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A Review on the Security of the Ethereum-Based DeFi Ecosystem

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Computer Modeling in Engineering & Sciences 2024年第4期139卷 69-101页

作者： Yue Xue Dunqiu Fan Shen Su Jialu Fu Ning Hu Wenmao Liu Zhihong Tian Cyberspace institute of Advanced Technology Guangzhou UniversityGuanzhou510000China Innovation Center NSFOCUS Inc.Beijing100089China Engineering Research Center of Integration and Application of Digital Learning Technology Ministry of EducationBeijing100816China

Decentralized finance(DeFi)is a general term for a series of financial products and services.It is based on blockchain technology and has attracted people’s attention because of its open,transparent,and intermediary free.Among them,the DeFi ecosystem based on Ethereum-based blockchains attracts the most attention.However,the current decentralized financial system built on the Ethereum architecture has been exposed to many smart contract vulnerabilities during the last few years.Herein,we believe it is time to improve the understanding of the prevailing Ethereum-based DeFi ecosystem security issues.To that end,we investigate the Ethereum-based DeFi security issues:1)inherited from the real-world financial system,which can be solved by macro-control;2)induced by the problems of blockchain architecture,which require a better blockchain platform;3)caused by DeFi invented applications,which should be focused on during the project development.Based on that,we further discuss the current solutions and potential directions ofDeFi security.According to our research,we could provide a comprehensive vision to the research community for the improvement of Ethereum-basedDeFi ecosystem security.

关键词： Blockchain smart contract decentralized finance DeFi security

Digital Economy,Entrepreneurship,and High-Quallty Economic Development:Empirical Evidence from Urban China

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Frontiers of Economics in China-Selected Publications from Chinese Universities 2022年第3期17卷 393-426页

作者： ZHAO Tao ZHANG Zhi LIANG Shangkun School of Public finance and Taxation Central University of Finance and EconomicsBeijing 100081China institute of China's Internet Economy Central University of Finance and EconomicsBeijing 100081China Business School Nanjing UniversityNanjing 210093China School of Accountancy Central University of Finance and EconomicsBeijing 100081China

The paper discusses the effects of the digital economy on highquality urban development and its mechanism.Theoretically,the digital economy can empower high-quality development by boosting entrepreneurial vitality.Empirically,the paper measures the overall level of the digital economy and high-quality development of the 222 Chinese cities at and above the prefecture level during 2011-2016,depicts the entrepreneurial vitality of the cities with the microscopic data of the business registration information and makes quantitative analysis on this basis.The result shows:Digital economy has remarkably improved high-quality development and this conclusion still exists after the robustness test selecting historical data as the instrumental variables and the Broadband China pilot policy as the quasi experiment.The analysis of the mechanism of action indicates that encouraging public entrepreneurship is an important mechanism of the digital economy to release the dividend of highquality development.Finally,thanks to the threshold model and the spatial model,it is found that the positive effect of the digital economy has the characteristics of nonlinear increment and spatial spillover of the“marginal effects.”The research of the paper stimulates the reasons for high-quality development and the understanding of the effects,mechanisms and regional differences of high-quality development empowered by the digital economy.

关键词： digital economy entrepreneurship high-quality development “Broadband China”pilot policy

Calculation and decomposition of regional household energy consumption in China:based on perspectives of urbanization and residents' consumption

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Chinese Journal of Population,Resources and Environment 2017年第2期15卷 132-141页

作者： Wen Guo Tianyan Zhao Hongjun Dai College of accounting Nanjing University of Finance & Economics College of Economics and Management Research Institute of Financial Development Nanjing University of Aeronautics and Astronautics School of accounting Capital University of Economics and Business

Demographic urbanization caused great changes in scale of residents' consumption and residents' lifestyle and then impacted changes of regional household energy consumption. This paper expanded Logarithmic Mean Decomposition Index method through introducing variables of urbanization and residential consumption into the model. It also analyzed the influences of six factors as energy structure, energy intensity, population scale, urbanization, residential consumption, and consumption inhibit on regional household energy consumption. Results showed that in 2003-2012, impact of urbanization on regional household energy consumption of Chinese three areas was significantly higher than population size. The "population gathered in eastern region" phenomenon caused eastern region getting the largest population scale effect. Driving force of residential consumption on regional household energy consumption was much higher than the other five effects. Due to the comparative advantage of residential consumption compared with government consumption, investment, and net export, the decrease of consumption ratio promoted the growth of regional household energy consumption. Energy intensity in Chinese three regions kept reducing in 2003-2012. The progress of energy utilization technology slowed the growth of regional household energy consumption, and energy intensity effect was most significant in the central region.

关键词：地区性都市化和分解消费精力家庭居民计算

Improving sentiment analysis accuracy with emoji embedding

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Journal of Safety Science and Resilience 2021年第4期2卷 246-252页

作者： Chuchu Liu Fan Fang Xu Lin Tie Cai Xu Tan Jianguo Liu Xin Lu College of Systems Engineering National University of Defense TechnologyChangsha410073China College of Computer National University of Defense TechnologyChangsha410073China School of Software Engineering Shenzhen Institute of Information TechnologyShenzhen518172China Institute of Accounting and Finance Shanghai University of Finance and EconomicsShanghai200433China

Due to the diversity and variability of Chinese syntax and semantics,accurately identifying and distinguishing individual emotions from online texts is challenging.To overcome this limitation,we incorporate a new source of individual sentiment,emojis,which contain thousands of graphic symbols and are increasingly being used for expressing emotion in online conversations.We examined popular sentiment analysis algorithms,including rule-based and classification algorithms,to evaluate the impact of supplementing emojis as additional features to improve the algorithm performance.Emojis were also translated into corresponding sentiment words when con-structing features for comparison with those directly generated from emoji label words.In addition,considering different functions of emojis in texts,we classified all posts in the dataset by their emoji usage and examined the changes in algorithm performance.We found that emojis are effective as expanding features for improving the accuracy of sentiment analysis algorithms,and the algorithm performance can be further increased by taking different emoji usages into consideration.In this study,we developed an improved emoji-embedding model based on Bi-LSTM(namely,CEmo-LSTM),which achieves the highest accuracy(around 0.95)when analyzing online Chinese texts.We applied the CEmo-LSTM algorithm to a large dataset collected from Weibo from December 1,2019 to March 20,2020 to understand the sentiment evolution of online users during the COVID-19 pandemic.We found that the pandemic remarkably impacted individual sentiments and caused more passive emotions(e.g.,horror and sadness).Our novel emoji-embedding algorithm creatively combined emojis as well as emoji usage with the sentiment analysis model and can handle emotion mining tasks more effectively and efficiently.

关键词： Sentiment analysis Emoji CEmo-LSTM Sentiment evolution COVID-19

Item-level Forecasting for E-commerce Demand with High-dimensional Data Using a Two-stage Feature Selection Algorithm

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Journal of Systems Science and Systems Engineering 2022年第2期31卷 247-264页

作者： Hongyan Dai Qin Xiao Nina Yan Xun Xu Tingting Tong Business School Central University of Finance and EconomicsBeijing 100081China Department of Management Operationsand MarketingCollege of Business AdministrationCalifornia State UniversityStanislausTurlockCA95382United States institute of Supply Chain Analytics&International Business College Dongbei University of Finance and EconomicsDalian 116025China

With the rapid development of information technology and fast growth of Internet users,e-commerce nowadays is facing complex business environment and accumulating large-volume and highdimensional data.This brings two challenges for demand forecasting.First,e-merchants need to find appropriate approaches to leverage the large amount of data and extract forecast features to capture various factors affecting the demand.Second,they need to efficiently identify the most important features to improve the forecast accuracy and better understand the key drivers for demand changes.To solve these challenges,this study conducts a multi-dimensional feature engineering by constructing five feature categories including historical demand,price,page view,reviews,and competition for e-commerce demand forecasting on item-level.We then propose a two-stage random forest-based feature selection algorithm to effectively identify the important features from the high-dimensional feature set and avoid overfittlng.We test our proposed algorithm with a large-scale dataset from the largest e-commerce platform in China.The numerical results from 21,111 items and 109 million sales observations show that our proposed random forest-based forecasting framework with a two-stage feature selection algorithm delivers 11.58%,5.81%and 3.68%forecast accuracy improvement,compared with the Autoregressive Integrated Moving Average(ARIMA),Random Forecast,and Random Forecast with one-stage feature selection approach,respectively,which are widely used in literature and industry.This study provides a useful tool for the practitioners to forecast demands and sheds lights on the B2C e-commerce operations management.

关键词： Forecasting e-commerce high-dimensional feature feature selection

Can media exposure improve stock price efficiency in China and why?

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China Journal of accounting Research 2016年第2期9卷 83-114页

作者： Jeong-Bon Kim Zhongbo Yu Hao Zhang School of accounting and finance University of Waterloo Shenzhen Stock Exchange Research institute College of Business City University of Hong Kong

The media in China has undergone extensive commercialization to become more market-driven over the last 35 years. Based on a sample of over two million newspaper articles, this study investigates whether the media in China has an incremental impact on stock price efficiency. We find that: as media coverage of a firm increases,(1) its stock price synchronicity decreases;(2)the probability of informed trading of its stock increases; and(3) the extent to which its stock price deviates from random walk decreases. Our interregional analysis over thirty-one provinces/regions within China reveals that the effects of the media on decreasing stock price synchronicity, increasing the probability of informed trading, and reducing stock price deviation from random walk are stronger in regions of weaker institutional development.Our findings suggest that a market-driven media can play the role of compensating for the underdeveloped governance institutions in transitional economies such as China.

关键词： Media exposure Stock price efficiency China

Corporate governance and audit fees:Evidence from companies listed on the Shanghai Stock Exchange

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China Journal of accounting Research 2012年第4期5卷 321-342页

作者： Xingze Wu Research Institute of Accounting and Finance Nanjing University

This study uses data from companies listed on the Shanghai Stock Exchange to investigate the relationship between corporate governance and audit fees. Full sample results reveal a significant negative relationship between corporate governance and audit fees, and subsample results further show that corporate governance's influence on audit fees is affected by corporate growth. The negative relationship between corporate governance and audit fees is economically and statistically significant in sample companies that grew moderately during the sample period, and mixed or insignificant in companies that experienced overly fast or negative growth.

关键词： Corporate governance Audit fees SSE Corporate Gove

Adaptive Single Piecewise Interpolation Reproducing Kernel Method for Solving Fractional Partial Differential Equation

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Journal of Donghua University(English Edition) 2022年第5期39卷 454-460页

作者：杜明婧 institute of Computer Information Management Inner Mongolia University of Finance and EconomicsHohhot 010070China

It is well-known that using the traditional reproducing kernel method(TRKM) for solving the fractional partial differential equation(FPDE) is very intractable. In this study, the adaptive single piecewise interpolation reproducing kernel method(ASPIRKM) is determined to solve the FPDE. This improved method not only improves the calculation accuracy, but also reduces the waste of time. Two numerical examples show that the ASPIRKM is a more time-saving numerical method than the TRKM.

关键词： fractional partial differential equation(FPDE) reproducing kernel method(RKM) single piecewise numerical solution

Reputation repair and corporate donations:An investigation of responses to regulatory penalties

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China Journal of accounting Research 2019年第3期12卷 293-313页

作者： Xue Xia Fei Teng Xiaolong Gu Center for accounting Financeand InstitutionsBusiness SchoolSun Yat-sen UniversityChina accounting School/International Business School Guangdong University of Finance and EconomicsChina institute of Capital Market and Audit Governance Studies for the Great Bay Area(Guangdong Hong-KongMacao)Guangdong University of Finance and EconomicsChina

According to the risk management and reputation insurance theory of corporate social responsibility, corporate donations can help a company to repair its reputation after a crisis.This study uses a propensity score matching–difference in difference(PSM + DID) methodology to investigate the charitable donation activities of companies that have been subject to regulatory penalties.The analysis of a sample of A-share listed companies in the 2004–2016 period shows that companies significantly increase their charitable donations after regulatory penalties, but this effect weakens over time.Further analysis reveals that non-state-owned companies, companies with higher ownership concentrations, and companies receiving severer penalties are more motivated to make donations after regulatory penalties.By studying the reputation repair behavior of companies that have been subject to regulatory penalties, this study offers further support for the risk management and reputation insurance theory of corporate social responsibility.It also enriches our understanding of companies’ active responses to regulatory penalties and provides insights into companies’ motives for making charitable donations.

关键词： Regulatory penalty Donation Reputation repair