The impact of market conditions, global market liquidity and high frequency trading on the price effects of trades in futures markets

This dissertation presents three sets of analysis on the price effects of trades in futures markets. Specifically, this dissertation examines the impact of market conditions, global market liquidity and high frequency trading (HFT) on the price effects of trades. The empirical evidence presented in this dissertation addresses a number of outstanding issues in the existing literature. The findings in this dissertation also provide valuable insights for regulators and market participants to understand the importance of market sentiment in the price formation process, systematic liquidity risk across international borders, and the role of HFT in influencing market quality on information sensitive days. The first set of empirical tests examines the impact of market conditions on the price effects of block trades in the E-mini S&P 500 index futures and SPDR S&P 500 exchange traded fund (ETF) for the period extending February 2014 to January 2016. Three discrete explanations have been developed by Kraus and Stoll (1972) and Scholes (1972) to account for the price effects associated with block trades: (1) short-run liquidity costs, (2) information, and (3) imperfect substitution. This dissertation focuses on the information effects and extends previous literature by examining the price effects of block trades in bull and bear market conditions. Specifically, it develops a theoretical model that predicts block purchases as being relatively more informed than sales in bear markets; and block sales being relatively more informed than purchases in bull markets. This dissertation uses a sample of block orders, identified as the largest one percent of transactions, in index future contracts and ETF shares across bull and bear market conditions. Results are robust to multiple definitions of market conditions. In the first definition, a bull market is identified as the period that depicts the largest cumulative return, and a bear market is defined as the period that depicts the smallest cumulative return. In the second definition, which is not a continuous trading period, a bull market is defined as the collection of macro-economic releases that are categorized as good news days, and a bear market as the collection of macro-economic releases that are categorized as bad news days. Empirical results provide similar findings between the two market sentiment definitions and demonstrates that the information price effect of block purchases is greater than sales during bearish periods and the information price effect of block sales is greater than buys during bullish periods. These empirical results are consistent with theoretical propositions developed that propose contrarian signals are more valuable than confirming signals. Further the findings contribute to the toolbox models espoused in the literature that examine the impact of market sentiment on the price formation process. The second set of empirical tests examines the impact of global market liquidity on the price effects of trades transacted in individual share price index futures markets. Global commonality in liquidity refers to the liquidity of an individual market co-moving with global-wide liquidity. Previous research has explained global commonality in liquidity in equity markets and not derivative markets. Considering the differences in market participants and speed of trading between share price index futures and equities, this dissertation extends previous literature by examining the global commonality in liquidity across nine share price index futures markets in five different MSCI regions over a 10-year period from October 2002 to September 2012. Further, the dissertation examines whether liquidity commonality varies over a 10-year period to identify if commonality in liquidity has become more pronounced in recent periods. Empirical results reveal strong evidence of global commonality in liquidity for index futures markets, i.e. the liquidity of the individual futures market co- moves with the global market liquidity, where liquidity is measured as the total price effect of trades. Furthermore, such liquidity commonality is higher in significance and more pervasive in recent years than that observed in early 2000. These results are robust to the inclusion of expiration effects, alternative weighting structures for global market liquidity and different measures of liquidity. As liquidity commonality is considered as a common risk factor shared by every country in the global markets, results reported in this analysis improve our understanding of systematic liquidity risk across international borders in index futures markets. The final set of empirical tests investigates the impact of HFT on the price effects of trades for futures contracts listed on the Australian Securities Exchange around scheduled macroeconomic announcements. High frequency trading increased sharply following the introduction of co-location in 2012 by the ASX (Frino et al. 2014). The existing literature mainly focuses on the overall impact of HFT on market quality in normal times, i.e. non-announcement periods, and finds that HFT improves liquidity in general. However, the impact of HFT on market liquidity around public information arrivals remains unclear, especially for the futures market. Furthermore, the causality effect between HFT and market liquidity is also a puzzle for the futures market. The futures market has different participants, speed of trading and market structure relative to the equity market. Announcement periods represent a very different informational environment relative to the normal times. This dissertation employs an exogenous event, the introduction of co-location facilities at the beginning of 2012 by the Australian Securities Exchange, to document the first empirical evidence on the impact of a reduction in latency on HFT and how HFT affects market liquidity around scheduled information releases for the futures market. Results of this dissertation demonstrate that HFT increases dramatically for intervals surrounding news releases after the introduction of co-location in Australia. Moreover, the results suggest that the increased amount of HFT improves market liquidity around macroeconomic announcements for various liquidity measures, including effective spreads, relative spreads, quoted spreads and different levels of market depth.