检索结果-南通市图书馆

第36届中国控制会议

作者： Bing Yang Zi-Jia Gong Wenqi Yang School of Mathematics and Statistics Shandong University School of Mathematics Shandong University

ISBN: (纸本)9781538629185

In this paper,we put forward deep neural network ensemble to model and predict Chinese stock market index（including Shanghai composite index and SZSE component index）,based on the input indices of recent days.A set of component networks are trained by historical data for this task,where Backpropagation and Adam algorithm are used to train each network *** approach combines these component networks to generate ensemble,which reduces the generalization *** of test examples are predicted with the model,and the trend predictions is calculated based on the predicted ***,relative errors between actual indices and predicted indices,as well as accuracy of trend predictions are computed to measure the performance of *** turns out that the model proposed in this paper can partially model and predict the Chinese stock *** accuracy of trend predictions of the daily barycenter,high,low are 71.34%,74.15%,74.15%respectively for Shanghai composite index and 75.95%,73.95%,72.34%respectively for SZSE component *** the predictions on close are unsatisfactory.

关键词： neural network machine learning ensemble learning stock index time series forecasting

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Design and Implementation of On-Line Hot Topic Discovery Model

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Wuhan University Journal of Natural Sciences 2006年第1期11卷 21-26页

作者： YE Hui-min CHENG Wei DAI Guan-zhong School of Automatic Control Northwestern Polyteehnieal University Xi＇an 710072 Shaanxi China Institute of Artificial Intelligence Beijing City University Beijing 100083 China

Internet has become a major medium for infomation transmission, how to detect hot topic on web, track the event development and forecast emergency is important to many fields, particularly to some government departments. On the basis of the researches in the field of topic detection and tracking, we propose a model for hot topic discovery that will pick out hot topics by automatically detecting, clustering and weighting topics on the websites within a time period. Based on the idea of stock index, we also introduce a topic index approach in following the growth of topics, which is useful to analyze and forecast the development of topics on web.

关键词： topic tracking stock index hot topic topic weight

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Realized volatility forecast of financial futures using timevarying HAR latent factor models

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Journal of Management Science and Engineering 2023年第2期8卷 214-243页

作者： Jiawen Luo Zhenbiao Chen Shengquan Wang School of Business Administration South China University of TechnologyGuangzhou510641China Institute of Advanced Studies in Humanities and Social Sciences Bejing Normal UniverstyZhuhai59087China

We forecast realized volatilities by developing a time-varying heterogeneous autoregressive(HAR)latent factor model with dynamic model average(DMA)and dynamic model selection(DMS)*** number of latent factors is determined using Chan and Grant's(2016)deviation information *** predictors in our model include lagged daily,weekly,and monthly volatility variables,the corresponding volatility factors,and a speculation *** addition,the time-varying properties of the best-performing DMA(DMS)-HAR-2FX models,including size,inclusion probabilities,and coefficients,are *** find that the proposed DMA(DMS)-HAR-2FX model outperforms the competing models for both in-sample and out-of-sample ***,the speculation variable displays strong predictability for forecasting the realized volatility of financial futures in China.

关键词： Realized volatility forecast HAR latent factor models Bayesian approaches Time-varying stock index Treasury bond futures

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Non-classical Algorithm for Time Series Prediction of the Range of Economic Phenomena With Regard to the Interaction of Financial Market Indicators

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Chinese Business Review 2014年第4期13卷 221-231页

作者： Monika Hadas-Dyduch University of Economics in Katowice Katowice Poland

The aim of the article is to present non-clasical copyrighted algorithm for prediction of time series, presenting macroeconomic indicators and stock market indices. The algorithm is based on artificial neural networks and multi-resolution analysis （the algorithm is based on Daubechies wavelet）. However, the main feature of the algorithm, which gives a good quality of the forecasts, is all included in the series analysis division into, a few partial under-series and prediction dependence on a number of other economic series. The algorithm used for the prediction, is copyrighted algorithm, labeled M.H-D in this article. Application of the algorithm was performed on a series presenting WIG 20. The forecast of WIG 20 was conditional on trading the Dow Jones, DAX, Nikkei, Hang Seng, taking into account the sliding time window. As an example application of copyrighted model, the forecast of WIG 20 for a period of two years, one year, six month was appointed. An empirical example is described. It shows that the proposed model can predict index with the scale of two years, one year, a half year and other intervals. Precision of prediction is satisfactory. An average absolute percentage error of each forecast was： 0.0099%---for two-year forecasts WIG 20; 0.0552%--for the annual forecast WIG 20; and 0.1788%---for the six-month forecasts WIG 20.

关键词： macroeconomic indicators stock index forecasting wavelet neural network wavelet transform Daubechies wavelet

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The Different Performance of the stock Market indexes of the Three Countries in Different International Events

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Psychology Research 2023年第7期13卷 302-311页

作者： Ziying Chen University of Glasgow GlasgowUnited Kingdom

During the period of different changes in the global situation,the stock indexes of China,the United States,and the United Kingdom all showed different ***,during the outbreak of the epidemic,they all received a huge impact,and due to the different policies and coping strategies of various countries,the follow-up performance also varies *** has only had a slight impact on the British domestic market in a short period time,and China and the United States have prepared for investment in the new market after Brexit,which has also caused the corresponding market index to perform better before the *** to the differences in the main market targets and the differences in the geographical location of countries,the negative impact on the British market was more obvious during the Russia-Ukraine conflict,while the stock indexes of China and the United States were relatively stable and even showed an upward *** can be seen from the data analysis that the markets in different countries are affected by time *** the growing correlation between the markets of various countries,investors should pay more attention to the global situation and the policy orientation of different *** risk diversification while taking policy dividends helps to obtain stable returns.

关键词： COVID-19 Brexit stock index global economic Russian-Ukraine conflict

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政治运动中情感、民意与股市的相关性研究

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新闻春秋 2015年第4期

作者：张翔

互联网的普及和技术的革新在改变人类生活方式的同时也重塑着传播生态。近年来以社交媒体为代表的互联网产品成为行业发展的热点。网络数字媒体（Networked Digital Media）正在改变着传统大众媒体的信息传播方式。在互联网开放式的架... 详细信息

互联网的普及和技术的革新在改变人类生活方式的同时也重塑着传播生态。近年来以社交媒体为代表的互联网产品成为行业发展的热点。网络数字媒体（Networked Digital Media）正在改变着传统大众媒体的信息传播方式。在互联网开放式的架构下，社交媒体（Social Media）的迅速兴起并卷入越来越多受众，通过网络上用户自产内容（User—generated Content）进行数据挖掘成为学界研究者特别是传播学研究者的研究新路径，对互联网文本进行的情感分析（Sentiment Analysis）也应运而生。尽管社交媒体上的数据挖掘变得越来越可行与可操作，但对这些目前数据的分析利用还停留在初级阶段，其分析结果也存在较高的不确定性，例如，社交媒体促进了公共表达的平权并卷入了巨大数量的参与者，但关于社交媒体上的用户行为和意见表达是否可以作为评估线下世界的民意与政治态度的问题，先前的研究却显示出完全不同的结果。其中一部分研究针对某一特定的政治事件或政治议题，通过比较社交媒体信息流（例如：推特流）的数量与现实民意指标（民意测验、媒体报道和股市指标等）进行比较，结果显示出社交媒体上的民意和实际民意指标呈现出正相关的关系。但同时也有其他的类似研究的结果社交媒体上的民意与实际民意指标并没有显现出关联性。在本研究中，发生在中国香港的“占领中环”运动（Occupy Central Movement）作为显著的政治事件，用户在推特平台上的表达被作为研究的对象。与先前研究的不同之处在于，本研究中，在与实际民意指标对比之前，会对收集到的关于香港“占领中环”运动的推特流（Tweet Stream）进行情感分析处理以获得更为精确的积极或消极的推特使用者情绪。经过分析得到的积极和消极情绪将会被换算成情感指标，与现实的民意指标——民意测验结果和股市指数进行比较，试图在前人研究的基础上加入情感分析的研究路径，探究关于特定公众政治议题上，社交网络（推特）上的情感反应和现实民意之间是否存在相关性，为政治传播研究以及政府机构对公众民意的把握提供新的参照。

关键词：社交媒体民意政治传播情感分析股市指数 Social media public opinion political communication sentiment analysis stock index

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