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This paper proposes a stock market prediction method exploiting sentiment analysis using financial microblogs (Sina Weibo). We analyze the microblog texts to find the financial sentiments, then combine the sentiments and the historical data of the Shanghai Composite Index (SH000001) to predict the stock market movements. Our framework includes three modules: Microblog Filter (MF), Sentiment Analysis...
This paper provides further evidence on the predictive power of online community traffic with regard to stock prices. Using the largest dataset to date, spanning 8 years and almost the complete set of SP500 stocks, we train a classifier using a set of features entirely extracted from web-traffic data of financial online communities. The classifier is shown to outperform the predictive power of a baseline...
As the rapid development of Internet technology, the influence to the financial fields of the financial information on the Web has become increasingly can not be ignored. Facing mass unstructured Web text about financial information, the paper present a method to calculate the tendency of text, and analysis the relationship between the emotional tendencies of Web financial information and the financial...
Most scholars applied dichotomy to the company financial distress research, which classifies listed companies into two categories. We apply trisection method, which classifies listed companies into three categories: financial distress companies, financial unstable companies and financial healthy companies, and apply principal component analysis method and ternary Logistic model to construct a financial...
PSO is an overall stochastic optimization algorithm based on the selection of the feature set and optimization of kernel function parameters, which has great impact on the forecasting performance of support vector machines (SVM) model. This paper presents the combining model (PSO-SVM) of the particle swarm optimization and support vector machine. This model uses the PSO to conduct the optimization...
In this paper, on the basis of previous studies derived the local government debt risk assessment model, established risk prediction methods by using BP artificial neural network model, and analyzed this method through an example. So provide a set of scientific method to evaluate the local government debt risk and predict the short-term risk. This is useful for adoption effective means to control...
This paper mainly discusses the study of models for financial distress pre-warning, trying to select general financial indexes by principal component analysis, and meanwhile adding nonfinancial indexes which reflect corporate governance state to complement. Logit Model which is more accurate in prediction is selected, with the 56 company samples including both delisting pre-warned companies and counterparts...
Since the cash flow information can be applied well in the evaluation of enterprise's financial situation, In this paper, the cash profit, which is the information connotation of cash flow, is a basis of financial evaluation index system and main criteria to define the distress companies. Two early warning models based on cash profit and traditional accounting profit separately are set up by logical...
Coal is one of the most important main energy-consuming resources in our society. It is important to forecast the coal requirement with high accuracy. BP neural network forecasting model has the typical of self-learning and self-adaptation. It is often used in these systems that are difficult to create accurate mathematical model. The factors such as the trend of the industrial coal, the rate of increased...
This paper designs a set of enterprise credit rating index system,in addition to traditional financial ratios, it joined the non-financial factors. then used the logical regression approach to create company's credit rating model, the result shows that the overall discrimination rate reached 95%, the models predict results accurately.
The tolerance and non-stability in financial indexes make changes to other sub-systems like human resources, economics, factory productions and etc. Having underling knowledge and a model to simulate such systems obtains a fine vision to estimate further and calculate hard-decision making tasks before execution like: dept from banks, cash injecting and insurance services. Using Neuro-fuzzy networks...
This paper used mixed logit model to predict credit risk of listed companies in China. In order to reduce the difficulty in dealing with the facts of correlation and multidimension of the financial indexes of listed companies and meanwhile to ensure that the data are not lost, we introduced factor analysis to the mixed logit equation and constructed a factor analysis mixed logit model. Fifteen factors...
A ldquotypical ST public corporationrdquo was constructed by us according to its stylebook based on the assumption of the bankruptcy tendency of any corporations, then a Grey Financial Alert Model Of the Public Corporations Based on Degree of Grey Incidence was further presented, and its grade can estimate the current financial risk of a public corporation and an example is employed to illustrate...
We present a generic method for analyzing the effect of process variability in nanoscale circuits. The proposed framework uses kernel and a generic tail probability estimator to eliminate the need for a-priori density choice for the nature of circuit variation. This allows capturing the true nature of the circuit variation from a few random samples of its observed responses. The data-driven, non-parametric,...
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