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Erschienen in: Review of Quantitative Finance and Accounting 4/2016

01.11.2016 | Original Research

Intraday jumps and trading volume: a nonlinear Tobit specification

verfasst von: Fredj Jawadi, Waël Louhichi, Abdoulkarim Idi Cheffou, Rivo Randrianarivony

Erschienen in: Review of Quantitative Finance and Accounting | Ausgabe 4/2016

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Abstract

This paper investigates the relationship between trading volume and volatility for four international stock markets (US: S&P500, UK: FTSE100, France: CAC40 and Germany: DAX30) in a context of global financial crisis. Unlike previous related studies, we use intraday data and apply a nonlinear econometric model to assess this relationship. In particular, we first break down intraday realized volatility into its continuous and jump components using the non-parametric approach developed by Barndorff-Nielsen and Shephard (J Financ Econom 4:1–30, 2006). Second, we investigate the volume–volatility relationship and test whether it varies according to volatility components (jumps and continuous component). While Giot et al. (J Empir Finance 17:168–175, 2010), among others, investigated the volume–volatility relationship in a linear context, our study contributes by estimating different nonlinear specifications (threshold model, nonlinear Tobit model) that enable us to capture further asymmetry and time-variation to better apprehend the effect of trading volume on realized volatility. Accordingly, our study yields two interesting findings. On the one hand, as expected there is a significant and positive relationship between trading volume and realized volatility, as well as with its components, confirming the importance of trading volume as a key to characterizing volatility. On the other hand, we show that this relationship exhibits asymmetry and nonlinearity, and that threshold models are more appropriate than linear model to characterize the volume volatility relationship.

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Fußnoten
1
To our knowledge, this is the first paper that studies volume-volatility with intraday data using a nonlinear econometric framework.
 
2
Jawadi and Ureche-Rangau (2013) used daily data.
 
3
For more details about these jump tests, see Jawadi et al. (2015).
 
4
To our knowledge, this is the first paper that estimates nonlinear Tobit and threshold models to investigate the volume-volatility relationship using high frequency data.
 
5
We eliminated trading days where the market was open for a shortened session as well as days with insufficient trading activity in order to provide a representative and consistent estimator for the realized volatility.
 
6
The same database of intraday stock prices was used by Jawadi et al. (2015) to investigate jump contagion among international stock markets.
 
7
We apply hereafter Box-Cox transformation to the volume series. Next, we compute and use their logarithms. This transformation enables to reduce the variance of trading volume.
 
8
As in Chevallier and Sévi (2012), we show strong and positive correlations between realized volatility and continuous volatility, reflecting the importance of the latter for volatility.
 
9
As in Chan and Fong (2006), Giot et al. (2010), Chevallier and Sévi (2012), we only reported the estimators for volume in order to save space. The other results, which show significant dummy variables and significant lagged variables are available upon request.
 
10
As for linear regression estimations, we only reported results that are associated with trading volume. The other results are available upon request.
 
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Metadaten
Titel
Intraday jumps and trading volume: a nonlinear Tobit specification
verfasst von
Fredj Jawadi
Waël Louhichi
Abdoulkarim Idi Cheffou
Rivo Randrianarivony
Publikationsdatum
01.11.2016
Verlag
Springer US
Erschienen in
Review of Quantitative Finance and Accounting / Ausgabe 4/2016
Print ISSN: 0924-865X
Elektronische ISSN: 1573-7179
DOI
https://doi.org/10.1007/s11156-015-0534-0

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