Pub Date : 2021-04-01DOI: 10.1109/CBFD52659.2021.00011
Junxian Wang
The Capital Asset Pricing model (CAPM) is recognized as one of the most important models in researching the relationship between the systematic risk and the expected returns for the stocks. However, the assumption of normal distribution is the main shortage of the original model. In this paper, a new distribution of Standardized Standard Asymmetric Exponential Power Distribution (SSAEPD) is introduced to replace the normal distribution assumption in the original CAPM to eliminate the inaccurate element in assumption and extend the function of CAPM. Meanwhile, this research also includes the discussion of error term volatility by introducing the Generalized AutoRegressive Conditional Heteroskedasticity model (GARCH). To test the hypotheses of the model, the paper collects the data from China300 index from the year 2000 to 2010 and applies maximum likelihood to estimate models. Method of maximum likelihood estimation is used to estimate the model. Markov Chain Monte Carlo (MCMC) method is used to generate random variables from Asymmetric Exponential Power Distribution (AEPD) for simulation. Akaike Information Criterion (AIC) is used to compare the model between different conditions. The results will shed lights on the decision making of risk management. What’s more, this will also benefit the certain group of investors in the financial markets.
资本资产定价模型(CAPM)是研究股票系统风险与预期收益关系的重要模型之一。然而，原模型的主要不足是对正态分布的假设。本文引入一种新的标准化标准非对称指数功率分布(SSAEPD)分布来取代原CAPM中的正态分布假设，消除了假设中的不准确因素，扩展了CAPM的功能。同时，本文还通过引入广义自回归条件异方差模型(GARCH)对误差项波动率进行了讨论。为了检验模型的假设，本文收集了中国300指数2000 - 2010年的数据，并采用极大似然法对模型进行估计。采用极大似然估计方法对模型进行估计。利用马尔可夫链蒙特卡罗(MCMC)方法从非对称指数功率分布(AEPD)中生成随机变量进行仿真。采用赤池信息准则(Akaike Information Criterion, AIC)对不同条件下的模型进行比较。研究结果将为风险管理决策提供启示。更重要的是，这也将使金融市场上的某些投资者群体受益。
{"title":"A New Capital Asset Pricing Model with GARCH-type Volatility and Asymmetric Exponential Power Distribution Error Terms","authors":"Junxian Wang","doi":"10.1109/CBFD52659.2021.00011","DOIUrl":"https://doi.org/10.1109/CBFD52659.2021.00011","url":null,"abstract":"The Capital Asset Pricing model (CAPM) is recognized as one of the most important models in researching the relationship between the systematic risk and the expected returns for the stocks. However, the assumption of normal distribution is the main shortage of the original model. In this paper, a new distribution of Standardized Standard Asymmetric Exponential Power Distribution (SSAEPD) is introduced to replace the normal distribution assumption in the original CAPM to eliminate the inaccurate element in assumption and extend the function of CAPM. Meanwhile, this research also includes the discussion of error term volatility by introducing the Generalized AutoRegressive Conditional Heteroskedasticity model (GARCH). To test the hypotheses of the model, the paper collects the data from China300 index from the year 2000 to 2010 and applies maximum likelihood to estimate models. Method of maximum likelihood estimation is used to estimate the model. Markov Chain Monte Carlo (MCMC) method is used to generate random variables from Asymmetric Exponential Power Distribution (AEPD) for simulation. Akaike Information Criterion (AIC) is used to compare the model between different conditions. The results will shed lights on the decision making of risk management. What’s more, this will also benefit the certain group of investors in the financial markets.","PeriodicalId":230625,"journal":{"name":"2021 International Conference on Computer, Blockchain and Financial Development (CBFD)","volume":"1 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":"129482304","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/cbfd52659.2021.00001
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Pub Date : 2021-04-01DOI: 10.1109/CBFD52659.2021.00030
Hainie Meng, Yunli Cheng, Xiaoru Chen, Qiaoxian Lai, Yaohua Lei
With the advent of the information age, the field of industrial control has achieved rapid development. Industrial equipment is connected to each other through bus network, and the deployment is relatively dispersed. Due to the lack of sufficient security of bus protocol, intruders use the information security hidden danger of bus protocol to attack the system. Therefore, the research on information security of fieldbus protocol is of great significance for information security protection in industrial field. In this paper, starting from the theory and practice, the commonly used several kinds of fieldbus in the industrial control system, namely the Modbus/RTU, CAN, Mr CAT bus research and analysis. Firstly, the Petri net formalized modeling method was used to model and analyze the above bus respectively. Secondly, the accessibility analysis method was used to analyze and verify the boundedness, reversibility and initiative of the model. Finally, the correctness of the model was guaranteed. Aiming at the hidden trouble existing in the current bus protocol, the attack behavior is formally described by Petri net model. In the experiment part, Modbus/RTU, CAN and Ether CAT field buses are used to build a hierarchical intelligent control system to simulate the actual industrial control scene. The system is divided into decision layer, control layer and executive layer to realize the communication between each layer and the upper and lower layers. In order to simulate the behavior of attackers, several attack experiments were carried out, including flood attack, eavesdropping to steal data frames, man-in-the-middle attack and other attack methods, to disrupt the normal operation of the system and record the experimental results. Finally, a bus monitoring system is designed, taking CAN bus as the monitoring object. The system CAN conduct real-time monitoring of the state when CAN bus transmits data according to the flow of data frames, and meanwhile conduct data collection to identify illegal data frames, so as to realize information security protection of the control system to a certain extent.The focus of this paper is to use Petri net modeling analysis method to analyze and study several field buses, and through the attack experiment to analyze the bus system information security risks, hoping that the research content of this paper can provide theoretical reference for the design and security protection of industrial control system.
{"title":"Research on information security technology based on hierarchical intelligent control system","authors":"Hainie Meng, Yunli Cheng, Xiaoru Chen, Qiaoxian Lai, Yaohua Lei","doi":"10.1109/CBFD52659.2021.00030","DOIUrl":"https://doi.org/10.1109/CBFD52659.2021.00030","url":null,"abstract":"With the advent of the information age, the field of industrial control has achieved rapid development. Industrial equipment is connected to each other through bus network, and the deployment is relatively dispersed. Due to the lack of sufficient security of bus protocol, intruders use the information security hidden danger of bus protocol to attack the system. Therefore, the research on information security of fieldbus protocol is of great significance for information security protection in industrial field. In this paper, starting from the theory and practice, the commonly used several kinds of fieldbus in the industrial control system, namely the Modbus/RTU, CAN, Mr CAT bus research and analysis. Firstly, the Petri net formalized modeling method was used to model and analyze the above bus respectively. Secondly, the accessibility analysis method was used to analyze and verify the boundedness, reversibility and initiative of the model. Finally, the correctness of the model was guaranteed. Aiming at the hidden trouble existing in the current bus protocol, the attack behavior is formally described by Petri net model. In the experiment part, Modbus/RTU, CAN and Ether CAT field buses are used to build a hierarchical intelligent control system to simulate the actual industrial control scene. The system is divided into decision layer, control layer and executive layer to realize the communication between each layer and the upper and lower layers. In order to simulate the behavior of attackers, several attack experiments were carried out, including flood attack, eavesdropping to steal data frames, man-in-the-middle attack and other attack methods, to disrupt the normal operation of the system and record the experimental results. Finally, a bus monitoring system is designed, taking CAN bus as the monitoring object. The system CAN conduct real-time monitoring of the state when CAN bus transmits data according to the flow of data frames, and meanwhile conduct data collection to identify illegal data frames, so as to realize information security protection of the control system to a certain extent.The focus of this paper is to use Petri net modeling analysis method to analyze and study several field buses, and through the attack experiment to analyze the bus system information security risks, hoping that the research content of this paper can provide theoretical reference for the design and security protection of industrial control system.","PeriodicalId":230625,"journal":{"name":"2021 International Conference on Computer, Blockchain and Financial Development (CBFD)","volume":"17 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":"128081862","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/CBFD52659.2021.00043
Bo Pan, Q. Tao, Dong Wang, Xiaorui Zhou
Aiming at realize the safety, reliable and efficient of LVC(Live, Virtual and Constructive) distributed simulation system. Wireless Sensor Networks (WSN) are widely depolyed in the LVC cross-domain nodes and sub-networks, by using blockchain technology with the advantages of distributed multi-center, collective maintenance and not easy to tamper. In the existing smart LVC networks, sensing data of the LVC WSNs has to be uploaded to a central node for storage and sharing. This central network has many security problems, such as data tampering and single node failure. In order to resolving this problem, the Consortium Blockchain technology is exploited to form a Data sharing and Storage on Consortium Blockchain. In this secure data storage and sharing system, cross-domain networks has some pre-selected data collection based station, which runs the smart contracts on the behalf of its domain nodes. The constraints about data sharing are set by the data owners, and smart contracts replaces the legal terms and laws to regulate the data visitors. Security and analysis show that this LVC blockchain system can achieve safe and effective data storage and sharing in cross-domain scenario.
旨在实现LVC(Live, Virtual and Constructive)分布式仿真系统的安全、可靠和高效。无线传感器网络(WSN)广泛部署在LVC跨域节点和子网中，采用区块链技术，具有分布式多中心、集体维护、不易篡改等优点。在现有的智能LVC网络中，LVC wsn的传感数据必须上传到中心节点进行存储和共享。这种中心网络存在数据篡改、单节点故障等安全问题。为了解决这一问题，利用联盟区块链技术，在联盟区块链上形成数据共享和存储。在这个安全的数据存储和共享系统中，跨域网络有一些预先选择的数据采集基地，这些基地代表其域节点运行智能合约。数据共享的约束由数据所有者设定，智能合约取代法律条款和法律来规范数据访问者。安全性和分析表明，该LVC区块链系统可以实现跨域场景下安全有效的数据存储和共享。
{"title":"Secure Data Access and Consensus Algorithm based on Consortium Blockchain in LVC","authors":"Bo Pan, Q. Tao, Dong Wang, Xiaorui Zhou","doi":"10.1109/CBFD52659.2021.00043","DOIUrl":"https://doi.org/10.1109/CBFD52659.2021.00043","url":null,"abstract":"Aiming at realize the safety, reliable and efficient of LVC(Live, Virtual and Constructive) distributed simulation system. Wireless Sensor Networks (WSN) are widely depolyed in the LVC cross-domain nodes and sub-networks, by using blockchain technology with the advantages of distributed multi-center, collective maintenance and not easy to tamper. In the existing smart LVC networks, sensing data of the LVC WSNs has to be uploaded to a central node for storage and sharing. This central network has many security problems, such as data tampering and single node failure. In order to resolving this problem, the Consortium Blockchain technology is exploited to form a Data sharing and Storage on Consortium Blockchain. In this secure data storage and sharing system, cross-domain networks has some pre-selected data collection based station, which runs the smart contracts on the behalf of its domain nodes. The constraints about data sharing are set by the data owners, and smart contracts replaces the legal terms and laws to regulate the data visitors. Security and analysis show that this LVC blockchain system can achieve safe and effective data storage and sharing in cross-domain scenario.","PeriodicalId":230625,"journal":{"name":"2021 International Conference on Computer, Blockchain and Financial Development (CBFD)","volume":"32 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":"124803573","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/CBFD52659.2021.00095
Pang Lei
The data in this paper mainly comes from Yunnan Statistical Yearbooks. The relationship between the level of financial aggregation and the investment rate of green energy industries in Yunnan province were used to illustrate financial aggregation’s impact on Yunnan’s green energy industries. Following analysis, the author reached the conclusion that the level of financial aggregation in some way promotes the province’s green energy industries. Seen from an economic perspective, green energy industries have become pillar industries of Yunnan’s economy and to some extent, positively affect the region’s economic development. Seen from an ecological perspective, developing green energy industries complies with relevant laws and regulations, and therefore, receives corresponding support from government and society. Generally speaking, it is necessary for us to develop green energy industries, for it can contribute to high-quality economy of the province.
{"title":"Digital Financial Aggregation’s Impact on Yunnan’s Green Energy Industries","authors":"Pang Lei","doi":"10.1109/CBFD52659.2021.00095","DOIUrl":"https://doi.org/10.1109/CBFD52659.2021.00095","url":null,"abstract":"The data in this paper mainly comes from Yunnan Statistical Yearbooks. The relationship between the level of financial aggregation and the investment rate of green energy industries in Yunnan province were used to illustrate financial aggregation’s impact on Yunnan’s green energy industries. Following analysis, the author reached the conclusion that the level of financial aggregation in some way promotes the province’s green energy industries. Seen from an economic perspective, green energy industries have become pillar industries of Yunnan’s economy and to some extent, positively affect the region’s economic development. Seen from an ecological perspective, developing green energy industries complies with relevant laws and regulations, and therefore, receives corresponding support from government and society. Generally speaking, it is necessary for us to develop green energy industries, for it can contribute to high-quality economy of the province.","PeriodicalId":230625,"journal":{"name":"2021 International Conference on Computer, Blockchain and Financial Development (CBFD)","volume":"31 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":"127967771","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/CBFD52659.2021.00040
Ming-yung Chen
Crude oil future is crucial to global financial markets. Even if many scholars pay attention to research those factors that can influence the price of crude oil future, the existing literature still rarely considers the impacts of the day-of-the-week effect on the volatility of crude oil future price. Based on heterogeneous autoregressive (HAR) theory, we create a new type of heterogeneous autoregressive (HAR) model by introducing a day-of-the-week effect to forecast the future volatility of the crude oil future prices. The empirical results indicate that the new models' accuracy is better than the original HAR model. And we find that the day-of-the-week effect has a significantly negative influence on crude oil futures' price volatility, especially in the short-term and the long-term. Our work is the first to introduce the day-of-the-week effect to identify more crude oil future market information. This paper provides a better forecasting method to study crude oil future volatility.
{"title":"Forecast on Crude Oil Futures linked with Day-of-the-week Effect","authors":"Ming-yung Chen","doi":"10.1109/CBFD52659.2021.00040","DOIUrl":"https://doi.org/10.1109/CBFD52659.2021.00040","url":null,"abstract":"Crude oil future is crucial to global financial markets. Even if many scholars pay attention to research those factors that can influence the price of crude oil future, the existing literature still rarely considers the impacts of the day-of-the-week effect on the volatility of crude oil future price. Based on heterogeneous autoregressive (HAR) theory, we create a new type of heterogeneous autoregressive (HAR) model by introducing a day-of-the-week effect to forecast the future volatility of the crude oil future prices. The empirical results indicate that the new models' accuracy is better than the original HAR model. And we find that the day-of-the-week effect has a significantly negative influence on crude oil futures' price volatility, especially in the short-term and the long-term. Our work is the first to introduce the day-of-the-week effect to identify more crude oil future market information. This paper provides a better forecasting method to study crude oil future volatility.","PeriodicalId":230625,"journal":{"name":"2021 International Conference on Computer, Blockchain and Financial Development (CBFD)","volume":"1 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":"129844701","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/CBFD52659.2021.00065
Zhaoying Wang, Xinyi Liu
Gold has always been crucial in economy in both ancient and modern societies and people are interested in investing in it all the times, whether in traditional physical gold or modern gold futures. In this paper, we want to use more advanced and scientific modern means to make prediction on the future volatility of gold futures to help investors make decisions and reduce risks. Based on heterogeneous autoregressive (HAR) theory, we establish three heterogeneous autoregressive realized volatility (HAR-RV) models to predict the future volatility of gold futures at three different horizons (daily, weekly, and monthly) utilizing 5-minute-frequency trading data in Chinese gold futures market from 01, 2008 to 02, 2021. The empirical result shows that our HAR-RV models is better at forecasting the future weekly volatility than future daily and monthly volatility, in terms of both statistical significance and level of goodness of fit. Also, the forecasted future volatility in daily, weekly and monthly HAR-RV models has a stronger relation with weekly, weekly and monthly realized volatility separately.
{"title":"HAR Model to Examine the Impact of Daily, Weekly, and Monthly Effect","authors":"Zhaoying Wang, Xinyi Liu","doi":"10.1109/CBFD52659.2021.00065","DOIUrl":"https://doi.org/10.1109/CBFD52659.2021.00065","url":null,"abstract":"Gold has always been crucial in economy in both ancient and modern societies and people are interested in investing in it all the times, whether in traditional physical gold or modern gold futures. In this paper, we want to use more advanced and scientific modern means to make prediction on the future volatility of gold futures to help investors make decisions and reduce risks. Based on heterogeneous autoregressive (HAR) theory, we establish three heterogeneous autoregressive realized volatility (HAR-RV) models to predict the future volatility of gold futures at three different horizons (daily, weekly, and monthly) utilizing 5-minute-frequency trading data in Chinese gold futures market from 01, 2008 to 02, 2021. The empirical result shows that our HAR-RV models is better at forecasting the future weekly volatility than future daily and monthly volatility, in terms of both statistical significance and level of goodness of fit. Also, the forecasted future volatility in daily, weekly and monthly HAR-RV models has a stronger relation with weekly, weekly and monthly realized volatility separately.","PeriodicalId":230625,"journal":{"name":"2021 International Conference on Computer, Blockchain and Financial Development (CBFD)","volume":"20 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":"126401694","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/CBFD52659.2021.00042
Siqi Yu
According to the latest ranking of TOP 1,000 World Banks 2020, the leading position of China’s four major banks have increased over their US counterparts: Industrial and Commercial Bank of China (ICBC) topped the list, followed by China Construction Bank (CCB) (No. 2), Agricultural Bank of China (ABOC) (No. 3) and Bank of China (BOC) (No. 4). Due to the influence of COVID-19, banks will come under more pressure as the result of the fiercer competition between them. Although the influence of Chinese banks in the world has increased, their comprehensive strength still needs to be improved. However, at present, there are relatively few academic evaluations on the comprehensive strength of Chinese banks, and the evaluation system is not perfect enough, and the evaluation indicators are not plentiful enough. Therefore, this paper analyses China’s four major state-owned banks’ data from 2015 to 2019 and establishe a fuzzy comprehensive evaluation model based on the analytic hierarchy process. The final conclusion that is drawn by this paper is about the ranking of these four banks’ comprehensive competitiveness: the strongest is Industrial and Commercial Bank of China, followed by China Construction Bank and Bank of China, and the weakest one is Agricultural Bank of China. The evaluation systemof this paper verifies the rationality of the international ranking and has important reference significance for banks to understand their own status and enhance their comprehensive competitiveness.
{"title":"Comprehensive Competitiveness Evaluation of China’s Four Big State-owned Banks——Fuzzy Comprehensive Evaluation Based on Analytic Hierarchy Process","authors":"Siqi Yu","doi":"10.1109/CBFD52659.2021.00042","DOIUrl":"https://doi.org/10.1109/CBFD52659.2021.00042","url":null,"abstract":"According to the latest ranking of TOP 1,000 World Banks 2020, the leading position of China’s four major banks have increased over their US counterparts: Industrial and Commercial Bank of China (ICBC) topped the list, followed by China Construction Bank (CCB) (No. 2), Agricultural Bank of China (ABOC) (No. 3) and Bank of China (BOC) (No. 4). Due to the influence of COVID-19, banks will come under more pressure as the result of the fiercer competition between them. Although the influence of Chinese banks in the world has increased, their comprehensive strength still needs to be improved. However, at present, there are relatively few academic evaluations on the comprehensive strength of Chinese banks, and the evaluation system is not perfect enough, and the evaluation indicators are not plentiful enough. Therefore, this paper analyses China’s four major state-owned banks’ data from 2015 to 2019 and establishe a fuzzy comprehensive evaluation model based on the analytic hierarchy process. The final conclusion that is drawn by this paper is about the ranking of these four banks’ comprehensive competitiveness: the strongest is Industrial and Commercial Bank of China, followed by China Construction Bank and Bank of China, and the weakest one is Agricultural Bank of China. The evaluation systemof this paper verifies the rationality of the international ranking and has important reference significance for banks to understand their own status and enhance their comprehensive competitiveness.","PeriodicalId":230625,"journal":{"name":"2021 International Conference on Computer, Blockchain and Financial Development (CBFD)","volume":"41 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":"123214678","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/CBFD52659.2021.00093
Ziyuan Ye
With the Chinese economy's gradual development over the past decades, people's income has increased, and people are paying more attention to financial asset investment. The ratio of return on investment in household financial assets may be significantly affected by financial knowledge level. Based on the big data from the Chinese Household Finance Survey (CHFS) questionnaire, this paper empirically tests the impact of financial knowledge on household investment returns. As an innovation, we use the Sharpe ratio that is calculated from the big data as a quantitative description of the household investment return rate, which is relatively novel. Based on the control of risk tolerance and other demographic-related characteristics, we find that financial knowledge has a significant role in promoting household investment returns.
{"title":"The Influence of Financial Knowledge on Household Investment Return Rate : ——Based on the Big Data Research of Sharpe ratio","authors":"Ziyuan Ye","doi":"10.1109/CBFD52659.2021.00093","DOIUrl":"https://doi.org/10.1109/CBFD52659.2021.00093","url":null,"abstract":"With the Chinese economy's gradual development over the past decades, people's income has increased, and people are paying more attention to financial asset investment. The ratio of return on investment in household financial assets may be significantly affected by financial knowledge level. Based on the big data from the Chinese Household Finance Survey (CHFS) questionnaire, this paper empirically tests the impact of financial knowledge on household investment returns. As an innovation, we use the Sharpe ratio that is calculated from the big data as a quantitative description of the household investment return rate, which is relatively novel. Based on the control of risk tolerance and other demographic-related characteristics, we find that financial knowledge has a significant role in promoting household investment returns.","PeriodicalId":230625,"journal":{"name":"2021 International Conference on Computer, Blockchain and Financial Development (CBFD)","volume":"17 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":"131261294","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/CBFD52659.2021.00021
Y. Kang, Yilin Chai, Xiaofan Bai, Yuxiao Du, Xinlu Zhang
With the development of computer technology, reinforcement learning algorithm is gradually applied in ecology. When the temperature changes greatly, mackerel and herring will not be able to sustain their lives, at which time they will choose to migrate to habitat suitable for their survival and reproduction. This will greatly affect the economic benefits of fishing companies which fishing in the fixed sea area. Therefore, this paper tries to find a reasonable method to predict the migration location of these two species of fish in the foreseeable future. To understand more clearly the survival status of herring and mackerel in the waters near Scotland, we collected a large amount of reliable data and established a prediction model based on Deep Q-Network (DQN). Given that there will be no dangerous situation at sea to affect the fishing operation, the habitats of herring and mackerel will gradually move to high latitudes in the next 50 years.
{"title":"Mackerel and Herring on the Move A Migration Research Based on Deep Q-network","authors":"Y. Kang, Yilin Chai, Xiaofan Bai, Yuxiao Du, Xinlu Zhang","doi":"10.1109/CBFD52659.2021.00021","DOIUrl":"https://doi.org/10.1109/CBFD52659.2021.00021","url":null,"abstract":"With the development of computer technology, reinforcement learning algorithm is gradually applied in ecology. When the temperature changes greatly, mackerel and herring will not be able to sustain their lives, at which time they will choose to migrate to habitat suitable for their survival and reproduction. This will greatly affect the economic benefits of fishing companies which fishing in the fixed sea area. Therefore, this paper tries to find a reasonable method to predict the migration location of these two species of fish in the foreseeable future. To understand more clearly the survival status of herring and mackerel in the waters near Scotland, we collected a large amount of reliable data and established a prediction model based on Deep Q-Network (DQN). Given that there will be no dangerous situation at sea to affect the fishing operation, the habitats of herring and mackerel will gradually move to high latitudes in the next 50 years.","PeriodicalId":230625,"journal":{"name":"2021 International Conference on Computer, Blockchain and Financial Development (CBFD)","volume":"274 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":"116846628","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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