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Gauging Liquidity Risk in Emerging Market Bond Index Funds

Author

Listed:
  • Serge Darolles
  • Jérémy Dudek
  • Gaëlle Le Fol

Abstract

ETFs and index funds have grown at very rapid rates in recent years. Originally launched to track some large liquid indices in developed markets, they now also concern less liquid asset classes such as emerging market bonds. Illiquidity certainly affects the quality of the replication, and in particular, liquidity might increase the tracking error of any index fund, i.e., the difference between the fund and the benchmark returns. The tracking error is then the first characteristic that investors consider when they select index funds. In this paper, we begin from the CDS-bond basis to simulate the tracking error (TE) of a hypothetical well-diversified fund investing in the emerging market bond universe. We compute the CDS-bond basis and the tracking error for 9 emerging market sovereign entities: Brazil, Chile, Hungary, Mexico, Poland, Russia, South Africa, Thailand and Turkey. All of these countries are included in the MSCI Emerging Market Debt in Local Currency index. Our sample period ranges from January 1, 2007 to March 26, 2012. Using a Regime Switching for Dynamic Correlations (RSDC) model, we show that the country-by-country tracking error is reduced by the diversification at the fund level. Moreover, we show that this diversification effect is less effective during crisis periods. This loss of diversification benefits is the main risk of index funds when they are designed to create a liquid exposure to illiquid asset classes.

Suggested Citation

  • Serge Darolles & Jérémy Dudek & Gaëlle Le Fol, 2016. "Gauging Liquidity Risk in Emerging Market Bond Index Funds," Annals of Economics and Statistics, GENES, issue 123-124, pages 247-269.
  • Handle: RePEc:adr:anecst:y:2016:i:123-124:p:247-269
    DOI: 10.15609/annaeconstat2009.123-124.0247
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    Keywords

    Emerging Markets; Sovereign Debt Market; Liquidity Risk Management; Dynamic Correlation; Regime Switching Models;

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • 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
    • G01 - Financial Economics - - General - - - Financial Crises
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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