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Investors pay attention to multi-level financial news ——"A pure waste of time" or "It’s worth it"

Procedia Computer Science 2022年 199卷 415-422页

作者： Wen Long Jiaqi Tian Yuanfeng Mao Yuan An School of Economics & Management University of Chinese Academy of Sciences Beijing 100190 P.R. China Research Center on Fictitious Economy & Data Science Chinese Academy of Sciences Beijing 100190 P.R. China Key Laboratory of Big Data Mining & Knowledge Management Chinese Academy of Sciences Beijing 100190 P.R. China Sino-Danish College University of Chinese Academy of Sciences Beijing 100049 P.R. China

In recent years,the efficiency of news communication has been greatly improved with the advance of Internet technology, and whether investors should pay attention to multiple levels of news when making trading decisions is worth pondering. However, Chinese scholars have paid little attention to the news hierarchy, and do not bring different levels of news into the prediction system. Therefore, this paper studies the stock price trend prediction from this perspective. This paper selects the medical industry as the representative, and adds its sub industry news and industry news to form a multi-level news system on the basis of individual stock news. In order to make better use of and extract the information contained in different levels of news, the multi-kernel learning model is incorporated on the basis of using SVM. The results suggest that the use of multi-level news can improve the accuracy of stock price trend prediction. Compared with the SVM model solely considering individual stock news, the prediction accuracy of multi-kernel learning model based on multi-level news is improved by 10%, which is of great significance for investment decision-making.

关键词： stock price trend multi-level financial news multi-kernel learning model

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The Dynamic Relationship between Macroeconomy and Stock Market in China: Evidence from Bayesian Network

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Complexity 2021年第1期2021卷 p1-12页

作者： Liu, Yue Feng, Haoyuan 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

As the most important component of the capital market, the stock market has always been regarded as the "barometer"of the macroeconomy. However, many researchers have found that the stock market and macroeconomy are operating separately. This paper uses the dynamic Bayesian network method to study the dynamic relationship between the Chinese macroeconomic system and the stock market. The study found that the correlation between the macroeconomic system and the stock market is not consistent in different time periods. For most of the time, the stock system and the macroeconomic system are relatively independent. However, several macroeconomic factors such as Purchase management Index could affect the stock market through some industries. A conclusion is drawn that the "barometer"function of the stock market is weak and easy to be damaged by factors such as the irrational sentiment of investors. © 2021 Yue Liu et al.

关键词： Financial markets

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Types and Evolutionary Boundaries of Agents

Types and Evolutionary Boundaries of Agents

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Artificial Intelligence Technology (ACAIT), Asian Conference on

作者： Feng Liu Ying Liu The Key Laboratory of Big Data Mining and Knowledge Management Chinese Academy of Sciences Research Center on Fictitious Economy and Data Science the Chinese Academy of Sciences Beijing China School of Economics and Management University of Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781665426312

Through the analysis of the characteristics of natural intelligent systems, the three laws of intelligence are exploringly proposed. The most important point is that any agent is a system with knowledge input, output, (dynamic) storage and creation abilities Since an agent has four abilities, and each ability has three states, including zero, infinity, and finite (between zero and infinity), 81 types of agents can be formed. Therefore, it can be inferred that Alpha point (No. 1), where all the four abilities of an agent are zero, and Omega point (No. 81), where all four abilities are infinite are the boundary of the evolution of Agent. This paper designs experiments to detect these 81 agents, and finds that 11 of them can be confirmed by experiments at present. Through the discussion of the states of Agents No. 64 to No. 81, fresh thinking is proposed for the generation and realization of the paradox.

关键词： Intelligent systems

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The Feature of the B&R Exchange Rate: Comparison with Main Currency Based on EMD Algorithm and Grey Relational Degrees 6th

The Feature of the B&R Exchange Rate: Comparison with Main C...

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6th International Conference on data Science, ICDS 2019

作者： Yixi, Cui Zixin, Liu Ziran, Li Kun, Guo University of Chinese Academy of Sciences Beijing China Key Laboratory of Big Data Mining and Knowledge Management School of Economics and Management UCAS Beijing China Minzu University of China Beijing China CFFEX Institute for Financial Derivatives Beijing China

ISBN: (纸本)9789811528095

According to BELT AND ROAD PORTAL, China has signed 173 cooperative documents with 125 countries and 29 international organizations along the Belt and Road (B&R) until April 2019, and the exchange rate volatility of currencies in the B&R are usually higher. In this paper, we firstly constructed the B&R exchange rate index on the basis of both the trade volumes and the foreign investment situation. After that, we compared it with the RMB exchange rate index. First, the EMD algorithm was used to decompose each index respectively into 8 IMFs and residual signal. Afterwards, based on grey comprehensive relational degrees, we reconstructed the market fluctuation term and noise term of each exchange rate index, and also get the trend term which is the residual signal. Then, we used comparative analysis to discuss and explain the features and relationship of exchange rate risk of RMB between the B&R and against main currencies, and found that in the long term, there was more devaluation risk of the currencies and regions along the B in the middle term, there was a lead-lag relationship between the two indexes, and the B&R exchange rate index is going to decline;in the short term, the exchange risk in the countries and regions along the B&R is greater than the worldwide RMB exchange rate risk. Finally, we put forward several relevant suggestions to help going-out enterprises to avoid and manage exchange rate risks effectively. © Springer Nature Singapore Pte Ltd 2020.

关键词： Roads and streets

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Multi-View Cost-Sensitive Kernel Learning for Imbalanced Classification Problem

SSRN

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SSRN 2023年

作者： Tang, Jingjing Hou, Zhaojie Yu, Xiaotong Fu, Saiji Tian, Yingjie School of Business Administration Southwestern University of Finance and Economics Chengdu611130 China Institute of Big Data Southwestern University of Finance and Economics Chengdu611130 China School of Economics and Management Beijing University of Posts and Telecommunications Beijing100876 China 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 MOE Social Science Laboratory of Digital Economic Forecasts and Policy Simulation UCAS Beijing100190 China School of Mathematical Sciences University of Chinese Academy of Sciences Beijing100049 China

Multi-view imbalanced learning concentrates on recognizing valuable patterns from multi-view imbalanced data. There exist numerous algorithm-level multi-view imbalanced learning methods including multi-view ensemble learning methods and multi-view cost-sensitive learning methods. However, these approaches have two drawbacks. Firstly, from the multi-view representation perspective, either ignore the agreement among different views, or fail to fully exploit the complementarity information contained in multi-view data. Secondly, from the class imbalanced perspective, multi-view ensemble learning first needs to design a specific data pre-processing scheme to generate views and then fuse the local and global information with multi-view ensemble schemes. So such models are closely related to practical problems and lacks universality. In contrast, multi-view cost-sensitive learning methods possess concise formulations. But the success of such methods depends on imposing appropriate misclassification cost to the majority and minority classes. Inspired by elegant merits of asymmetric LINEX loss function, we propose a multi-view costsensitive kernel learning method with LINEX loss termed as MVCSKL. It not only fully exploits the consensus and complementary information of multiple views, but also adaptively learns and adjusts the misclassification cost of different classes through the asymmetric LINEX loss function. Besides, the introduction of the kernel function enables the MVCSKL model to handle complex nonlinear problem and further guarantees the prediction performance of the model. Furthermore, we adopt the alternating direction method of multipliers and gradient descent algorithm to solve MVCSKL. Based on the Rademacher complexity, we analyze the generalization capability of MVCSKL. Extensive experiments are conducted to verify the effectiveness of the proposed model. © 2023, The Authors. All rights reserved.

关键词： Support vector machines

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Discovering the relationship between the number of film review topics and box office with NLP techniques

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Procedia Computer Science 2024年 242卷 640-646页

作者： Bo Li Wei Dai Shang Liu Yong Shi School of Finance and Economics Wuhan City Vocational College No. 10 Yezhihu West Road Hongshan District Wuhan 430064 China PKU-WUHAN Institute for Artificial Intelligence No. 770 Gaoxin Avenue Hongshan District Wuhan 430070 China School of Economics Shanghai University 99 Shangda Road BaoShan District Shanghai 200444 China School of Economics and Management University of Chinese Academy of Sciences No. 3 Zhongguancun South Yitiao Beijing 100190 China Research Center on Fictitious Economy and Data Science Chinese Academy of Sciences No. 80 Zhongguancun East Road Beijing 100190 China Key Laboratory of Big Data Mining and Knowledge Management Chinese Academy of Sciences No. 80 Zhongguancun East Road Beijing 100190 China

Numerous movie reviews on the internet can be used to analyze audience experiences of movies and provide inspiration for the operation and production of movies. In this work, we integrate and match the review data on Douban and the box office data on the website ***, and utilize the topic model in natural language processing to determine the number of each movie review topics, then establish an regression equation to analyze the relationship between the number of topics and movie box office. Our analysis shows a significant positive correlation between film box office and the number of movie review topics, and we have provided an explanation for this. Finally, we also analyzed the practical application value of this work.

关键词： Film Reviews Topic Model Sentiment Analysis Latent Dirichlet Allocation (LDA) Biterm Topic Model (BTM)

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Impact of China Railway Express on Urban Exports: Evidence from Prefectural-Level City Economic data

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Procedia Computer Science 2022年 214卷 1222-1227页

作者： Bochao Yan Xin Tian Shiyong Deng Junfeng Wu Research Center on Fictitious Economy and Data Science Chinese Academy of Sciences Beijing 100190 China School of Economics and Management University of Chinese Academy of Sciences Beijing 100190 China Key Laboratory of Big Data Mining and Knowledge Management Chinese Academy of Sciences Beijing 100190 China China Railway Fifth Survey and Design Institute Group Co. Ltd. Beijing 102600 China Shanghai WinJoin Information Technology Co. Ltd. Shanghai 200126 China

As a key project of infrastructure connectivity in the “Five-Pronged Approach” of strategic construction “The Belt and Road”, the China Railway Express, has significantly improved the level of trade level in countries along the railway. This study uses an empirical model to correlate the container export data of China Railway Express from June 2020 to June 2021 with the export value and finds that the trade volume of China Railway Express is positively correlated with the export value of cities. The relationship between the operation of the China Railway Express and the export trade of cities that enjoy the rail service is rigorously explained through the actual data of the operation of the China Railway Express provided by the enterprises. The empirical results further prove the positive impact of the China Railway Express on cities that enjoy the rail service.

关键词： The Belt Road China Railway Express Trade

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Penetration Effect of Informatization on Technological Progress in Logistics Industry: Empirical Evidence from Inter-provincial Panel data in China

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Procedia Computer Science 2022年 214卷 1249-1255页

作者： Yaling Gong Xin Tian Zuoliang Jiang Yamin Jiao School of Economics and Management Yuzhang Normal University Nanchang 330103 China School of Economics and Management University of Chinese Academy of Sciences Beijing 100190 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 Beijing 100190 China Shanghai HEADING Information Engineering Co. Ltd. Shanghai 201112 Shanghai Winjoin Information Technology Co. Ltd. Shanghai 200126

This paper investigates pervasiveness effect of information technology on the technological progress of logistics in China. Using panel data of 30-regions in China during 2008 to 2020, we propose both static and dynamic panel data models, and find both resource level and spreading rate of information technology have negative influences on technological progress of logistics. The resource level of information technology has a short-term effect on technological progress of logistics, whereas the spreading rate of information technology has a long-term effect. Moreover, the result reveals that the discordant problem of information construction of logistics between resource level and spreading rate cause the negative influence of information technology.

关键词： Pervasiveness effect Information technology Technological progress Logistics industry

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Pyramid scheme model for consumption rebate frauds

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Chinese Physics B 2019年第7期28卷 549-556页

作者： Yong Shi Bo Li Wen Long School of Economics and Management University of Chinese Academy of Sciences Beijing 100190 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 Beijing 100190 China

There are various types of pyramid schemes that have inflicted or are inflicting losses on many people in the *** propose a pyramid scheme model which has the principal characters of many pyramid schemes that have appeared in recent years: promising high returns, rewarding the participants for recruiting the next generation of participants, and the organizer takes all of the money away when they find that the money from the new participants is not enough to pay the previous participants interest and *** assume that the pyramid scheme is carried out in the tree network, Erd?s–Réney(ER) random network, Strogatz–Watts(SW) small-world network, or Barabasi–Albert(BA) scale-free *** then give the analytical results of the generations that the pyramid scheme can last in these *** also use our model to analyze a pyramid scheme in the real world and we find that the connections between participants in the pyramid scheme may constitute a SW small-world network.

关键词： pyramid scheme complex networks small-world networks

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Price change prediction of ultra high frequency financial data based on temporal convolutional network

arXiv

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arXiv 2021年

作者： Dai, Wei An, Yuan Long, Wen 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

Through in-depth analysis of ultra high frequency (UHF) stock price change data, more reasonable discrete dynamic distribution models are constructed in this paper. Firstly, we classify the price changes into several categories. Then, temporal convolutional network (TCN) is utilized to predict the conditional probability for each category. Furthermore, attention mechanism is added into the TCN architecture to model the time-varying distribution for stock price change data. Empirical research on constituent stocks of Chinese Shenzhen Stock Exchange 100 Index (SZSE 100) found that the TCN framework model and the TCN (attention) framework have a better overall performance than GARCH family models and the long short-term memory (LSTM) framework model for the description of the dynamic process of the UHF stock price change sequence. In addition, the scale of the dataset reached nearly 10 million, to the best of our knowledge, there has been no previous attempt to apply TCN to such a large-scale UHF transaction price dataset in Chinese stock market. Copyright © 2021, The Authors. All rights reserved.

关键词： Long short-term memory

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