Governing systemic and cascading disaster risk in Indonesia: where do we stand and future outlook

PurposeThis paper aims to identify key factors for a contextualised Systemic Risk Governance (SRG) framework and subsequently explore how systemic risks can be managed and how local institutional mechanisms can be tweaked to deal with the complex Indonesian risk landscape.Design/methodology/approachUsing a case study from Palu triple-disasters in Central Sulawesi, Indonesia, the authors demonstrate how inland earthquakes in 2018 created cascading secondary hazards, namely tsunamis, liquefactions and landslides, caused unprecedented disasters for the communities and the nation. A qualitative analysis was conducted using the data collected through a long-term observation since 2002.FindingsThe authors argue that Indonesia has yet to incorporate an SRG approach in its responses to the Palu triple-disasters. Political will is required to adopt more appropriate risk governance modes that promote the systemic risk paradigm. Change needs to occur incrementally through hybrid governance arrangements ranging from formal/informal methods to self- and horizontal and vertical modes of governance deemed more realistic and feasible. The authors recommend that this be done by focusing on productive transition and local transformation.Originality/valueThere is growing awareness and recognition of the importance of systemic and cascading risks in disaster risk studies. However, there are still gaps between research, policy and practice. The current progress of disaster risk governance is not sufficient to achieve the Sendai Framework for Disaster Risk Reduction (2015–2030) unless there is an effective governing system in place at the local level that allow actors and institutions to simultaneously manage the interplays of multi-hazards, multi-temporal, multi-dimensions of vulnerabilities and residual risks. This paper contributes to these knowledge gaps.

Managing systemic risk in emergency management, organizational resilience and climate change adaptation

PurposeThis paper applies the theory of cascading, interconnected and compound risk to the practice of preparing for, managing, and responding to threats and hazards. Our goal is to propose a consistent approach for managing major risk in urban systems by bringing together emergency management, organisational resilience, and climate change adaptation.Design/methodology/approachWe develop a theory-building process using an example from the work of the Greater London Authority in the United Kingdom. First, we explore how emergency management approaches systemic risk, including examples from of exercises, contingency plans and responses to complex incidents. Secondly, we analyse how systemic risk is integrated into strategies and practices of climate change adaptation. Thirdly, we consider organisational resilience as a cross cutting element between the approaches.FindingsLondon has long been a champion of resilience strategies for dealing with systemic risk. However, this paper highlights a potential for integrating better the understanding of common points of failure in society and organisations, especially where they relate to interconnected domains and where they are driven by climate change.Originality/valueThe paper suggests shifting toward the concept of operational continuity to address systemic risk and gaps between Emergency Management, Organizational Resilience and Climate Change Adaptation.

Tail-event driven NETwork dependence in emerging markets

This paper employs the Tail Event NETwork (TENET) to identify financial markets with greater potential risk, and simultaneously investigate the interdependence between them. We find strong time-varying connectedness across 23 emerging markets during the main crisis episodes, including the most recent COVID-19 pandemic, using data from January 1995 to May 2021. The network analysis revealed that emerging European markets are top risk transmitters, whereas emerging Asian markets are top risk receivers. China showed disconnection from the network, reflecting its diversification potential for investors. Our findings offer several policy and regulatory implications. • We investigated the tail-event network dependence of 23 emerging markets;• Tail-Event NETwork (TENET) technique has been employed;• We show that European emerging markets are top risk transmitters, while Asian economies are top risk receivers;• Chinese market is decoupled from the rest of markets analysed. [ FROM AUTHOR] Copyright of Emerging Markets Review is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

The role of credit lines and multiple lending in financial contagion and systemic events

Banks play a crucial role in providing liquidity to borrowers, particularly during crises (Kashyap et al., 2002 [33]). The existence of multiple lending relationships between banks and borrowers has been seen as an element that reduces the risk of liquidity shortage for debtors (Detragiache et al., 2000). In this paper, we aim to show how the interaction of these two aspects with solvency and liquidity requirements might have implications for the stability of the banking system, which might still need to be fully analyzed. We show that if other sources of liquidity are unavailable or too costly for banks, multiple lending might be a key element in a systemic liquidity shortage and a large drop in lending to the economy. These findings are particularly relevant for understanding how macroeconomic shocks, such as the relatively recent outbreak of COVID-19, could impact the real economy, as well as for assessing the implications of alternative banking resolution mechanisms.

Herding behavior and systemic risk in global stock markets

This paper provides new evidence of herding due to non- and fundamental information in global equity markets. Using quantile regressions applied to daily data for 33 countries, we investigate herding during the Eurozone crisis, China's market crash in 2015–2016, in the aftermath of the Brexit vote and during the Covid-19 Pandemic. We find significant evidence of herding driven by non-fundamental information in case of negative tail market conditions for most countries. This study also investigates the relationship between herding and systemic risk, suggesting that herding due to fundamentals increases when systemic risk increases more than when driven by non-fundamentals. Granger causality tests and Johansen's vector error-correction model provide solid empirical evidence of a strong interrelationship between herding and systemic risk, entailing that herding behavior may be an ex-ante aspect of systemic risk, with a more relevant role played by herding based on fundamental information in increasing systemic risk.

How Crisis Affects Crypto: Coronavirus as a Test Case

Everybody is talking about cryptocurrencies. These digital tokens, which started in a one-asset market, have swiftly ballooned into a massive and diverse "cryptomarket. " The cryptomarket is still mostly unregulated, but this is about to change. With President Biden's adoption of the Executive Order on Ensuring Responsible Development of Digital Assets, regulatory initiatives are being adopted abroad, and global regulation looms ahead. In light of the expected regulatory changes, two important questions emerge: is there a clear rationale for legal intervention in the cryptomarket? And if so, what type of regulation is optimal?This Article is the first to consider how to regulate the cryptomarket through an empirical analysis of how the COVID-19 crisis affected the cryptomarket. We take a two-step approach to answer these pivotal questions. First, we analyze empirical evidence from the early days of the COVID-19 pandemic to better understand the risks posed by the cryptomarket when a crisis emerges. Second, we apply a law-and-economics approach to identify which market failures are consistent with the data and derive novel regulatory lessons. Our empirical analysis reveals an interesting pattern: investors initially shifted funds to the cryptomarket when the pandemic erupted, but then made a U-turn and diverted funds out of cryptocurrencies, leading to a plunge in the market. We maintain that such investor behavior can have both rational and behavioral explanations, which in turn affects the optimal choice of regulation.Accordingly, we map each rational and behavioral explanation onto potential market failures by surveying different possible interpretations of our findings, such as substitution effects between traditional markets and the cryptomarket, exploitation of investors in the form of pump-and-dump schemes, and other criminal activities. We then discuss how each type of failure can serve as justification for regulation and derive regulatory lessons on how to best intervene in the cryptomarket depending on the source of the market failure.

Global Systemic Risk Dynamic Network Connectedness during the Covid-19: Evidence from Nonlinear Granger Causality

This study examined the global systemic risk network connectedness during the COVID-19 pandemic by focusing on the stock, bond, and foreign exchange markets of 14 countries (2000–2021). We found that the commonality among multiple markets was high, while the systemic risk of COVID-19 was smaller than that of the 2007–2008 financial crisis. Additionally, the exposure of bond markets to systemic risk was larger than the exchange rate and stock markets. Although the stock and bond markets were the main sources of risk during the pandemic, the foreign exchange market had the strongest connection with the global financial network.

The mean reversion/persistence of financial cycles: Empirical evidence for 24 countries worldwide

Research background: The globalization trend has inevitably enhanced the connectivity of global financial markets, making the cyclicality of financial activities and the spread of market imbalances have received widespread attention, especially after the global financial crisis. Purpose of the article: To reduce the negative effects of the contagiousness of the financial cycles, it is necessary to study the persistence of financial cycles and carve out the total connectedness, spillover paths, and sources of risks on a global scale. In addition, understanding the relationship between the financial cycle and economic development is an important way to prevent financial crises. Methods: This paper adopts the nonlinear smoothing transition autoregressive (STAR) model to extract cyclical and phase characteristics of financial cycles based on 24 countries during 1971Q1?2015Q4, covering developed and developing countries, the Americas, Europe, and Asia regions. In addition, the frequency connectedness approach is used to measure the connectedness of financial cycles and the relationship between the global financial cycle and the global economy. Findings & value added: The analysis reveals that aggregate financial cycles persist for 13.3 years for smoothed and 8.7 years for unsmoothed on average. The national financial cycles are asynchronous and exhibit more prolonged expansions and faster contractions. The connectedness of financial cycles is highly correlated with systemic crises and contributes to the persistence and harmfulness of shocks. It is mainly driven by short-term components and exhibits more pronounced interconnectedness within regions than across regions. During the financial crisis, the global financial cycle movements precede and are longer than the business fluctuations. Based on the study, some policy implications are presented. This paper emphasizes the impact of systemic crises on the persistence of financial cycles and their connectedness, which contributes to refining research related to the coping mechanisms of financial crises.

Analyzing the Stock Volatility Spillovers in Chinese Financial and Economic Sectors

By regarding the Chinese financial and economic sectors as a system, this article studies the stock volatility spillover in the system and explores its effects on the overall performance of the macroeconomy in China. The recent outbreak of COVID-19, U.S.-China trade friction, and three historical financial turbulences are involved to distinguish the changes in the spillover in these distinct crises, which has seldom been unveiled in the literature. By considering that the stock volatility spillover may vary over distinct timescales, the spillovers are disclosed through innovatively constructing the multi-scale spillover networks, followed by connectedness computation, based on variational mode decomposition (VMD) and generalized vector autoregression (GVAR) process. Our empirical analysis first demonstrates the different levels of increases in the total sectoral volatility spillover and changes in the roles of the sectors in the system under the aforementioned crises. Besides, the increases in the sectoral spillover in the long-term are verified to negatively impact the macroeconomy and can thereby act as warning signals.

Volatility Spillovers between Stock and Energy Markets during Crises: A Comparative Assessment between the 2008 Global Financial Crisis and the Covid-19 Pandemic Crisis

This paper investigates volatility spillovers between energy and stock markets during periods of crises. Our main findings reveal that transmissions of volatilities among these markets during the Covid-19 pandemic crisis exceeded the ones recorded throughout the 2008 global financial crisis. All stock markets are net transmitters of volatility to energy markets during the 2008 global financial crisis while they show different patterns during the Covid-19 crisis. We also provide evidence of asymmetric volatility spillovers among stock and energy markets. Our results also indicate that on average natural gas provides better hedging effectiveness to the stock markets than crude oil.

Stock-bond dependence and flight to/from quality

This paper investigates the stock-bond dependence structure using a dependence-switching copula model. The model allows stock-bond dependence to switch between positive dependence regimes (contagions or crashes of the two markets during downturns or booms in both markets during upturns) and negative dependence regimes (flight-to-quality from stock markets to bond markets or flight-from-quality from bond markets to stock markets). Using data from four developed markets including the US, Canada, Germany, and France for the period between January 1985 and August 2022, we find that the within-country stock-bond (extreme) dependence could be both positive and negative. In the positive dependence regimes, the stock-bond dependence is asymmetric with stronger left tail dependence than the right tail dependence, giving evidence of a higher likelihood of joint stock-bond market crashes or contagions during market downturns than the collective stock-bond market booms. Under the negative dependence regimes, we find both flight-from-quality and flight-to-quality, with flight-to-quality being more dominant in the North American markets while flight -from-quality is more prominent in the European markets. Further, the dependence switches between positive and negative regimes over time. Moreover, the dependence is mainly in the positive regimes before 2000 while mostly in the negative regimes after that, indicating contagions mostly before 2000 and flights afterwards. Further, the dependence switches between positive and negative regimes around financial crises and the COVID-19 pandemic. These results greatly enrich the findings in the existing literature on the co-movements of stock-bond markets and are important for risk management and asset pricing.

The systemic risk in Thailand: the role of tourism industry

The study analyses the contribution of the tourism, banking, property fund and real estate, and finance and securities industries to the systemic risk of Thailand. Using quantile regression, the study estimates the measures of systemic risk (conditional Value-at-Risk (CoVaR) and delta conditional Value-at-Risk ( increment CoVaR)) and examines the relevance of various industries in increasing the systemic risk of Thailand using Kolmogorov - Smirnov test. The findings support the relevance of the tourism industry in significantly contributing to the systemic risk in Thailand. The study also highlights the systemic relevance of the tourism industry during the COVID-19 period in Thailand, when the industry was severely impacted, which adversely affected its systemic risk.

The systemic risk of US oil and natural gas companies

We analyse the evolution of the systemic risk impact of oil and natural gas companies since 2000. This period is characterised by several events that affected energy source markets: the real effect of the global financial crisis, the explosion of shale production and the diffusion of the Covid-19 pandemic. The price of oil and natural gas showed extreme swings, impacting companies' financial situations, which, accompanied by technological developments in shale production, had an impact on the debt issuance and on the overall risk level of the oil and natural gas sector. By studying the systemic impact of oil and natural gas companies on risk in the financial market, measured by the ΔCoVaR, we observe that in the most recent decade, their role is sensibly increasing compared to 2000–2010, even accounting for the possible effect associated with the increase in companies' sizes. In addition, our results show evidence of a decreasing relevance of traditional drivers of systemic risk, suggesting that additional factors might be present. Finally, when focusing on the impact of Covid-19, we document its relevant role in fuelling the increase in the oil and natural gas companies' systemic impact. © 2023 The Authors

Macroprudential policy and institutional arrangement

Experience shows that various economic and financial crises, including the COVID-19 pandemic, pose complex challenges for the central bank when it comes to implementing macroprudential policy. From a broader perspective, macroprudential policy consists of three pillars-balanced intermediation, system resilience and inclusion-which correspond to the problems that need to be addressed by central bank policy. In the future, macroprudential policy will encounter challenges associated with digitalization and the surge of fintech and bigtech, increasing social inequality, and climate-change risks, all of which will embolden policy transformation and the innovation of its instruments. © BI Institute 2022. All rights reserved.

Systemic Risk of China's Financial Industry during the Spread of the COVID-19 Epidemic and the Breakdown of Crude Oil Negotiation

This research first adopts three indicators to measure the systemic risk of different financial industries in China. Second, we employ the Time Varying Parameter-Stochastic Volatility-Vector Auto Regression (TVP-SV-VAR) model to investigate the time-varying relationship among COVID-19 epidemic, crude oil price, and financial systemic risk. The results herein not only help us grasp the current level of systematic risk in China, but also can assist at improving the early warning risk indicators and enhance the risk management system. Lastly, this research can also help investors to make reasonable asset planning.

Diversification benefits of NFTs for conventional asset investors: Evidence from CoVaR with higher moments and optimal hedge ratios

This study investigates the risk and returns on one of the newest digital asset classes instruments, non-fungible tokens (NFTs), by accounting for tail dependence of higher-order moments and portfolio characteristics. We used a wide range of asset classes, encompassing equites, fixed income securities, and commodities, and document the desirable hedging and portfolio attributes of NFTs by employing Conditional Value-at-Risk (CoVaR) and ∆CoVaRs with various copula functions. We found that NFTs exhibit beneficial investment and hedging attributes under all market conditions, including the Covid-19 pandemic. Our findings have important implications for investors, risk managers, and regulators. © 2023 Elsevier B.V.

Unpacking systemic, cascading, and compound risks: A case based analysis of Asia Pacific

The Sendai Framework for Disaster Risk Reduction aims to reduce disaster risk and loss by prioritizing activities that promote a better understanding of disaster risk. It prioritizes activities such as understanding disaster risk and its dimensions, with a focus on preventing the creation of new risks, reducing existing ones, and preparing for residual risks. The concept of systemic, cascading, and compound risks is becoming increasingly important in disaster risk management. However, there is a lack of understanding about these terms and how they overlap and differ in real-world applications. The COVID-19 pandemic has highlighted the evolving and underlying risk patterns in our interconnected society, making it crucial to bridge this gap. The paper explores the existing literature on systemic, cascading, and compound risks, using a secondary literature review and content analysis. It provides a conceptual overview of the three risks and supports the review with an analysis of 40 case studies in the Asia Pacific region. The analysis focuses on the hazards, underlying vulnerabilities, impacted systems, and the complex interconnections between them. Based on the findings, the authors provide recommendations for the management of systemic, cascading, and compound risks in the future. © 2023

Multilayer networks in the frequency domain: Measuring extreme risk connectedness of Chinese financial institutions

We propose multilayer networks in the frequency domain, including the short-term, medium-term, and long-term layers, to investigate the extreme risk connectedness among financial institutions. Using the conditional autoregressive value at risk (CAViaR) tool to measure the extreme risk of financial institutions, we construct extreme risk networks and inter-sector extreme risk networks of 36 Chinese financial institutions through the proposed approach. We observe that the extreme risk connectedness across financial institutions is heterogeneous in the short-, medium-, and long-term. In general, the long-term connectedness among financial institutions rises sharply during times of financial stress, such as the 2015 Chinese stock market turbulence and the 2020 COVID-19 pandemic. Moreover, we note that the insurers are key players in driving the inter-sector extreme risk networks, because the inter-sector systemic importance of insurance institutions is dominant. Finally, our conclusions provide valuable information for regulators to prevent systemic risk. © 2023 Elsevier B.V.

The social construction of systemic risk: towards an actionable framework for risk governance

Purpose: This paper explores the building blocks of risk governance systems that are equipped to manage systemic risk in the 21st century. Whilst approaches to risk governance have been evolving for more than a decade, recent disasters have shown that conventional risk management solutions need to be complemented with a multidimensional risk approach to govern complex risks and prevent major, often simultaneous, crises with cascading and knock-on effects on multiple, interrelated systems at scale. The paper explores which risk governance innovations will be essential to provide the enabling environment for sustainable development that is resilient to interrelated shocks and risks. Design/methodology/approach: This interdisciplinary literature review-based thought piece highlights how systemic risk is socially constructed and identifies guiding principles for systemic risk governance that could be actionable by and provide entry points for local and national governments, civil society and the private sector. particularly in low- and middle-income countries (LMIC), in a way that is relevant to the achievement of the 2030 Agenda for Sustainable Development. This considers preparedness, response and resilience, but more importantly prospective and corrective risk control and reduction strategies and mechanisms. Only when systemic risk is framed in a way that is relevant to the political agendas of countries will it be possible to begin a dialogue for its governance. Findings: The paper identifies opportunities at the global, national and local levels, which together draw up a viable framework for systemic risk governance that (1) embraces the governance of sustainability and resilience through a strengthened holistic governance framework for social, economic, territorial and environmental development;(2) improves managing conventional risk to ultimately manage systemic risks;(3) fosters the understanding of vulnerability and exposure to gain insight into systemic risk;(4) places a greater focus on prospective risk management;(5) manages systemic risk in local infrastructure systems, supply chains and ecosystems;(6) shifts the focus from protecting privatized gains to managing socialized risk. Originality/value: The choices and actions that societies take on the path of their development are contributing intentionally or unintentionally to the construction of systemic risks, which result in knock-on effects among interconnected social, environmental, political and economic systems. These risks are manifesting in major crises with cascading effects and a real potential to undermine the achievement of the SDGs, as COVID-19 is a stark reminder of. This paper offers the contours of a new risk governance paradigm that is able to navigate the new normal in a post-COVID world and is equipped to manage systemic risk. © 2023, Emerald Publishing Limited.

Systemic risk and financial system network using financial risk meter: the case of Vietnam

In the financial market, systemic risk is defined as the possibility that an event at the company level could trigger severe instability or collapse of an entire industry or the whole economy. Thus, understanding systemic risk is crucial for the financial institutions, large corporations, investors and regulators. This article investigates systemic risk and spillover effect using the new Financial Risk Meter ((Formula presented.)) index, which is obtained from running quantile linear regression and Least Absolute Shrinkage and Selection Operator ((Formula presented.)) method. The (Formula presented.) index is obtained to identify the highly risky periods, the contributors to systemic risk and the potential activators of spillover effect. Moreover, interconnection between firms can be visualized as a network. We use a data set consisting of daily stock returns from 35 financial institutions and real estate firms in Vietnam, combined with 4 macroeconomic variables over the period from November 2011 to December 2020. The findings indicate that over the considered period, some detected highly risky periods are 2012, 2018 and 2020, probably due to the non-performing loan crisis in Vietnam, US-China trade war and global COVID-19 outbreak. Some active activators of risk spillover effect are also identified. © 2023 Informa UK Limited, trading as Taylor & Francis Group.