The Experts below are selected from a list of 157992 Experts worldwide ranked by ideXlab platform
Jorge Ponce - One of the best experts on this subject based on the ideXlab platform.
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Systemic Risk: History, Measurement and Regulation
2019Co-Authors: Yvonne Kreis, Dietmar Leisen, Jorge PonceAbstract:Systemic Risk: History, Measurement and Regulation presents an overview of this emerging form of Risk from a global perspective. Systemic Risks endanger entire financial systems, not just individual financial institutions. In this volume, the authors review how Systemic Risk has evolved over the last 40 years across continents to come to the forefront of regulatory attention. They then discuss transmissions channels, provide a review of Systemic Risk measures, and describe new regulations that have been introduced, as well as the theory and practice of financial stability committees that have been set up internationally. Overall, the book provides a practical guide to understand, identify, assess and control Systemic Risk. While the financial research on Systemic Risk has strongly increased since the events of 2008, this book is a first in providing a detailed yet concise overview of the topic, covering the history of Systemic Risk, its measurement, and its regulation. The authors provide both academic and practitioner-oriented insights, and draw on their different regions of expertise to provide a global perspective on Systemic Risk.
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Characterizing Systemic Risk
2019Co-Authors: Yvonne Kreis, Dietmar Leisen, Jorge PonceAbstract:We start our discussion of Systemic Risk measures with broad economic concepts that influence this form of Risk. This prepares the ground for Systemic Risk measurement in Section 5.2. Finally, Section 5.3 provides an overview of measures based on market data…
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Defining Systemic Risk
2019Co-Authors: Yvonne Kreis, Dietmar Leisen, Jorge PonceAbstract:In Chapters 1–3, we have shown that Systemic events have common features across time and how a globalized financial system in the new century has created new challenges. Accordingly, the definition of what constitutes Systemic Risk has evolved over time. This chapter presents an overview of Systemic Risk and its evolution…
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Systemic Risk and Insurance Regulation
Risks, 2018Co-Authors: Fabiana Gómez, Jorge PonceAbstract:This paper provides a rationale for the macro-prudential regulation of insurance companies, where capital requirements increase in their contribution to Systemic Risk. In the absence of Systemic Risk, the formal model in this paper predicts that optimal regulation may be implemented by capital regulation (similar to that observed in practice, e.g., Solvency II ) and by actuarially fair technical reserve. However, these instruments are not sufficient when insurance companies are exposed to Systemic Risk: prudential regulation should also add a Systemic component to capital requirements that is non-decreasing in the firm’s exposure to Systemic Risk. Implementing the optimal policy implies separating insurance firms into two categories according to their exposure to Systemic Risk: those with relatively low exposure should be eligible for bailouts, while those with high exposure should not benefit from public support if a Systemic event occurs.
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Systemic Risk and insurance regulation
2018Co-Authors: Fabiana Gómez, Jorge PonceAbstract:Without Systemic Risk exposure, the formal model in this paper predicts that optimal regulation may be implemented by capital regulation (alike that observed in practice) and actuarially fair technical reserve. However, these instruments are not enough when insurance companies are exposed to Systemic Risk. In this case, prudential regulation should also add a Systemic component to capital requirements which is non-decreasing in the firm's exposure to Systemic Risk. Implementing the optimal policy implies to separate insurance firms in two categories according to their exposure to Systemic Risk: those with relatively low exposure should be eligible for bailouts, while those with high exposure should not benefit from public support if a Systemic event occurs.
Hersh Shefrin - One of the best experts on this subject based on the ideXlab platform.
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Sentiment, Asset Prices, and Systemic Risk
SSRN Electronic Journal, 2012Co-Authors: Giovanni Barone-adesi, Loriano Mancini, Hersh ShefrinAbstract:Regulators charged with monitoring Systemic Risk need to focus on sentiment as well as narrowly defined measures of Systemic Risk. This chapter describes techniques for jointly monitoring the co-evolution of sentiment and Systemic Risk. To measure Systemic Risk, we use Marginal Expected Shortfall. To measure sentiment, we apply a behavioral extension of traditional pricing kernel theory, which we supplement with external proxies. We illustrate the technique by analyzing the dynamics of sentiment before, during, and after the global financial crisis which erupted in September 2008. Using stock and options data for the S&P 500 during the period 2002–2009, our analysis documents the statistical relationship between sentiment and Systemic Risk.
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Systemic Risk and Sentiment Chapter Contribution to Handbook on Systemic Risk
2011Co-Authors: Giovanni Barone-adesi, Loriano Mancini, Hersh ShefrinAbstract:Regulators charged with monitoring Systemic Risk need to focus on sentiment as well as narrowly defined measures of Systemic Risk. This chapter describes techniques for jointly monitoring the co-evolution of sentiment and Systemic Risk. To measure Systemic Risk, we use Marginal Expected Shortfall. To measure sentiment, we apply a behavioral extension of traditional pricing kernel theory, which we supplement with external proxies. We illustrate the technique by analyzing the dynamics of sentiment before, during, and after the global financial crisis which erupted in September 2008. Using stock and options data for the S&P 500 during the period 2002–2009, our analysis documents the statistical relationship between sentiment and Systemic Risk.
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Systemic Risk and Sentiment Chapter Contribution to Handbook on Systemic Risk Edited by Jean-Pierre Fouque and Joe Langsam
2011Co-Authors: Giovanni Barone-adesi, Loriano Mancini, Hersh ShefrinAbstract:Regulators charged with monitoring Systemic Risk need to focus on sentiment as well as narrowly defined measures of Systemic Risk. This chapter describes techniques for jointly monitoring the co-evolution of sentiment and Systemic Risk. To measure Systemic Risk, we use Marginal Expected Shortfall. To measure sentiment, we apply a behavioral extension of traditional pricing kernel theory, which we supplement with external proxies. We illustrate the technique by analyzing the dynamics of sentiment before, during, and after the global financial crisis which erupted in September 2008. Using stock and options data for the S&P 500 during the period 2002–2009, our analysis documents the statistical relationship between sentiment and Systemic Risk.
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Handbook on Systemic Risk: Systemic Risk and Sentiment
Handbook on Systemic Risk, 1Co-Authors: Giovanni Barone-adesi, Loriano Mancini, Hersh ShefrinAbstract:Abstract Regulators charged with monitoring Systemic Risk need to focus on sentiment as well as narrowly defined measures of Systemic Risk. This chapter describes techniques for jointly monitoring the co-evolution of sentiment and Systemic Risk. To measure Systemic Risk, we use Marginal Expected Shortfall. To measure sentiment, we apply a behavioral extension of traditional pricing kernel theory, which we supplement with external proxies. We illustrate the technique by analyzing the dynamics of sentiment before, during, and after the global financial crisis which erupted in September 2008. Using stock and options data for the SP JEL Codes : E61, G01, G02, G28 Introduction The report of the Financial Crisis Inquiry Commission (FCIC, 2011) emphasizes the importance of Systemic Risk and sentiment. These two concepts, and the relationship between them, are important for regulatory bodies such as the Financial Stability Oversight Council (FSOC) who, with the support of the Office of Financial Research (OFR), is charged with the responsibility for monitoring Systemic Risk throughout the financial system. This chapter describes tools regulators can use to monitor sentiment and its impact on Systemic Risk.
Arvind Krishnamurthy - One of the best experts on this subject based on the ideXlab platform.
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A Macroeconomic Framework for Quantifying Systemic Risk
American Economic Journal: Macroeconomics, 2019Co-Authors: Arvind KrishnamurthyAbstract:Systemic Risk arises when shocks lead to states where a disruption in financial intermediation adversely affects the economy and feeds back into further disrupting financial intermediation. We present a macroeconomic model with a financial intermediary sector subject to an equity capital constraint. The novel aspect of our analysis is that the model produces a stochastic steady state distribution for the economy, in which only some of the states correspond to Systemic Risk states. The model allows us to examine the transition from "normal" states to Systemic Risk states. We calibrate our model and use it to match the Systemic Risk apparent during the 2007/2008 financial crisis. We also use the model to compute the conditional probabilities of arriving at a Systemic Risk state, such as 2007/2008. Finally, we show how the model can be used to conduct a macroeconomic "stress test" linking a stress scenario to the probability of Systemic Risk states.
Ciamac C. Moallemi - One of the best experts on this subject based on the ideXlab platform.
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An Axiomatic Approach to Systemic Risk
Management Science, 2013Co-Authors: Chen Chen, Garud Iyengar, Ciamac C. MoallemiAbstract:Systemic Risk refers to the Risk of collapse of an entire complex system as a result of the actions taken by the individual component entities or agents that comprise the system. Systemic Risk is an issue of great concern in modern financial markets as well as, more broadly, in the management of complex business and engineering systems. We propose an axiomatic framework for the measurement and management of Systemic Risk based on the simultaneous analysis of outcomes across agents in the system and over scenarios of nature. Our framework defines a broad class of Systemic Risk measures that accomodate a rich set of regulatory preferences. This general class of Systemic Risk measures captures many specific measures of Systemic Risk that have recently been proposed as special cases and highlights their implicit assumptions. Moreover, the Systemic Risk measures that satisfy our conditions yield decentralized decompositions; i.e., the Systemic Risk can be decomposed into Risk due to individual agents. Furthermore, one can associate a shadow price for Systemic Risk to each agent that correctly accounts for the externalities of the agent's individual decision making on the entire system. This paper was accepted by Gerard P. Cachon, stochastic models and simulation.
Giovanni Barone-adesi - One of the best experts on this subject based on the ideXlab platform.
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Sentiment, Asset Prices, and Systemic Risk
SSRN Electronic Journal, 2012Co-Authors: Giovanni Barone-adesi, Loriano Mancini, Hersh ShefrinAbstract:Regulators charged with monitoring Systemic Risk need to focus on sentiment as well as narrowly defined measures of Systemic Risk. This chapter describes techniques for jointly monitoring the co-evolution of sentiment and Systemic Risk. To measure Systemic Risk, we use Marginal Expected Shortfall. To measure sentiment, we apply a behavioral extension of traditional pricing kernel theory, which we supplement with external proxies. We illustrate the technique by analyzing the dynamics of sentiment before, during, and after the global financial crisis which erupted in September 2008. Using stock and options data for the S&P 500 during the period 2002–2009, our analysis documents the statistical relationship between sentiment and Systemic Risk.
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Systemic Risk and Sentiment Chapter Contribution to Handbook on Systemic Risk
2011Co-Authors: Giovanni Barone-adesi, Loriano Mancini, Hersh ShefrinAbstract:Regulators charged with monitoring Systemic Risk need to focus on sentiment as well as narrowly defined measures of Systemic Risk. This chapter describes techniques for jointly monitoring the co-evolution of sentiment and Systemic Risk. To measure Systemic Risk, we use Marginal Expected Shortfall. To measure sentiment, we apply a behavioral extension of traditional pricing kernel theory, which we supplement with external proxies. We illustrate the technique by analyzing the dynamics of sentiment before, during, and after the global financial crisis which erupted in September 2008. Using stock and options data for the S&P 500 during the period 2002–2009, our analysis documents the statistical relationship between sentiment and Systemic Risk.
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Systemic Risk and Sentiment Chapter Contribution to Handbook on Systemic Risk Edited by Jean-Pierre Fouque and Joe Langsam
2011Co-Authors: Giovanni Barone-adesi, Loriano Mancini, Hersh ShefrinAbstract:Regulators charged with monitoring Systemic Risk need to focus on sentiment as well as narrowly defined measures of Systemic Risk. This chapter describes techniques for jointly monitoring the co-evolution of sentiment and Systemic Risk. To measure Systemic Risk, we use Marginal Expected Shortfall. To measure sentiment, we apply a behavioral extension of traditional pricing kernel theory, which we supplement with external proxies. We illustrate the technique by analyzing the dynamics of sentiment before, during, and after the global financial crisis which erupted in September 2008. Using stock and options data for the S&P 500 during the period 2002–2009, our analysis documents the statistical relationship between sentiment and Systemic Risk.
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Handbook on Systemic Risk: Systemic Risk and Sentiment
Handbook on Systemic Risk, 1Co-Authors: Giovanni Barone-adesi, Loriano Mancini, Hersh ShefrinAbstract:Abstract Regulators charged with monitoring Systemic Risk need to focus on sentiment as well as narrowly defined measures of Systemic Risk. This chapter describes techniques for jointly monitoring the co-evolution of sentiment and Systemic Risk. To measure Systemic Risk, we use Marginal Expected Shortfall. To measure sentiment, we apply a behavioral extension of traditional pricing kernel theory, which we supplement with external proxies. We illustrate the technique by analyzing the dynamics of sentiment before, during, and after the global financial crisis which erupted in September 2008. Using stock and options data for the SP JEL Codes : E61, G01, G02, G28 Introduction The report of the Financial Crisis Inquiry Commission (FCIC, 2011) emphasizes the importance of Systemic Risk and sentiment. These two concepts, and the relationship between them, are important for regulatory bodies such as the Financial Stability Oversight Council (FSOC) who, with the support of the Office of Financial Research (OFR), is charged with the responsibility for monitoring Systemic Risk throughout the financial system. This chapter describes tools regulators can use to monitor sentiment and its impact on Systemic Risk.
