Price discovery and volatility spillovers in the DJIA index and futures markets

Tse, Yiuman

doi:10.1002/(sici)1096-9934(199912)19:8<911::aid-fut4>3.0.co;2-q

Cited by 235 publications

(92 citation statements)

References 50 publications

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“…Kawaller et al (1987), Stoll and Whaley (1990) and Chan (1992), among others, report the S&P 500 futures plays a dominant role in price discovery. Tse (1999 and 2001) finds evidence of a significant bidirectional information flow between the DJIA index and the floor‐traded futures, but reports the futures price leads the cash price in price discovery.…”

Section: Introductionmentioning

confidence: 99%

Intraday Price Discovery in the DJIA Index Markets

Tse

Bandyopadhyay

Shen

2006

Business Fin & Account

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This paper explores the dynamics of price discovery between the Dow Jones Industrial Average (DJIA) index and its three derivative products: the DIAMOND exchange-traded fund (ETF), the floor-traded regular futures, and the electronically traded mini futures. Even though the American Stock Exchange is the primary listing exchange for the ETF, the analysis indicates that the electronically traded ETF on the Archipelago (ArcaEx) electronic communications network dominates the price discovery process for DIAMOND shares. The E-mini futures contribute the most to price discovery, followed by the ArcaEx DIAMOND. The DJIA index and regular futures contribute least to price discovery. The analysis is repeated using the derivatives of the S&P 500 index as a robustness check. The results indicate that multi-market trading ensures greater pricing efficiency. Informed traders favor electronic trading because of immediate and anonymous trade execution. Copyright 2006 The Authors Journal compilation (c) 2006 Blackwell Publishing Ltd.

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Section: Introductionmentioning

confidence: 99%

Intraday Price Discovery in the DJIA Index Markets

Tse

Bandyopadhyay

Shen

2006

Business Fin & Account

Self Cite

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“…In recent decades, there has been increasing interest in modeling the mean and volatility spillovers that exists across different financial markets [3][4][5][6][7].Tse finds that there is a significant bidirectional information flow between the Dow Jones Industrial Average index and the index futures markets with a bivariate EGARCH model [3].Papapetrou studied the dynamic relationship among oil prices, real stock prices, interest rates, real economic activity and employment through a multivariate VAR approach [4]. Papapetrou made a conclusion that oil price changes affect real economic activity and employment while stock returns do not lead to changes in real activity or employment.Mensiexamined the return links and volatility spillovers between the S&P 500 and commodity price indices using a VAR-GARCH model [5].Lee applied the dynamic conditional correlation (DCC), constant conditional correlation (CCC) and BEKK models to investigate the volatility spillover between the stock prices of the Group of Seven and WTI crude oil prices [6].…”

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confidence: 99%

The evolution of spillover effects between oil and stock markets across multi-scales using a wavelet-based GARCH–BEKK model

Liu

Huang

et al. 2017

Physica A: Statistical Mechanics and its Applications

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Aiming to investigate the evolution of mean and volatility spillovers between oil and stock marketsin the time and frequency dimensions,we employed WTI crude oil prices, the S&P 500 (USA) index and the MICEX index (Russia) for the period Jan. 2003-Dec. 2014 as sample data. We first applied a wavelet-based GARCH-BEKK method to examine the spillover features in frequency dimension.To consider the evolution of spillover effectsin time dimension at multiple-scales, we then divided the full sample period into three sub-periods, pre-crisis period, crisis period, and post-crisis period. The results indicate thatspillover effects varyacross wavelet scales in terms of strength and direction.By analysis the time-varying linkage, we found the different evolution features of spillover effects between the Oil-US stock market and Oil-Russia stock market. The spillover relationship between oil and US stock market is shifting to short-termwhile the spillover relationship between oil and Russia stock market is changing to all time scales. That result implies that the linkage between oil and US stock market is weakening in the long-term, and the linkage between oil and Russia stock market is getting close in all time scales. This may explain the phenomenon that the US stock index and the Russia stock index showed the opposite trend with the falling of oil price in the post-crisis period. .

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“…Chan et al . () observe bilateral spillover between index futures and cash index markets in the US, while Tse () finds a bilateral and asymmetric spillover effect in the US. Moreover, the effect increases in intensity for futures to cash markets.…”

Section: Literature Review and Hypothesesmentioning

confidence: 99%

The Volatility Spillover Effect between Index Options and their Underlying Markets: Evidence from the US, the UK, and Taiwan

Chan

Peretti

Wang

et al. 2017

Asia-Pac J of Fin Stud

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This study examines the volatility spillover effect among five index options and their underlying markets. Results show that the bidirectional volatility spillover effect and the cross‐market leverage effect exist between index options and their underlying markets. Our findings confirm that the volatility spillover effect is generally outweighed by shocks in the underlying market, and that the options implied price volatility is provoked by the information shock occurring in both the cash and options markets to a higher degree. Through the volatility impulse response function, this study shows that the options implied prices are more sensitive to innovations in both markets.

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Price discovery and volatility spillovers in the DJIA index and futures markets

Cited by 235 publications

References 50 publications

Intraday Price Discovery in the DJIA Index Markets

Intraday Price Discovery in the DJIA Index Markets

The evolution of spillover effects between oil and stock markets across multi-scales using a wavelet-based GARCH–BEKK model

The Volatility Spillover Effect between Index Options and their Underlying Markets: Evidence from the US, the UK, and Taiwan

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