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On account of great significance of financial distress prediction for corporations, it is essential to construct an effective prediction model for managers and investors. Traditional financial distress prediction methods design static models using samples within a period of time, but the static models are insensitive to changes, such as concept drift in financial distress. This paper proposed a dynamic...
This paper investigates the modeling of risk due to market and funding liquidity by capturing the joint dynamics of three time series: the treasury-Eurodollar spread, the VIX, and a metric derived from the S&P 500 spread. We propose a two-regime mean-reverting model for explaining the behaviour of three time series, which mirror liquidity levels for financial markets. An expectation-maximisation...
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 the global optimization of genetic algorithm to construct a genetic neural network model (GANN) forecasting listed company financial crisis. The model optimizes input variables of neural network model forecasting financial crisis. Forecasting of financial distress of listed companies in Shanghai and Shenzhen A share markets indicates that this model bears a better ability to predict...
According to the traditional idea of Z-Score model and characteristics of Chinese real estate industry, this paper will reconstruct the new Z-Score model for the Chinese real estate enterprise financial prediction by re-observing the sensitive financial indicators. The new model realizes “two-years-ahead” risk prediction to timely avoid financial crisis and difficulties caused to Chinese real estate...
Based on financial information of listed manufacturing companies, the research aims at predicting financial distress using the integrated model of factor analysis and discriminant analysis to establish the model, and tests the prediction accuracy of the model. The results show that the model in this paper has higher discriminant precision, and it makes further explanation that the choice of financial...
This paper does the empirical research on the relevance of ownership structure and financial distress in listed companies based on the data of ST corporations because of abnormal financial positions in year 2005–2009 and the paired corporations. The ownership structure is described by the nature of controlling shareholder, ownership centralization, ownership balancing and managements' holding percentage...
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...
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...
Cash flow can be used to evaluate the financial situation of the company during its business period, while this important item is always neglected in the real life. Consequently, financial distress appears as the cash flow situation does not work well. In this article, I try to present several cash flow indicators which can prevent the company from being caught by financial distress if a good precautionary...
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 mainly discusses the financial data of listed 71 medicine companies in order to establish a more accurate financial pre-warning model with the analysis of BP (Back Propagation)-neural network, by choosing 38 comprehensive indexes which reflect the financial distress, basing on the study of comparison of financial pre-warning models. The result shows that BP-neural network model is of high...
Using the samples of ST companies listed in Shanghai and Shenzhen Stock Exchange from the year 2002 to 2007, this paper empirically studies the influences of the companies' political connection on how the companies falling into financial distress gains the government subsidies. The conclusions are as follows: when private companies fall into financial distress, its political connection has significant...
Western finance theory indicates that hedging increases firm value by reducing expected taxes, expected costs of financial distress, or other agency costs. This paper examines the use of financial derivatives for the purpose of risk management in a sample of 1151 China non-financial firms and its potential impacts on firm value and accounting performance. We find a positive relation between firm accounting...
Based on a lot of related literatures, the authors suggest a Financial Distress Prediction System incorporated the Expected Default Frequency (EDF) into Logit regression model. The empirical findings suggest that the EDF calculated by KMV model is significantly associated with the probability of default in both 3rd and 4th quarters prior to the financial crisis of sample firms. Thus, an incorporation...
Financial decisions are difficult because of complex unpredictable factors but play critical role in financial activities. In this paper, we investigate the decision making problems and applied methods by considering different categories of financial ratios as input to the CGA-LSSVM model, which with we present a framework for the financial decision support system.
To eliminate limitations of traditional early-warning of financial distress methods, an artificial immune algorithm based early-warning of financial distress is presented. To begin with, both antigens and memory antibodies with class information added to artificial immune network are trained to learn the feature of training samples. In this way, memory antibody cells pool can represent these samples...
Lately, many notorious financial distress and bankruptcy events occurred in the world economic. As we known, bankruptcy of Lehman Brothers Holdings Inc. (LEH) is the largest bankruptcy filing in U.S. history in 2008. These events have serious impacted on the socio-economic and investment in public wealth. Due to solve this dilemma, this research collected 68 listed companies as the raw data from Taiwan...
This paper studies debt holders' belief updating and equity owners' financing decisions under asymmetric information during financial distress. This is done within a continuous-time framework, where the relevant state variable is assumed to follow an arithmetic Brownian motion (ABM). ABM can take negative values and has very realistic feature compared with geometric Brownian motion (GBM). Using Chapter...
In the predicting financial distress, we know that irrelevant or correlated features in the samples could spoil the performance of the SVR classifier, leading to decrease of prediction accuracy. In order to solve the problems mentioned above, this paper use rough sets as a preprocessor of SVR to select a subset of input variables and employ the particle swarm optimization algorithm (PSOA) to optimize...
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