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11th International Conference on Information Technology and Quantitative management, ITQM 2024

作者： Long, Wen Gao, Jing Guo, Man School of Economics and Management University of Chinese Academy of Sciences Beijing100090 China Research Center on Fictitious Economy & Data Science Chinese Academy of Sciences Beijing100190 China Key Laboratory of Big Data Mining & Knowledge Management Chinese Academy of Sciences Beijing100190 China

Both structured market data and unstructured financial news data can significantly affect stock price fluctuations. Therefore, relying only on a single data source for stock price trend prediction may produce information bias. This article combines these two types of heterogeneous data and systematically compares the effectiveness of different data fusion technologies to establish the optimal data integration strategy, thereby improving the accuracy of stock price prediction. Specifically, this paper innovatively proposes a stock price trend prediction model named MVL-SVM. The model successfully combines multi-perspective learning with support vector machine, and realizes the effective fusion of stock market data and financial news data. It is worth mentioning that the prediction accuracy of MVL-SVM model using direct fusion method is more than 30% higher than that of index modeling method, which indicates that direct fusion method can fully learn effective information from multiple information sources, thus significantly improving the prediction effect. © 2024 The Authors.

关键词： data accuracy

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Review of graph construction and graph learning in stock price prediction 9th

Review of graph construction and graph learning in stock pri...

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9th International Conference on Information Technology and Quantitative management, ITQM 2022

作者： Wang, Yunong Qu, Yi Chen, Zhensong Research Center on Fictitious Economy and Data Science Chinese Academy of Sciences Beijing100190 China Key Laboratory of Big Data Mining and Knowledge Management Chinese Academy of Sciences Beijing100190 China School of Management and Engineering Capital University of Economics and Business Beijing100070 China

Precise prediction of stock prices leads to more profits and more effective risk prevention, which is of great significance to both investors and regulators. Recent years, various kinds of information not directly-relevant with stock prices have received more attention, such as texts, images or connections. These external information has the potential of reflecting or influencing fluctuations, and thus, given the utilization of advanced analyzing techniques, the forecasting performance of stock prices could be promoted substantially. For instance, graph neural network models have expanded into many other disciplines including stock price prediction, and exhibited impressive representation learning ability. However, in stock markets, well-defined graphs are rarely seen and how to formulate the graph structures needed remains a challenging problem. Towards this end, this article presents a comprehensive overview of graph construction and graph learning in stock price prediction, by reviewing the existing studies, summarizing its general paradigm, special cases and proposing possible prospects. Our research not only systematically reveals the feasible ways of constructing graphs in financial markets, but also provides insights for further implementations of graph learning models into stock prediction tasks. © 2022 The Authors. Published by Elsevier B.V.

关键词： Financial markets

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Volatility and risk contagion of international stock market in the context of COVID-19 10

Volatility and risk contagion of international stock market ...

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10th International Conference on Information Technology and Quantitative management, ITQM 2023

作者： Long, Wen Zeng, Yuhan Guo, Man School of Economics and Management University of Chinese Academy of Sciences Beijing100090 China Research Center on Fictitious Economy and Data Science Chinese Academy of Sciences Beijing100190 China Key Laboratory of Big Data Mining and Knowledge Management Chinese Academy of Sciences Beijing100190 China

In order to reveal the impact of the outbreak of COVID-19 epidemic on risk contagion in the international stock market, this paper establishes an ARMA-GARCH-Copula model based on the R-Vine structure to empirically analyze the stock index data of 19 important countries(regions) around the world, and uses complex network to display the risk contagion path. This research shows that the risk contagion correlation of the global stock market has significantly improved due to the impact of COVID-19;The correlation of risk transmission among European countries is significantly higher than that of other regions, reflecting a closer integration connection between EU countries;Finally, unlike previous literature, this article finds that stock market of Hong Kong in China has become an important node in the international stock market, playing an important role in the risk network before and after the epidemic. © 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://***/licenses/by-nc-nd/4.0) Peer-review under responsibility of the scientific committee of the Tenth International Conference on Information Technology and Quantitative management.

关键词： COVID-19

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The asset allocation utility of digital cryptocurrency 9th

The asset allocation utility of digital cryptocurrency

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9th International Conference on Information Technology and Quantitative management, ITQM 2022

作者： Long, Wen Wang, Maohua Guo, Man School of Economics and Management University of Chinese Academy of Sciences Beijing100090 China Research Center on Fictitious Economy and Data Science Chinese Academy of Sciences Beijing100190 China Key Laboratory of Big Data Mining and Knowledge Management Chinese Academy of Sciences Beijing100190 China

In recent years, the digital cryptocurrency market has witnessed rapid development, but its asset allocation function has yet to be verified. In this paper, DCC-GARCH model is used to estimate the dynamic correlation between digital cryptocurrency and current mainstream assets, and the corresponding hedging effect of digital cryptocurrency is studied. Then, three mainstream asset allocation strategies are selected to analyze the risk and return of asset allocation portfolio after adding digital cryptocurrency, which verifies the asset allocation utility of digital cryptocurrency. This study can provide investment basis for investors and has certain theoretical and practical significance. © 2022 The Authors. Published by Elsevier B.V.

关键词： Electronic money

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Research on Liquidity Measurement and Influencing Factors of China Carbon Emission Allocation Trading Market 10

Research on Liquidity Measurement and Influencing Factors of...

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10th International Conference on Information Technology and Quantitative management, ITQM 2023

作者： Shi, Yong Peng, Shuyang Yu, Anqi Guo, Kun School of Economics and Management University of Chinese Academy of Sciences Beijing100190 China Research Center on Fictitious Economy and Data Science Chinese Academy of Sciences Beijing100190 China Key Laboratory of Big Data Mining and Knowledge Management Chinese Academy of Sciences Beijing100190 China

Considering multi-dimensional concepts of liquidity, we introduces two classical liquidity measures to quantify the liquidity of China carbon emission allowance(CCEA) trading markets, and analyze their trading activities. Then monthly unbalanced panel was constructed based on daily trading data to further study on the influencing factors of CCEA market. We find that: 1) No matter what method we take, the Hubei pilot is the most liquid in the context of overall running periods, and the national carbon market and Guangdong pilot are also well performed compared to the other markets. 2)The foundation of national generalized market could bring about noticeable changes on the liquidity of carbon market, and Guangdong market which is one of the 8 carbon market pilots become more developed and liquid, while no significant variation in the rest of 7 pilots. 3) The emission control enterprises of each pilot have no inborn incentive to trade proactively, therefore transactions are concentrated on the performance cycle. 4)Regression results show that the price at the end of each month, trading volumes aggregated in each month, trading frequency of each month are all positively correlated with the liquidity, and return volatility of each month, carbon market fragmentation are negatively related to the liquidity. Finally we put forward some suggestion and policy recommendation rested on the above qualitative and quantitative analysis. © 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://***/licenses/by-nc-nd/4.0) Peer-review under responsibility of the scientific committee of the Tenth International Conference on Information Technology and Quantitative management.

关键词： Emission control

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China's New Third Board Market: Opportunities and Challenges

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Procedia Computer Science 2015年 55卷 1050-1059页

作者： Yumeng Li Xiangying Meng Xianhua Wei School of Management University of Chinese Academy Sciences Beijing 100010 China Key Laboratory of Big Data Mining and Knowledge Management Chinese Academy of Sciences

The New Third Board Market is China's OTC market, established in 2006. Compared to China's Main Board Market and the Second Board Market, it attracts a lot of start-up companies needing financing with lower listing requirements. Meanwhile, it is full of opportunities and challenges that appeal to numerous securities traders and investors with the rapid development momentum. This paper is intended to build a comprehensive and systematic knowledge framework of China's New Third Board Market for those enterprises and individuals interested in it, and to provide a research base for future researchers.

关键词： China's New Third Board Market SME financing market makers opportunities challanges

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COVID-19 Impact on Global Electricity Generation Structure-Based on Sustainable Development Perspective 9th

COVID-19 Impact on Global Electricity Generation Structure-B...

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9th International Conference on Information Technology and Quantitative management, ITQM 2022

作者： Peng, Shuyang Yang, Xian Lu, Haibo Guo, Kun School of Economics and Management University of Chinese Academy of Sciences Beijing100190 China Research Center on Fictitious Economy and Data Science Chinese Academy of Sciences Beijing 100190 China Key Laboratory of Big Data Mining and Knowledge Management Chinese Academy of Sciences Beijing100190 China

This paper has sorted out the general logic of the impact of COVID-19 on energy consumption. In the short term, the epidemic has forced governments to adopt different levels of lockdown measures. The total electricity consumption decreased and the share of renewable energy has increased. Based on the International Energy Agency's (IEA) data on electricity production and consumption, this paper analyzes the long-term effects: The COVID-19 pandemic does affect overall electricity demand and market structure in the short term, but in the long term, the impact of the pandemic is detrimental to the proportion of electricity generated from renewable sources. Increased, especially in hard-hit countries. The impact on countries with different levels of development is different, and countries with higher levels of economic development are better able to resist such exogenous shocks. The pandemic is still ongoing, how to steadily promote sustainable development? In this paper we suggest that to cope with climate change, to accomplish energy transformation and upgrading or even sustainable development, we should not only rely on reducing human activities, but give more support to countries with low development levels in realizing sustainable development. © 2022 The Authors. Published by Elsevier B.V.

关键词： COVID-19

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Exploring the heterogeneity of social media: dataset and a pilot study 15

Exploring the heterogeneity of social media: Dataset and a p...

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7th International Conference on Internet Multimedia Computing and Service, ICIMCS 2015

作者： Lu, Dongyuan Zheng, Nan School of Information Technology and Management University of International Business and Economics Beijing100029 China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China Key Laboratory of Big Data Mining and Knowledge Management Chinese Academy of Sciences Beijing100190 China

ISBN: (纸本)9781450335287

Social media has exploded beyond anyone's wildest imagination, and User Generated Content (UGC) is propagated online at an unparalleled level. Organizing and associating the heterogeneous UGC data in different social media networks is playing a more and more important role in comprehensive user modeling and social media applications. Since social media data are essentially user-centric, which are generated from user and customized for user, we introduce a user-centric dataset to analyze and exploit the social media heterogeneity, which involves with six popular social media networks and 180, 000 overlapped users. A pilot study on the collected dataset is conducted to demonstrate the limitations of traditional content-centric metrics in analyzing the cross-OSN data. Finally, we conclude this work with discussions on the potentials of usercentric framework for cross-OSN organization and association. © 2015 ACM.

关键词： Social networking (online)

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Impact of Live Streamer Characteristics and Customer Response on Live-streaming Performance: Empirical Evidence from e-Commerce Platform 9th

Impact of Live Streamer Characteristics and Customer Respons...

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9th International Conference on Information Technology and Quantitative management, ITQM 2022

作者： Zhou, Xiaohui Tian, Xin Research Center on Fictitious Economy and Data Science Chinese Academy of Sciences Beijing100190 China School of Economics and Management University of Chinese Academy of Sciences Beijing100190 China Key Laboratory of Big Data Mining and Knowledge Management Chinese Academy of Sciences Beijing100190 China

As an emerging form of marketing, live streaming has a positive effect on the ability of e-Commerce platforms to attract traffic and increase sales. It has become another important competitive area in the industry. Based on an alternative learning theory model, the influencing factors of live streaming on e-Commerce platforms are studied, and the data findings can be applied to brand marketing and platform performance improvement. Quantitative and qualitative analyses were conducted using tens of thousands of live-streaming data, and the findings show that live interaction and live streamer follower accumulation have a significant positive effect on the number of sold users. Through the empirical study of real data, this paper inspires participants to fully embrace the effect of live streaming and enhance the consumer shopping experience. © 2022 The Authors. Published by Elsevier B.V.

关键词： Electronic commerce

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Do Media Reports Matter to House Price Expectations?Evidence from Beijing

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Journal of Systems Science and Information 2022年第4期10卷 388-409页

作者： Jing HE Diandian MA Xiuting LI Jichang DONG Postdoctoral Research Center of Agricultural Bank of China Beijing 100005China School of Statistics Renmin University of ChinaBeijing 100872China School of Economics and Management University of Chinese Academy of SciencesBeijing 100190China Key Laboratory of Big Data Mining and Knowledge Management Chinese Academy of SciencesBeijing 100190China

House price expectations(HPE)is a key factor affecting housing market *** Beijing as an example,this study innovatively proposes an internet data-based measurement of HPE and text analysis-based quantification of media reports from media attention and media *** model is performed to empirically test the impact of media reports on the level and accuracy of *** empirical results show no significant relationship between media attention and the level of HPE,but a significant relationship to the accuracy of *** higher the media attention(i.e.,the more intensive the media reports),the smaller the deviation between HPE and actual housing *** attitude of media reports is significantly related to the level and accuracy of *** is easier to guide the formation of HPE through media reports with clear opinions,indicating that media could promote the sustainable development of the real estate market.

关键词： media reports real estate market housing prices public expectations

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