Journal of Financial Stability最新文献

The breakdown of the interbank market was a critical moment in the unfolding of the global financial crisis of 2007–2008. We argue that the adequate pricing of risks is critical for the functioning of a market of such vital importance as the interbank market. We use a unique panel data set that allows us to quantify counterparty risk and different types of systemic risks associated with interbank exposures. We use a simultaneous equation model for interbank lending and deposit rates to study whether counterparty risk and systemic risk are adequately priced. As expected, we find that riskier banks on average pay a higher deposit rate. However, on average, banks grant a discount in their lending rates to riskier banks. For systemic risk, we also find mixed results. The positive effect on the deposit rate declines, but the negative effect on the lending rate remains. We argue that the mixed results regarding the pricing of systemic risk might ex-post justify parts of the Basel III reform package that forces systemically important banks to hold higher capital buffers.

In this cover paper, we introduce a Special Issue (SI) published after the fourth edition of a series of financial stability conferences organized by Bank of Mexico, CEMLA, Bank of Canada, Zurich University and the Journal of Financial Stability in November 2021. Before providing our perspective on why the research papers included into the SI are of great relevance, we give a brief and personal overview of recent directions in financial stability research in general, esp., related to topics accentuated by the COVID-19 pandemic or post-pandemic economic and financial conditions and their complexity. Papers published in the SI cover four topics of research in the financial stability field, featuring some outstanding and innovative projects presented during the conference. The first topic is on interconnectedness and shock transmission in the financial system, diving deep into asset fire sales, interconnectedness of various segments of the financial system, in addition to banks, on the optimality of systemic risk capital buffers, and on how risks are priced in the interbank market network. The second one touches upon climate change risks looking at investors’ reactions to international climate policy developments, in particular on the Paris Agreement front and how to jointly model physical and transition risk in the banking system, including the important concept of double materiality. The third topic is represented by projects focused on policy analysis for systemic risk mitigation, specifically dealing with macroprudential policy instruments and crisis mitigation policies. Finally, research papers in the last topic on big data and market data focus on the innovative ways to explore the growing body of data sources, such as data collected by regulators, including credit register data, supervisory data and market data on financial transactions, to better understand sources and implications of systemic risk.

We examine the impact of fire sales on the UK financial system through commonly held assets across different financial sectors. In particular, we model indirect contagion via fire sales across UK banks and non-banks subject to different types of constraints. We find that performing a stress simulation that does not account for common asset holdings across multiple sectors can severely underestimate the fire sale losses in the financial system. In addition, pro-rata liquidation strategy would result in a higher level of fire sale losses in the system as whole, but a waterfall strategy may produce a higher spillover effect for a passive institution (or a passive sector) that chooses not to promptly liquidate any of its assets during distress while other institutions decide to do so.

This paper studies the dynamics of contagion across the banking, insurance and shadow banking sectors of 18 advanced economies in the period 2006-2018. We construct Granger causality-in-risk networks and introduce higher-order aggregate networks and higher-order node centralities in an economic setting to capture non-Markovian network features. Our approach uncovers the dynamics of financial contagion as it is transmitted across segments of the financial system and jurisdictions. The calculated higher-order centralities identify sectors in distress as the nodes through which contagion propagates. The banking system emerges as the primary source and transmitter of stress while banks and shadow banks are highly interconnected. The insurance sector is found to contribute less to stress transmission in all periods, except during the global financial crisis. The proposed approach is able to identify clearly the sectors that are critical for the transmission of financial contagion, in contrast to the commonly used memoryless measures of network centrality.

Using granular data from the Spanish Credit Register, we study the contagion of financial distress via the credit quality channel in the Spanish interbank market. We propose a non-linear contagion mechanism dependent on banks’ balance-sheet structure (specifically, their leverage ratios). Moreover, we explicitly model uncertainty in lenders’ assessments of the probability of default of their borrowers, thus incorporating agents’ lack of complete information and heterogeneous expectations in their assessment of future outcomes. We perform multiple simulations across a wide range of possible levels of stress in the system, and we focus on disentangling the effects of these two key model components by comparing the results of our model with those of a linear and deterministic counterpart. In this way, we find that non-linear contagion leads to substantially larger losses than its linear counterpart for a wide range of intermediate levels of stress in the system, while its effects become negligible for very low and very high stress levels. Regarding uncertainty, we find that its effects, while smaller than those of non-linear contagion, are nonetheless relevant and most important around levels of stress at which different parts of the system become unstable. Interestingly, losses can be amplified or mitigated with respect to the deterministic case depending on the specific level of stress considered. Finally, the interaction between both model components—non-linear contagion and uncertainty—alters the area where uncertainty matters.

In this paper we present a methodology of model-based calibration of additional capital needed in an interconnected financial system to minimize potential contagion losses. Building on ideas from combinatorial optimization tailored to controlling contagion in case of complete information about an interbank network, we augment the model with three plausible types of fire sale mechanisms. We then demonstrate the power of the methodology on the euro area banking system based on a network of 373 banks. On the basis of an exogenous shock leading to defaults of some banks in the network, we find that the contagion losses and the policy authority’s ability to control them depend on the assumed fire sale mechanism and the fiscal budget constraint that may or may not restrain the policy authorities from infusing money to halt the contagion. The modelling framework could be used both as a crisis management tool to help inform decisions on capital/liquidity infusions in the context of resolutions and precautionary recapitalizations or as a crisis prevention tool to help calibrate capital buffer requirements to address systemic risks due to interconnectedness.

We examine the social desirability of macroprudential measures, particularly those aimed at riskier home buyers. We examine the effectiveness of these measures against social costs, such as reduced access to the housing ladder for poorer households. Our analysis shows that the measures implemented so far have not limited access to credit or the housing markets. They have been effective in limiting the riskiest loans, minimizing negative equity episodes, reducing systemic risks by debilitating the house price-leverage spiral, and limiting the depths of contractions of a range of macro-financial variables. The welfare of households has also improved. Costs from these measures have been limited and have materialized through a rise in the age-income profile of first-time buyers, and somewhat more attenuated booms. Our results point to the conclusion that macroprudence is desirable when insulated from short-term interference and quick gains. The economy becomes more robust and even households in the lowest decile of the wealth distribution benefit from the general equilibrium effects of more stable financial provision.

We extend Jin and Myers’s (2006) model to derive the relation between stock price crash risk and operating leverage (i.e., the fraction of fixed costs in total costs). The model predicts that (1) firms’ operating leverage decreases as stock price crash risk increases and (2) the negative effect of crash risk on operating leverage is more pronounced when firms are closer to the crash threshold or when managers face higher costs of stock price crashes. We empirically test the model predictions using a large sample of manufacturing firms in the US and find consistent results. Further analysis shows that higher levels of crash risk lead to a less sticky cost behavior. In addition, crash risk–driven operating deleveraging effectively reduces stock return volatility and enhances operating performance in subsequent years. Collectively, our findings reveal that crash-prone firms adopt a more flexible cost structure to delay stock price crashes and mitigate adverse outcomes.

Few studies investigate whether ESG mitigates the harmful effects of changes in firms’ external environments. We evidence that ESG mitigated the impact of COVID-19 work-from-home and workplace prescriptions amongst several other pandemic-related government regulatory interventions, even when controlling for firm size. In a novel approach, we apply scrutiny of firms to restrict our cross-national sample to only firms with no cross-border trade, that is, explicitly domestically focused operational processes irrespective of the endpoint of corporate sales, enhancing methodological robustness. Consequently, we isolate an ESG effect. Results indicate the existence of a premium during the onset of each analysed national pandemic experience, particularly pronounced for those corporations that had achieved more substantiative ESG-based preparation and development before the onset of the COVID-19 pandemic.

Digitalization is a crucial strategy for firms to gain a competitive advantage. This study utilizes data from Chinese listed firms from 2011 to 2020 to examine how digitalization affects firms' stock price informativeness. Empirical results demonstrate that digitalization reduces stock price synchronicity and promotes firms' stock price informativeness. Moreover, digitalization improves stock price informativeness by enhancing investment efficiency and firm value, reducing information asymmetry, and alleviating agency costs. These findings suggest that effective digital strategies and capabilities constitute an important yet underappreciated resource that enables firms to generate value-relevant information and improve the information environment in emerging capital markets. Our study contributes new evidence on the financial market implications of digital transformation from a resource-based view perspective.