Pub Date : 2021-04-01DOI: 10.1109/CBFD52659.2021.00080
Duwei Xiang
In semiconductor production lines, uncertainties about the health of processes and wafers usually lead to "major scrap events" and higher costs. The industry focuses on quality assurance processes. ABCtronics’ plant is facing the problem of downtime which is a matter of concern for semiconductor companies. By observation, the pattern follows Gamma distribution. Thus, the ion-implanter of the IC chips ought to be replaced. After calculations of Beta Distribution are done, it shows that the company’s original fabrication process is in good shape. The QRT has proposed a quality control policy Chip Testing Method (ICTM) to replace the existing policy Individual Lot Acceptance Testing Method (LATM). There are two types of distributions chosen, Hypergeometric and Beta Distribution. Both shows that the new manufacturing technology adopted by ICTM can effectively improve the accepted rate of chips. From observing our data, we know that the time before IC chip failure (in years) is exponentially distributed. There is a very high chance that ABCtronics will meet the expectations of PQRsystems for having a product lifetime of 6 years or higher. Multiple linear regression model has better explanatory power. We consider the industry overall is experiencing a medium level demand.
{"title":"Case Report on Semiconductor Company ABCtronics","authors":"Duwei Xiang","doi":"10.1109/CBFD52659.2021.00080","DOIUrl":"https://doi.org/10.1109/CBFD52659.2021.00080","url":null,"abstract":"In semiconductor production lines, uncertainties about the health of processes and wafers usually lead to \"major scrap events\" and higher costs. The industry focuses on quality assurance processes. ABCtronics’ plant is facing the problem of downtime which is a matter of concern for semiconductor companies. By observation, the pattern follows Gamma distribution. Thus, the ion-implanter of the IC chips ought to be replaced. After calculations of Beta Distribution are done, it shows that the company’s original fabrication process is in good shape. The QRT has proposed a quality control policy Chip Testing Method (ICTM) to replace the existing policy Individual Lot Acceptance Testing Method (LATM). There are two types of distributions chosen, Hypergeometric and Beta Distribution. Both shows that the new manufacturing technology adopted by ICTM can effectively improve the accepted rate of chips. From observing our data, we know that the time before IC chip failure (in years) is exponentially distributed. There is a very high chance that ABCtronics will meet the expectations of PQRsystems for having a product lifetime of 6 years or higher. Multiple linear regression model has better explanatory power. We consider the industry overall is experiencing a medium level demand.","PeriodicalId":230625,"journal":{"name":"2021 International Conference on Computer, Blockchain and Financial Development (CBFD)","volume":"38 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":"128441395","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/CBFD52659.2021.00037
Xin Pengzhe, Deng Qianyu
In recent years, the development of deep learning has led to unprecedented advances in computer vision, making it possible to use artificial intelligence to identify shop names. This paper proposes a store entity identification system based on deep learning, which consists of three modules. The text detection module adopts Cascade Mask R-CNN. The text recognition module adopts Attention LSTM. The named entity recognition module adopts Bert-BiLSTM-CRF. It can recognize all the text information in the picture and extract the shop name accurately. The final score can reach 91.12%. Our research saves the time of traditional manual extraction of the shop name in the picture, and provides technical support for the intelligent development of the shop management system.
{"title":"A Store Entity Identification Method Based on Deep Learning","authors":"Xin Pengzhe, Deng Qianyu","doi":"10.1109/CBFD52659.2021.00037","DOIUrl":"https://doi.org/10.1109/CBFD52659.2021.00037","url":null,"abstract":"In recent years, the development of deep learning has led to unprecedented advances in computer vision, making it possible to use artificial intelligence to identify shop names. This paper proposes a store entity identification system based on deep learning, which consists of three modules. The text detection module adopts Cascade Mask R-CNN. The text recognition module adopts Attention LSTM. The named entity recognition module adopts Bert-BiLSTM-CRF. It can recognize all the text information in the picture and extract the shop name accurately. The final score can reach 91.12%. Our research saves the time of traditional manual extraction of the shop name in the picture, and provides technical support for the intelligent development of the shop management system.","PeriodicalId":230625,"journal":{"name":"2021 International Conference on Computer, Blockchain and Financial Development (CBFD)","volume":"21 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":"132100664","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 "Blockchain Plus" intelligent parking matching guidance system was designed on the basis of the analysis of the technologies of blockchain, parking space reservations, parking matching guidance, vehicle service navigation. The system consists of application layer, blockchain technical service layer, network layer, and data layer, using blockchain technologies such as aggregation chain architecture based consensus algorithm services, smart contract services, and anti-counterfeiting verification supported by digital DNA, to provide services such as parking space reservation, intelligent matching parking space, vehicle service navigation to optimize parking matching, parking searching, and parking route guidance. The system performance test shows that the average matching time, average parking searching time, average parking index, average parking success rate and other performance data are better than other similar parking service systems. Therefore, this system can offer a proven help to solve the problems including unbalanced supply and demand of parking space in urban area, travel difficulties and so on.
{"title":"Design of \"Blockchain Plus\" intelligent parking matching guidance system","authors":"Yuxia Zhang, Qiuxiang Wu, Bingquan Wu, Xiang-lin Pan, Fei Liang","doi":"10.1109/CBFD52659.2021.00053","DOIUrl":"https://doi.org/10.1109/CBFD52659.2021.00053","url":null,"abstract":"The \"Blockchain Plus\" intelligent parking matching guidance system was designed on the basis of the analysis of the technologies of blockchain, parking space reservations, parking matching guidance, vehicle service navigation. The system consists of application layer, blockchain technical service layer, network layer, and data layer, using blockchain technologies such as aggregation chain architecture based consensus algorithm services, smart contract services, and anti-counterfeiting verification supported by digital DNA, to provide services such as parking space reservation, intelligent matching parking space, vehicle service navigation to optimize parking matching, parking searching, and parking route guidance. The system performance test shows that the average matching time, average parking searching time, average parking index, average parking success rate and other performance data are better than other similar parking service systems. Therefore, this system can offer a proven help to solve the problems including unbalanced supply and demand of parking space in urban area, travel difficulties and so on.","PeriodicalId":230625,"journal":{"name":"2021 International Conference on Computer, Blockchain and Financial Development (CBFD)","volume":"35 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":"132171186","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/CBFD52659.2021.00051
Rui-ying Zheng
Artificial intelligence is the technology which takes simulating and expanding human intelligence as the core. In 2019, the Government Accounting System was officially implemented, and colleges and other administrative institutions will implement the "Double Accounting System". Artificial intelligence is facing great opportunities and challenges in improving the accounting system of colleges and universities. This paper analyses the above opportunities and challenges, and puts forward the innovation models of college accounting system from the perspective of artificial intelligence, including intelligent parallel accounting model, intelligent sequential accounting model, intelligent automatic accounting model and intelligent separate accounting model to provide references for the adjustment of accounting information system in colleges and universities.
{"title":"Challenges and Innovations of Colleges Accounting System from the Perspective of Artificial Intelligence","authors":"Rui-ying Zheng","doi":"10.1109/CBFD52659.2021.00051","DOIUrl":"https://doi.org/10.1109/CBFD52659.2021.00051","url":null,"abstract":"Artificial intelligence is the technology which takes simulating and expanding human intelligence as the core. In 2019, the Government Accounting System was officially implemented, and colleges and other administrative institutions will implement the \"Double Accounting System\". Artificial intelligence is facing great opportunities and challenges in improving the accounting system of colleges and universities. This paper analyses the above opportunities and challenges, and puts forward the innovation models of college accounting system from the perspective of artificial intelligence, including intelligent parallel accounting model, intelligent sequential accounting model, intelligent automatic accounting model and intelligent separate accounting model to provide references for the adjustment of accounting information system in colleges and universities.","PeriodicalId":230625,"journal":{"name":"2021 International Conference on Computer, Blockchain and Financial Development (CBFD)","volume":"4 7 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":"121477931","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/CBFD52659.2021.00054
Liu Chenxi, Yilin Cai, Xinlu Zhang, Jiatong Tan
With the acceleration of the urbanization process and the development of social economy, the motor vehicle ownership rate of urban residents is increasing day by day. Therefore, traffic congestion is becoming a major problem in cities around the world. These phenomena not only waste residents’ time and money, but also cause serious pollution to the environment. Therefore, traffic congestion monitoring is of great significance for analyzing the problem of traffic flow stability. To improve the prediction accuracy of urban road traffic congestion, this paper proposes a conges-tion discrimination model based on Pattern Mining according to relevant res. Then we combine a lot of data for data mining. Given the urban road traffic congestion real-time identification problem, we extract some key factors. Based on the Stata flow prediction model, we used the Beijing traffic data set model to verify the multi-log linear regression. Finally, we obtain the high accuracy traffic congestion regression model.
{"title":"Geographic Information Traffic Detection Model","authors":"Liu Chenxi, Yilin Cai, Xinlu Zhang, Jiatong Tan","doi":"10.1109/CBFD52659.2021.00054","DOIUrl":"https://doi.org/10.1109/CBFD52659.2021.00054","url":null,"abstract":"With the acceleration of the urbanization process and the development of social economy, the motor vehicle ownership rate of urban residents is increasing day by day. Therefore, traffic congestion is becoming a major problem in cities around the world. These phenomena not only waste residents’ time and money, but also cause serious pollution to the environment. Therefore, traffic congestion monitoring is of great significance for analyzing the problem of traffic flow stability. To improve the prediction accuracy of urban road traffic congestion, this paper proposes a conges-tion discrimination model based on Pattern Mining according to relevant res. Then we combine a lot of data for data mining. Given the urban road traffic congestion real-time identification problem, we extract some key factors. Based on the Stata flow prediction model, we used the Beijing traffic data set model to verify the multi-log linear regression. Finally, we obtain the high accuracy traffic congestion regression model.","PeriodicalId":230625,"journal":{"name":"2021 International Conference on Computer, Blockchain and Financial Development (CBFD)","volume":"22 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":"126326519","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/CBFD52659.2021.00104
Jie Sun
Blockchain was once hailed as an important direction of the fourth industrial revolution with its decentralization concept. The logistics industry is the largest application scenario of blockchain after finance. This paper designed the emergency logistics support system which is based on blockschain collaboration. And this system is constructed from material supply and demand management, material scheduling management, etc. In this system, smart contracts are automatically executed throughout the process and highly reliable, providing a shared but non-tamperable distributed logistics database to ensure the real-time query logistics information. Under the joint maintenance of all parties, every logistics transfer is recorded on the blockchain. This will not only improve the efficiency of emergency logistics management in emergencies, but also help enhance transparency. At the same time, the timeliness and adaptability of material allocation have been fully guaranteed.
{"title":"Research on collaborative construction of emergency logistics support system and blockchain","authors":"Jie Sun","doi":"10.1109/CBFD52659.2021.00104","DOIUrl":"https://doi.org/10.1109/CBFD52659.2021.00104","url":null,"abstract":"Blockchain was once hailed as an important direction of the fourth industrial revolution with its decentralization concept. The logistics industry is the largest application scenario of blockchain after finance. This paper designed the emergency logistics support system which is based on blockschain collaboration. And this system is constructed from material supply and demand management, material scheduling management, etc. In this system, smart contracts are automatically executed throughout the process and highly reliable, providing a shared but non-tamperable distributed logistics database to ensure the real-time query logistics information. Under the joint maintenance of all parties, every logistics transfer is recorded on the blockchain. This will not only improve the efficiency of emergency logistics management in emergencies, but also help enhance transparency. At the same time, the timeliness and adaptability of material allocation have been fully guaranteed.","PeriodicalId":230625,"journal":{"name":"2021 International Conference on Computer, Blockchain and Financial Development (CBFD)","volume":"56 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":"121158504","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/CBFD52659.2021.00015
Jingqi Liu, Xinzhen Pei, Junyan Zou
Accounting information is an essential basis for investors to make decisions, and it is vital to analyze the impact of accounting information on stock prices accurately. Therefore, this article establishes Factor Analysis-Artificial Neural Network-Radial Basis Function (FA-ANN-MLP) model, through empirical analysis of Sinopec Group’s stock prices and accounting information, to explore accounting information indicators that significantly affect stock prices and Predict the trend of stock price rise and fall. The results show that the accuracy of the model’s prediction is 81.7%, and profitability and earnings per share are significant factors that affect stock prices. This model has a high accuracy rate in predicting stock price rise and fall, providing investors with a theoretical basis.
{"title":"Analysis and Research on the Stock Volatility Factors of Chinese Listed Companies Based on the FA-ANN-MLP Model","authors":"Jingqi Liu, Xinzhen Pei, Junyan Zou","doi":"10.1109/CBFD52659.2021.00015","DOIUrl":"https://doi.org/10.1109/CBFD52659.2021.00015","url":null,"abstract":"Accounting information is an essential basis for investors to make decisions, and it is vital to analyze the impact of accounting information on stock prices accurately. Therefore, this article establishes Factor Analysis-Artificial Neural Network-Radial Basis Function (FA-ANN-MLP) model, through empirical analysis of Sinopec Group’s stock prices and accounting information, to explore accounting information indicators that significantly affect stock prices and Predict the trend of stock price rise and fall. The results show that the accuracy of the model’s prediction is 81.7%, and profitability and earnings per share are significant factors that affect stock prices. This model has a high accuracy rate in predicting stock price rise and fall, providing investors with a theoretical basis.","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":"133241526","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/CBFD52659.2021.00027
Chaoqi Wu, Jinming Zhang
It is an essential process for investors to construct a portfolio in the equity market. However, the uncertain volatility in the market is a drag to construct a certain portfolio. Based on several blue-chip stocks from S&P, this paper aims at constructing an optimal portfolio with risky assets. The autoregressive moving average (ARMA) model and the Mean-Variance model are selected for investigations. Specifically, the paper builds time series models and forecasts the future returns with a rolling window based on the ARMA model. Then, the predicted weekly returns are used to calculate the Efficient Frontier (EF) of every single period using Monte Carlo simulation. Furthermore, the optimal point with the highest Sharpe Ratio locates the upper-left area of the EF is adopted to set up and adjust the portfolio of each period. The back-test results show that the portfolio performed well compared to the S&P500 index. On top of that, the ARMA model selected performed well in predicting the future return of targeted stocks. Moreover, the Mean-Variance Model, abbreviated as MV model afterward, with maximized Sharpe ratio, also generates agreeable results. Specifically, the weight on new advanced industrial stocks and retail stocks are relatively high in the portfolio. This empirical process further proves two important facts in financial markets. (1) It is feasible to forecast future stock by returns in the past; (2) it is advisable to pay more attention to new advanced industrial stocks and retail stocks. Adding these kinds of stocks into the portfolio is more potential to gain high returns with correspondingly low volatility.
{"title":"Portfolio Construction Based on the ARMA Model and the Mean-Variance Theory","authors":"Chaoqi Wu, Jinming Zhang","doi":"10.1109/CBFD52659.2021.00027","DOIUrl":"https://doi.org/10.1109/CBFD52659.2021.00027","url":null,"abstract":"It is an essential process for investors to construct a portfolio in the equity market. However, the uncertain volatility in the market is a drag to construct a certain portfolio. Based on several blue-chip stocks from S&P, this paper aims at constructing an optimal portfolio with risky assets. The autoregressive moving average (ARMA) model and the Mean-Variance model are selected for investigations. Specifically, the paper builds time series models and forecasts the future returns with a rolling window based on the ARMA model. Then, the predicted weekly returns are used to calculate the Efficient Frontier (EF) of every single period using Monte Carlo simulation. Furthermore, the optimal point with the highest Sharpe Ratio locates the upper-left area of the EF is adopted to set up and adjust the portfolio of each period. The back-test results show that the portfolio performed well compared to the S&P500 index. On top of that, the ARMA model selected performed well in predicting the future return of targeted stocks. Moreover, the Mean-Variance Model, abbreviated as MV model afterward, with maximized Sharpe ratio, also generates agreeable results. Specifically, the weight on new advanced industrial stocks and retail stocks are relatively high in the portfolio. This empirical process further proves two important facts in financial markets. (1) It is feasible to forecast future stock by returns in the past; (2) it is advisable to pay more attention to new advanced industrial stocks and retail stocks. Adding these kinds of stocks into the portfolio is more potential to gain high returns with correspondingly low volatility.","PeriodicalId":230625,"journal":{"name":"2021 International Conference on Computer, Blockchain and Financial Development (CBFD)","volume":"9 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":"133994989","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/CBFD52659.2021.00109
Yezhou Yang, Songqi Liu, Yuning Li
As a new financial service model, digital finance has an important impact on the development of the real economy. Based on the data of GEM private enterprises from 2013 to 2018 as samples, this paper examines the relationship between digital financial inclusion and private enterprise innovation from the perspective of influence path and regional heterogeneity. The results show that digital finance can promote the innovation of private enterprises, and the conclusion is still valid after controlling endogenous and replacing variable indicators. Further research finds that digital finance can promote the innovative development of private enterprises on the GEM by alleviating the financing constraints. In addition, the influence of digital finance on the innovation of private enterprises has significant regional heterogeneity, and the promoting effect is stronger in the developed eastern regions. This study enriches the relevant research on the impact of digital finance on enterprise innovation, and concludes that the government should increase its support for private enterprises, establish and improve the risk control mechanism of digital finance, and coordinate the regional development of digital finance.
{"title":"Research on the influence mechanism and regional heterogeneity of digital finance on enterprise innovation : —Empirical analysis based on private enterprises on GEM","authors":"Yezhou Yang, Songqi Liu, Yuning Li","doi":"10.1109/CBFD52659.2021.00109","DOIUrl":"https://doi.org/10.1109/CBFD52659.2021.00109","url":null,"abstract":"As a new financial service model, digital finance has an important impact on the development of the real economy. Based on the data of GEM private enterprises from 2013 to 2018 as samples, this paper examines the relationship between digital financial inclusion and private enterprise innovation from the perspective of influence path and regional heterogeneity. The results show that digital finance can promote the innovation of private enterprises, and the conclusion is still valid after controlling endogenous and replacing variable indicators. Further research finds that digital finance can promote the innovative development of private enterprises on the GEM by alleviating the financing constraints. In addition, the influence of digital finance on the innovation of private enterprises has significant regional heterogeneity, and the promoting effect is stronger in the developed eastern regions. This study enriches the relevant research on the impact of digital finance on enterprise innovation, and concludes that the government should increase its support for private enterprises, establish and improve the risk control mechanism of digital finance, and coordinate the regional development of digital finance.","PeriodicalId":230625,"journal":{"name":"2021 International Conference on Computer, Blockchain and Financial Development (CBFD)","volume":"26 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":"133776817","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/CBFD52659.2021.00079
Zhi Hui, Cheng Kai, Zhou Ziting
Option is one of the most special representative products in the financial market. This paper shows that the basic concept of Asian options and European options. Then we make a summary for Asian and European options about formers' studies, respectively. Further, we present a Monte Carlo simulation to sample asset price paths for both Asian options and European options. Apple Inc. Common Stock (AAPL) is chosen as a market example which we can obtain market prices. This paper introduces the classic's formula for geometric Brownian motion, then simulating financial asset prices. Monte Carlo simulation can solve the pricing problem well because of its obvious advantages such as flexibility, easy realization, and estimation error. This paper focuses on the characteristics of Asian options and European options. Scatterplots obtained from the simulation data are used to compare and analyze the difference between Asian options and European options. It is concluded that the investment risk of Asian options is smaller than European options
{"title":"Comparative analysis of Asian and European options based on Monte Carlo simulation","authors":"Zhi Hui, Cheng Kai, Zhou Ziting","doi":"10.1109/CBFD52659.2021.00079","DOIUrl":"https://doi.org/10.1109/CBFD52659.2021.00079","url":null,"abstract":"Option is one of the most special representative products in the financial market. This paper shows that the basic concept of Asian options and European options. Then we make a summary for Asian and European options about formers' studies, respectively. Further, we present a Monte Carlo simulation to sample asset price paths for both Asian options and European options. Apple Inc. Common Stock (AAPL) is chosen as a market example which we can obtain market prices. This paper introduces the classic's formula for geometric Brownian motion, then simulating financial asset prices. Monte Carlo simulation can solve the pricing problem well because of its obvious advantages such as flexibility, easy realization, and estimation error. This paper focuses on the characteristics of Asian options and European options. Scatterplots obtained from the simulation data are used to compare and analyze the difference between Asian options and European options. It is concluded that the investment risk of Asian options is smaller than European options","PeriodicalId":230625,"journal":{"name":"2021 International Conference on Computer, Blockchain and Financial Development (CBFD)","volume":"10 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":"123079443","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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