商品市场同步和持久的结构性变化:来自高频数据的证据

IF 0.3 Q4 BUSINESS, FINANCE
David Bicchetti, Nicolas Maystre
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引用次数: 68

摘要

本文分析了1997-2011年期间美国几个商品市场和股票市场收益之间的日内变动。通过利用新的高频数据库,我们在(i) 1小时,(ii) 5分钟,(iii) 10秒和(iv) 1秒频率下计算各种滚动相关性。使用这个数据库,我们记录了一个同步的结构性断裂,其特征是偏离零,始于2008年,此后一直持续。这与最近商品期货交易所的金融创新,特别是高频交易活动和算法策略对这些相关性产生影响的观点是一致的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Synchronized and Long-Lasting Structural Change on Commodity Markets: Evidence from High Frequency Data
This paper analyses the intraday co-movements between returns on several commodity markets and on the stock market in the United States over the 1997-2011 period. By exploiting a new high frequency database, we compute various rolling correlations at (i) 1-hour, (ii) 5-minute, (iii) 10-second, and (iv) 1-second frequencies. Using this database, we document a synchronized structural break, characterized by a departure from zero, which starts in the course of 2008 and continues thereafter. This is consistent with the idea that recent financial innovations on commodity futures exchanges, in particular the high frequency trading activities and algorithm strategies have an impact on these correlations.
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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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