Lending to European Households and Non-Financial Corporations: Growth and Trends Key findings from the ECRI Statistical Package 2019. ECRI Statistics, October 2019

The ECRI Statistical Package 2019 provides data on outstanding credit granted by monetary-financial institutions (MFIs) to households and non-financial corporations (NFCs) for the period from 1995 to 2018. Credit volumes and annual growth rates are broken down by sector and credit type to enable detailed insights into credit market developments over time and across countries. It comprises 45 countries including the EU Member States, EU candidate and EFTA countries as well as the US, Canada, Japan, Australia, Russia, Mexico and Saudi Arabia

Relation between Financial Market Structure and the Real Economy: Comparison between Clustering Methods

We quantify the amount of information filtered by different hierarchical clustering methods on correlations between stock returns comparing it with the underlying industrial activity structure. Specifically, we apply, for the first time to financial data, a novel hierarchical clustering approach, the Directed Bubble Hierarchical Tree and we compare it with other methods including the Linkage and k-medoids. In particular, by taking the industrial sector classification of stocks as a benchmark partition, we evaluate how the different methods retrieve this classification. The results show that the Directed Bubble Hierarchical Tree can outperform other methods, being able to retrieve more information with fewer clusters. Moreover, we show that the economic information is hidden at different levels of the hierarchical structures depending on the clustering method. The dynamical analysis on a rolling window also reveals that the different methods show different degrees of sensitivity to events affecting financial markets, like crises. These results can be of interest for all the applications of clustering methods to portfolio optimization and risk hedging.Comment: 31 pages, 17 figure

Two Dimensions of Combating Over-Indebtedness: Consumer protection and financial stability. ECRI Research Report No. 18, 28 October 2016

The expansion of credit markets has fostered economic growth across the European Union, but it has also produced a sharp increase in the average level of household indebtedness. As a consequence of the financial crisis, the drop in households’ disposable income has undermined the ability of many EU households to honour their financial commitments. Against this background, this paper investigates the complexity of indebtedness and draws a distinction between its legal and economic dimensions in order to better understand the phenomenon. Despite efforts made by the European Commission, we found that the definition of indebtedness and over-indebtedness still lacks precision. Mirroring the interventions of national legislators in terms of consumer protection, over-indebtedness in the EU tends to be narrowly defined in terms of its relationship with insolvency. Therefore, further efforts need to be taken in designing the necessary measures to alleviate and prevent over-indebtedness. Accordingly, this study focuses on the role of financial education, analyses the impact of the relevant EU directives, collects important evidence in support of harmonising debt-advice services and explores the path towards a common methodology of early detection of vulnerable households

Taking stock. Assessing the current status and evolution of the United Nations Security Council’s legislative resolutions

The present essay intends to provide for an in-depth analysis concerning the enactment of new legislative resolutions by the UN Security Council with a view to dealing with foreign terrorist fighters and Islamic State of Iraq and the Levant as well. It will be argued that, instead of voicing unweavering concerns about the Council's increasing tendency to resort to this specific tool, UN Member States have widely welcomed these resolutions, deeming them necessary and proportionate response to urgent threats faced by the International Community as a whole. Accordingly, this has generated a clear distinction between the previous legislative resolutions and the recent ones. As a result, by dwelling more specifically on States' utterances made during the meetings devoted to discuss these new general resolutions, it is argued that such resolutions are to be looked upon as subsequent practice pursuant to Article 31, paragraph 3(b) of 1969 Vienna Convention on the Law of Treaties (VCLT), which means that they are relevant in order to interpret Article 41 of the UN Charter. Ultimately, and based on the assumption that States are now more inclined to accept general obligations in the counter-terrorism's domain, the manuscript addresses the topic of how the UN Security Council should legislate in order to secure the widest acceptance possible and be in accordance with several International Law's requirements

Key findings from the ECRI Statistical Package 2020. CEPS ECRI Statistics 05 Oct 2020.

Key findings from the ECRI Statistical Package 2020 • In 2019, loans to EU households and non-financial corporations (NFC) increased by 2.5%. • For the fifth year in a row, total loans in non-euro area countries grew more than loans in euro area countries. • Compared to 2018, the growth rate of total loans in 2019 increased from 1.9% to 2.4% in the euro area, and in non-euro area countries the growth rate was from 2.8% to 3.7%. • Between 2018 and 2019, household loans in EU increased by 3.5% and non-financial corporations (NFC) loans increased by 1.2%. • Total household loans grew most in Bulgaria (+13.5%), Hungary (+12.3%), Malta (+10.0%), Poland (+8.1%), Slovakia (+8.0%) and Lithuania (+7.8%). The largest contractions were registered in Greece (-8.6%), Cyprus (-5.2%). • Hungary (+8.1%), Austria (+6.7%), Luxembourg (+6.7%), Finland (+6.6%), Bulgaria (+5.9%) and Germany (+5.7%) were among the member states with the largest growth rates in NFC loans. Significant reductions were registered in Greece (-11.8%), Cyprus (-9.0%), Italy (-7.0%) and Ireland (-5.6%). • Since the Covid-19 outbreak the transaction flows and outstanding amount of loans to non-financial corporations have increased significantly, while household loans transaction flows have fallen and loan growth stabilised

Beyond public debt. The Hidden Rapid Erosion of EU Government Balance Sheets is a Financial Threat to Society How to stop it. CEPS Commentary, March 2019

The EU is built on the promise of peace, economic prosperity and–since the Maastricht Treaty–also fiscal responsibility. The absence in several member states of a culture promoting responsible public financial management, however, has led to excessive public indebtedness, which negatively affects today’s economy and weighs heavily on the shoulders of future generations. Against this background, this paper argues that the introduction of modern Public Financial Management (PFM) systems–which not only take into account public debt but also non-debt liabilities and non-financial assets–can contribute to coupling economic growth with responsible fiscal policy. The tools exist and can provide the essential elements for stability and growth for member states and the EU as a whole. Changing the public management culture and reforming government accounts to reflect economic reality are essential steps Europe must take before it can reap the full benefits, and thereby create the necessary fiscal space and deliver better services to European citizens

Clustering and hierarchy of financial markets data: advantages of the DBHT

We present a set of analyses aiming at quantifying the amount of information filtered by di↵erent hierarchical clustering methods on correlations between stock returns. In particular we apply, for the first time to financial data, a novel hierarchical clustering approach, the Directed Bubble Hierarchical Tree (DBHT), and we compare it with other methods including the Linkage and k-medoids. In particular by taking the industrial sector classification of stocks as a benchmark partition we evaluate how the di↵erent methods retrieve this classification. The results show that the Directed Bubble Hierarchical Tree outperforms the other methods, being able to retrieve more information with fewer clusters. Moreover, we show that the economic information is hidden at di↵erent levels of the hierarchical structures depending on the clustering method. The dynamical analysis also reveals that the di↵erent methods show di↵erent degrees of sensitivity to financial events, like crises. These results can be of interest for all the applications of clustering methods to portfolio optimization and risk hedging

The Future of EU ATM Markets. Impacts of digitalisation and pricing policies on business models. CEPS Research Report, October 2018

ATMs constitute a critical component in today’s infrastructure for facilitating cash payments. However, ongoing digitalisation (cashless payments, e-commerce and online banking) is challenging the role of ATMs and putting pressure on the cash infrastructure in the EU. The shift from cash to cashless payments reduces the need for cash withdrawals and the rise of online banking challenges the bank branch as the traditionally most prevalent location for ATMs. Moreover, the introduction of pricing policies might also change the dynamics in EU ATM markets. Transparency and price caps on the so-called dynamic currency conversion (DCC) as well as potential reductions in interchange fees will put pressure on the revenues of certain ATMs. Against this background, this report assesses the sensitivity of EU ATM markets to ongoing digitalisation and pricing policies. The impact of these developments is assessed across business models in Belgium, France, Germany, Greece, Poland, Portugal, Spain and Sweden, which are representative of the ATM markets in all EU member states. Location characteristics are determined and costs and revenues estimated for the 146,821 ATM locations across these eight EU member states in mid-2018

Risk diversification: a study of persistence with a filtered correlation-network approach

The evolution with time of the correlation structure of equity returns is studied by means of a filtered network approach investigating persistences and recurrences and their implications for risk diversification strategies. We build dynamically Planar Maximally Filtered Graphs from the correlation structure over a rolling window and we study the persistence of the associated Directed Bubble Hierarchical Tree (DBHT) clustering structure. We observe that the DBHT clustering structure is quite stable during the early 2000' becoming gradually less persistent before the unfolding of the 2007-2008 crisis. The correlation structure eventually recovers persistence in the aftermath of the crisis settling up a new phase, distinct from the pre-cysts structure, where the market structure is less related to industrial sector activity. Notably, we observe that - presently - the correlation structure is loosing again persistence indicating the building-up of another, different, phase. Such dynamical changes in persistence and their occurrence at the unfolding of financial crises rises concerns about the effectiveness of correlation-based portfolio management tools for risk diversification

Interplay between past market correlation structure changes and future volatility outbursts.

We report significant relations between past changes in the market correlation structure and future changes in the market volatility. This relation is made evident by using a measure of "correlation structure persistence" on correlation-based information filtering networks that quantifies the rate of change of the market dependence structure. We also measured changes in the correlation structure by means of a "metacorrelation" that measures a lagged correlation between correlation matrices computed over different time windows. Both methods show a deep interplay between past changes in correlation structure and future changes in volatility and we demonstrate they can anticipate market risk variations and this can be used to better forecast portfolio risk. Notably, these methods overcome the curse of dimensionality that limits the applicability of traditional econometric tools to portfolios made of a large number of assets. We report on forecasting performances and statistical significance of both methods for two different equity datasets. We also identify an optimal region of parameters in terms of True Positive and False Positive trade-off, through a ROC curve analysis. We find that this forecasting method is robust and it outperforms logistic regression predictors based on past volatility only. Moreover the temporal analysis indicates that methods based on correlation structural persistence are able to adapt to abrupt changes in the market, such as financial crises, more rapidly than methods based on past volatility