The Experts below are selected from a list of 8931 Experts worldwide ranked by ideXlab platform
Simon Wolfe - One of the best experts on this subject based on the ideXlab platform.
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An Early Warning Indicator for Liquidity Shortages in the Interbank Market
International Journal of Finance & Economics, 2019Co-Authors: Andrea Eross, Andrew Urquhart, Simon WolfeAbstract:This study investigates an early warning indicator for liquidity shortages in the short‐term Interbank Market. To identify structural breaks and their persistence, an autoregressive two‐state regime switching model is presented. The variability in the LIBOR–OIS spread along with thresholds, which delimit four intensities, reveals regime changes consistent with liquidity crashes. The transition between the states is state dependent, and the posterior estimates for the crisis and noncrisis states are estimated using the Gibbs sampler. We forecast our early warning indicator up to December 2011 and show that the estimates are superior to a random walk with drift. Therefore, the model is an effective early warning indicator of an imminent liquidity shortage impacting the Interbank Market.
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propagation of endogenous liquidity shocks within the Interbank Market
Journal of International Money and Finance, 2016Co-Authors: Andrea Eross, Andrew Urquhart, Simon WolfeAbstract:A common assumption made in the literature is that financial risk is exogenous and therefore shocks originate from outside the system. However, in reality both exogenous and endogenous risk affect the smooth functioning of financial Markets, with the later having a more pronounced and at times devastating effect. We propose a novel multivariate endogenous model with time-varying transition probabilities which is able to describe the propagation of liquidity shocks in the Interbank Market while predicting liquidity crashes. We show that liquidity shocks, originating from movements of the US LIBOR-OIS spread, drive regime changes in the US-German bond spread.
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Liquidity Risk Contagion in the Interbank Market
Journal of International Financial Markets Institutions and Money, 2016Co-Authors: Andrea Eross, Andrew Urquhart, Simon WolfeAbstract:This paper studies liquidity risk contagion within the Interbank Market by assessing the long-run relationship of short-term interest rate spreads from January 2002 to December 2015. In particular, we model the interaction between the LIBOR–OIS spread, euro fixed-float OIS swap rate and the three-month US-German bond spread and discover strong evidence of structural innovations affecting the Interbank Market. We find that when the short-term Interbank Market is affected by a liquidity shock, the LIBOR–OIS spread is a leader in moving back to equilibrium, while the euro-dollar currency swap rate and the US-German bond spreads are followers. Moreover, we find long-run cointegrating relationships and bi-directional causality between the spreads. However, structural breaks identified as prospective financial crises affect the long-run relationships and liquidity shocks drive Interbank rates and spread fluctuations. Therefore, liquidity shocks propagating within the Interbank Market can forecast benchmark interest movements, and ultimately this has significant implications for policy-makers and Market players alike.
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An Early Warning Indicator for Liquidity Shortages in the Interbank Market: A Regime Switching Approach
SSRN Electronic Journal, 2015Co-Authors: Andrea Eross, Andrew Urquhart, Simon WolfeAbstract:The financial crisis of 2007-08 is recognised to be the worst crisis since the Great Depression of the 1930s and as a result, liquidity risk in the Interbank Market has gained increased attention. The main objective of this study is to create an early warning indicator for liquidity shortages in the short-term Interbank Market. To identify structural breaks and their persistence, a novel univariate two-state regime switching model is presented. The variability in the LIBOR-OIS spread along with thresholds of different levels reveal regime changes consistent with liquidity crashes. Thus, the model acts as an early-warning indicator of an imminent liquidity shortage striking the Interbank Market. Depending which state the system is in, the series is modelled either as a first-order autoregressive process, or as a Gaussian white noise process. The transition between the states is described by a Markov process, and the probability of being in a crisis or non-crisis period is estimated using Bayesian inference.
Andrea Eross - One of the best experts on this subject based on the ideXlab platform.
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An Early Warning Indicator for Liquidity Shortages in the Interbank Market
International Journal of Finance & Economics, 2019Co-Authors: Andrea Eross, Andrew Urquhart, Simon WolfeAbstract:This study investigates an early warning indicator for liquidity shortages in the short‐term Interbank Market. To identify structural breaks and their persistence, an autoregressive two‐state regime switching model is presented. The variability in the LIBOR–OIS spread along with thresholds, which delimit four intensities, reveals regime changes consistent with liquidity crashes. The transition between the states is state dependent, and the posterior estimates for the crisis and noncrisis states are estimated using the Gibbs sampler. We forecast our early warning indicator up to December 2011 and show that the estimates are superior to a random walk with drift. Therefore, the model is an effective early warning indicator of an imminent liquidity shortage impacting the Interbank Market.
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propagation of endogenous liquidity shocks within the Interbank Market
Journal of International Money and Finance, 2016Co-Authors: Andrea Eross, Andrew Urquhart, Simon WolfeAbstract:A common assumption made in the literature is that financial risk is exogenous and therefore shocks originate from outside the system. However, in reality both exogenous and endogenous risk affect the smooth functioning of financial Markets, with the later having a more pronounced and at times devastating effect. We propose a novel multivariate endogenous model with time-varying transition probabilities which is able to describe the propagation of liquidity shocks in the Interbank Market while predicting liquidity crashes. We show that liquidity shocks, originating from movements of the US LIBOR-OIS spread, drive regime changes in the US-German bond spread.
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Liquidity Risk Contagion in the Interbank Market
Journal of International Financial Markets Institutions and Money, 2016Co-Authors: Andrea Eross, Andrew Urquhart, Simon WolfeAbstract:This paper studies liquidity risk contagion within the Interbank Market by assessing the long-run relationship of short-term interest rate spreads from January 2002 to December 2015. In particular, we model the interaction between the LIBOR–OIS spread, euro fixed-float OIS swap rate and the three-month US-German bond spread and discover strong evidence of structural innovations affecting the Interbank Market. We find that when the short-term Interbank Market is affected by a liquidity shock, the LIBOR–OIS spread is a leader in moving back to equilibrium, while the euro-dollar currency swap rate and the US-German bond spreads are followers. Moreover, we find long-run cointegrating relationships and bi-directional causality between the spreads. However, structural breaks identified as prospective financial crises affect the long-run relationships and liquidity shocks drive Interbank rates and spread fluctuations. Therefore, liquidity shocks propagating within the Interbank Market can forecast benchmark interest movements, and ultimately this has significant implications for policy-makers and Market players alike.
-
An Early Warning Indicator for Liquidity Shortages in the Interbank Market: A Regime Switching Approach
SSRN Electronic Journal, 2015Co-Authors: Andrea Eross, Andrew Urquhart, Simon WolfeAbstract:The financial crisis of 2007-08 is recognised to be the worst crisis since the Great Depression of the 1930s and as a result, liquidity risk in the Interbank Market has gained increased attention. The main objective of this study is to create an early warning indicator for liquidity shortages in the short-term Interbank Market. To identify structural breaks and their persistence, a novel univariate two-state regime switching model is presented. The variability in the LIBOR-OIS spread along with thresholds of different levels reveal regime changes consistent with liquidity crashes. Thus, the model acts as an early-warning indicator of an imminent liquidity shortage striking the Interbank Market. Depending which state the system is in, the series is modelled either as a first-order autoregressive process, or as a Gaussian white noise process. The transition between the states is described by a Markov process, and the probability of being in a crisis or non-crisis period is estimated using Bayesian inference.
Maria Semenova - One of the best experts on this subject based on the ideXlab platform.
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Transparency and Market discipline: evidence from the Russian Interbank Market
Annals of Finance, 2020Co-Authors: François Guillemin, Maria SemenovaAbstract:This article investigates the role of bank voluntary disclosure, as a source of information about risk, in the Interbank Market. Using data on the 179 largest Russian banks over the period of 2004–2013 we test whether the ability to attract Interbank loans is sensitive to various transparency indices such as those disclosing bank risks, board composition, or even corporate event details. We show that larger but riskier banks—at least in terms of credit risk—behave more transparently and disclose more. The article is the first to provide evidence that the ability to attract funds in the Interbank Market is positively correlated with the degree of transparency. This result is stable for various aspects of disclosure.
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Market Discipline in the Interbank Market: Evidence from Russia
Eastern European Economics, 2015Co-Authors: Irina Andrievskaya, Maria SemenovaAbstract:The efficiency of the Interbank Market depends largely on its inherent disciplining mechanisms. This paper investigates the discipline mechanisms of Russia’s Interbank Market, testing the hypothesis that Market discipline in Russia was strong enough to constrain excessive risk-taking by participating banks before, during, and after the 2008–2009 financial crisis. The existence and efficiency of quantity-based Market discipline are investigated using the Arellano-Bover and Blundell-Bond linear dynamic panel-data estimations. Our approach detects Market discipline only during the financial crisis, not before or after. Even during the crisis, the efficiency of Market discipline in curbing bank risk-taking was rather low.
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Market Discipline and the Russian Interbank Market
SSRN Electronic Journal, 2013Co-Authors: Irina Andrievskaya, Maria SemenovaAbstract:The Interbank Market plays an important role in the overall function of the financial system. The efficiency of the Interbank Market, in turn, depends largely on its inherent disciplining mechanisms. This paper investigates the discipline mechanisms of Russia's Interbank Market, testing the hypothesis that Market discipline in Russia was strong enough to constrain excessive risk-taking by participating banks before, during, and after the 2008- 2009 financial crisis. The existence of quantity-based Market discipline is investigated using Heckman's sample selection model and the efficiency of Market discipline is studied with a panel data model. Our approach detects Market discipline only during the financial crisis, not before or after. Even during the crisis, its efficiency in curbing bank risk-taking was rather low. JEL Classification: G21, G01, P2. Keywords: Market discipline, Interbank Market, risk-taking, banks, Russia
Stefan Thurner - One of the best experts on this subject based on the ideXlab platform.
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Network topology of the Interbank Market
Quantitative Finance, 2004Co-Authors: Michael Boss, Helmut Elsinger, Martin Summer, Stefan ThurnerAbstract:We provide an empirical analysis of the network structure of the Austrian Interbank Market based on Austrian Central Bank (OeNB) data. The Interbank Market is interpreted as a network where banks are nodes and the claims and liabilities between banks define the links. This allows us to apply methods from general network theory. We find that the degree distributions of the Interbank network follow power laws. Given this result we discuss how the network structure affects the stability of the banking system with respect to the elimination of a node in the network, i.e. the default of a single bank. Further, the Interbank liability network shows a community structure that exactly mirrors the regional and sectoral organization of the current Austrian banking system. The banking network has the typical structural features found in numerous other complex real-world networks: a low clustering coefficient and a short average path length. These empirical findings are in marked contrast to the network structures that have been assumed thus far in the theoretical economic and econo-physics literature.
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an empirical analysis of the network structure of the austrian Interbank Market
Financial Stability Report, 2004Co-Authors: Michael Boss, Helmut Elsinger, Martin Summer, Stefan ThurnerAbstract:We provide an empirical analysis of the network structure of the Austrian Interbank Market based on a unique data set of the Oesterreichische Nationalbank (OeNB). The analysis relies on the idea that an Interbank Market can be interpreted as a network where the banks form the nodes and the claims and liabilities between them define the edges of the network. This approach allows us to apply results from general network theory, which is widely applied in other scientific disciplines — mainly in physics. Specifically, we use different measures from this network theory to investigate the empirical network structure of the Austrian banking system. We focus on the question of how this structure affects the stability of the network (the banking system) with respect to the elimination of a node in the network (the default of a single bank). Regarding the network structure, we find that there are very few banks with many Interbank linkages whereas there are many with only a few links. This feature of networks has been repeatedly found to be conducive to the robustness of the network against the random breakdown of links (the default of single institutions due to external shocks). In addition, the Interbank network shows a community structure that exactly mirrors the regional and sectoral organization of the current Austrian banking system. Moreover, the banking network has typical structural features found in numerous other complex real world networks: a low clustering coefficient and a relatively short average shortest path length. These empirical findings are in marked contrast to network structures that have been assumed in the theoretical economic and econo-physics literature.
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the network topology of the Interbank Market
arXiv: Condensed Matter, 2003Co-Authors: Michael Boss, Helmut Elsinger, Martin Summer, Stefan ThurnerAbstract:We provide an empirical analysis of the network structure of the Austrian Interbank Market based on a unique data set of the Oesterreichische Nationalbank (OeNB). We show that the contract size distribution follows a power law over more than 3 decades. By using a novel ''dissimilarity'' measure we find that the Interbank network shows a community structure that exactly mirrors the regional and sectoral organization of the actual Austrian banking system. The degree distribution of the Interbank network shows two different power law exponents which are one-to-one related to two sub-network structures, differing in the degree of hierarchical organization. The banking network moreover shares typical structural features known in numerous complex real world networks: a low clustering coefficient and a relatively short average shortest path length. These empirical findings are in marked contrast to Interbank networks that have been analyzed in the theoretical economic and econo-physics literature.
Andrew Urquhart - One of the best experts on this subject based on the ideXlab platform.
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An Early Warning Indicator for Liquidity Shortages in the Interbank Market
International Journal of Finance & Economics, 2019Co-Authors: Andrea Eross, Andrew Urquhart, Simon WolfeAbstract:This study investigates an early warning indicator for liquidity shortages in the short‐term Interbank Market. To identify structural breaks and their persistence, an autoregressive two‐state regime switching model is presented. The variability in the LIBOR–OIS spread along with thresholds, which delimit four intensities, reveals regime changes consistent with liquidity crashes. The transition between the states is state dependent, and the posterior estimates for the crisis and noncrisis states are estimated using the Gibbs sampler. We forecast our early warning indicator up to December 2011 and show that the estimates are superior to a random walk with drift. Therefore, the model is an effective early warning indicator of an imminent liquidity shortage impacting the Interbank Market.
-
propagation of endogenous liquidity shocks within the Interbank Market
Journal of International Money and Finance, 2016Co-Authors: Andrea Eross, Andrew Urquhart, Simon WolfeAbstract:A common assumption made in the literature is that financial risk is exogenous and therefore shocks originate from outside the system. However, in reality both exogenous and endogenous risk affect the smooth functioning of financial Markets, with the later having a more pronounced and at times devastating effect. We propose a novel multivariate endogenous model with time-varying transition probabilities which is able to describe the propagation of liquidity shocks in the Interbank Market while predicting liquidity crashes. We show that liquidity shocks, originating from movements of the US LIBOR-OIS spread, drive regime changes in the US-German bond spread.
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Liquidity Risk Contagion in the Interbank Market
Journal of International Financial Markets Institutions and Money, 2016Co-Authors: Andrea Eross, Andrew Urquhart, Simon WolfeAbstract:This paper studies liquidity risk contagion within the Interbank Market by assessing the long-run relationship of short-term interest rate spreads from January 2002 to December 2015. In particular, we model the interaction between the LIBOR–OIS spread, euro fixed-float OIS swap rate and the three-month US-German bond spread and discover strong evidence of structural innovations affecting the Interbank Market. We find that when the short-term Interbank Market is affected by a liquidity shock, the LIBOR–OIS spread is a leader in moving back to equilibrium, while the euro-dollar currency swap rate and the US-German bond spreads are followers. Moreover, we find long-run cointegrating relationships and bi-directional causality between the spreads. However, structural breaks identified as prospective financial crises affect the long-run relationships and liquidity shocks drive Interbank rates and spread fluctuations. Therefore, liquidity shocks propagating within the Interbank Market can forecast benchmark interest movements, and ultimately this has significant implications for policy-makers and Market players alike.
-
An Early Warning Indicator for Liquidity Shortages in the Interbank Market: A Regime Switching Approach
SSRN Electronic Journal, 2015Co-Authors: Andrea Eross, Andrew Urquhart, Simon WolfeAbstract:The financial crisis of 2007-08 is recognised to be the worst crisis since the Great Depression of the 1930s and as a result, liquidity risk in the Interbank Market has gained increased attention. The main objective of this study is to create an early warning indicator for liquidity shortages in the short-term Interbank Market. To identify structural breaks and their persistence, a novel univariate two-state regime switching model is presented. The variability in the LIBOR-OIS spread along with thresholds of different levels reveal regime changes consistent with liquidity crashes. Thus, the model acts as an early-warning indicator of an imminent liquidity shortage striking the Interbank Market. Depending which state the system is in, the series is modelled either as a first-order autoregressive process, or as a Gaussian white noise process. The transition between the states is described by a Markov process, and the probability of being in a crisis or non-crisis period is estimated using Bayesian inference.