Network Economics
http://lists.repec.org/mailman/listinfo/nep-net
Network Economics2014-10-03Yi-Nung YangFilling in the Blanks: Network Structure and Interbank Contagion
http://d.repec.org/n?u=RePEc:bis:biswps:455&r=net
The network pattern of financial linkages is important in many areas of banking and finance. Yet bilateral linkages are often unobserved, and maximum entropy serves as the leading method for estimating counterparty exposures. This paper proposes an efficient alternative that combines information-theoretic arguments with economic incentives to produce more realistic interbank networks that preserve important characteristics of the original interbank market. The method loads the most probable links with the largest exposures consistent with the total lending and borrowing of each bank, yielding networks with minimum density. When used in a stress-testing context, the minimum-density solution overestimates contagion, whereas maximum entropy underestimates it. Using the two benchmarks side by side defines a useful range that bounds the cost of contagion in the true interbank network when counterparty exposures are unknown.Kartik Anand, Ben Craig, Goetz von Peter2014-08Interbank markets, networks, entropy, intermediation, systemic riskIntermediation in Networks
http://d.repec.org/n?u=RePEc:trf:wpaper:471&r=net
I study intermediation in networked markets using a stochastic model of multilateral bargaining in which traders compete on different routes through the network. I characterize stationary equilibrium payoffs as the fixed point of a set of intuitive value function equations and study efficiency and the impact of network structure on payoffs. There is never too little trade but there may be an inefficiency through too much trade in states where delay would be efficient. With homogenous trade surplus the payoffs for players that are not essential to a trade opportunity go to zero as trade frictions vanish.Siedlarek, Jan-Peter2014-07-20bargaining; financial networks;intermediation; matching; middlemen; networks; over-the-counter markets; stochastic gamesBeyond the Power Law: Uncovering Stylized Facts in Interbank Networks
http://d.repec.org/n?u=RePEc:arx:papers:1409.3738&r=net
We use daily data on bilateral interbank exposures and monthly bank balance sheets to study network characteristics of the Russian interbank market over Aug 1998 - Oct 2004. Specifically, we examine the distributions of (un)directed (un)weighted degree, nodal attributes (bank assets, capital and capital-to-assets ratio) and edge weights (loan size and counterparty exposure). We search for the theoretical distribution that fits the data best and report the "best" fit parameters. We observe that all studied distributions are heavy tailed. The fat tail typically contains 20\% of the data and can be systematically described by a truncated power law. In most cases, however, separating the bulk and tail parts of the data is hard, so we proceed to study the full range of the events. We find that the stretched exponential and the log-normal distributions fit the full range of the data best. These conclusions are robust to 1) whether we aggregate the data over a week, month, quarter or year; 2) whether we look at the "growth" versus "maturity" phases of interbank market development; and 3) with minor exceptions, whether we look at the "normal" versus "crisis" operation periods. In line with prior research, we find that the network topology changes greatly as the interbank market moves from a "normal" to a "crisis" operation period.Benjamin Vandermarliere, Alexei Karas, Jan Ryckebusch, Koen Schoors2014-09Information Aggregation and Optimal Market Size
http://d.repec.org/n?u=RePEc:mlb:wpaper:1182&r=net
This paper studies a rational expectations model of trading where strategic traders face information asymmetries and endowment shocks. We show that negative partici- pation externalities arise due to an endogenous interaction between information aggre-gation and multiple trading motives. Moreover, the negative externalities are strong enough to make optimal market size ?nite. In a decentralized process of market for- mation, multiple markets can survive due to the negative externalities among traders. The model also predicts: (i) that only in a su¢ ciently large market the equilibrium multiplicity due to self-ful?lling trading motives can arise, (ii) that a high correlation in endowment shocks can make markets extremely illiquid.Kei Kawakami2014Asymmetric information, Aggregate shock, Imperfect competition, Market fragmentation, Multiple equilibria, Network externality puzzle, Price impact.