Knowledge that Transforms

This paper assesses the spillovers from the global financial crisis on the cost and structure of cross-border funding of Chilean banks. To do so, it uses a novel dataset of individual lending operations between Chilean banks and their foreign counterparties between 2008 and 2016. The paper finds that global banks that experienced the largest hikes in their funding costs and were based in countries with large increases in sovereign risk increased spreads to Chilean banks most in this period, and that global financial turbulences also spilled through to the funding cost of Chilean banks. After the financial crisis of 2008 and 2009 the Chilean banking system underwent a significant change in its sources of funding, with a shift to new bank counterparties and a higher reliance on bond financing. The paper provides evidence that distance, as well as the intensity and age of banking relationships matter for the cost of cross border borrowing. Hence, this shift of sources of funding was initially a costly process. Over time as banking relationships developed with new counterparties, the cost of this shift decreased.

This paper studies the reaction of selected CEE (satellite) currencies to increased financial stress in the euro area (core) and also in global financial markets. We suggest that this reaction might be non-linear; the “safe haven” status of a satellite currency may hold in calm periods, but breaks down when risk aversion is elevated. A stylized model of portfolio allocation between assets denominated in euro and the satellite currency suggests the presence of two regimes characterized by different reactions of the exchange rate to an increased stress in the euro area. In the “diversification” regime, the satellite currency appreciates in reaction to an increase in the expected variance of EUR assets, while in the “flight to safety” regime, the satellite currency depreciates in response to increased expected volatility. We suggest that the switch between regimes is related to changes in risk aversion, driven by the level of strains in the financial system as captured by financial stress indicators. Using the Bayesian Markov-switching VAR model, the presence of these regimes is identified in the case of the Czech koruna, the Hungarian forint and the Polish zloty.

The recent implementation of the Basel III framework has re-ignited the debate around the link between actual capital levels, performance and capital requirements in the banking sector. There is a dominant view in the earlier empirical literature in favor of a positive effect of capital on performance. Using panel data gathered by the French supervisor, we also find evidence of this beneficial effect of capital, but try to go one step further by distinguishing between regulatory and voluntary capital. Using a two-step estimation procedure, and controlling for many factors (risk, asset composition, etc.), we show that voluntary capital, i.e. capital held by banks irrespective of their regulatory requirements, turns out to be the sole component of capital that affects performance positively. In contrast, the effect of regulatory capital on profitability appears to be insignificant, indicating that so far the increase in capital requirements has not been detrimental to bank profitability in France.

We develop a framework to analyse the credit default swap (CDS) market as a network of risk transfers among counterparties. From a theoretical perspective, we introduce the notion of flow-of-risk and provide sufficient conditions for a bow-tie network architecture to endogenously emerge as a result of intermediation. This architecture shows three distinct sets of counterparties: (i) Ultimate Risk Sellers (URS), (ii) Dealers (indirectly connected to each other), (iii) Ultimate Risk Buyers (URB). We show that the probability of widespread distress due to counterparty risk is higher in a bow-tie architecture than in more fragmented network structures. Empirically, we analyse a unique global dataset of bilateral CDS exposures on major sovereign and financial reference entities in 2011–2014. We find the presence of a bow-tie network architecture consistently across both reference entities and time, and that the flow-of-risk originates from a large number of URSs (e.g. hedge funds) and ends up in a few leading URBs, most of which are non-banks (in particular asset managers). Finally, the analysis of the CDS portfolio composition of the URBs shows a high level of concentration: in particular, the top URBs often show large exposures to potentially correlated reference entities.

Previous work suggests that the charter value hypothesis is theoretically grounded and empirically supported, but not universally. Accordingly, this paper aims to perform an analysis of the relations between charter value, risk taking, and supervision, taking into account the relations’ complexity. Specifically, using the CAMELS rating system as a general framework for supervision, we study how charter value relates to risk and supervision by means of classification and regression tree analysis. The sample covers the period 2005–2016 and consists of listed banks in countries that were members of the Eurozone when it came into existence, along with Greece. To evaluate the crisis consequences, we also separately analyze four subperiods and countries that required financial aid from third parties and those that did not so, along with large and small banks. Our results reflect the complexity of the relations between charter value, supervision, and risk. Indeed, supervision and charter value seem aligned regarding only some types of risk.

Previous studies of consumer debt risk estimate low sensitivities to negative shocks, contradicting the historical data. This work proposes a heterogeneous agents model of household finances and credit risk. Families suffer labor income shocks and choose from a menu of loans contracts, defaulting on debt commitments when unable to finance minimum consumption standards. Using a variety of survey data I simulate household credit default for Chile over the last 20 years, replicating successfully the highs and lows of consumer delinquency. Some households are shown to be highly vulnerable to changes in interest rates, credit maturities and liquidity.

We study the sensitivity of banks’ credit supply to small and medium size enterprises (SMEs) in the UK with respect to the banks’ financial condition before and during the financial crisis. Employing unique data on the geographical location of all bank branches in the UK, we connect firms’ access to bank credit to the financial condition (i.e., bank health and the use of core deposits) of all bank branches in the vicinity of the firm for the period 2004–2011. Before the crisis, banks’ local financial conditions did not influence credit availability irrespective of the functional distance (i.e., the distance between bank branch and bank headquarters). However, during the crisis, we find that SMEs with banks within their vicinity that have stronger financial conditions faced greater credit availability when the functional distance is close. Our results point to a “flight to headquarters” effect during the financial crisis.

Using the test of Granger-causality in tail of Hong et al. (2009), we define and construct Granger-causality tail risk networks between 33 systemically important banks (G-SIBs) and 36 sovereign bonds worldwide. Our purpose is to exploit the structure of the Granger-causality tail risk networks to identify periods of distress in financial markets and possible channels of systemic risk propagation. Combining measures of connectedness of these networks with the ratings of the sovereign bonds, we propose a flight-to-quality indicator to identify periods of turbulence in the market. Our measure clearly peaks at the onset of the European sovereign debt crisis, signaling the instability of the financial system. Finally, we use the connectedness measures of the networks to forecast the quality of sovereign bonds. We find that connectedness is a significant predictor of the cross-section of bond quality.

Capturing financial network linkages and contagion in stress test models are important goals for banking supervisors and central banks responsible for micro- and macroprudential policy. However, granular data on financial networks is often lacking, and instead the networks must be reconstructed from partial data. In this paper, we conduct a horse race of network reconstruction methods using network data obtained from 25 different markets spanning 13 jurisdictions. Our contribution is two-fold: first, we collate and analyze data on a wide range of financial networks. And second, we rank the methods in terms of their ability to reconstruct the structures of links and exposures in networks.