IDEAS home Printed from https://ideas.repec.org/p/arx/papers/0902.2756.html
   My bibliography  Save this paper

Monitoring dates of maximal risk

Author

Listed:
  • Erick Trevino Aguilar

Abstract

Monitoring means to observe a system for any changes which may occur over time, using a monitor or measuring device of some sort. In this paper we formulate a problem of monitoring dates of maximal risk of a financial position. Thus, the systems we are going to observe arise from situations in finance. The measuring device we are going to use is a time-consistent measure of risk. In the first part of the paper we discuss the numerical representation of conditional convex risk measures which are defined in a space Lp(F,R) and take values in L1(G,R). This will allow us to consider time-consistent convex risk measures in L1(R). In the second part of the paper we use a time-consistent convex risk measure in order to define an abstract problem of monitoring stopping times of maximal risk. The penalty function involved in the robust representation changes qualitatively the time when maximal risk is for the first time identified. A phenomenon which we discuss from the point of view of robust statistics.

Suggested Citation

  • Erick Trevino Aguilar, 2009. "Monitoring dates of maximal risk," Papers 0902.2756, arXiv.org.
  • Handle: RePEc:arx:papers:0902.2756
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/0902.2756
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Stiglitz, Joseph E & Weiss, Andrew, 1981. "Credit Rationing in Markets with Imperfect Information," American Economic Review, American Economic Association, vol. 71(3), pages 393-410, June.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Hakenes, Hendrik & Schnabel, Isabel, 2011. "Bank size and risk-taking under Basel II," Journal of Banking & Finance, Elsevier, vol. 35(6), pages 1436-1449, June.
    2. RenÈ Garcia, 2002. "Are the Effects of Monetary Policy Asymmetric?," Economic Inquiry, Western Economic Association International, vol. 40(1), pages 102-119, January.
    3. Assaf Razin & Efraim Sadka & Chi-Wa Yuen, 1999. "An Information-Based Model of Foreign Direct Investment: The Gains from Trade Revisited," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 6(4), pages 579-596, November.
    4. Innes, Robert, 1987. "Adverse Selection And Tax Externalities In A Model Of Entrepreneurial Investment," Working Papers 225812, University of California, Davis, Department of Agricultural and Resource Economics.
    5. Li, Yuanyuan & Wigniolle, Bertrand, 2017. "Endogenous information revelation in a competitive credit market and credit crunch," Journal of Mathematical Economics, Elsevier, vol. 68(C), pages 127-141.
    6. Sevcan Yesiltas, 2009. "Financing Constraints and Investment: The Case of Turkish Manufacturing Firms," 2009 Meeting Papers 874, Society for Economic Dynamics.
    7. Janvier D. Nkurunziza, 2005. "Reputation and Credit without Collateral in Africa`s Formal Banking," Economics Series Working Papers WPS/2005-02, University of Oxford, Department of Economics.
    8. Cowling, Marc, 2010. "The role of loan guarantee schemes in alleviating credit rationing in the UK," Journal of Financial Stability, Elsevier, vol. 6(1), pages 36-44, April.
    9. Weill, Laurent, 2011. "How corruption affects bank lending in Russia," Economic Systems, Elsevier, vol. 35(2), pages 230-243, June.
    10. Otto Eckstein & Allen Sinai, 1986. "The Mechanisms of the Business Cycle in the Postwar Era," NBER Chapters, in: The American Business Cycle: Continuity and Change, pages 39-122, National Bureau of Economic Research, Inc.
    11. Popoyan, Lilit & Napoletano, Mauro & Roventini, Andrea, 2017. "Taming macroeconomic instability: Monetary and macro-prudential policy interactions in an agent-based model," Journal of Economic Behavior & Organization, Elsevier, vol. 134(C), pages 117-140.
    12. Waters, George A., 2013. "Quantity rationing of credit and the Phillips curve," Journal of Macroeconomics, Elsevier, vol. 37(C), pages 68-80.
    13. Hartarska, Valentina M. & Nadolnyak, Denis A., 2012. "Financing Constraints and Access to Credit in Post Crisis Environment: Evidence from New Farmers in Alabama," 2012 Annual Meeting, August 12-14, 2012, Seattle, Washington 124882, Agricultural and Applied Economics Association.
    14. Jiao Wang & Lima Zhao & Arnd Huchzermeier, 2021. "Operations‐Finance Interface in Risk Management: Research Evolution and Opportunities," Production and Operations Management, Production and Operations Management Society, vol. 30(2), pages 355-389, February.
    15. Elyasiani, Elyas & Mansur, Iqbal & Pagano, Michael S., 2007. "Convergence and risk-return linkages across financial service firms," Journal of Banking & Finance, Elsevier, vol. 31(4), pages 1167-1190, April.
    16. Andriakopoulos, Konstantinos & Ladas, Augoustinos & Andriakopoulos, Panagiotis, 2020. "Bank efficiency and leasing in U.S.A. banking system," MPRA Paper 112645, University Library of Munich, Germany.
    17. Hainz, Christa & Dinh, Thanh & Kleimeier, Stefanie, 2011. "Collateral and its Determinants: Evidence from Vietnam," Proceedings of the German Development Economics Conference, Berlin 2011 36, Verein für Socialpolitik, Research Committee Development Economics.
    18. Abbassi, Puriya & Bräuning, Falk & Fecht, Falko & Peydró, José-Luis, 2014. "Cross-border liquidity, relationships and monetary policy: Evidence from the Euro area interbank crisis," Discussion Papers 45/2014, Deutsche Bundesbank.
    19. Altshuler, Rosanne & Grubert, Harry, 2003. "Repatriation taxes, repatriation strategies and multinational financial policy," Journal of Public Economics, Elsevier, vol. 87(1), pages 73-107, January.
    20. Cowling, Marc & Ughetto, Elisa & Lee, Neil, 2018. "The innovation debt penalty: Cost of debt, loan default, and the effects of a public loan guarantee on high-tech firms," Technological Forecasting and Social Change, Elsevier, vol. 127(C), pages 166-176.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:arx:papers:0902.2756. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: . General contact details of provider: http://arxiv.org/ .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.