Seismogenesis of aftershocks occurring in the Kachchh seismic zone for more than last 10 years is investigated through modeling of fractal dimensions, b-value, seismic velocities, stress inversion, and Coulomb failure stresses, using aftershock data of the 2001 Bhuj earthquake....

Forecasting exchange rate movements is challenging, as they exhibit high volatility, complexity and noise. Most traditional models cannot forecast exchange rates, with significantly higher accuracy, than a random walk model. In this study, a non-linear model called artificial neural network...

This study examines the dynamic causal (linear as well as non-linear) relationship between trading volume and return and between volatility and returns. We have used the vector autoregression based Granger causality framework to examine the linear causality, while the non-linear causality have...

The purpose of this paper is to develop and identify the best hybrid model to predict stock index returns. We develop three different hybrid models combining linear ARIMA and non-linear models such as support vector machines (SVM), artificial neural network (ANN) and random forest (RF) models to...

A practical, DEM-based practical method is proposed to enhance flood risk management in fluvial areas by quantifying relative risk as a function of vulnerability to inland and evacuation difficulty. Both measures are based mainly on the topography of the region, so the method does not require...

This study attempts to forecast the next day’s returns of two time series in the Hang Seng Index (HSI) and Standard & Poor’s (S&P) 500 indices using Artificial Neural Networks (ANN) with past returns as input variables. Results from ANN are compared with those from the...

Biobutanol can become the replacement of petroleum gasoline in near future. However, economic feasibility of biobutanol production from ABE fermentation is suffering due to the unavailability of cheap feedstocks, production inhibition and inefficient product recovery processes. Here, economic...

High temporal and spatial variability of rainfall qualifies India to be highly vulnerable to floods. Recurring floods of various magnitudes play havoc with the lives and property of the people, leading to unplanned development and unchecked environmental degradation, thwarting and retarding the...

This study examines the nature of interdependence, and return and volatility spillovers, for three Indian exchange rates: US dollar (USD), Euro and British Pound. We use the spillover index methodology of Diebold and Yilmaz (2009) to analyse precisely and independently the returns and volatility...

The purpose of the study is to examine whether the returns and volatility for Indian exchange rates possess non-linear dependence. Furthermore, an attempt is made through a rolling-window approach to check whether non-linear dependence is time-varying. The study employs approximate entropy...