This book includes selected papers submitted to the ICADABAI-2017 conference, offering an overview of the new methodologies and presenting innovative applications that are of interest to both academicians and practitioners working in the area of analytics. It discusses predictive analytics...

This article examines, what makes rural household a preferred choice for formal lenders? It develops sample selected ordered probit model to address this question. While, the selection equation models the determinants of access to credit, an ordered probit model is used to determine the factors...

Artificial Neural Network (ANN) has been shown to be an efficient tool for non-parametric modelling of data in a variety of different contexts where the output is a non-linear function of the inputs. These include business forecasting, credit scoring, bond rating, business failure prediction,...

In this article we propose two new methods of portfolio allocation which are applicable for all return distributions. The properties of these new methods are compared with that of Markowitz's mean-variance method using extensive simulation. It is found that the new methods perform appreciably in...

I consider the problem of detecting and predicting regime switching behaviour in the context of Indian Stock Market data. First I discuss detection of volatility change points using the LRT and the Binary Segmentation procedure of Vostrikova (1981). The detected volatility changes are correlated...

Demand forecasting methods usually adopt the approach of minimizing certain forms of error or maximizing a likelihood function. However, for an end user, such objective functions are often the means to achieve optimum results over various key performance indicators in respective domains. A...