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Abnormal Returns in the Ibovespa Using Models for High-Frequency Data

Author

Listed:
  • Nelson Ferreira Fonseca

    (Federal University of Minas Gerais)

  • Wagner Moura Lamounier

    (FACE-UFMG)

  • Aureliano Angel Bressan

    (FACE-UFMG)

Abstract

This article aims to identify profitable trading strategies based on the effects of leads and lags between the spot and futures equity markets in Brazil, using high frequency data. To achieve this objective and based on historical data of the Bovespa and the Bovespa Future indexes, four forecasting models have been built: ARIMA, ARFIMA, VAR, and VECM. The trading strategies tested were: net trading strategy, buy and hold strategy, and filter strategy – better than average predicted return. The period of analysis of this paper extends from August 1, 2006 to October 16, 2009. In this work, it was possible to obtain abnormal returns using trading strategies with the VAR model on the effects of leads and lags between the Bovespa index and Bovespa Future index.

Suggested Citation

  • Nelson Ferreira Fonseca & Wagner Moura Lamounier & Aureliano Angel Bressan, 2012. "Abnormal Returns in the Ibovespa Using Models for High-Frequency Data," Brazilian Review of Finance, Brazilian Society of Finance, vol. 10(2), pages 243-265.
    • Handle: RePEc:brf:journl:v:10:y:2012:i:2:p:243-265
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    More about this item

    Keywords

    trading strategies; high-frequency data; IBOVESPA;
    All these keywords.

    JEL classification:

    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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