infonet-economy

Financial institutions form multilayer networks by engaging in contracts with each other and by holding exposures to common assets. As a result, the default probability of one institution depends on the default probability of all of the other institutions in the network. Here, we show how small errors on the knowledge of the network of contracts can lead to large errors in the probability of systemic defaults. From the point of view of financial regulators, our findings show that the complexity of financial networks may decrease the ability to mitigate systemic risk, and thus it may increase the social cost of financial crises.

The practice of lobbying in the interest of economic or social groups plays an important role in the policy making process of most economies. We carry out a multi-level network analysis of the relations among lobbying organizations in the EU transparency register, focusing on the domain of finance and climate. We find that the network centrality of organizations has no simple relation with their size and each layer provides additional complementary information to characterize organizations' influence. At a more aggregate level, groups of interest differ very much in terms of internal cohesiveness and thus in their ability to advocate coherently. Groups also differ in their centrality and thus in their ability to influence each other.

We introduce a network valuation model (hereafter NEVA) for the ex-ante valuation of claims among financial institutions connected in a network of liabilities. Similar to previous work, the new framework allows to endogenously determine the recovery rate on all claims upon the default of some institutions. In addition, it also allows to account for ex-ante uncertainty on the asset values, in particular the one arising when the valuation is carried out at some time before the maturity of the claims. The framework encompasses as special cases both the ex-post approaches of Eisenberg and Noe and its previous extensions, as well as the ex-ante approaches, in the sense that each of these models can be recovered exactly for special values of the parameters. We characterize the existence and uniqueness of the solutions of the valuation problem under general conditions on how the value of each claim depends on the equity of the counterparty. Further, we define an algorithm to carry out the network valuation and we provide sufficient conditions for convergence to the maximal solution.

We study the international transmission of shocks from the banking to the real sector during the global financial crisis. For identification, we use matched bank-firm level data, including many small and medium-sized firms, in Eastern Europe and Central Asia. We find that internationally-borrowing domestic and foreign-owned banks contract their credit more during the crisis than domestic banks that are funded only locally. Firms that are dependent on credit and at the same time have a relationship with an internationally-borrowing domestic or a foreign bank (as compared to a locally-funded domestic bank) suffer more in their financing and real performance. Single-bank-relationship firms, small firms and firms with intangible assets suffer most. For credit-independent firms, there are no differential effects. Our findings suggest that financial globalization has intensified the international transmission of financial shocks with substantial real consequences.

Different modes of external finance provide heterogeneous benefits for the borrowing firms. Informal finance offers informational advantages whereas formal finance is scalable. Using unique survey data from China, we find that informal finance is associated with higher sales growth for small firms but lower sales growth for large firms. We identify a complementary effect between informal and formal finance for the sales growth of small firms, but not for large firms. Co-funding, thereby simultaneously using the informational advantage of informal finance and the scalability of formal finance, is therefore the optimal choice for small firms.

As of this writing in June 2016, the markets are predicting Venezuela to be on the brink of default. On June 1, 2016, the 6 month CDS contract traded at about 7000bps which translates into a likelihood of default of over 90%. Our interest in the Venezuelan crisis is that its outstanding sovereign bonds have a unique set of contractual features that, in combination with its near-default status, have created a natural experiment. This experiment has the potential to shed light on one of the long standing questions that sits at the intersection of the fields of law and finance, the question of the degree to which financial markets price contract terms. We find evidence to suggest that at least within the confines of a near-default scenario, the markets are highly sensitive to even small differences in contract language.

Financial networks have shown to be important in understanding systemic events in credit markets. In this paper, we investigate how the structure of those networks can affect the capacity of regulators to assess the level of systemic risk. We introduce a model to compute the individual and systemic probability of default in a system of banks connected in a generic network of credit contracts and exposed to external shocks with a generic correlation structure. Even in the presence of complete knowledge, we identify conditions on the network for the emergence of multiple equilibria. Multiple equilibria give rise to uncertainty in the determination of the default probability. We show how this uncertainty can affect the estimation of systemic risk in terms of expected losses. We further quantify the effects of cyclicality, leverage, volatility and correlations. Our results are relevant to the current policy discussions on new regulatory framework to deal with systemic events of distress as well as on the desirable level of regulatory data disclosure.

Traditional economic theory could not explain, much less predict, the near collapse of the financial system and its long-lasting effects on the global economy. Since the 2008 crisis, there has been increasing interest in using ideas from complexity theory to make sense of economic and financial markets. Concepts, such as tipping points, networks, contagion, feedback, and resilience have entered the financial and regulatory lexicon, but actual use of complexity models and results remains at an early stage. Recent insights and techniques offer potential for better monitoring and management of highly interconnected economic and financial systems and, thus, may help anticipate and manage future crises

The interconnectedness of the financial system is one of the main factors contributing to systemic risk. The financial crisis has shown how the network of intrafinancial exposures may, in times of systemic distress, amplify initially small shocks. In this work, the authors build on the DebtRank methodology by introducing the notion of a network of leverage and propose a two-round stress test exercise. In the first round, a shock hits banks’ external assets; in the second round, these initial losses reverberate in the network of interbank exposures because of the devaluation of interbank obligations. Losses in the second round result from a multiplicative effect between external and interbank leverage. The authors then apply the stress test to the largest EU banks for the years 2008–2013. They find that second-round losses are at least as large as first-round losses; neglecting these effects could therefore lead to a severe underestimation of systemic risk.