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What influences portfolio contagion among open-end mutual funds?

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  • Liu, Junbin
  • Liu, Xiaoxing
  • Shi, Guangping

Abstract

This paper investigates the time-varying impacts of macroeconomic factors on portfolio contagion. Mining and using overlapping portfolio data covering more than 600 open-end mutual funds and 1900 stocks in China's stock market from 2007 to 2015, we construct a directed weighted network and calculate its degree of portfolio contagion. The time-varying parameter VAR model with stochastic volatility (TVP-VAR-SV model) using the stochastic model specification search (SMSS) method is applied to explore the impacts. We find that the stock market cycle and the investor sentiment show a more significantly positive time-varying impact on portfolio contagion during periods of stability. The volatility of portfolio contagion is greater during financial environment turmoil.

Suggested Citation

  • Liu, Junbin & Liu, Xiaoxing & Shi, Guangping, 2019. "What influences portfolio contagion among open-end mutual funds?," Finance Research Letters, Elsevier, vol. 30(C), pages 145-152.
  • Handle: RePEc:eee:finlet:v:30:y:2019:i:c:p:145-152
    DOI: 10.1016/j.frl.2018.06.011
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    References listed on IDEAS

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    1. Malcolm Baker & Jeffrey Wurgler, 2006. "Investor Sentiment and the Cross‐Section of Stock Returns," Journal of Finance, American Finance Association, vol. 61(4), pages 1645-1680, August.
    2. 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.
    3. Amihud, Yakov, 2002. "Illiquidity and stock returns: cross-section and time-series effects," Journal of Financial Markets, Elsevier, vol. 5(1), pages 31-56, January.
    4. Blocher, Jesse, 2016. "Network externalities in mutual funds," Journal of Financial Markets, Elsevier, vol. 30(C), pages 1-26.
    5. Giorgio E. Primiceri, 2005. "Time Varying Structural Vector Autoregressions and Monetary Policy," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 72(3), pages 821-852.
    6. Eric Eisenstat & Joshua C. C. Chan & Rodney W. Strachan, 2016. "Stochastic Model Specification Search for Time-Varying Parameter VARs," Econometric Reviews, Taylor & Francis Journals, vol. 35(8-10), pages 1638-1665, December.
    7. Kyle, Albert S, 1985. "Continuous Auctions and Insider Trading," Econometrica, Econometric Society, vol. 53(6), pages 1315-1335, November.
    8. Peralta, Gustavo & Zareei, Abalfazl, 2016. "A network approach to portfolio selection," Journal of Empirical Finance, Elsevier, vol. 38(PA), pages 157-180.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Mutual funds network; Portfolio contagion; SMSS-TVP-VAR-SV model;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy

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