Dynamics of information leadership in the volatility complex with trading time changes: Evidence from VIX futures and VIX ETPs

IF 0.3 Q4 BUSINESS, FINANCE
Catalina Hurwitz, Suchi Mishra, R. Daigler, Ihsan Badshah
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引用次数: 0

Abstract

We examine the effect of VIX futures’ new trading hours on price discovery as these causal relations have not been investigated before and are consequential for regulators and practitioners involved in the VIX futures market. Our data include VIX futures and VIX ETPs for four different periods in which trading hours were changed. Employing three different measures of information share, we find that VXX ETN leads VIX futures in 2009 and 2010, while in 2011 and 2013, the ETPs’ leadership varies depending on the exchange-traded product under consideration. Furthermore, in 2013 before the change of trading hours, the VIX futures contribute more to price discovery than they do after trading hours expansion. Less of the price discovery occurs from the exchange-traded products in the latter half of the trading period in 2010. OLS regression results of the determinants of price discovery as well as panel regression results show that the effect of volume and spread, which are the main determinants of price discovery in the prior literature, change significantly before and after futures trading hour expansions, for both VIX futures and ETPs.
波动率复合体中信息领导力随交易时间变化的动力学:来自波动率指数期货和波动率指数ETP的证据
我们研究了波动率指数期货的新交易时间对价格发现的影响,因为这些因果关系之前没有被调查过,对于参与波动率指数期货市场的监管机构和从业者来说是重要的。我们的数据包括四个不同时期的波动率指数期货和波动率指数etp,其中交易时间发生了变化。采用三种不同的信息共享度量,我们发现VXX ETN在2009年和2010年领先于VIX期货,而在2011年和2013年,etp的领先地位取决于所考虑的交易所交易产品。此外,在2013年交易时间改变前,VIX期货对价格发现的贡献大于交易时间扩大后的贡献。2010年交易期后半段,交易所交易产品的价格发现较少。价格发现决定因素的OLS回归结果以及面板回归结果表明,对于VIX期货和etp而言,交易量和价差的影响在期货交易时间延长前后都发生了显著变化,这是先前文献中价格发现的主要决定因素。
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来源期刊
Algorithmic Finance
Algorithmic Finance BUSINESS, FINANCE-
CiteScore
0.40
自引率
0.00%
发文量
6
期刊介绍: Algorithmic Finance is both a nascent field of study and a new high-quality academic research journal that seeks to bridge computer science and finance. It covers such applications as: High frequency and algorithmic trading Statistical arbitrage strategies Momentum and other algorithmic portfolio management Machine learning and computational financial intelligence Agent-based finance Complexity and market efficiency Algorithmic analysis of derivatives valuation Behavioral finance and investor heuristics and algorithms Applications of quantum computation to finance News analytics and automated textual analysis.
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