IDEAS home Printed from https://ideas.repec.org/a/pcp/pucrev/y2017i79p87-104.html
   My bibliography  Save this article

Metal Prices and International Market Risk in the Peruvian Stock Market

Author

Listed:
  • Mauricio Zevallos
  • Fernanda Villarreal
  • Carlos Del Carpio
  • Omar Abbara

Abstract

In this paper we use the conditional Value at Risk (CoVaR) and CoVaR variation (∆CoVaR) proposed by Adrian and Brunnermeier (2008, 2011, 2016) to estimate the Peruvian stock mar-ket risk (through the IGBVL) conditioned on the international financial market (given that the S&P500) and conditioned on three of the main commodities exported by Peru: copper, silver and gold. Moreover, the CoVaR measures are compared with the VaR of the IGBVL to understand the differences using conditional and unconditional risk measure estimators. The results show that both CoVaR and ∆CoVaR are useful indicators to measure the Peruvian stock market risk.

Suggested Citation

  • Mauricio Zevallos & Fernanda Villarreal & Carlos Del Carpio & Omar Abbara, 2017. "Metal Prices and International Market Risk in the Peruvian Stock Market," Revista Economía, Fondo Editorial - Pontificia Universidad Católica del Perú, vol. 40(79), pages 87-104.
  • Handle: RePEc:pcp:pucrev:y:2017:i:79:p:87-104
    as

    Download full text from publisher

    File URL: https://revistas.pucp.edu.pe/index.php/economia/article/view/19274/19419
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Acharya, Viral V., 2009. "A theory of systemic risk and design of prudential bank regulation," Journal of Financial Stability, Elsevier, vol. 5(3), pages 224-255, September.
    2. Danielsson, Jon & James, Kevin R. & Valenzuela, Marcela & Zer, Ilknur, 2016. "Model risk of risk models," Journal of Financial Stability, Elsevier, vol. 23(C), pages 79-91.
    3. Viral V. Acharya & Lasse H. Pedersen & Thomas Philippon & Matthew Richardson, 2017. "Measuring Systemic Risk," The Review of Financial Studies, Society for Financial Studies, vol. 30(1), pages 2-47.
    4. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-370, March.
    5. Ding, Zhuanxin & Granger, Clive W. J. & Engle, Robert F., 1993. "A long memory property of stock market returns and a new model," Journal of Empirical Finance, Elsevier, vol. 1(1), pages 83-106, June.
    6. Patton, Andrew J., 2012. "A review of copula models for economic time series," Journal of Multivariate Analysis, Elsevier, vol. 110(C), pages 4-18.
    7. Mauricio Arias & Juan Carlos Mendoza & David Perez-Reyna, 2011. "Applying CoVaR to measure systemic market risk: the Colombian case," IFC Bulletins chapters, in: Bank for International Settlements (ed.), Proceedings of the IFC Conference on "Initiatives to address data gaps revealed by the financial crisis", Basel, 25-26 August 2010, volume 34, pages 351-364, Bank for International Settlements.
    8. Mauricio Zevallos, 2008. "Estimación del riesgo bursátil peruano," Revista Economía, Fondo Editorial - Pontificia Universidad Católica del Perú, issue 62, pages 109-126.
    9. Mr. Jorge A Chan-Lau, 2010. "Balance Sheet Network Analysis of Too-Connected-to-Fail Risk in Global and Domestic Banking Systems," IMF Working Papers 2010/107, International Monetary Fund.
    10. Kee-Hong Bae & G. Andrew Karolyi & René M. Stulz, 2003. "A New Approach to Measuring Financial Contagion," The Review of Financial Studies, Society for Financial Studies, vol. 16(3), pages 717-763, July.
    11. Huang, Xin & Zhou, Hao & Zhu, Haibin, 2012. "Assessing the systemic risk of a heterogeneous portfolio of banks during the recent financial crisis," Journal of Financial Stability, Elsevier, vol. 8(3), pages 193-205.
    12. Wong, Alfred Y-T. & Fong, Tom Pak Wing, 2011. "Analysing interconnectivity among economies," Emerging Markets Review, Elsevier, vol. 12(4), pages 432-442.
    13. Mauricio Zeballos & Carlos del Carpio, 2015. "Metal Returns, Stock Returns and Stock Market Volatility," Revista Economía, Fondo Editorial - Pontificia Universidad Católica del Perú, vol. 38(75), pages 101-122.
    14. Brice Hakwa & Manfred Jager-Ambro.zewicz & Barbara Rudiger, 2012. "Measuring and Analysing Marginal Systemic Risk Contribution using CoVaR: A Copula Approach," Papers 1210.4713, arXiv.org, revised Nov 2012.
    15. Girardi, Giulio & Tolga Ergün, A., 2013. "Systemic risk measurement: Multivariate GARCH estimation of CoVaR," Journal of Banking & Finance, Elsevier, vol. 37(8), pages 3169-3180.
    16. Espino, Freddy & Rabanal, Alejandro, 2011. "Riesgo de Interconexión en el Mercado Interbancario Peruano," Revista Moneda, Banco Central de Reserva del Perú, issue 148, pages 13-16.
    17. Andrew J. Patton, 2006. "Modelling Asymmetric Exchange Rate Dependence," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 47(2), pages 527-556, May.
    18. Del Carpio, Carlos & Zevallos, Mauricio, 2010. "Estimación de capital por riesgo de precio: Evaluandometodologías para el caso peruano," Revista Estudios Económicos, Banco Central de Reserva del Perú, issue 19, pages 47-62.
    19. Céline Gauthier & Alfred Lehar & Moez Souissi, 2010. "Macroprudential Regulation and Systemic Capital Requirements," Staff Working Papers 10-4, Bank of Canada.
    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. Zevallos, Mauricio & Villarreal, Fernanda & Del Carpio, Carlos & Abbara, Omar, 2014. "Influencia de los precios de los metales y el mercado internacional en el riesgo bursátil peruano," Working Papers 2014-023, Banco Central de Reserva del Perú.
    2. Castro, Carlos & Ferrari, Stijn, 2014. "Measuring and testing for the systemically important financial institutions," Journal of Empirical Finance, Elsevier, vol. 25(C), pages 1-14.
    3. Rahman, Md Lutfur & Troster, Victor & Uddin, Gazi Salah & Yahya, Muhammad, 2022. "Systemic risk contribution of banks and non-bank financial institutions across frequencies: The Australian experience," International Review of Financial Analysis, Elsevier, vol. 79(C).
    4. Danielsson, Jon & James, Kevin R. & Valenzuela, Marcela & Zer, Ilknur, 2016. "Model risk of risk models," Journal of Financial Stability, Elsevier, vol. 23(C), pages 79-91.
    5. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2013. "Financial Risk Measurement for Financial Risk Management," Handbook of the Economics of Finance, in: G.M. Constantinides & M. Harris & R. M. Stulz (ed.), Handbook of the Economics of Finance, volume 2, chapter 0, pages 1127-1220, Elsevier.
    6. Ellis, Scott & Sharma, Satish & Brzeszczyński, Janusz, 2022. "Systemic risk measures and regulatory challenges," Journal of Financial Stability, Elsevier, vol. 61(C).
    7. Silva, Walmir & Kimura, Herbert & Sobreiro, Vinicius Amorim, 2017. "An analysis of the literature on systemic financial risk: A survey," Journal of Financial Stability, Elsevier, vol. 28(C), pages 91-114.
    8. Wang, Bo & Xiao, Yang, 2023. "Risk spillovers from China's and the US stock markets during high-volatility periods: Evidence from East Asianstock markets," International Review of Financial Analysis, Elsevier, vol. 86(C).
    9. Tian, Maoxi & Alshater, Muneer M. & Yoon, Seong-Min, 2022. "Dynamic risk spillovers from oil to stock markets: Fresh evidence from GARCH copula quantile regression-based CoVaR model," Energy Economics, Elsevier, vol. 115(C).
    10. Paola Bongini & Laura Nieri, 2014. "Identifying and Regulating Systemically Important Financial Institutions," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 43(1), pages 39-62, February.
    11. Pham, Thach N. & Powell, Robert & Bannigidadmath, Deepa, 2021. "Systemically important banks in Asian emerging markets: Evidence from four systemic risk measures," Pacific-Basin Finance Journal, Elsevier, vol. 70(C).
    12. Zhou, Wei & Chen, Yan & Chen, Jin, 2022. "Risk spread in multiple energy markets: Extreme volatility spillover network analysis before and during the COVID-19 pandemic," Energy, Elsevier, vol. 256(C).
    13. Tobias Adrian & Markus K. Brunnermeier, 2016. "CoVaR," American Economic Review, American Economic Association, vol. 106(7), pages 1705-1741, July.
      • Tobias Adrian & Markus K. Brunnermeier, 2008. "CoVaR," Staff Reports 348, Federal Reserve Bank of New York.
      • Tobias Adrian & Markus K. Brunnermeier, 2011. "CoVaR," NBER Working Papers 17454, National Bureau of Economic Research, Inc.
    14. Tian, Maoxi & Guo, Fei & Niu, Rong, 2022. "Risk spillover analysis of China’s financial sectors based on a new GARCH copula quantile regression model," The North American Journal of Economics and Finance, Elsevier, vol. 63(C).
    15. Su, EnDer, 2014. "Measuring Contagion Risk in High Volatility State between Major Banks in Taiwan by Threshold Copula GARCH Model," MPRA Paper 58161, University Library of Munich, Germany.
    16. Liu, Bing-Yue & Fan, Ying & Ji, Qiang & Hussain, Nazim, 2022. "High-dimensional CoVaR network connectedness for measuring conditional financial contagion and risk spillovers from oil markets to the G20 stock system," Energy Economics, Elsevier, vol. 105(C).
    17. Alexander, Carol & Han, Yang & Meng, Xiaochun, 2023. "Static and dynamic models for multivariate distribution forecasts: Proper scoring rule tests of factor-quantile versus multivariate GARCH models," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1078-1096.
    18. EnDer Su, 2017. "Measuring and Testing Tail Dependence and Contagion Risk Between Major Stock Markets," Computational Economics, Springer;Society for Computational Economics, vol. 50(2), pages 325-351, August.
    19. Xin Huang & Hao Zhou & Haibin Zhu, 2012. "Systemic Risk Contributions," Journal of Financial Services Research, Springer;Western Finance Association, vol. 42(1), pages 55-83, October.
    20. Xisong Jin, 2018. "How much does book value data tell us about systemic risk and its interactions with the macroeconomy? A Luxembourg empirical evaluation," BCL working papers 118, Central Bank of Luxembourg.

    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:pcp:pucrev:y:2017:i:79:p:87-104. See general information about how to correct material in RePEc.

    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: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/depucpe.html .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.