Time and Trading Behaviour with an Electronic Order Book: Evidence from the Spanish Futures Market

2001 ◽  
Author(s):  
Pascal Barneto
Keyword(s):  
Futures Market ◽  
Order Book ◽  
Trading Behaviour ◽  
Electronic Order

Individual investors surpass their reputation: Trading behaviour on the Polish futures market

2010 ◽  
Vol 34 (4) ◽  
pp. 480-492 ◽  
Author(s):  
Martin T. Bohl ◽  
Christiane Goodfellow ◽  
Jedrzej Bialkowski
Keyword(s):  
Futures Market ◽  
Individual Investors ◽  
Trading Behaviour

Order Book Price Impact in the Chinese Soybean Futures Market

2020 ◽  
Author(s):  
Muzhao Jin ◽  
Fearghal Joseph Kearney ◽  
Youwei Li ◽  
Yung Chiang Yang
Keyword(s):  
Futures Market ◽  
Price Impact ◽  
Order Book ◽  
Book Price

scholarly journals STATIONARY DISTRIBUTION OF THE VOLUME AT THE BEST QUOTE IN A POISSON ORDER BOOK MODEL

2017 ◽  
Vol 20 (06) ◽  
pp. 1750039
Author(s):  
IOANE MUNI TOKE
Keyword(s):  
Stochastic Process ◽  
Stationary Distribution ◽  
Markov Processes ◽  
Applied Probability ◽  
Order Book ◽  
Markovian Model ◽  
Limit Order ◽  
Market Order ◽  
Electronic Order

We develop a Markovian model that deals with the volume offered at the best quote of an electronic order book. The volume of the first limit is a stochastic process whose paths are periodically interrupted and reset to a new value, either by a new limit order submitted inside the spread or by a market order that removes the first limit. Using applied probability results on killing and resurrecting Markov processes, we derive the stationary distribution of the volume offered at the best quote. All proposed models are empirically fitted and compared, stressing the importance of the proposed mechanisms.

scholarly journals Individual and institutional trading volume around firm-specific announcements

2016 ◽  
Vol 12 (4) ◽  
pp. 422-444 ◽  
Author(s):  
Priyantha Mudalige ◽  
Petko S Kalev ◽  
Huu Nhan Duong
Keyword(s):  
Institutional Investors ◽  
Trading Volume ◽  
Securities Market ◽  
Individual Investors ◽  
Order Book ◽  
Volume Data ◽  
Content Type ◽  
Before And After ◽  
Abnormal Trading Volume ◽  
Trading Behaviour

Purpose – The purpose of this paper is to investigate the immediate impact of firm-specific announcements on the trading volume of individual and institutional investors on the Australian Securities Exchange (ASX), during a period when the market becomes fragmented. Design/methodology/approach – This study uses intraday trading volume data in five-minute intervals prior to and after firm-specific announcements to measure individual and institutional abnormal volume. There are 70 such intervals per trading day and 254 trading days in the sample period. The first 10 minutes of trading (from 10.00 to 10.10 a.m.) is excluded to avoid the effect of opening auction and to ensure consistency in the “starting time” for all stocks. The volume transacted during five-minute intervals is aggregated and attributed to individual or institutional investors using Broker IDs. Findings – Institutional investors exhibit abnormal trading volume before and after announcements. However, individual investors indicate abnormal trading volume only after announcements. Consistent with outcomes expected from a dividend washing strategy, abnormal trading volume around dividend announcements is statistically insignificant. Both individual and institutional investors’ buy volumes are higher than sell volumes before and after scheduled and unscheduled announcements. Research limitations/implications – The study is Australian focused, but the results are applicable to other limit order book markets of similar design. Practical implications – The results add to the understanding of individual and institutional investors’ trading behaviour around firm-specific announcements in a securities market with continuous disclosure. Social implications – The results add to the understanding of individual and institutional investors’ trading behaviour around firm-specific announcements in a securities market with continuous disclosure. Originality/value – These results will help regulators to design markets that are less predatory on individual investors.

The Role of Visual Analysis in the Regulation of Electronic Order Book Markets

2014 ◽  
Author(s):  
Mark E. Paddrik ◽  
Richard Haynes ◽  
Andrew Todd ◽  
Peter Beling ◽  
William Scherer
Keyword(s):  
Visual Analysis ◽  
Order Book ◽  
Electronic Order ◽  
Book Markets

Anticipatory Traders and Trading Speed

2018 ◽  
Vol 54 (2) ◽  
pp. 729-758 ◽  
Author(s):  
Raymond P. H. Fishe ◽  
Richard Haynes ◽  
Esen Onur
Keyword(s):  
High Frequency ◽  
Futures Market ◽  
Order Book ◽  
Order Entry ◽  
Oil Futures ◽  
West Texas ◽  
Informed Traders ◽  
Price Trends ◽  
Crude Oil Futures

We examine whether speed is an important characteristic of traders who anticipate local price trends. These anticipatory participants correctly trade prior to the overall market and systematically act before other participants. They use manual and algorithmic order entry methods, but most are not fast enough to be high frequency traders (HFTs). Those anticipating price trends have impacts as if they are informed traders, while the case for anticipatory participants affecting the volume of other traders is rejected. A follow-up sample shows significant attrition in accounts and difficulty maintaining the anticipatory strategies. To identify anticipatory traders, we devise novel methods to isolate local price trends using order book data from the West Texas Intermediate (WTI) crude oil futures market.

Visual analysis to support regulators in electronic order book markets

2016 ◽  
Vol 36 (2) ◽  
pp. 167-182 ◽  
Author(s):  
Mark E. Paddrik ◽  
Richard Haynes ◽  
Andrew E. Todd ◽  
William T. Scherer ◽  
Peter A. Beling
Keyword(s):  
Visual Analysis ◽  
Order Book ◽  
Electronic Order ◽  
Book Markets

Order book price impact in the Chinese soybean futures market

2021 ◽  
Author(s):  
Muzhao Jin ◽  
Fearghal Kearney ◽  
Youwei Li ◽  
Yung Chiang Yang
Keyword(s):  
Futures Market ◽  
Price Impact ◽  
Order Book ◽  
Book Price
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