Absolute vs. relative speed in high-frequency trading

IF 0.3 Q4 BUSINESS, FINANCE Algorithmic Finance Pub Date : 2019-04-17 DOI:10.3233/AF-180253
G. Virgilio
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引用次数: 1

Abstract

This paper addresses the little investigated topic of the relationship between the speed of exchange servers, an absolute reference for the system, and trading speed, considered relative to the former. This is a major issue, as trading speed overwhelming the capability of the server to cope with the incoming orders might jeopardise the orderly functioning of the markets. It will be shown how, by raising the speed of trading and increasing the number of the agents operating in the market, it is possible to generate a crisis, no matter how performing the exchange server is. The paper presents a theoretical framework and then verifies its occurrence by analysing audit trail data. The theoretical framework shows a scenario in which under certain, heavy but by no means uncommon, conditions, the excess speed of the trading agents with respect to servers is capable of exacerbating price volatility, leading to vicious feedback loops capable of potentially creating a financial crisis. The empirical part analyses data taken from a particularly volatile day and compares them with much less volatile days. It results that, because of excessive speed, one of the most widely used techniques for minimising risk, order churning, can cause a major crisis.
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高频交易中的绝对速度与相对速度
本文讨论了一个研究较少的主题,即交换服务器的速度(系统的绝对参考)与交易速度之间的关系,相对于前者。这是一个主要问题,因为交易速度超过了服务器处理传入订单的能力,可能会危及市场的有序运行。它将展示,通过提高交易速度和增加市场上的代理人数量,无论交易所服务器的性能如何,都有可能产生危机。本文提出了一个理论框架,然后通过分析审计跟踪数据来验证其发生。该理论框架显示了一种情况,在某些严重但绝非罕见的条件下,交易代理相对于服务器的过快能够加剧价格波动,导致恶性反馈循环,从而可能引发金融危机。实证部分分析了波动性特别大的一天的数据,并将其与波动性小得多的一天进行了比较。结果是,由于速度过快,最广泛使用的最小化风险的技术之一,订单搅动,可能会导致重大危机。
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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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