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(1 - 3 of 3)
- Title
- High Frequency Trading and Its Impact on Market Quality in U.S. Futures Market
- Creator
- Wang, Chao
- Date
- 2020
- Description
-
This research focuses on the effects of high frequency trading (HFT) on market liquidity in US futures market. This research utilizes a unique...
Show moreThis research focuses on the effects of high frequency trading (HFT) on market liquidity in US futures market. This research utilizes a unique data set consisting of all book events for multiple underlying assets and contracts during calendar year 2018, covering all trading days information of E-mini S&P 500, Gold, Eurodollar, Crude Oil, Corn and Soybean futures with their nearby and deferred contract data each day. This study extends findings from existing HFT equity research (e.g. Brocher et al., 2016; Frino et al., 2019, etc.) that HFT promotes market liquidity, into the commodity market. It also addresses HFT’s contributions to price discovery, and find it varies by types of commodities. Furthermore, the research identifies how an HFT phenomenon, the Cancel Cluster, impacts the futures market. Also, this research verifies and extends the models in Frino et al. (2019) to multiple commodities. Finally, a series of promising future analyses are suggested.
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- Title
- High Frequency Trading and the Impact of Volume-Duration on Market Quality in the U.S. Futures Markets
- Creator
- Xu, Xiaoruo
- Date
- 2023
- Description
-
This paper examines the impact of High Frequency Trading (HFT) on market quality in the U.S. futures market through the lens of Adjusted...
Show moreThis paper examines the impact of High Frequency Trading (HFT) on market quality in the U.S. futures market through the lens of Adjusted Volume-Durations (AVD). By using the unique nanosecond level TAQ CME datasets of commodities futures in 2018, which include Crude Oil, E-mini S&P 500, Eurodollar, Gold, Corn and Soybean, I create the AVDs of each dataset, then conduct the regression analysis on market quality variables with the independent variables including AVDs and other key variables, and the results show that as AVD decreases, the market quality deteriorates, thus HFT positively affects market quality in the U.S. futures market. In order to explore the main driver of AVD on market quality in the futures market, I use the Autoregressive Conditional Duration Model to decompose AVDs into expected AVDs (AEVD), which is the component of AVD that is influenced by past AVDs and unexpected AVDs (AUVD), which is the component of AVD that is not captured by past AVDs but by unanticipated events, and then conduct the regression analysis on market quality variables with the independent variables including AEVD, AUVD and other key variables. The result shows that AEVD has a higher impact on liquidity than AUVD, but the impact of AEVD and AUVD on volatility is mixed in the U.S. futures market. However, except for the conclusions get from the based multivariate regression results, I also explain why there are some outliers for the Eurodollar, soybean and gold, and why HFT has more explicit impact on agricultural futures market.
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- Title
- INFORMATION EFFICIENCY AND THE EFFECT OF HIGH FREQUENCY TRADING IN THE U.S. FUTURES MARKETS
- Creator
- CHA, SEUNG YOUN
- Date
- 2021
- Description
-
The paper gives an empirical analysis with the U.S. futures market data on how High Frequency Trading, HFT can improve the information...
Show moreThe paper gives an empirical analysis with the U.S. futures market data on how High Frequency Trading, HFT can improve the information efficiency of asset prices. Various analyses were conducted to determine the degree of efficiency of information in futures high-frequency trading. The paper tries to explain the effect of high-frequency trading on the efficiency of the market in various ways and tries to propose stepping stones for developing a new market analysis measure.The research builds a coherent framework for analyzing both linear and non-linear market efficiency and applies it to a variety of futures contracts using high- frequency data. The major finding of this paper is that market efficiency levels vary widely over time depending on market characteristics. The paper also finds that HFT activities are higher when the market is inefficient. The paper analyzes the relationship between high frequency trading activities and market efficiency and discovers the mechanism. The story that HFT activity responds to market efficiency needs is especially strong in the E-mini, S&P500 futures contract.
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