Computationally Efficient Bootstrap Prediction Intervals for Returns and Volatilities in ARCH and GARCH Processes

We propose a novel, simple, efficient and distribution-free re-sampling technique for developing prediction intervals for returns and volatilities following ARCH/GARCH models. In particular, our key idea is to employ a Box–Jenkins linear representation of an ARCH/GARCH equation and then to adapt a sieve bootstrap procedure to the nonlinear GARCH framework. Our simulation studies indicate that the new re-sampling method provides sharp and well calibrated prediction intervals for both returns and volatilities while reducing computational costs by up to 100 times, compared to other available re-sampling techniques for ARCH/GARCH models. The proposed procedure is illustrated by an application to Yen/U.S. dollar daily exchange rate data.

Export, Import and Inter—State Sales - A Study in Tax Law

This thesis is a study in sales tax law, a study on the triple concept of export, import and inters—State sales. It is in seventeen chapters spread in five parts. The introductory is an overview. It presents the thematic thrust of what follows. Part two deals with incidence of sales tax on export and import and the scope of exemption. Part three focuses attention on the various dimensions of the problem of inter—State sale. Part four is an inquiry into parliamentary control on taxes over sales and purchases and highlights inter—State and intra-State implications of discriminatory tax. Part five contains the results of empirical study and the general conclusions of the thesis. In the past no attempt has been made to analyse on identical lines the problems dealt with in this thesis