Pub Date : 2021-04-01DOI: 10.1109/CBFD52659.2021.00101
Heng Li, Xiaoxi Zhu, Xiao Wang
This article introduces a quantitative analysis method of selected stocks with Python. Firstly, the portfolio weight of the six selected technology stocks with maximum Sharpe Ratio was determined. Secondly, the performance of the portfolio according to the historical data was back-tested. Also, Fama-French three-factor model was used to analyze the factors that might affect the stock price and a regression analysis was done on these factors. Through quantitative analysis, the portfolio weights with maximum Sharpe Ratio and minimum volatility of target stocks could be given out respectively.
{"title":"Quantitative Analysis of Stock Portfolio: Taking Six Technology Companies as Example","authors":"Heng Li, Xiaoxi Zhu, Xiao Wang","doi":"10.1109/CBFD52659.2021.00101","DOIUrl":"https://doi.org/10.1109/CBFD52659.2021.00101","url":null,"abstract":"This article introduces a quantitative analysis method of selected stocks with Python. Firstly, the portfolio weight of the six selected technology stocks with maximum Sharpe Ratio was determined. Secondly, the performance of the portfolio according to the historical data was back-tested. Also, Fama-French three-factor model was used to analyze the factors that might affect the stock price and a regression analysis was done on these factors. Through quantitative analysis, the portfolio weights with maximum Sharpe Ratio and minimum volatility of target stocks could be given out respectively.","PeriodicalId":230625,"journal":{"name":"2021 International Conference on Computer, Blockchain and Financial Development (CBFD)","volume":"88 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128422997","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 : 2021-04-01DOI: 10.1109/CBFD52659.2021.00098
Zhao Qiao
Supply chain management is the basic condition for agricultural e-commerce development, and joint logistics is the inevitable outcome of the e-commerce era. The supply chain management strategy for agricultural e-commerce on the basis of joint logistics is a new mode for marketization of agricultural products. Combining with the application of electronic commerce, B2C platform connects directly to agricultural producers and terminal consumers for logistics cost reducing and supply chain management improvement. This paper will start from the existing problems of agricultural products e-commerce supply chain management, lead to suggestions for the future management of agricultural products e-commerce supply chain.
{"title":"The supply-chain management strategy of agricultural B2C E-commerce on the basis of joint logistics","authors":"Zhao Qiao","doi":"10.1109/CBFD52659.2021.00098","DOIUrl":"https://doi.org/10.1109/CBFD52659.2021.00098","url":null,"abstract":"Supply chain management is the basic condition for agricultural e-commerce development, and joint logistics is the inevitable outcome of the e-commerce era. The supply chain management strategy for agricultural e-commerce on the basis of joint logistics is a new mode for marketization of agricultural products. Combining with the application of electronic commerce, B2C platform connects directly to agricultural producers and terminal consumers for logistics cost reducing and supply chain management improvement. This paper will start from the existing problems of agricultural products e-commerce supply chain management, lead to suggestions for the future management of agricultural products e-commerce supply chain.","PeriodicalId":230625,"journal":{"name":"2021 International Conference on Computer, Blockchain and Financial Development (CBFD)","volume":"101 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123990925","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 : 2021-04-01DOI: 10.1109/CBFD52659.2021.00077
Fan Zhang, Ye Ding
This article analyzes the basic concepts of supply chain finance, participating institutions, business methods, and exposure to risks. The author combined the basic content of the Internet of Things and block chain technology to carry out research. This paper studies the specific applications of the Internet of Things and block chain technology in supply chain financial risk identification, supply chain financial risk assessment, full-process logistics supervision, smart contract transaction management, corporate financial statement sorting, and risk prevention measures. The author's purpose is to improve the financial risk management level of the enterprise supply chain and promote the stable development of the enterprise economy.
{"title":"Research on the Application of Internet of Things and Block Chain Technology in Improving Supply Chain Financial Risk Management","authors":"Fan Zhang, Ye Ding","doi":"10.1109/CBFD52659.2021.00077","DOIUrl":"https://doi.org/10.1109/CBFD52659.2021.00077","url":null,"abstract":"This article analyzes the basic concepts of supply chain finance, participating institutions, business methods, and exposure to risks. The author combined the basic content of the Internet of Things and block chain technology to carry out research. This paper studies the specific applications of the Internet of Things and block chain technology in supply chain financial risk identification, supply chain financial risk assessment, full-process logistics supervision, smart contract transaction management, corporate financial statement sorting, and risk prevention measures. The author's purpose is to improve the financial risk management level of the enterprise supply chain and promote the stable development of the enterprise economy.","PeriodicalId":230625,"journal":{"name":"2021 International Conference on Computer, Blockchain and Financial Development (CBFD)","volume":"155 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134359464","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}
As a kind of financial asset, blockchain digital currency attracts investors' attention. Based on bitcoin price data and three kinds of stock market data, this paper constructs a second-order lag VAR model to test their influence mechanism. Conclusion: there is no causal relationship between bitcoin and stock market index. Verify the original hypothesis: bitcoin can better avoid market risk and has the property of market hedging assets. This paper makes a contribution to the cross study of special currency and financial market.
{"title":"Analysis of blockchain digital currency and market risk based on VAR","authors":"Yi Jing, Haiqi Li, Shuheng Ren, Yuan Wang, Chu-Min Huang, Leqi Xu","doi":"10.1109/CBFD52659.2021.00102","DOIUrl":"https://doi.org/10.1109/CBFD52659.2021.00102","url":null,"abstract":"As a kind of financial asset, blockchain digital currency attracts investors' attention. Based on bitcoin price data and three kinds of stock market data, this paper constructs a second-order lag VAR model to test their influence mechanism. Conclusion: there is no causal relationship between bitcoin and stock market index. Verify the original hypothesis: bitcoin can better avoid market risk and has the property of market hedging assets. This paper makes a contribution to the cross study of special currency and financial market.","PeriodicalId":230625,"journal":{"name":"2021 International Conference on Computer, Blockchain and Financial Development (CBFD)","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134536136","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}
The key challenge of remote sensing aircraft target (RSAT) recognition is that features generated by similar target are difficult to distinguish. To solve the problem, we present a double-triplet-pseudo-siamese (DTPS) architecture to learn to distinguish the subtle discriminative features between similar targets. Specifically, we first construct image triplet and mask triplet, which are then sent to the convolutional neural networks, fully connected layers and softmax sequentially for classification. Besides the classification predictions, we utilize standard templates for contrastive prediction in the test process and introduce a discriminative fusion method to fuse the multiple prediction. In addition, we utilize classification loss, contrast loss and triplet loss during training, which help the network to distinguish similar targets by metric learning. We conduct extensive experiments on benchmark RSAT datasets to demonstrate the effectiveness of our network and the experimental results show that the performance of the proposed method surpasses other existing methods.
{"title":"Double-Triplet-Pseudo-Siamese Architecture For Remote Sensing Aircraft Target Recognition","authors":"Xu Cao, H. Zou, Xinyi Ying, Runlin Li, Shitian He, Fei Cheng","doi":"10.1109/CBFD52659.2021.00034","DOIUrl":"https://doi.org/10.1109/CBFD52659.2021.00034","url":null,"abstract":"The key challenge of remote sensing aircraft target (RSAT) recognition is that features generated by similar target are difficult to distinguish. To solve the problem, we present a double-triplet-pseudo-siamese (DTPS) architecture to learn to distinguish the subtle discriminative features between similar targets. Specifically, we first construct image triplet and mask triplet, which are then sent to the convolutional neural networks, fully connected layers and softmax sequentially for classification. Besides the classification predictions, we utilize standard templates for contrastive prediction in the test process and introduce a discriminative fusion method to fuse the multiple prediction. In addition, we utilize classification loss, contrast loss and triplet loss during training, which help the network to distinguish similar targets by metric learning. We conduct extensive experiments on benchmark RSAT datasets to demonstrate the effectiveness of our network and the experimental results show that the performance of the proposed method surpasses other existing methods.","PeriodicalId":230625,"journal":{"name":"2021 International Conference on Computer, Blockchain and Financial Development (CBFD)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114330058","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 : 2021-04-01DOI: 10.1109/CBFD52659.2021.00100
Mei Jin, Fan Li
Based on the hypothesis of bounded rationality and from the perspective of internal and external forces, this paper constructs an evolutionary game model between state-owned enterprises and external regulators, state-owned enterprise management and anti money laundering risk control department, and studies how to improve the internal control of state-owned enterprises. The results show that the supervision cost of regulators, the social benefits of strict supervision and the utility loss of loose supervision are the main factors that affect the improvement of the internal control system of anti money laundering of state-owned enterprises. In order to solve the connivance attitude of state-owned enterprises, it is necessary to combine punishment mechanism with incentive compensation mechanism, improve social supervision mechanism, and promote self-discipline of state-owned enterprises. These conclusions provide a theoretical reference for state-owned enterprises to improve the internal control of anti money laundering.
{"title":"Improvement of Internal Control of Anti Money Laundering in State-owned Enterprises Based on Evolutionary Game Analysis","authors":"Mei Jin, Fan Li","doi":"10.1109/CBFD52659.2021.00100","DOIUrl":"https://doi.org/10.1109/CBFD52659.2021.00100","url":null,"abstract":"Based on the hypothesis of bounded rationality and from the perspective of internal and external forces, this paper constructs an evolutionary game model between state-owned enterprises and external regulators, state-owned enterprise management and anti money laundering risk control department, and studies how to improve the internal control of state-owned enterprises. The results show that the supervision cost of regulators, the social benefits of strict supervision and the utility loss of loose supervision are the main factors that affect the improvement of the internal control system of anti money laundering of state-owned enterprises. In order to solve the connivance attitude of state-owned enterprises, it is necessary to combine punishment mechanism with incentive compensation mechanism, improve social supervision mechanism, and promote self-discipline of state-owned enterprises. These conclusions provide a theoretical reference for state-owned enterprises to improve the internal control of anti money laundering.","PeriodicalId":230625,"journal":{"name":"2021 International Conference on Computer, Blockchain and Financial Development (CBFD)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114536953","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 : 2021-04-01DOI: 10.1109/CBFD52659.2021.00050
X. Mao
Investor sentiment is an important factor that affects investors' decision-making behaviors. Especially when the emotions are very social, people's behaviors will tend to be consistent, leading to market fluctuations. Some scholars tried to study the impact of investor sentiment on market return and volatility. However, they are not able to get a consistent result. This paper constructs an investor sentiment index (CICSI) by principal component analysis. Based on heterogeneous autoregressive (HAR) theory, this paper establishes three HAR models extended by CICSI to forecast the volatility of Shanghai Composite Index. The empirical results reveal that new models’ accuracy is higher than the original one. Data indicates that the decomposed CICSI contains much forecasting information on market volatility, especially in the short-term. By decomposing CICSI, the goodness of fit of the model was improved by 11.08%. This study fills in the gap of previous research by using high-frequency data and decompose investor sentiment. Further study can be applied to find more relative variables to extend the model and improve prediction accuracy.
{"title":"Forecast on Shanghai Composite Index linked with Investor Sentiment Effect","authors":"X. Mao","doi":"10.1109/CBFD52659.2021.00050","DOIUrl":"https://doi.org/10.1109/CBFD52659.2021.00050","url":null,"abstract":"Investor sentiment is an important factor that affects investors' decision-making behaviors. Especially when the emotions are very social, people's behaviors will tend to be consistent, leading to market fluctuations. Some scholars tried to study the impact of investor sentiment on market return and volatility. However, they are not able to get a consistent result. This paper constructs an investor sentiment index (CICSI) by principal component analysis. Based on heterogeneous autoregressive (HAR) theory, this paper establishes three HAR models extended by CICSI to forecast the volatility of Shanghai Composite Index. The empirical results reveal that new models’ accuracy is higher than the original one. Data indicates that the decomposed CICSI contains much forecasting information on market volatility, especially in the short-term. By decomposing CICSI, the goodness of fit of the model was improved by 11.08%. This study fills in the gap of previous research by using high-frequency data and decompose investor sentiment. Further study can be applied to find more relative variables to extend the model and improve prediction accuracy.","PeriodicalId":230625,"journal":{"name":"2021 International Conference on Computer, Blockchain and Financial Development (CBFD)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114578179","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 : 2021-04-01DOI: 10.1109/CBFD52659.2021.00041
Lingling Mao, Dan Zhang, Yanwei Zhang
The issue of reducts is the basic issue in any rough set model. In the article, we present the notion of the reduct in a pythagorean fuzzy covering table (i.e., pythagorean fuzzy β-covering approximation space (PFCAS)). Moreover, we add and remove several objects of the universe to compute reducts of them. First, the definitions of the PFCAS and it’s reduct are presented. Then, two new PFCASs are proposed when we add and remove some objects from the original universe. Finally, several properties of reducts in pythagorean fuzzy (PF) β-coverings are studied while adding some objects.
{"title":"Reducts in Pythagorean Fuzzy Covering Table While Changing the Information","authors":"Lingling Mao, Dan Zhang, Yanwei Zhang","doi":"10.1109/CBFD52659.2021.00041","DOIUrl":"https://doi.org/10.1109/CBFD52659.2021.00041","url":null,"abstract":"The issue of reducts is the basic issue in any rough set model. In the article, we present the notion of the reduct in a pythagorean fuzzy covering table (i.e., pythagorean fuzzy β-covering approximation space (PFCAS)). Moreover, we add and remove several objects of the universe to compute reducts of them. First, the definitions of the PFCAS and it’s reduct are presented. Then, two new PFCASs are proposed when we add and remove some objects from the original universe. Finally, several properties of reducts in pythagorean fuzzy (PF) β-coverings are studied while adding some objects.","PeriodicalId":230625,"journal":{"name":"2021 International Conference on Computer, Blockchain and Financial Development (CBFD)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123895328","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 : 2021-04-01DOI: 10.1109/CBFD52659.2021.00049
Gaohan Yu
As the degree of informatization in the financial industry continues to deepen, Internet technology is playing an increasingly important role in the collection and analysis of financial data. The use of Internet technology makes it possible to collect large-scale data and accurately analyze data. The large-capacity financial database puts forward higher requirements on the efficiency and accuracy of data analysis tools. As a new type of computer language, Python language can better complete the sniffing and collection of Internet resources, so that it can become an important tool for financial data collection and analysis. With the continuous development of science and technology, Python technology also has certain risks and problems. This article aims to analyze the key applications of Python in financial data analysis, and how to do a quantitative analysis of risks based on Python.
{"title":"Financial data analysis and risk quantification based on Python","authors":"Gaohan Yu","doi":"10.1109/CBFD52659.2021.00049","DOIUrl":"https://doi.org/10.1109/CBFD52659.2021.00049","url":null,"abstract":"As the degree of informatization in the financial industry continues to deepen, Internet technology is playing an increasingly important role in the collection and analysis of financial data. The use of Internet technology makes it possible to collect large-scale data and accurately analyze data. The large-capacity financial database puts forward higher requirements on the efficiency and accuracy of data analysis tools. As a new type of computer language, Python language can better complete the sniffing and collection of Internet resources, so that it can become an important tool for financial data collection and analysis. With the continuous development of science and technology, Python technology also has certain risks and problems. This article aims to analyze the key applications of Python in financial data analysis, and how to do a quantitative analysis of risks based on Python.","PeriodicalId":230625,"journal":{"name":"2021 International Conference on Computer, Blockchain and Financial Development (CBFD)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122211153","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 : 2021-04-01DOI: 10.1109/CBFD52659.2021.00074
Tong Fuchao, Xiaoping Yan
With the emergence of the currency, as its underlying technology of block chain technology is becoming more and more attention. The technological innovation of block chain technology^ own decentralization and strong trust mechanism is consistent with the financial essence, which has injected new blood into the development of Internet finance, promoted the innovation of financial products, and strengthened the trend of mixed operation in the financial industry.At the same time, the current chain financial law regulation system seriously lagging behind the block chain of financial innovation. In block chain technology development, financial regulators need to reform the existing block chain legal supervision system, can fit new technology bring new regulatory requirements.
{"title":"Research on Problems in Financial Legal Supervision of Blockchain in China from the Perspective of Internet","authors":"Tong Fuchao, Xiaoping Yan","doi":"10.1109/CBFD52659.2021.00074","DOIUrl":"https://doi.org/10.1109/CBFD52659.2021.00074","url":null,"abstract":"With the emergence of the currency, as its underlying technology of block chain technology is becoming more and more attention. The technological innovation of block chain technology^ own decentralization and strong trust mechanism is consistent with the financial essence, which has injected new blood into the development of Internet finance, promoted the innovation of financial products, and strengthened the trend of mixed operation in the financial industry.At the same time, the current chain financial law regulation system seriously lagging behind the block chain of financial innovation. In block chain technology development, financial regulators need to reform the existing block chain legal supervision system, can fit new technology bring new regulatory requirements.","PeriodicalId":230625,"journal":{"name":"2021 International Conference on Computer, Blockchain and Financial Development (CBFD)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123239848","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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