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.

A new corner reflector antenna with periodic strip subreflectors

This paper presents the design of a new type of corner reflector (CR) antenna and the experimental investigation of its radiation characteristics. The design involves the addition of planar parallel periodic strips to the two sides of a CR antenna. The position, angular orientation, and number of strips have a notable effect on the H-plane radiation characteristics of the antenna. Certain configurations of the new antenna are capable of producing very sharp axial beams with gain on the order of 5 dB over the square corner reflector antenna. A configuration that can provide symmetric twin beams with enhanced gain and reduced half-power beam width (HPBW) is also presented.