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This paper presents a machine learning method for event-driven stock prediction, using L1 regularized Logistic regression model. It studies the stock price movement after listed companies make announcements. The model uses specific events extracted from these announcements and combine with financial indicators of listed companies, macro indicators, and technical indicators as dependent variables....
One of the biggest challenges that higher learning institutions face today is to improve the placement performance of students. The placement prediction is more complex when the complexity of educational entities increase. Educational institutes look for more efficient technology that assist better management and support decision making procedures or assist them to set new strategies. One of the effective...
Client churn prediction model is widely acknowledged as an effective way of realizing customer life-time value especially in service-oriented industries and under a competitive business environment. Churn model allows targeting of clients for retention campaigns and is a critical component of customer relationship management(CRM) and business intelligence systems. There are numerous statistical models...
The Direct Selling Industry in the Philippines is continuously growing as more people become direct sellers. With this, the ability of direct selling companies to manage its sellers will be a challenge. Customer Lifetime Value (CLV), or the monetary value a customer is expected to contribute to the company before churning, is one measure that can be used as a basis for managing customers and for this...
We propose a novel approach for predicting Web user click intention, using pupil dilation data generated by an eye-tracking device as input. Our goal is to determine if this variable is useful to differentiate choice and no-choice states, and if so, to generate a classification model for predicting choice understood as a click. For this, we performed an experiment with 25 healthy subjects in which...
Small and medium-sized enterprises play a very important role in China's economic and social development. Their development is inseparable from the financial support, and the development of credit business is also an important aspect of bank's operation. At the time of solving the problem of financing difficulties of small and medium-sized enterprises, how to manage credit risk will become an important...
Long-term investors are interested in identifying the characteristics of companies that are likely to triple in value over the next five years, which equates to return of approximately 25 percent per year over the period. Such companies are known as compounders due to their high compounded rate of return. This paper reports on an analysis of corporate and market data undertaken with the goal of identifying...
Financial services companies are concerned with identifying when customers have moved because of customer service and marketing concerns. Knowing when customers have moved can create opportunities for these companies to better market their financial products and provide improved customer service. This paper focuses on identifying features of customers who have moved for the purpose of predicting customer...
During the last decades and recession of 2007–2009 witnessed many global financial crises. Consequently, this research represents a proactive study via introducing new modeling tool; in order to diagnose the financial distress and assess its probability of occurrence. The Neuro-Logit is a new approach for diagnosis, prediction and forecasting corporate financial distress. This tool acts as Logit (Logistic...
In this paper, we propose a method that extracts information from sequences of financial ratios and investigate the usefulness of this information for bankruptcy prediction, which constitutes an important class of financial services. We use the annual financial reports available from an external financial information services provider to extract predictors based on the Markov for Discrimination (MFD)...
The subjects of the study are listed petrochemical companies in China. We regard ST as a symbol of financial crisis for an enterprise. T-test and relevant linear test are applied to determine the model variables and Logistic regression to build the forecasting model of financial crisis, then the data of ST enterprise samples and non-ST enterprise samples are used for analysis. With the forecasting...
The purpose of this paper is to propose and validate the combined model for bankruptcy prediction for the Malaysian firms. This combined model is adopted from previous studies by combining Ohlson logit model, Springate-Canadian model and macroeconomic factors. The proposed combined model is developed by using the financial and macroeconomic constructs. The result indicates that logistic regression...
This paper uses listed companies as research object, selects 102 2006–2008 ST companies and 102 paired normal companies as an analysis sample, the other 40 selected in 2009 as a test sample. Logistic Regression is used to constructed Early warning model, the results show that: The model that contains the three indicators — a return on assets, asset-liability ratio and total asset turnover is able...
This paper samples 30 listed companies which were the first time to ST (special treatment) because of abnormal financial situation after the announcement of 2008 Annual Report. The paper sets out from the perspective of financial indicators, introduces a new indicator of "total stock market value / total liabilities", and establishes the financial distress alert model with the use of Binary...
This paper uses the existing model to forecast the audit opinion in 2009 and makes the comparison between the predictions and the actual audit opinion based on the data of Chinese listed companies on GEM board in 2009. The results show that the predictions match the actual audit opinion. It means Chinese listed companies on GEM board maintain a good auditing quality. Moreover, the financial report...
Based on the forefathers' research, this paper made an empirical study on reason of financial distress. We chose the panel data of new ST companies between 2004 and 2006 and used the method of Logistic regression to find the result. The empirical results indicated that not all the countermeasures we chosen are effective. At last, we got our conclusion that the indicators of current ratio, cash flow...
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...
This paper takes the listed SME of which total stock issue is less than four hundred million in Shanghai and Shenzhen main board stock market of manufacturing industry as research object, selects 40 Special Treatment (ST) Enterprises and 40 Non- Special Treatment (Non- ST) Enterprises as samples, screens out the variable which has marked influence on financial crisis by T Test and factor analysis,...
This paper uses Lib-SVM algorithm of RBF kernel and linear kernel to develop a model for detecting regulating-profits financial statement fraud with the data of 112 Chinese listed companies. It turns out that the prediction accuracy of Lib-SVM algorithm for RBF kernel function model is 86.667%, the overall accuracy is 87.5%. And the prediction accuracy of the Lib-SVM linear kernel function model is...
In order to study the early warning of companies' financial risk, this paper used two models based on factor analysis, which are logistic regression and BP neural network. Finally, for the warming accuracy, BP neural network model is better than logistic regression model.
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