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A Test for Trading Time Hypothesis on Weekends under Time Varying Autoregression with Heteroskedasti

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  • Yun-Yeong Kim

    (Dankook University)

Abstract

Standard daily financial time series analyses using autoregressive (AR) models typically disregard weekends following the trading time hypothesis (TTH) because the relevant assets of the models are not traded (and thus, their prices are not observed) on weekends. However, weekends may affect asset prices through time discounting as well as through shocks/news occurring on weekends. In this regard, we suggest a test for the TTH by using an AR(1) model, where many asset prices are closely approximated by an AR(1) process. The proposing test statistics are based upon the differences of AR coefficients and error variances between Monday and the other weekdays. Asymptotic normality of the suggested test statistics under the TTH and model stationarity is proved. Under the model of nonstationarity, the test statistic is asymptotically pivotal/non-standard and the critical values are given from the Monte Carlo simulations. In an application for the United States S&P 500 data during the years 2000-2011, we found that the TTH was rejected, particularly during the years of war and financial crisis. We also confirmed a weakening of the weekend effect as depicted in Chow, Hsiao and Solt (2003), and Connolly’s (1989) results. It requires us to revise the dynamic analyses using a time series model of asset prices considering the weekends.

Suggested Citation

  • Yun-Yeong Kim, 2013. "A Test for Trading Time Hypothesis on Weekends under Time Varying Autoregression with Heteroskedasti," Korean Economic Review, Korean Economic Association, vol. 29, pages 97-118.
    • Handle: RePEc:kea:keappr:ker-20130630-29-1-05
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    References listed on IDEAS

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    More about this item

    Keywords

    Weekends; Asset Prices; Trading Time Hypothesis; Time Varying Autoregression;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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