A Radial Basis Function Approach to Earnings Forecast

Abstract

SUMMARY The fundamental management problem of decision making in a climate where future values of important variables are unknown and can at best be estimated using traditional statistical techniques is addressed. The incorporation of forecast models into management decision‐support systems is critical for the overall success of organizational accounting information systems, where managers require confidence in the information that they use. The neural network paradigm has been described as a promising nonparametric approach, negating the required, and sometimes restrictive, statistical assumptions. The application of the neural network paradigm to the area of earnings forecasting is presented. A radial basis function (RBF) approach is developed and tested empirically using data from the Hong Kong Hang Seng 100 Index and macroeconomic data, mimicking an actual business valuation/forecast exercise. Results show that the RBF approach is superior to regression and financial analysts in earnings forecast. Copyright © 2012 John Wiley & Sons, Ltd.

A predictive system integrating intrinsic mode functions, artificial neural networks, and genetic algorithms for forecasting S&P500 intra‐day data

“…To better and properly forecast financial time series while adequately dealing with their respective nonlinear, nonstationary and noisy aspects, other workers used advanced and sophisticated intelligent systems such as gene expression programming (Karathanasopoulos, 2017), case‐based reasoning systems (Li et al ., 2013), ensemble and fusion intelligent systems (Albanis and Batchelor, 2007; Lahmiri, 2014a, 2018a; Sun, 2012), artificial neural networks (Aragonés et al ., 2007; Biscontri, 2012; Dunis et al ., 2013; Fadlalla and Amani, 2014; Haefke and Helmenstein, 2002; Vojinovic et al ., 2001), hybrid neuro‐fuzzy systems (Schott and Kalita, 2011; Trinkle, 2005), hybrid systems based on artificial neural networks and econometric models (Parot et al ., 2019), and deep learning (Galeshchuk and Mukherjee, 2017; Lahmiri and Bekiros, 2019).…”

Outsourcing and Market Value of the Firm: Toward a Comprehensive Model

“…The former are often customized to the needs of the buyer or focal firm, while the latter are more generic, involving standardized business process solutions that are used to drive down cost. Finally, the paper adds to the literature in AIS that has applied novel quantitative methods to financial research (Biscontri, 2012;Miller, 2012).The remainder of the paper is organized as follows. In Section 2 we review the literature on outsourcing and event studies.…”