Default risk in an interconnected banking system with endogeneous asset markets : [Version: August 2011]

This paper analyzes the emergence of systemic risk in a network model of interconnected bank balance sheets. Given a shock to asset values of one or several banks, systemic risk in the form of multiple bank defaults depends on the strength of balance sheets and asset market liquidity. The price of bank assets on the secondary market is endogenous in the model, thereby relating funding liquidity to expected solvency - an important stylized fact of banking crises. Based on the concept of a system value at risk, Shapley values are used to define the systemic risk charge levied upon individual banks. Using a parallelized simulated annealing algorithm the properties of an optimal charge are derived. Among other things we find that there is not necessarily a correspondence between a bank's contribution to systemic risk - which determines its risk charge - and the capital that is optimally injected into it to make the financial system more resilient to systemic risk. The analysis has policy implications for the design of optimal bank levies. JEL Classification: G01, G18, G33 Keywords: Systemic Risk, Systemic Risk Charge, Systemic Risk Fund, Macroprudential Supervision, Shapley Value, Financial Networ

Economics of Spectrum Allocation in Cognitive Radio Networks

Cognitive radio networks (CRNs) are emerging as a promising technology for the efficient use of radio spectrum. In these networks, there are two levels of networks on each channel, primary and secondary, and secondary users can use the channel whenever the primary is not using it. Spectrum allocation in CRNs poses several challenges not present in traditional wireless networks; the goal of this dissertation is to address some of the economic aspects thereof. Broadly, spectrum allocation in CRNs can be done in two ways- (i) one-step allocation in which the spectrum regulator simultaneously allocates spectrum to primary and secondary users in a single allocation and (ii) two-step allocation in which the spectrum regulator first allocates spectrum to primary users, who in turn, allocate unused portions on their channels to secondary users. For the two-step allocation scheme, we consider a spectrum market in which trading of bandwidth among primaries and secondaries is done. When the number of primaries and secondaries is small, we analyze price competition among the primaries using the framework of game theory and seek to find Nash equilibria. We analyze the cases both when all the players are located in a single small location and when they are spread over a large region and spatial reuse of spectrum is done. When the number of primaries and secondaries is large, we consider different types of spectrum contracts derived from raw spectrum and analyze the problem of optimal dynamic selection of a portfolio of long-term and short-term contracts to sell or buy from the points of view of primary and secondary users. For the one-step allocation scheme, we design an auction framework using which the spectrum regulator can simultaneously allocate spectrum to primary and secondary users with the objective of either maximizing its own revenue or maximizing the social welfare. We design different bidding languages, which the users can use to compactly express their bids in the auction, and polynomial-time algorithms for choosing the allocation of channels to the bidders

Multi-Objective and Financial Portfolio Optimization of Carrier-Sense Multiple Access Protocols with Cooperative Diversity

8th International Workshop on Multiple Access Communications (MACOM2015), Helsinki, Finland.This paper presents a trade-off design and optimization of a class of wireless carrier-sense multiple access protocols where collision-free transmissions are assisted by the potential cooperative retransmissions of inactive terminals with a correct copy of the original transmission. Terminals are enabled with a decode-and-forward relaying protocol. The analysis is focused on asymmetrical settings, where terminals experience different channel and queuing statistics. This work is based on multi-objective and financial portfolio optimization tools. Each packet transmission is thus regarded not only as a network resource, but also as a financial asset with different values of return and risk (or variance of the return). The objective of this financial optimization is to find the transmission policy that simultaneously maximizes return and minimizes risk in the network. The work is focused on the characterization of the boundaries (envelope) of different types of trade-off performance regions: the conventional throughput region, sum-throughput vs. fairness, sum-throughput vs. power, and return vs. risk regions. Fairness is evaluated by means of the Gini-index, which is a metric commonly used in economics to measure income inequality. Transmit power is directly linked to the global transmission rate. The protocol is shown to outperform non-cooperative solutions under different network conditions that are here discussed