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Computing stock price comovements with a three-regime panel smooth transition error correction model

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Abstract

This paper studies the hypothesis of stock price comovements toward the US market for a large sample of developed and emerging stock markets (G6, BRICS, and MENA) over the periods of February 1970–June 2012, January 1995–June 2012, and June 2005–June 2012. To consider cross-market heterogeneity and asymmetrical time-variation in stock market integration, we propose an innovative threshold panel cointegration specification based on a panel smooth transitions error correction model. This specification enables us to identify different integration regimes that transit smoothly, which further reproduces the effects of market frictions and behavioral heterogeneity among the markets under consideration. Accordingly, we distinguish between efficient and inefficient market states. Further, we show that, while MENA and BRICS are segmented with the US market, a nonlinear mean-reversion of stock prices is observed for the G6 markets, suggesting evidence of heterogeneous threshold market integration. This suggests global diversification benefits from a US-MENA portfolio, while only per-regime investment opportunities appear for US-G6 and US-BRICS portfolios.

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Notes

  1. Harry Markowitz was awarded the Nobel Prize in Economics in 1990 and a PhD in Economics from the University of Chicago in 1954, for the same line of research. However, this was not obvious, at least to Professor Milton Friedman, who argued that portfolio theory is not economics. However, as Harry Markowitz recalled in his Nobel Prize speech in 1990, “at the time I defended my dissertation (in 1954), portfolio theory was not part of Economics. But now (in 1990) it is”.

  2. We only focus on recent empirical studies on stock market comovements that provide evidence of time-varying financial integration; for a more detailed survey, see Chlibi et al. (2015, 2016).

  3. Nonlinearity in financial market dynamics can be justified differently with the theories of heterogeneous expectations (Boswijk et al. 2007), information asymmetry, switching regimes and time variations in the fundamentals (Jawadi 2009; Jawadi and Prat 2016), mimetic behavior and animal spirit effect (Akerlof and Shiller 2010), transaction and arbitrage costs (Jawadi and Prat 2012).

  4. Koedijk et al. (2010) suggested that the panel data tests enable us to capture further heterogeneity in mean reversion. It is also required to better control for measurement errors in stock prices (Ben Ameur et al. 2016).

  5. As in time series, the transition variable can be an exogenous variable, lagged endogenous variable, or combination of explanatory variables.

  6. See Hansen (1999) for more details on the multiple regime PTR models.

  7. See Béreau et al. (2010) for an application of PSTECM on exchange rates, and Boubaker and Sghaier (2014) for an application of this model to the insurance market. To the best of our knowledge, the PSTECM has not been applied before to assess stock price adjustment and comovements. However, time series STR and STECM models have also often been applied to stock markets (see Jawadi and Prat (2012) for a survey on these models).

  8. When γ → 0, the PSTECM converges toward a linear PECM (Eq. (2)), while, for γ → ∝, a PSTECM converges toward a PTECM.

  9. See Boubaker and Sghaier (2014) for more details on this linearity test.

  10. See Teräsvirta and Anderson (1992) for more details.

  11. See Van Dijk et al. (2002) for more details on the estimation procedure of the STECM model. As for time series, a PSTECM is estimated using the same NLS method.

  12. The above database does not provide neither daily nor weekly data.

  13. usai denotes the stock return of the US stock index.

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Authors and Affiliations

  1. LAREQUAD, University of Tunis El Manar, Tunis, Tunisia

    Souhir Chlibi

  2. University of Evry, 2 Rue Facteur Cheval, 91000, Evry, France

    Fredj Jawadi & Souhir Chlibi

  3. EDC Paris Business School, Paris, France

    Abdoulkarim Idi Cheffou

Authors
  1. Fredj Jawadi
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  2. Souhir Chlibi
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  3. Abdoulkarim Idi Cheffou
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Correspondence to Fredj Jawadi.

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Jawadi, F., Chlibi, S. & Cheffou, A.I. Computing stock price comovements with a three-regime panel smooth transition error correction model. Ann Oper Res 274, 331–345 (2019). https://doi.org/10.1007/s10479-018-2805-3

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