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La interconexión en las instituciones de inversión colectiva no alternativas y el riesgo sistémico

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  • Ramiro Losada
  • Ricardo Laborda

Abstract

Este trabajo analiza la interconexión entre las instituciones de inversión colectiva (IIC) no alternativas gestionadas y comercializa-das en España, y con respecto a los mercados de valores en los que operan. Los resultados muestran que las IIC no alternativas no deben considerarse importantes en términos de propagación de impactos negativos y desempeñarían un papel limitado desde un punto de vista sistémico. Esta conclusión puede complementarse con el segundo resultado principal del trabajo: no existe una relación a largo plazo (cointegración) entre la interconexión de las IIC no alternativas y sus mercados subyacentes y el riesgo sisté-mico en los mercados financieros. Además, a corto plazo, se observa que un impacto negativo en el riesgo sistémico financiero provocaría un aumento en el nivel de interconexión, sin embargo no se podría afirmar lo contrario: que un impacto negativo sobre el nivel de interconexión no causaría un aumento en la medida de riesgo sistémico.

Suggested Citation

  • Ramiro Losada & Ricardo Laborda, 2020. "La interconexión en las instituciones de inversión colectiva no alternativas y el riesgo sistémico," CNMV Documentos de Trabajo CNMV Documentos de Trabaj, CNMV- Comisión Nacional del Mercado de Valores - Departamento de Estudios y Estadísticas.
  • Handle: RePEc:cnv:docutr:dt_71es
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    References listed on IDEAS

    as
    1. Francis X. Diebold & Kamil Yilmaz, 2009. "Measuring Financial Asset Return and Volatility Spillovers, with Application to Global Equity Markets," Economic Journal, Royal Economic Society, vol. 119(534), pages 158-171, January.
    2. Garman, Mark B & Klass, Michael J, 1980. "On the Estimation of Security Price Volatilities from Historical Data," The Journal of Business, University of Chicago Press, vol. 53(1), pages 67-78, January.
    3. Diebold, Francis X. & Yılmaz, Kamil, 2014. "On the network topology of variance decompositions: Measuring the connectedness of financial firms," Journal of Econometrics, Elsevier, vol. 182(1), pages 119-134.
    4. Jozef Baruník & Tomáš Křehlík, 2018. "Measuring the Frequency Dynamics of Financial Connectedness and Systemic Risk," Journal of Financial Econometrics, Oxford University Press, vol. 16(2), pages 271-296.
    5. Goldstein, Itay & Jiang, Hao & Ng, David T., 2017. "Investor flows and fragility in corporate bond funds," Journal of Financial Economics, Elsevier, vol. 126(3), pages 592-613.
    6. 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.
    7. Nicholson, William B. & Matteson, David S. & Bien, Jacob, 2017. "VARX-L: Structured regularization for large vector autoregressions with exogenous variables," International Journal of Forecasting, Elsevier, vol. 33(3), pages 627-651.
    8. Diebold, Francis X. & Yilmaz, Kamil, 2015. "Financial and Macroeconomic Connectedness: A Network Approach to Measurement and Monitoring," OUP Catalogue, Oxford University Press, number 9780199338306.
    9. Sokbae Lee & Myung Hwan Seo & Youngki Shin, 2017. "Correction," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(518), pages 883-883, April.
    10. Sylvain Benoit & Jean-Edouard Colliard & Christophe Hurlin & Christophe Pérignon, 2017. "Where the Risks Lie: A Survey on Systemic Risk," Review of Finance, European Finance Association, vol. 21(1), pages 109-152.
    11. Ms. Froukelien Wendt, 2015. "Central Counterparties: Addressing their Too Important to Fail Nature," IMF Working Papers 2015/021, International Monetary Fund.
    12. 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.
    13. Kremer, Manfred & Lo Duca, Marco & Holló, Dániel, 2012. "CISS - a composite indicator of systemic stress in the financial system," Working Paper Series 1426, European Central Bank.
    14. Lawrence Schmidt & Allan Timmermann & Russ Wermers, 2016. "Runs on Money Market Mutual Funds," American Economic Review, American Economic Association, vol. 106(9), pages 2625-2657, September.
    15. repec:ecb:ecbwps:20111426 is not listed on IDEAS
    16. Toda, Hiro Y. & Yamamoto, Taku, 1995. "Statistical inference in vector autoregressions with possibly integrated processes," Journal of Econometrics, Elsevier, vol. 66(1-2), pages 225-250.
    17. Johansen, Soren, 1995. "Likelihood-Based Inference in Cointegrated Vector Autoregressive Models," OUP Catalogue, Oxford University Press, number 9780198774501.
    18. Sylvain Benoit & Jean-Edouard Colliard & Christophe Hurlin & Christophe Pérignon, 2017. "Where the Risks Lie: A Survey on Systemic Risk," Review of Finance, European Finance Association, vol. 21(1), pages 109-152.
    19. Koop, Gary & Pesaran, M. Hashem & Potter, Simon M., 1996. "Impulse response analysis in nonlinear multivariate models," Journal of Econometrics, Elsevier, vol. 74(1), pages 119-147, September.
    20. Diebold, Francis X. & Yilmaz, Kamil, 2012. "Better to give than to receive: Predictive directional measurement of volatility spillovers," International Journal of Forecasting, Elsevier, vol. 28(1), pages 57-66.
    21. Pesaran, H. Hashem & Shin, Yongcheol, 1998. "Generalized impulse response analysis in linear multivariate models," Economics Letters, Elsevier, vol. 58(1), pages 17-29, January.
    22. Eli Ofek & Matthew Richardson, 2003. "DotCom Mania: The Rise and Fall of Internet Stock Prices," Journal of Finance, American Finance Association, vol. 58(3), pages 1113-1137, June.
    23. Kalok Chan & Vicentiu Covrig & Lilian Ng, 2005. "What Determines the Domestic Bias and Foreign Bias? Evidence from Mutual Fund Equity Allocations Worldwide," Journal of Finance, American Finance Association, vol. 60(3), pages 1495-1534, June.
    24. Granger, C W J, 1969. "Investigating Causal Relations by Econometric Models and Cross-Spectral Methods," Econometrica, Econometric Society, vol. 37(3), pages 424-438, July.
    25. Li, Jing, 2006. "Testing Granger Causality in the presence of threshold effects," International Journal of Forecasting, Elsevier, vol. 22(4), pages 771-780.
    26. Ross, Stephen A, 1989. " Information and Volatility: The No-Arbitrage Martingale Approach to Timing and Resolution Irrelevancy," Journal of Finance, American Finance Association, vol. 44(1), pages 1-17, March.
    27. Raghuram G. Rajan, 2006. "Has Finance Made the World Riskier?," European Financial Management, European Financial Management Association, vol. 12(4), pages 499-533, September.
    28. Eli Ofek & Matthew Richardson, 2003. "DotCom Mania: The Rise and Fall of Internet Stock Prices," Journal of Finance, American Finance Association, vol. 58(3), pages 1113-1138, June.
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