Liquidity Resilience in the UK Gilt Futures Market: Evidence from the Order Book

2018 ◽  
Author(s):  
Jonathan Fullwood ◽  
Daniele Massacci
Keyword(s):  
Futures Market ◽  
Order Book ◽  
The Uk

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

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.

Fractional versus decimal pricing: Evidence from the UK Long Gilt futures market

2005 ◽  
Vol 25 (5) ◽  
pp. 419-442 ◽  
Author(s):  
Owain Ap Gwilym ◽  
Ian Mcmanus ◽  
Stephen Thomas
Keyword(s):  
Futures Market ◽  
The Uk

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

scholarly journals Impact of the Adjustment of Maximum Order Volume on Pricing Efficiency of Stock Index Futures in China

2020 ◽  
Vol 2020 ◽  
pp. 1-20
Author(s):  
Liang Wang ◽  
Tingjia Xu ◽  
Longhao Qin ◽  
Xianyan Xiong
Keyword(s):  
Futures Market ◽  
Informed Trading ◽  
Stock Index ◽  
Stock Index Futures ◽  
Order Book ◽  
Maximum Order ◽  
Index Futures ◽  
Pricing Efficiency ◽  
Probability Of Informed Trading ◽  
The Impact

In April 2017, China Financial Futures Exchange adjusted the maximum order volume of single trading in stock index futures, and this paper conducts research on this event. Firstly, it analyzes the influence of the adjustment of maximum order volume on the characteristics of the limit order book with high-frequency data and the impact of ordering situation on the trading depth and volatility of each contract with panel data. Secondly, it takes high-frequency tick-by-tick data to explore the causal relationship between the ordering situation and the probability of informed trading and analyzes the impact of the event on the probability of informed trading. Finally, the dynamic factor analysis method is used to quantify the pricing efficiency based on the probability of informed trading and the characteristics of limit order book, and the influence of the event on the pricing efficiency of stock index futures market is discussed. The results show that the reduction of maximum order volume has different effects on dominant contracts and nondominant contracts of stock index futures. After the event, the overall trading volume of the market increased, where the trading volume of dominant contracts decreased and that of nondominant contracts increased. For dominant contracts, the depth, slope, and liquidity decrease, the spread increases, and the probability of informed trading decreases so that the pricing efficiency becomes worse, while the results of nondominant contracts are the opposite. For Chinese stock index futures market, the pricing efficiency is greatly reduced and the resource allocation capacity is weakened under the influence of the event. Therefore, the adjustment of maximum order volume is not conducive to the healthy development of the stock index futures market. It is suggested that the reduction of the maximum order volume is only implemented for nondominant contracts.

Reinforcement-learning-based optimal trading in a simulated futures market with heterogeneous agents

SIMULATION ◽  
2021 ◽  
pp. 003754972110611
Author(s):  
Nadi Serhan Aydin
Keyword(s):  
Reinforcement Learning ◽  
Optimal Strategy ◽  
Programming Model ◽  
Futures Market ◽  
Order Book ◽  
Optimal Trading ◽  
True Value ◽  
Waiting Strategy ◽  
Collective Information ◽  
Insight Into

This paper simulates a futures market with multiple agents and sequential auctions, where agents receive long-lived heterogeneous signals on the true value of an asset and with a known deadline. The evolution of the amount of differential information and its impact on the distribution of overall gains and the pace of truth discovery is examined for various depth levels of the limit order book (LOB). The paper also formulates a dynamic programming model for the problem and presents an associated reinforcement learning (RL) algorithm for finding optimal strategy in exploiting informational disparity. This is done from the perspective of an agent whose information is superior to the collective information of the rest of the market. Finally, a numerical analysis is presented based on a futures market example to validate the proposed methodology for finding the optimal strategy. We find evidence in favor of a waiting strategy where agent does not reveal her signal until the last auction before the deadline. This result may help bring more insight into the micro-structural dynamics that work against market efficiency.

MARKET IMPACT AND ORDER BOOK CHARACTERISTICS IN THE KOREAN FUTURES MARKET

2011 ◽  
Vol 22 (11) ◽  
pp. 1269-1279
Author(s):  
JUNGHOON LEE ◽  
JANGHYUK YOUN ◽  
WOOJIN CHANG
Keyword(s):  
Futures Market ◽  
Stock Index ◽  
Market Response ◽  
Stock Index Futures ◽  
Order Book ◽  
Market Impact ◽  
Limit Order ◽  
Index Futures ◽  
Market Order ◽  
The Impact

We have examined the order book characteristics and market impact on the Korean stock index futures market (KOSPI 200 index futures). The distribution of order volumes generally follows power-law distribution. The estimated exponents are 1.9 for market order, 2.5 for limit order, and 2.1 for cancel order. This result is different from the case of stocks where the exponent of market order is larger than that of limit order. The order likelihood is distinctively high in every 50's of order volume, which implies the behavioral characteristics of human preference on round-up numbers. The distributions of bid–ask spread and the best quotes volume provide the evidence of the liquidity of KOSPI 200 index futures market. We have obtained the concave relationship between market impact and transaction volume as well. Finally, the market response behavior is observed regarding various transaction sizes. The size of market response is estimated to be proportional to the size of transaction. Also, the larger the transaction size is, the longer it takes to recover the stability from the impact triggered by transaction.

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