High-frequency cross-correlation in a set of stocks

By G. Bonanno, Fabrizio Lillo, Rosario Nunzio Mantegna. 2000

260 citations recorded by the source corpus.

The high-frequency cross-correlation existing between pairs of stocks traded in a financial market are investigated in a set of 100 stocks traded in US equity markets. A hierarchical organization of the investigated stocks is obtained by determining a metric distance between stocks and by investigating the properties of the subdominant ultrametric associated with it. A clear modification of the hierarchical organization of the set of stocks investigated is detected when the time horizon used to determine stock returns is changed. The hierarchical location of stocks of the energy sector is investigated as a function of the time horizon.

Subfields: Computer Networks and Communications, Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/6427f46d9488a890a0855b9b597c80bae19e6833

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Networks and Communications

1. C. K. Tse
2. B. Liu
3. Sinno Jialin Pan
4. Jing Liu
5. Francis Chung-Ming Lau
6. Arjun Mukherjee

In Economics and Econometrics

1. C. K. Tse
2. Qing Li
3. Jing Liu
4. Francis Chung-Ming Lau
5. Raphael Heiko Heiberger
6. Gangjin Wang
7. Chi Xie

In Finance

1. C. K. Tse
2. Qing Li
3. Jing Liu
4. Francis Chung-Ming Lau

Citations in the corpus

• Econophysics: Empirical facts and agent-based models (2009, unknown): “in Bonanno et al. (2001a); Reno (2003).”
• A network perspective of the stock market (2010, methodology): “Recently, analyses based on network models have been proposed for studying the correlations of stock prices, including the works of Mantegna (1999), Vandewalle et al. (2001), Bonanno et al. (2001), Bonnanno et al. (2003), Bonanno et al. (2004), and Onnela et al. (2003).”
• Correlation, Hierarchies, and Networks in Financial Markets (2008, unknown): “However in general hierarchical methods perform quite well in identifying groups of stocks belonging to the same economic sector (Mantegna, 1999; Bonanno et al., 2001; Coronnello et al., 2005).”
• Exploiting Social Relations and Sentiment for Stock Prediction (2014, background): “Financial network models study the correlations of stocks in a graph-based view (Tse et al., 2010; Mantegna, 1999; Vandewalle et al., 2001; On-nela et al., 2003; Bonanno et al., 2001).”