An Environment for Rapid Derivatives Design and Experimentation

In the highly competitive world of modern finance, new derivatives are continually required to take advantage of changes in financial markets, and to hedge businesses against new risks. The research described in this paper aims to accelerate the development and pricing of new derivatives in two different ways. Firstly, new derivatives can be specified mathematically within a general framework, enabling new mathematical formulae to be specified rather than just new parameter settings. This Generic Pricing Engine (GPE) is expressively powerful enough to specify a wide range of stand¬ard pricing engines. Secondly, the associated price simulation using the Monte Carlo method is accelerated using GPU or multicore hardware. The parallel implementation (in OpenCL) is automatically derived from the mathematical description of the derivative. As a test, for a Basket Option Pricing Engine (BOPE) generated using the GPE, on the largest problem size, an NVidia GPU runs the generated pricing engine at 45 times the speed of a sequential, specific hand-coded implementation of the same BOPE. Thus a user can more rapidly devise, simulate and experiment with new derivatives without actual programming.

Secure Full-Duplex Small-Cell Networks in a Spectrum Sharing Environment

In this paper, we propose three relay selection schemes for full-duplex heterogeneous networks in the presence of multiple cognitive radio eavesdroppers. In this setup, the cognitive small-cell nodes (secondary network) can share the spectrum licensed to the macro-cell system (primary network) on the condition that the quality-of-service of the primary network is always satisfied subjected to its outage probability constraint. The messages are delivered from one small-cell base station to the destination with the help of full-duplex small-cell base stations, which act as relay nodes. Based on the availability of the network’s channel state information at the secondary information source, three different selection criteria for full-duplex relays, namely: 1) partial relay selection; 2) optimal relay selection; and 3) minimal self-interference relay selection, are proposed. We derive the exact closed-form and asymptotic expressions of the secrecy outage probability for the three criteria under the attack of non-colluding/colluding eavesdroppers. We demonstrate that the optimal relay selection scheme outperforms the partial relay selection and minimal self-interference relay selection schemes at the expense of acquiring full channel state information knowledge. In addition, increasing the number of the full-duplex small-cell base stations can improve the security performance. At the illegitimate side, deploying colluding eavesdroppers and increasing the number of eavesdroppers put the confidential information at a greater risk. Besides, the transmit power and the desire outage probability of the primary network have great influences on the secrecy outage probability of the secondary network.