This paper investigates the use of strategies to enhance an existing machine learning tool, C4.5, to deal with concept drift and non-determinism in a time series domain. Temporal prediction is a difficult problem faced in most human endeavours. While many specialised time series prediction techniques have been developed, these techniques have limitations. Most are restricted to modeling whole s...

Artificial Intelligence models (AI) which computerize human reasoning has found a challenging test bed for various paradigms in many areas including financial time series prediction. Extensive researches have resulted in numerous financial applications using AI models. Since stock investment is a major investment activity, Lack of accurate information and comprehensive knowledge would result in...

Support vector regression (SVR) has long been proven to be a successful tool to predict financial time series. The core idea of this study is to outline an automated framework for achieving a faster and easier parameter selection process, and at the same time, generating useful prediction uncertainty estimates in order to effectively tackle flexible real-world financial time series prediction p...

Bankruptcy has long been an important topic in finance and accounting research. Recent headline bankruptcies have included Enron, Fannie Mae, Freddie Mac, Washington Mutual, Merrill Lynch, and Lehman Brothers. These bankruptcies and their financial fallout have become a serious public concern due to huge influence these companies play in the real economy. Many researchers began investigating ba...

Financial market dynamics forecasting has long been a focus of economic research. A stochastic time effective function neural network (STNN) with principal component analysis (PCA) developed for financial time series prediction is presented in the present work. In the training modeling, we first use the approach of PCA to extract the principal components from the input data, then integrate the ...

The purpose of this paper is to analyze financial ratios of Australian Mining companies in order to specify and quantify the variables which are effective indicators and predictors of corporate distress. Using financial ratios, the paper explores the quantifiable characteristics of potential bankrupts using cutting edge Recursive Partitioning techniques like Discriminant Analysis, Decision Tree...

There has been an increasing attention on the influences online financial information has on the financial markets. In the meanwhile, the volatility of trading volumes, just as the volatility of stock returns, has an inseparable association with financial risks. It has been considered that there might exist some direct or indirect correlations between online financial information volumes and fi...

This study validates some aspects of agency theory, resource dependency and organization theory referring to the Sri Lankan context. The sample includes 205 non-financial listed firms prepared in a balanced panel for six years. Implications are provided insufficiency financial variables predicting corporate distress. Financial together with governance jointly enhance predictive power Less likelih...