Investigating Intertrade Durations using Copulas: An Experiment with NASDAQ Data

IF 0.3 Q4 BUSINESS, FINANCE
Ranjan R. Chakravarty, Sudhanshu Sekhar Pani
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引用次数: 0

Abstract

The pattern of dependence between liquidity, durations (orders and trades) and bid-ask spreads in a limit order market are examined in high resolution invoking copulas and graph theory. Using intraday data from a sample of NASDAQ 100 stocks and an experimental design, we study the information pathways in markets in the presence of algorithmic traders. Our results confirm that multivariate analysis is more appropriate to investigate these information pathways. We observe that the strength and nature of the dependence between variables vary through the trading day. We confirm the existence of stylised aspects of algorithmic trading, such as tail dependence in trade durations, a balance between buy and sell side in order durations, liquidity and bid-ask spreads, and the bid-ask spread and liquidity trade-off in the dependence structure.
使用Copulas调查贸易间持续时间:纳斯达克数据的实验
在高分辨率调用copula和图论的情况下,研究了限价订单市场中流动性、持续时间(订单和交易)和买卖价差之间的依赖模式。使用纳斯达克100指数股票样本的盘中数据和实验设计,我们研究了在算法交易者存在的情况下市场中的信息路径。我们的研究结果证实,多元分析更适合研究这些信息通路。我们观察到,变量之间的依赖性的强度和性质在整个交易日都有所不同。我们证实了算法交易的风格化方面的存在,例如交易持续时间中的尾部依赖性、订单持续时间中买卖双方之间的平衡、流动性和买卖价差,以及依赖结构中的买卖价差和流动性权衡。
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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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