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This chapter proposes a measure of systemic default interconnectedness between banks, non-banks, housing finance companies in India and globally systemically important banks based on variance decompositions associated with a multiple variable vector autoregression of probability of default of the institutions. We call it the “vulnerability spillover index” (VSI). The vulnerability indices capture all the major macro and financial stress events in the Indian and global economy explaining the interconnections between sectors and underlying reasons for spillovers and potential for a systemic crisis. Thresholds of VSI are calculated which may enable prediction of financial stress events.

We employ three systemic risk measures of banks, including the systemic risk index (SRISK) and marginal expected shortfall (MES) of Brownlees and Engle (2017) and the conditional Value-at-Risk (ΔCoVaR) of Adrian and Brunnermeier (2016), to analyze bank's exposure and contribution to systemic risk in the banking system when a financial crisis occurs. We find evidence that time-varying systemic risk exists, and systemic risk exposures escalate with the interconnectedness of banks. We also find revenue diversification is another significant factor that reduces a bank's exposure to systemic risk but not for banks in Taiwan and Singapore.

Financial systemic risk is often assessed by the interconnectedness of financial institutes (FI) in terms of cross-ownership, overlapping investment portfolios, interbank credit exposures, etc. Less is known about the interconnectedness between FIs through the lens of consumer credits. Using detailed consumer credit data in Canada, this chapter constructs a novel banking network to measure FIs’ interconnectedness in the consumer credit markets. Results show that FIs on average are more connected to each other over the sample period, with the interconnectedness measure increases by 19% from 2013 Q4 to 2019 Q4. FIs with more diversified portfolios are more connected in the network. Among various types of FIs, secondary FIs have the notable increase in interconnectedness. Domestic Systemically Important Banks and secondary FIs offering a broad range of loan products are more connected to large FIs, while those specialized in single loan types are more connected to their industry peers. FI connectedness is also significantly related to their participation in the mortgage markets.

This chapter explores the influence of the banking and insurance sectors on the economic growth of Czechia, a nation with unique financial dynamics ideal for this study. Our aim is to ascertain the contribution of these financial institutions to economic growth, addressing the divergence in empirical findings that have marked this research area for decades. We scrutinise the impact of various factors, including sectoral development and the efficiency and stability of these institutions, all within the Czech context. Utilising the Granger causality test, we assess the role of several indicators related to the development of the banking and insurance sectors. Our findings reveal that in Czechia, the evolution and operational efficiency of these financial institutions significantly drive economic growth. This study provides an in-depth understanding of the role these sectors play in the Czech economic landscape, affirming their crucial contribution to the nation's economic prosperity.

Purpose – The global financial crisis of 2007–2009 has highlighted the need for reform of financial regulation in several jurisdictions across the globe, including the United Kingdom and the United States. This chapter argues that the reforms need to be comprehensive and will therefore have to cover several aspects of financial regulation.

Design/methodology/approach – The chapter critically examines some of the areas where reforms are most needed. This involves consideration of the merits and demerits of multi-functional or universal banking. It also involves consideration of the systemic and other problems that arise as a result of the increasingly international nature of banking and other financial services. Moreover, it examines the need for regulators to understand and keep pace with financial innovation. Furthermore, it involves discussion on the need to improve corporate governance and remuneration policies in banks and other financial services providers as well as the need for adequate arrangements for dealing with bank insolvencies and collapses.

Findings – Market fundamentalism and over-reliance on the alleged self-correcting powers of the market have led to excessive deregulation and liberalisation in world financial markets. Financial regulatory reforms will therefore have to be substantial and comprehensive to properly address the problems caused by excessive financial liberalisation.

Originality/value – The chapter examines significant issues that academics, regulators and policy makers should consider when devising or implementing reforms designed to prevent, or reduce the impact of, financial crises in the future.

This chapter investigates the presence of a difference in the systemic risk level between Islamic and conventional banks in Bangladesh. The authors compare systemic resilience of three types of banks: fully fledged Islamic banks, purely conventional banks (CB), and CB with Islamic windows. The authors use the market-based systemic risk measures of marginal expected shortfall and systemic risk to identify which type is more vulnerable to a systemic event. The authors also use ΔCoVaR to identify which type contributes more to a systemic event. Using a sample of observations on 27 publicly traded banks operating over the 2005–2014 period, the authors find that CB is the least resilient sector to a systemic event, and is the one that has the highest contribution to systemic risk during crisis times.

The latest financial crisis has stressed the need of understanding the world financial system as a network of interconnected institutions, where financial linkages play a fundamental role in the spread of systemic risks. In this paper we propose to enrich the topological perspective of network models with a more structured statistical framework, that of Bayesian Gaussian graphical models. From a statistical viewpoint, we propose a new class of hierarchical Bayesian graphical models that can split correlations between institutions into country specific and idiosyncratic ones, in a way that parallels the decomposition of returns in the well-known Capital Asset Pricing Model. From a financial economics viewpoint, we suggest a way to model systemic risk that can explicitly take into account frictions between different financial markets, particularly suited to study the ongoing banking union process in Europe. From a computational viewpoint, we develop a novel Markov chain Monte Carlo algorithm based on Bayes factor thresholding.