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Portfolio Flows, Global Risk Aversion and Asset Prices in Emerging Markets

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  • Nasha Ananchotikul
  • Longmei Zhang

Abstract

In recent years, portfolio flows to emerging markets (EMs) have become increasingly large and volatile. Using weekly portfolio fund flows data, the paper finds that their short-run dynamics are driven mostly by global “push†factors. To what extent do these cross-border flows and global risk aversion drive asset volatility in EMs? We use a Dynamic Conditional Correlation (DCC) Multivariate GARCH framework to estimate the impact of portfolio flows and the VIX index on three asset prices, namely equity returns, bond yields and exchange rates, in 17 emerging economies. The analysis shows that global risk aversion has a significant impact on the *volatility* of asset prices, while the magnitude of that impact correlates with country characteristics, including financial openness, the exchange rate regime, as well as macroeconomic fundamentals such as inflation and the current account balance. In line with earlier literature, portfolio flows to EMs are also found to affect the *level* of asset prices, as was the case in particular during the global financial crisis.

Suggested Citation

  • Nasha Ananchotikul & Longmei Zhang, 2016. "Portfolio Flows, Global Risk Aversion and Asset Prices in Emerging Markets," PIER Discussion Papers 36, Puey Ungphakorn Institute for Economic Research.
    • Handle: RePEc:pui:dpaper:36
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    References listed on IDEAS

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    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Portfolio Flows; Global Risk Aversion; Asset Prices; Exchange Rate;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • F37 - International Economics - - International Finance - - - International Finance Forecasting and Simulation: Models and Applications

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