Structural models: Intra/Inter-day volatility transmission and spillover persistence of the HSI, HSIF and S&amp;P500 futures

Gannon, Gerard; Choi, Daniel F.S.

doi:10.1016/s1057-5219(99)80036-2

Cited by 10 publications

(6 citation statements)

References 8 publications

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“…This structure accounts for similar U-shaped patterns in intra-day index futures volatility and volume of trade. Volatility spillovers from the U.S. index futures to Hong Kong index futures and stock markets are tested with 15-min sampled data within a bi-variate structural simultaneous systems framework in Gannon and Choi (1998). These latter two structural models separately focus on market specific volatility transmission and international volatility spillover effects.…”

Section: Introductionmentioning

confidence: 99%

Simultaneous volatility transmissions and spillover effects: U.S. and Hong Kong stock and futures markets

Gannon

2005

International Review of Financial Analysis

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Section: Introductionmentioning

confidence: 99%

Simultaneous volatility transmissions and spillover effects: U.S. and Hong Kong stock and futures markets

Gannon

2005

International Review of Financial Analysis

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“…In contrast to the aforementioned articles, Gannon and Choi (1998) and Gannon (2005) use a system of simultaneous equations to identify contemporaneous volatility spillover effects between the Hang Seng stock index spot and futures volatility and the overnight S&P 500 stock market index futures volatility. In particular, Gannon (2005) documents significant volatility spillover effects from the US to Hong Kong stock index futures market.…”

mentioning

confidence: 99%

Dynamic spillover effects in futures markets: UK and US evidence

Antonakakis

Floros

Kizys

2016

International Review of Financial Analysis

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Previous studies on spillover effects in future markets have so far confined themselves to static analyses. In this study, we use a newly introduced spillover index to examine dynamic spillovers between spot and futures market volatility, volume of futures trading and open interest in the UK and the US. Based on a dataset over the period February 25, 2008 to March 14, 2013, that encompasses both the global financial crisis and the Eurozone debt crisis, we find that spot and futures volatilities in the UK (US) are net receivers (net transmitters) of shocks to volume of futures trading and open interest. The analysis also sheds light on the dynamic interdependence of spot and futures market volatilities between the US and the UK. Specifically, the spot and futures volatility spillovers between the UK and US markets are of bidirectional nature, however, they are affected by major economic events such as the global financial and Eurozone debt crisis. Several robustness checks endorse our main findings. Overall, these results have important implications for various market participants and financial sector regulators.

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“…In this respect, the model is similar to the GARCH-based model of Engle et al (1990), which considers the fl ow of volatility through different geographical locations around the world. They fi nd that information fl ow in one geographical location has a signifi cant impact upon subsequent information fl ow in other geographical locations (for similar evidence from foreign exchange markets, equity markets, futures markets, and treasury markets, see Melvin and Melvin, 2003;Gallo, 2001;Gannon and Choi, 1998;and Fleming and Lopez, 1999;respectively). 10 The VARMA-V(A) model assumes that A 0 = M 0 = I 2 , where I 2 is an identity matrix of dimension (2 × 2).…”

Section: Volatility Forecastingmentioning

confidence: 96%

The predictive value of temporally disaggregated volatility: evidence from index futures markets

Taylor¹

2008

Journal of Forecasting

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This paper examines the benefits to forecasters of decomposing close-to-close return volatility into close-to-open (nighttime) and open-to-close (daytime) return volatility. Specifically, we consider whether close-to-close volatility forecasts based on the former type of (temporally aggregated) data are less accurate than corresponding forecasts based on the latter (temporally disaggregated) data. Results obtained from seven different US index futures markets reveal that significant increases in forecast accuracy are possible when using temporally disaggregated volatility data. This result is primarily driven by the fact that forecasts based on such data can be updated as more information becomes available (e.g., information flow from the preceding close-to-open|nighttime trading session). Finally, we demonstrate that the main findings of this paper are robust to the index futures market considered, the way in which return volatility is constructed, and the method used to assess forecast accuracy. Copyright © 2008 John Wiley & Sons, Ltd.

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Structural models: Intra/Inter-day volatility transmission and spillover persistence of the HSI, HSIF and S&P500 futures

Cited by 10 publications

References 8 publications

Simultaneous volatility transmissions and spillover effects: U.S. and Hong Kong stock and futures markets

Simultaneous volatility transmissions and spillover effects: U.S. and Hong Kong stock and futures markets

Dynamic spillover effects in futures markets: UK and US evidence

The predictive value of temporally disaggregated volatility: evidence from index futures markets

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