Market-based Risk Measures Research Articles

The Emotion Magnitude Effect: Navigating Market Dynamics Amidst Supply Chain Events

During the volatile market period of 2019–2021, characterized by geopolitical shifts, economic sanctions, pandemics, natural disasters, and wars, the global market presented a complex landscape for financial decision making and motivated this study. This study makes two groundbreaking and novel contributions. First, we augment Plunket’s emotional research and leverage the emotional classification algorithm in Fin-Emotion to introduce a novel quantitative metric, “emotion magnitude”, that captures the emotional undercurrents of the market. When integrated with traditional time series analysis using Temporal Convolutional Networks applied to stock market futures, this metric offers a more holistic understanding of market dynamics. In our experiments, incorporating it as a feature led to significantly better performance on both the training and validation sets (9.26%, 52.11%) compared to traditional market-based risk measures, in predicting futures market trends based on the commodities and supply chains analyzed. Second, we deploy a multidimensional data science framework that synthesizes disparate data streams and analyses. This includes stock metrics of sector-leading companies, the time horizon of significant market events identified based on company stock data, and the extraction of further knowledge concepts identified through “emotion magnitude” analysis. Our approach stitches together countries, commodities, and supply chains identified in the targeted news search and identifies the domestic companies impacted based on the time horizon of these emotional supply chain events. This methodology culminates in a unified knowledge graph that not only highlights the relationships between supply chain disruptions, affected corporations, and commodities but also quantifies the broader systemic implications of such market events that are revealed. Collectively, these innovations form a robust analytical tool for financial risk strategy, empowering stakeholders to navigate an ever-evolving financial global ecosystem with enhanced insights. This graph encapsulates multi-dimensional forces and enables stakeholders to anticipate and understand the broader causal implications of related supply chain and market events (such as economic sanctions’ impact on the energy, technology, and telecommunication sectors).

Bank competition, regulatory capital, and risk taking: international evidence

PurposeMotivated by recent financial liberalization policies in emerging markets, this study investigates whether bank competition and regulatory capital affect bank risk taking in an international banking context.Design/methodology/approachBank competition is regressed, using GLS regression, on various measures of bank risk, to reflect regulatory, accounting and market-based risk-taking. The authors use a sample of publicly traded banks operating in Africa during 2004–2019.FindingsResults show that higher level of bank competition increases bank risk taking and results in greater financial fragility in the absence of banking capital regulations. Furthermore, larger capital adequacy ratios control the risk-taking incentives of managers and guard banks against the risk of default. Further tests confirm the significance of market-based risk measures over accounting and regulatory measures.Practical implicationsFindings are relevant to bank managers and regulators in their sustained effort of finding an optimal balance between bank competition and financial stability. Increased competition should be balanced with capital regulations to curtail bank excessive risky behavior and derive the social benefits of greater competition in the market while sustaining overall economic growth.Originality/valueThis study provides novel evidence in an international context. First, it uses regulatory, accounting and market-based measures of bank risk taking to reflect regulators', management and market participants' emphasis. Another original contribution is the investigation of bank competition across African economies characterized by financial liberalization, stringent banking system and interesting socio-economic challenges.

Climate-change scenarios require volatility effects to imply substantial credit losses: shocks drive credit risk not changes in economic trends

IntroductionLong-run Macro-Prudential stability objectives for the banking system have recently motivated a detailed focus on potential future credit risks stemming from climate change. Led by regulators and the NGFS, early approaches apply smooth, top-down scenarios that utilize carbon emissions data combined with physical risk metrics. This general climate stress test approach assesses future credit losses for individual firms and the banking system. While the NGFS approach is in its infancy, a number of discussion points have been raised related to how the approach assesses future credit risks. In contrast to the NGFS approach that focuses on changes to long-run economic growth trends, higher credit risks generally arise from unexpected economic shocks to cashflows and asset values. Systematic shocks that impact many firms like those observed during the last three economic recessions clearly produce higher volatility and systematic deviations from average economic trends.MethodsIn this paper we briefly review aspects of current climate stress test approaches to set the context for our primary focus on assessing future climate induced credit risk and credit risk volatility using a multi credit-factor portfolio framework applied to a benchmark US C&I credit portfolio. First we compare various NGFS climate scenarios using NGFS GDP measures to a CCAR severely adverse stress scenario. We then undertake two additional assessments of future climate driven credit risk by applying an assumed relationship between NGFS global mean temperatures (GMTs) and credit-factor volatilities. All three prospective climate credit risk assessments utilize an empirically-based, credit-factor model estimated from market-based measures of credit risk to highlight the potential role for climate induced increases in volatility. The potential future drivers of volatility could stem from narrower physical risks or broader macro-economic, social or other systematic shocks driven by climate change. All three predicted credit loss assessments suggest that volatility not changes to economic trends ultimately drives higher potential credit risks relating to climate change.ContributionsThe key contributions of this paper are the application of empirically based credit factor models combined with higher climate-driven volatility assumptions that support statistical assessment of how climate change could impact credit risk losses.

Financial crisis probability measurement model

Methods. The research used the method of analysis and synthesis – to clarify the nature of modern financial crises, the method of grouping – to determine the types of financial crises, general and specific – to differentiate between different types of financial crises, econometric methods – to quantify the level of systemic risk in the financial sector that leads to the financial crisis. Results. Excessive credit growth, the main cause of financial crises, is reflected in the insufficient capitalization of the financial sector. The paper briefly reviews the theoretical and empirical studies on the developments in these markets around the financial crisis. Market-based measures of systemic risk, such as SRISK, which stands for systemic risk, allow monitoring of how such vulnerabilities emerge and progress in real time. Novelty. This paper presents a quantitative assessment of the level of systemic risk in the financial sector that leads to a financial crisis. The model builds on the theory that deleveraging will have a price impact and the greater the magnitude of the deleveraging, the more dangerous the adjustment. In its most extreme case, the real economy has restricted access to credit as the financial sector experiences a fire sale, thus endogenously generating a financial crisis. Practical value. In an econometric framework, the relationship between SRISK and severity of financial crisis for different developed countries is given. The paper focuses on financial crises characterized by disruptions in credit supply, the lower tail of which may be related to various factors. A report on the probability of a financial crisis is provided in real-time from an indication of excessive credit growth. The study shows the important role of the cross-border external effect of financial noncapitalization.

Credit booms and bank risk in Southeast Asian countries: does credit information sharing matter?

PurposeThis study investigates the relationship between credit booms and bank risk in Association of Southeast Asian Nations (ASEAN) countries, with credit information sharing acting as a moderator.Design/methodology/approachThe authors use a two-step System Generalized Method of Moments (SGMM) estimator on a sample of 79 listed banks in 5 developing ASEAN countries: Indonesia, Philippines, Malaysia, Thailand and Vietnam in the period 2006–2019. In addition, the authors perform robustness tests with different proxies for credit booms and bank risk. The data are collected on an annual basis.FindingsBank risk is positively related to credit booms and is negatively associated with credit information sharing. Further, credit information sharing reduces the detrimental effect of credit booms on bank stability. The authors find that both public credit registries and private credit bureaus are effective in enhancing bank stability in ASEAN countries. These results are robust to regression models with alternative proxies for credit booms and bank risk.Research limitations/implicationsBanks in ASEAN countries tend to have strong lending growth to support the economy, but this could be detrimental to stability of the sector. Credit information sharing schemes should be encouraged because these schemes might enable growth of credit without compromising bank stability. Therefore, policymakers could promote private credit bureaus (PCB) and public credit registries (PCR) to realize their benefits. The authors' research focuses on developing ASEAN countries, but future research could provide more evidence by expanding this study to other emerging economies. In-depth interviews and surveys with bankers and regulatory bodies about these concerns could provide additional insights in the future.Originality/valueThe study is the first to examine the role of PCB and PCR in alleviating the negative impact of credit booms on bank risk. Furthermore, the authors use both accounting-based and market-based risk measures to provide a fuller view of the impact. Finally, there is little evidence on the link between credit booms, credit information sharing and bank risk in ASEAN, so the authors aim to fill this gap.

On the information content of credit ratings and market-based measures of default risk

We examine the ability of ratings and market-based measures to predict defaults. Although market-based measures are more accurate at horizons up to one year, ratings complement market-based measures and are not redundant in predicting defaults across horizons. Market-based measures differ from ratings in that they respond to both cash-flow and discount-rate news, while ratings respond primarily to cash-flow news, which is more informative of future defaults. Ratings ignore transitory shocks to credit risk, while market-based measures do not. Rating agencies respond to transitory shocks with watches rather than downgrades. Ratings are more informative during expansions and for speculative grade firms.

Measuring bank risk: Forward-looking z-score

While the z-score has been widely used to evaluate bank risk, it is criticized as a backward-looking measure. We propose a forward-looking method to construct the z-score by incorporating analyst forecasts. Empirical results show that the forward-looking z-score can predict the movement of the standard z-score one quarter ahead of time, and its predictive ability on banks' downward risk is better than the standard z-score. Moreover, we find that the predictive ability of the forward-looking z-score improves after the Dodd-Frank Act of 2010, especially for large banks, showing the consequences of strengthened regulation and transparency. The forward-looking z-score is also significantly associated with the probability of default and market-based risk measures and can provide predictive signals for banks' future profitability. Overall, our findings suggest that the forward-looking z-score mitigates the shortcomings of the standard z-score and provides a reliable early warning signal for banks' future risk and performance.

Fresh evidence on the relationship between market power and default risk of Indian banks

In a uniquely designed empirical set-up involving a large set of Indian banks, this study establishes the relationship between market-based measures of default risk represented by Distance-to-Default (DD) and Distance-to-Capital (DC), and the market power reflected through the efficiency-based Lerner index. The results exhibit an inverse relationship between bank market power and bank default risk. Gross Nonperforming Assets (GNPAs), economic growth, and stock market volatility appear as other significant determinants of bank default risk. In the Indian context, this is the first study that utilizes a bank risk measure that incorporates the capital adequacy thresholds embedded under the revised Prompt Corrective Action (PCA) framework.

Diversity and risk taking in Islamic banks: Does public listing matter?

This study examines two dimensions of diversity on the board of directors (BOD) and the sharia supervisory board (SSB), namely, gender diversity and educational diversity, and their influence on risk taking by Islamic banks. The study extends the literature by examining whether the influence of gender and educational diversity on Islamic banks' risk taking differs based on whether the bank is publicly listed. Based on a sample of Islamic banks in twenty-six countries, the findings suggest that greater representation of women on the BOD decreases the insolvency risk at listed Islamic banks and that the educational diversity of BOD and SSB members has a significant influence on Islamic banks’ risk taking, conditional on whether they are publicly listed. The results are robust to market-based risk measures and the use of a difference–generalized method of moments estimator and propensity score matching technique.

Holding company affiliation and bank stability: Evidence from the US banking sector

Is affiliation with a multibank holding company beneficial for bank stability? We revisit this question by examining the response of market-based risk measures of independent and multibank-holding-company banks to an exogenous negative shock (the 2005 US hurricane season). We find evidence consistent with bank holding companies playing an important role in mitigating negative shocks, with affiliates of more liquid holdings remaining more stable in terms of both systemic and individual stability. We also conduct an event study showing that markets perceive multibank-holding-company banks' dynamics after the shock as value-enhancing.

ESG Didn’t Immunize Stocks Against the Covid-19 Market Crash

Environmental, social, and governance (“ESG”) scores have been widely touted as indicators of share price resilience during the COVID-19 crisis. Contrary to this conventional wisdom, we present robust evidence that, once industry affiliation, market-based measures of risk, and accounting-based measures of performance, financial position, and intangibles investments have been controlled for, ESG offers no such positive explanatory power for returns during the COVID crisis. Specifically, ESG is insignificant in fully specified returns regressions for each of the Q1 2020 COVID market crisis period, and for the full COVID year of 2020. By contrast, a measure of the firm’s stock of investments in internally generated intangible assets is an economically and statistically significant positive determinant of returns during each of the Q1 market implosion and full 2020 COVID year periods. Our results are robust to alternative measures of returns, as well as to using Refinitiv, Refinitiv II, and MSCI data to capture ESG performance. We conclude that ESG did not immunize stocks during the COVID-19 crisis, but that investments in intangible assets did.

Measuring and mitigating systemic risks: how the forging of new alliances between central bank and academic economists legitimize the transnational macroprudential agenda

After the great financial crisis of 2007–2009, central banks were handed a macroprudential mandate to contain systemic risks, a mandate seen as endangering their independence due to expected distributional conflicts. At the same time, depoliticization through scientific expertise was largely foreclosed, as systemic risk was a largely undefined concept. This paper focuses on how central banks dealt with this conundrum. It examines the scientific debate on systemic risk and macroprudential regulation post-crisis, focusing on the debate’s impact on final regulation. Employing author-topic-modeling on a unique dataset of 2397 published economic papers on the relevant topics, we detect the formation of a new alliance between central bankers and academic economists working jointly on developing systemic risk measures. Centered around a hinge of systemic risk contribution by individual banks, this new alliance expresses itself by incorporating the macroprudential concerns of practitioners into abstract market-based systemic risk measures. These measures develop incrementally, using and repurposing techniques from financial economics pre-crisis to legitimize and justify macroprudential interventions post-crisis. This alliance allows us to account for the incremental change witnessed post-crisis and point to its potential for long-term fundamental change.

An Empirical Examination of the Term Structure Fundamentals of Credit Spreads

Using an exponential model of jumps to default, this research investigates the fundamentals that determine the spreads required by investors for corporate credit risk at different maturities. The empirical results indicate that credit default swap (CDS) prices across the term spectrum are strongly associated with interrelated probabilities of cash, income, and valuation insolvency, as well as with market-based measures of systematic risk. Although the financial functions best-fitting CDS prices are found to vary somewhat by maturity, an integrated model with constant parameters across time, company, and term is found to explain about 50% of individual credit spreads both in sample and ex post. <b>TOPICS:</b>Credit risk management, credit default swaps <b>Key Findings</b> • Using nonnegative least squares procedures to find the structural model forms which best fit credit spreads across the term structure, this empirical research explains more than half of individual credit default swap prices in and out of sample. • Credit default swap prices with shorter terms (like 1–3 years) are found to be most strongly determined by the probability of a company generating negative income and running out of cash, but the likelihood of cash and income insolvency is discovered to have important impacts at longer maturities of 5–10 years. • The 378,401 individual credit spreads in the sample over the 2008–2019 interval are found to incorporate time-varying systematic risk premiums (estimated from market prices), as well as reflect the integrated risks of income, cash, and valuation insolvency on any day.

Why discontinue operations? Interrelated elements of the corporate focus hypothesis

PurposeThe purpose of this paper is to reexamine the corporate focus hypothesis to establish the characteristics of firms that discontinue operations. The authors concentrate on four interrelated elements of the hypothesis, diversification, performance, financial constraint and market-based risk measures. The authors also examine whether firms reporting positive- or negative-valued discontinued operations have different characteristics.Design/methodology/approachAnalyzing discontinued operations provides a broad sample of strategically important exit decisions using a variety of different disposal methods. The authors use logistic regression models to explore whether the elements of the corporate focus hypotheses, and interactions between them, explain decisions to discontinue operations, and also the differences between firms making negative- and positive-valued announcements.FindingsFirms that discontinue operations are more diverse, with weak operating performance, higher financial constraints and perform poorly in financial markets. Interrelationships between these factors strongly affect exit decisions. Companies reporting negative-valued discontinued operations are smaller, make lower capital investments and face greater cash constraints and market risk. Those announcing positive-valued discontinuations are larger and make higher payouts and capital expenditures. Their overall performance is weaker than for control firms, but clearly superior to companies discontinuing negative-valued operations.Originality/valueDiscounted operations represent a wide range of exit decisions. They provide a much larger sample than most previous studies of divestitures. The authors include β, the Sharpe ratio, cash holdings, payouts to shareholders, capital expenditures and also cross-product terms between the elements of the corporate focus hypothesis, all of which have received little attention in prior research. There are significant differences between firms announcing positive and negative-valued discontinued operations.

Networks and market-based measures of systemic risk: the European banking system in the aftermath of the financial crisis

This article investigates the behaviour of the European banking system during the financial crises that occurred in the last decades. Among the various approaches for measuring systemic risk, we consider network analysis, which describes the linkages among financial institutions and their whole structure. We construct a time-varying network of the European banking system. Banks are linked to form a global interconnected system and they mutually influence one another in terms of risk. We model their reciprocal influence via a weighted and directed network, in which weights are related to risk measures that are based on equity returns. Then, we apply two network indicators to investigate the prominence of a bank in spreading and receiving risk from the others. The results enable us to capture many features of the banking system while identifying the global systemically important banks. Moreover, the results of the analysis over time show how interconnections change over periods that are characterized by various economic scenarios.

VOLATILITY MEASURES, LIQUIDITY AND CREDIT LOSS PROVISIONS DURING PERIODS OF FINANCIAL DISTRESS

In this paper, we investigate the role of liquidity in banks lending activity and how liquidity provision is related to bank’s credit risk and others market-based risk measures, such as bank’s implied volatility skew from options traded on the market and realized volatility from futures contract on LIBOR, during periods of global financial distress. Credit risk is given by the ratio between loan loss reserves and total assets and we find that losses from lending activity force banks to build up new liquidity provisions only during the period of financial distress. Liquidity ratio is given by the sum of cash and short-term assets over total assets and we discovered that credit risk reduces liquidity ratio only in bad times, as this demand for liquid asset is suddenly switched on and the more reserves from loan losses the bank has, the more it cleans its balance sheet from long-term commitments in order to replenish its cash and short-term securities. When we control for market-based risk measures, we evidence that both implied volatility skew and LIBOR’s realized volatility are negatively related with the liquidity ratio and are useful in predicting a distress in bank’s liquidity holdings.

Correlation between the 2014 EU-wide stress tests and the market-based measures of systemic risk

In this paper, we compare the results of the European Banking Authority (EBA) stress tests conducted in 2014 with the market-based measures of capital losses, which are the marginal expected shortfall (MES), the systemic risk measure (SRISK) and the delta conditional value at risk (ΔCoVaR). These measures allow us to estimate the expected capital shortfall in the case of a crisis. The empirical analysis is performed on a sub-sample of the banks included in the stress test exercise, because only 57 European banks, in 22 countries, are publicly traded. We find that the SRISK is the best predictor of systemic risk among the 3 systemic risk measures, since it is the most correlated with the stress test results. Furthermore, we focus on the realized outcomes (realized loss, realized return and realized volatility) and compare them with the 2014 EU stress test results.

Testing the Systemic Risk Differences in Banks

This paper contains a testing framework for the reliability of systemic risk measurement of banks, using the three leading market-based measures of systemic risk. We test whether the difference within the same category and across dfferent categories of systemic risk of individual banks is signifcant. We find that in general the systemic risk categories defined by the Financial Stability Board are dfferent from those constructed in a full pairwise comparison approach based on the market measures. Moreover, these dfferences were more pronounced during episodes of high market turbulence.To account for model risk we introduce a more robust ranking method based on nonparametric confidence intervals. We show that there is a large number of banks with overlapping confidence intervals of their market-based systemic risk measures.Further, similarity measures indicate that the scoring based rankings are not perfectly aligned with rankings produced by market based systemic risk measures.

Market Reaction to Banks' Accounting Valuation and Risk Reporting Choices

We examine banks’ discretion on accounting valuation and risk-weight reporting for investment securities and how these two aspects of securities reporting are associated with market-based risk measures. Using a sample of US publicly listed banks from 2001 to 2014, we find evidence indicating that the risk weight of available-for-sale (AFS) securities moderates the positive association between AFS accounting valuation and banks’ bid–ask spreads. However, such moderation is not valid for held-to-maturity (HTM) securities. Our model specifies the endogeneity in accounting classification and the decision in assigning risk weights for investment securities. Our results remain robust after controlling for macroeconomic conditions, bank-specific characteristics, and alternative measures of information asymmetry. In addition, we find that the negative moderation of regulatory risk weight is more pronounced in banks that are either weakly capitalized or engaged in earnings management.

Assessing sovereign default risk: A bottom-up approach

This study assesses sovereign default risk of individual U.S. states utilizing information about default risk at the company level. We link integrated risk factors of the private sector to the overall sovereign risk of state governments in conjunction with additional financial variables. Using data on Moody’s KMV expected default frequencies (EDFs) on corporate default risk, we derive credit risk indicators for different industries. Building on these measures, we then develop state level credit risk indicators encompassing industry compositions to explain the behaviour of credit default swap (CDS) spreads for individual states. We find that market-based measures of private sector credit risk are strongly associated with subsequent shifts in sovereign credit risk premiums, as measured by CDS spreads. The developed credit risk indicators are highly significant in forecasting sovereign CDS spreads at weekly and monthly sampling frequencies. Overall, our findings suggest a strong predictive link between market expectations of private sector credit quality and expectations of sovereign credit quality - a connection that is not directly discernible from scoring models.