Companies have obligation to create real economic value for their shareholders. Managers and top executives have been under constant pressures to adopt “value-based management” from their shareholders and other market participants. Participants in financial markets are actively involved in individual companies’ operations through leveraged buyouts, hostile take-over, and proxy contests, and top...

This research project investigates the ability of neural networks, specifically, the backpropagation algorithm, to integrate fundamental and technical analysis for financial performance prediction. The predictor attributes include 16 financial statement variables and 11 macroeconomic variables. The rate of return on common shareholders’ equity is used as the to-be-predicted variable. Financial ...

This paper investigates the predictive ability of financial variables for real growth in the euro area through bivariate and multivariate non-parametric Granger causality tests. Apart from assessing the within-country forecasting ability of commonly-employed financial variables, such as the term spread, the stock market returns and the growth of real money supply, we also test for cross-country...

Time series modeling and analysis is central to most financial and econometric data modeling. With increased globalization in trade, commerce and finance, national variables like gross domestic productivity (GDP) and unemployment rate, market variables like indices and stock prices and global variables like commodity prices are more tightly coupled than ever before. This translates to the use o...

The present study aims at developing an aggregate financial stability index by using banking sector indices to assess financial stability and examine if the variable of credit-to-GDP gap corresponds to its long-term trend which represents the macro-prudential indicator has co-movement with the built financial stability index? To this end, monthly banking balance sheet data were collected from t...

As financial time series are inherently noisy and non-stationary, it is regarded as one of the most challenging applications of time series forecasting. Due to the advantages of generalization capability in obtaining a unique solution, support vector regression (SVR) has also been successfully applied in financial time series forecasting. In the modeling of financial time series using SVR, one ...

The purpose of this research is to provide a model for reporting quality of financial information based on behavioral and value accounting of listed companies in Tehran Stock Exchange which is based on Structural Equation Modeling. This research in terms of applied purpose is applied research and in terms of data collection method is post-semi experimental research in the field of proofing acco...

The paper investigates the empirical significance of revenue management in determining firm-level fixed capital investment when investment opportunities are controlled for by two of the recently-introduced empirical fundamentals: profitability shocks and the gap measure between the desired and actual capital stocks (mandated investment rate). Tobin's q is also included in the analyses for the p...