Skip to main content
SpringerLink
Log in

Global Risk Factor Theory and Risk Scenario Generation Based on the Rogov-Causality Test of Time Series Time-Warped Longest Common Subsequence

  • Chapter
  • First Online:
Financial Econometrics and Empirical Market Microstructure

  • 2771 Accesses

Abstract

The paper is concerned with the global risk factor theory and the Rogov-causality test of time-warped longest common subsequence for risk management purposes, including the prospects of hedging and portfolio diversification of operational risks. The author discusses the interaction of all types of risk, the role of human error and the effect of space weather (geomagnetic activity taking into account the interplanetary magnetic field (IMF) polarity). The RogovIndex© family of global risk factor indices is described as part of the risk indicator time series database. The paper discusses the apparatus of time series data, mining including hierarchical clustering based on time-warped longest common subsequence similarity (T-WLCSS). The Rogov-causality test is offered for risk scenario generation. The test involves analyzing the time-lag cumulative distribution function for the longest common subsequence of time series.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 109.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 139.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 139.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    Prior to the incident, there had been a change in the storm-time variation index Dst (a space weather indicator) by 43 nT over a period from 4.00 p.m. (local time) on December 19, 2005 to 6.00 a.m. on December 20, 2005. Although this was, of course, only an increment of variation rather than an absolute value, one should keep in mind that a variation level of −50 nT is equivalent to a mild storm rated on the National Oceanic and Atmospheric Administration (NOAA) geomagnetic storm scales as a G1 (such geomagnetic storms sometimes affect the start of animal migration, cause fluctuations in electric power systems, etc.).

  2. 2.

    To avoid misinterpreting the term “Rogov-causality,” one should bear in mind that the presence of Rogov-causality does not mean the existence of a proven cause-effect relationship, but rather characterizes the temporality (the existence of prevailing succession of events in time).

References

  • Cass, D., & Shell, K. (1983). Do sunspots matter? Journal of Political Economy, 91(21), 193–228.

    Article  Google Scholar 

  • Chizhevsky, A. (1936). The terrestrial echo of solar storms. Moscow: Mysl.

    Google Scholar 

  • “Geomagnetic Storms” OECD/IFP Futures Project on “Future Global Shocks” CENTRA Technology, Inc., on behalf of Office of Risk Management and Analysis, United States Department of Homeland Security 14.01.2011 IFP/WKP/FGS (2011).

    Google Scholar 

  • Granger, C. W. J. (1969). Investigating causal relations by econometric models and cross-spectral methods. Econometrica, 37(3), 424–438.

    Article  Google Scholar 

  • Guo, A., & Siegelmann, H. T. (2004). Time-warped longest common subsequence algorithm for music retrieval. At proceedings of ISMIR.

    Google Scholar 

  • Homer, S., & Sylla, R. (1996). A history of interest rates. Rutgers, NJ: Rutgers University Press.

    Google Scholar 

  • Hyman, A. (2001). The case for solar weather derivatives: A special to the desk. Crownsville, MD: Scudder.

    Google Scholar 

  • Jansen, F., Pirjola, R., & Favre, R. (2000). Space weather: Hazard to the earth? Zurich: Swiss Reinsurance Company.

    Google Scholar 

  • Jevons, W. S. (1878). Commercial crises and sun-spots. Nature, 19(14), 33–37.

    Article  Google Scholar 

  • Keogh, E., & Ratanamahatana, C. A. (2005). Exact indexing of dynamic time warping. Knowledge and Information Systems, 7(3), 358–386.

    Article  Google Scholar 

  • Krivelyova, A., & Robotti, C. (2003). Playing the field: Geomagnetic storms and international stock markets. Working Paper 2003–2005. Federal Reserve Bank of Atlanta.

    Google Scholar 

  • Mansurov, S. M. (1969). New evidence of a relationship between magnetic fields in space and on earth. Geomagnetic Aeronautics, 9, 622–623.

    Google Scholar 

  • Merton, R. C. (1974). The pricing of corporate debt: The risk structure of interest rates. Journal of Finance, 29(2), 449–470.

    Google Scholar 

  • Otsuka, K., Yamanaka, T., Cornelissen, G., Breus, T., Chibisov, S. M., Baevsky, R., et al. (2000). Altered chronome of heart rate variability during span of high magnetic activity. Scripta Medica (Brno), 73, 111–116.

    Google Scholar 

  • Randazzo, M. R., Cappelli, D., Keeney, M., Moore, A. P., & Kowalski, E. (2004). Insider threat study: Illicit cyber activity in the banking and finance sector. U.S. Secret Service and CERT® Coordination Center.

    Google Scholar 

  • Ratanamahatana, C.A., Lin J., Gunopulos D., Keogh E., Vlachos M., and Das G. (2010): Data Mining and Knowledge Discovery Handbook 2010. 2nd edn. O. Maimon, L. Rokach (eds.). Springer. Pages 1049–1077, (2010)

    Google Scholar 

  • Reason, J. T. (2000). Human error: Models and management. British Medical Journal, 320(7237), 768–770.

    Article  Google Scholar 

  • Rogov, M. A. (2002). Method for forming risk management contracts by means of a computer system. International patent application PCT/RU2002/000509 of 26.11.2002 published by The International Bureau on 10.06.2004 under No. WO 2004049228.

    Google Scholar 

  • Rogov, M. A. (2003). Chaos, fractals, the neurofinancial theory and quantum financial mathematics in the new risk management paradigm. In RelStat conference. Lecture conducted from TSI, Riga.

    Google Scholar 

  • Rogov, M. A. (2005). Global risk factors. In The international symposium on stochastic models in reliability, safety, security and logistics. Lecture from Negev Academic College of Engineering, Beer Sheva, Israel.

    Google Scholar 

  • Rogov, M. (2006). Global risk factors. Journal of Business Economics and Management, 8(1), 25–28.

    Google Scholar 

  • Rogov, M. (2011). Financial risk management (FRM) and enterprise risk-management (ERM) convergence (manifesto). Issues of Risk Analysis, Vol. 8, 2011, No. 3, page 88 (2011)

    Google Scholar 

  • Sankoff, D., & Kruskal, J. (1983). Time warps, string edits, and macromolecules: The theory and practice of sequence comparison. Boston, MA: Addison Wesley.

    Google Scholar 

  • Shappell, S. A., & Wiegmann D. A. (2000) The human factors analysis and classification system. HFACS Final Report. U.S. Department of Transportation.

    Google Scholar 

  • Spiegel, E. A. (1993). Chaotic dynamics of the solar cycle. Annual Report. Air Force Office of Scientific Research.

    Google Scholar 

  • Svalgaard, L. (1968). Sector structure of the interplanetary magnetic field and daily variation of the geomagnetic field at high latitudes. Geophysical papers R-6, Danish Meteorological Institute, Copenhagen.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Dubna International University, Dubna, Moscow Oblast, Russia

    Mikhail Rogov

Authors
  1. Mikhail Rogov
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Mikhail Rogov .

Editor information

Editors and Affiliations

  1. Department of Economics, University of Illinois, Urbana, Illinois, USA

    Anil K. Bera

  2. Perm State University, Perm, Russia

    Sergey Ivliev

  3. Scuola Normale Superiore, Pisa, Italy

    Fabrizio Lillo

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer International Publishing Switzerland

About this chapter

Cite this chapter

Rogov, M. (2015). Global Risk Factor Theory and Risk Scenario Generation Based on the Rogov-Causality Test of Time Series Time-Warped Longest Common Subsequence. In: Bera, A., Ivliev, S., Lillo, F. (eds) Financial Econometrics and Empirical Market Microstructure. Springer, Cham. https://doi.org/10.1007/978-3-319-09946-0_18

Download citation

Publish with us

Policies and ethics

Search

Navigation