely fragile area with abundant mineral resources and broad prospects for exploration and development. In the Big Data Era, the article analyzes the status and role of the mining industry in the economic and social development of Xinjiang from two dimensions: the contribution of the mining economy and the contribution of the employment situation. It is concluded that the mining industry has a multiplier effect on the growth of the national economy and maintains stability in improving the employment situation in the entire region. The mining industry is the pillar industry of Xinjiang's economic development. However, in the context of the development of green mining, the contribution rate of the mining economy and the contribution of employment continued to weaken. Based on the SWOT model, taking Kezhou as an example, the article analyzes in detail the strengths, weakness, opportunities and threats of Kezhou in the development of green mining. Finally, the article proposes the development strategy of green mining economy in the ecologically fragile area of Xinjiang from four aspects. The first is strength opportunity strategy: to create a green mining development demonstration zone and promote the construction of green mines across the region ； to coordinate the use of two resources and two markets to enhance the resource security and corporate development. The second is weakness opportunity strategy: to establish a green mine construction standard system and improve supporting policies for green mining development; to adhere to the "bringing in" and "going out" strategies, and use technological innovation to lead the development of green mining. The third is strength threats strategy: that is, firmly to establish the concept of green development and implement the social responsibility of mining enterprises; to encourage enterprises to extend the industrial chain and increase the added value of mineral products. The fourth is weakness threats strategy: that is, to optimize the industrial development structure and develop resource industry clusters; to optimize the spatial layout of industries to drive regional economic development; to strengthen the introduction of scientific and technological talents and enhance the competitiveness of mining enterprises.
{"title":"Research on the Development Strategy of Green Mining Economy in Xinjiang's Ecological Fragile Area in the Big Data Era","authors":"C. Wang, Min Fang, Xiang Huang, Jianing Dong","doi":"10.4108/eai.18-11-2022.2327167","DOIUrl":"https://doi.org/10.4108/eai.18-11-2022.2327167","url":null,"abstract":": Located in northwestern China, Xinjiang is an extremely fragile area with abundant mineral resources and broad prospects for exploration and development. In the Big Data Era, the article analyzes the status and role of the mining industry in the economic and social development of Xinjiang from two dimensions: the contribution of the mining economy and the contribution of the employment situation. It is concluded that the mining industry has a multiplier effect on the growth of the national economy and maintains stability in improving the employment situation in the entire region. The mining industry is the pillar industry of Xinjiang's economic development. However, in the context of the development of green mining, the contribution rate of the mining economy and the contribution of employment continued to weaken. Based on the SWOT model, taking Kezhou as an example, the article analyzes in detail the strengths, weakness, opportunities and threats of Kezhou in the development of green mining. Finally, the article proposes the development strategy of green mining economy in the ecologically fragile area of Xinjiang from four aspects. The first is strength opportunity strategy: to create a green mining development demonstration zone and promote the construction of green mines across the region ； to coordinate the use of two resources and two markets to enhance the resource security and corporate development. The second is weakness opportunity strategy: to establish a green mine construction standard system and improve supporting policies for green mining development; to adhere to the \"bringing in\" and \"going out\" strategies, and use technological innovation to lead the development of green mining. The third is strength threats strategy: that is, firmly to establish the concept of green development and implement the social responsibility of mining enterprises; to encourage enterprises to extend the industrial chain and increase the added value of mineral products. The fourth is weakness threats strategy: that is, to optimize the industrial development structure and develop resource industry clusters; to optimize the spatial layout of industries to drive regional economic development; to strengthen the introduction of scientific and technological talents and enhance the competitiveness of mining enterprises.","PeriodicalId":436941,"journal":{"name":"Proceedings of the 4th International Conference on Economic Management and Model Engineering, ICEMME 2022, November 18-20, 2022, Nanjing, China","volume":"114 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123331702","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.4108/eai.18-11-2022.2327145
Riquan Wen, Alexey Chernov
{"title":"The Impact of COVID-19 on China's Small and Medium-sized Enterprises and their Response","authors":"Riquan Wen, Alexey Chernov","doi":"10.4108/eai.18-11-2022.2327145","DOIUrl":"https://doi.org/10.4108/eai.18-11-2022.2327145","url":null,"abstract":"","PeriodicalId":436941,"journal":{"name":"Proceedings of the 4th International Conference on Economic Management and Model Engineering, ICEMME 2022, November 18-20, 2022, Nanjing, China","volume":"84 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121431991","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.4108/eai.18-11-2022.2327196
Youlong Xu, Wan Liu
{"title":"Data Envelopment Analysis of Safety Performance Indicators and Economic Indicators of Bohai Rim Nuclear Power Unit based on DEA Model","authors":"Youlong Xu, Wan Liu","doi":"10.4108/eai.18-11-2022.2327196","DOIUrl":"https://doi.org/10.4108/eai.18-11-2022.2327196","url":null,"abstract":"","PeriodicalId":436941,"journal":{"name":"Proceedings of the 4th International Conference on Economic Management and Model Engineering, ICEMME 2022, November 18-20, 2022, Nanjing, China","volume":"118 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114121010","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.4108/eai.18-11-2022.2326920
Xinxiang Zhao
{"title":"The Economics of Using Data Processing to Analyze Changes in Population Flows","authors":"Xinxiang Zhao","doi":"10.4108/eai.18-11-2022.2326920","DOIUrl":"https://doi.org/10.4108/eai.18-11-2022.2326920","url":null,"abstract":"","PeriodicalId":436941,"journal":{"name":"Proceedings of the 4th International Conference on Economic Management and Model Engineering, ICEMME 2022, November 18-20, 2022, Nanjing, China","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116071055","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.4108/eai.18-11-2022.2326911
Xiaoyan Liu
{"title":"Influence of Cross-Border Economic Cooperation in Border Areas on Sino-Vietnam Opening-up Based on Grey Correlation Model","authors":"Xiaoyan Liu","doi":"10.4108/eai.18-11-2022.2326911","DOIUrl":"https://doi.org/10.4108/eai.18-11-2022.2326911","url":null,"abstract":"","PeriodicalId":436941,"journal":{"name":"Proceedings of the 4th International Conference on Economic Management and Model Engineering, ICEMME 2022, November 18-20, 2022, Nanjing, China","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121157924","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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