Skip to main content Accessibility help

We use cookies to distinguish you from other users and to provide you with a better experience on our websites. Close this message to accept cookies or find out how to manage your cookie settings.

Close cookie message
×
Hostname: page-component-745bb68f8f-s22k5 Total loading time: 0 Render date: 2025-02-11T09:10:40.096Z Has data issue: false hasContentIssue false

25 - Systemic Risk and Sentiment

from PART VIII - BEHAVIORAL FINANCE: THE PSYCHOLOGICAL DIMENSION OF SYSTEMIC RISK

Published online by Cambridge University Press:  05 June 2013

By
Giovanni Barone-Adesi ,
Loriano Mancini  and
Hersh Shefrin
Edited by
Jean-Pierre Fouque  and
Joseph A. Langsam
Giovanni Barone-Adesi
Affiliation:
University of Lugano
Loriano Mancini
Affiliation:
Swiss Finance Institute at EPFL
Hersh Shefrin
Affiliation:
Santa Clara University
Jean-Pierre Fouque
Affiliation:
University of California, Santa Barbara
Joseph A. Langsam
Affiliation:
University of Maryland, College Park
Get access

Summary

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 S&P 500 during the period 2002–2009, our analysis documents the statistical relationship between sentiment and systemic risk.

Keywords Systemic risk, Marginal Expected Shortfall, Pricing Kernel, Overconfidence, Optimism; 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.

Type
Chapter
Information
Handbook on Systemic Risk , pp. 714 - 742
Publisher: Cambridge University Press
Print publication year: 2013

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Acharya, V., L., Pedersen, T., Philippon, and M., Richardson (2010). Measuring systemic risk. Technical Report, Department of Finance, New York University.Google Scholar
Aït-Sahalia, Y., and A., Lo (2000). Nonparametric risk management and implied risk aversion. Journal of Econometrics 94 9–51.CrossRefGoogle Scholar
Baker, M., and J., Wurgler (2006). Investor sentiment and the cross-section of stock returns. Journal of Finance 61 1645–1680.CrossRefGoogle Scholar
Barone-Adesi, G., R., Engle, and L., Mancini (2008). A GARCH option pricing model with filtered historical simulation. Review of Financial Studies 21 1223–1258.CrossRefGoogle Scholar
Barone-Adesi, G., L., Mancini, and H., Shefrin (2012). A tale of two investors: estimating risk aversion, optimism, and overconfidence. Working paper, Santa Clara University.Google Scholar
Barsky, R., F. T., Juster, M., Kimball, and M., Shapiro (1997). Preference parameters and behavioral heterogeneity: an experimental approach in the health and retirement survey. Quarterly Journal of Economics 107 537–579.Google Scholar
Brownlees, C., and R., Engle (2010). Volatility, correlation and tails for systemic risk management. Working paper, New York University.Google Scholar
Campbell, J., and R., Shiller (1998). Valuation ratios and the long run market outlook. Journal of Portfolio Management 24 11–26.CrossRefGoogle Scholar
Campbell, J., and J., Cochran (1999). By force of habit: a consumption-based explanation of aggregate stock market behavior. Journal of Political Economy 107 205–251.CrossRefGoogle Scholar
Cochrane, J. (2005). Asset Pricing, 2nd edition. Princeton: Princeton University Press.Google Scholar
Covitz, D., N., Liang, and G., Suarez (2009). The evolution of a financial crisis: runs in the asset-backed commercial paper market. Working paper, Federal Reserve Board.Google Scholar
Duan, J.-C., and J.-G., Simonato (1998). Empirical martingale simulation for asset prices. Management Science 44 1218–1233.CrossRefGoogle Scholar
Gilchrist, S., and E., Zakrajšek (2012). Credit spreads and business cycle fluctuations. American Economic Review, forthcoming.Google Scholar
Glosten, L., R., Jagannathan, and D., Runkle (1993). On the relation between the expected value and the volatility of the nominal excess return on stocks. Journal of Finance 48 1779–1801.CrossRefGoogle Scholar
Hens, T., and C., Reichlin (2011). Three solutions to the pricing kernel puzzle. Working paper, University of Zürich.Google Scholar
Jackwerth, J. C. (2000). Recovering risk aversion from options prices and realized returns. Review of Financial Studies 13 433–451.CrossRefGoogle Scholar
Jouini, E., and C., Napp (2006). Heterogeneous beliefs and asset pricing in discrete time. Journal of Economic Dynamics and Control 30 1233–1260.CrossRefGoogle Scholar
Jouini, E., and C., Napp (2007). Consensus consumer and intertemporal asset pricing with heterogeneous beliefs. Review of Economic Studies 74 1149–1174.CrossRefGoogle Scholar
Kahneman, D., and A., Tversky (1979). Prospect theory: an analysis of decision making under risk. Econometrica 47 263–292.CrossRefGoogle Scholar
Lopes, L. L., and G. C., Oden (1999). The role of aspiration level in risk choice: a comparison of cumulative prospect theory and SP/A theory. Journal of Mathematical Psychology 43 286–313.CrossRefGoogle Scholar
Meyer, D., and J., Meyer (2005). Relative risk aversion: what do we know?Journal of Risk and Uncertainty 31 243–262.CrossRefGoogle Scholar
Rosenberg, J., and R., Engle (2002). Empirical pricing kernels. Journal of Financial Economics 64 341–372.CrossRefGoogle Scholar
Shefrin, H. (2008). A Behavioral Approach to Asset Pricing, 2nd edition. Boston: Elsevier Academic Press.Google Scholar
Tversky, A., and D., Kahneman (1992). Advances in prospect theory: cumulative representation of uncertainty. Journal of Risk and Uncertainty 5 297–323.CrossRefGoogle Scholar
Ziegler, A. (2007). Why does implied risk aversion smile?Review of Financial Studies 20 859–904.CrossRefGoogle Scholar

Save book to Kindle

To save this book to your Kindle, first ensure no-reply@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Available formats
×

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

Available formats
×