The network of the Italian stock market during the 2008–2011 financial crises

Coletti, Paolo; Murgia, Maurizio

doi:10.3233/af-160177

Cited by 10 publications

(6 citation statements)

References 51 publications

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“…The authors of [24] used the rolling correlation coefficients (RCC) technique based on different time widows on the German stock market, and their results demonstrate structural breaks in the evolution of the global distance. Moreover, numerous studies used the minimum spanning tree (MST) approach to investigate the network structures and topology of the local stock markets, for example, the UK stock market [25,26], Brazil stock market [27], China stock market [28,29], Vietnam stock market [30], German stock market [31], Turkey stock market [32], Italy stock market [33], and Pakistan Stock market [34,35].…”

Section: Literature Reviewmentioning

confidence: 99%

The Impact of COVID-19 on the Dynamic Topology and Network Flow of World Stock Markets

Memon

Yao

2021

Journal of Open Innovation: Technology, Market, and Complexity

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Studies examining the impact of COVID-19 using network dynamics are scant and tend to evaluate a specific local stock market. We present a thorough investigation of 58 world stock market networks using a complex network approach spanning across the uncertain times that have resulted from the coronavirus outbreak. First, we use the daily closing prices of the world stock market indices to construct dynamic complex networks and sixteen minimum spanning tree (MST) maps for the period from December 2019 to March 2021. Second, we present the topological evolution properties of time-varying MSTs by applying normalized tree length, diameter, average path length, and centrality measures. Moreover, the empirical results suggest that (1) the highest correlation among the world stock markets is observed during the first wave of the COVID-19 pandemic in the months of February–March 2020; (2) most of the MSTs appear lower in hierarchy, and many chain-like structures are formed due to the sheer impact of pandemic-related crises; (3) Germany remained a hub node in many of the MSTs; and (4) the tree severely contracted during the first wave of the COVID-19 outbreak (during the months of February and March 2020) and expanded slightly afterwards. Moreover, the results obtained from this study can be used for the development of financial stability policies and stock market regulations worldwide.

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Section: Literature Reviewmentioning

confidence: 99%

The Impact of COVID-19 on the Dynamic Topology and Network Flow of World Stock Markets

Memon

Yao

2021

Journal of Open Innovation: Technology, Market, and Complexity

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“…A centrality measure reveals the most influential stocks in the network. There are four commonly used centrality measures in many studies such as degree centrality, betweenness centrality, closeness centrality and eigenvector centrality (Coletti, 2016;Coletti & Murgia, 2016;. In addition, an overall centrality measure is calculated to determine an overall role of each stock.…”

Section: Centrality Measuresmentioning

confidence: 99%

A Network Analysis of Shariah-Compliant Stocks across Global Financial Crisis: A Case of Malaysia

Mahamood¹,

Bahaludin²,

Abdullah³

2019

MAS

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Financial network is a complex system in which transaction of securities take place. Due to its complexity, a minimum spanning tree (MST) technique is used to visualize the structure. This paper investigates the topological structure of 125 shariah-compliant stocks traded in Bursa Malaysia from the year 2000 until 2017. Financial networks of the shariah-compliant stocks are constructed using MST for three duration periods namely the pre-crisis, during crisis and post-crisis. To determine the important stocks in the networks, centrality measures are applied such as degree centrality, betweenness centrality, closeness centrality and eigenvector centrality. Lastly, overall centrality measures are computed to identify the overall characteristic of each node. The findings showed that, KUB Malaysia Berhad was the most influential stock in the pre-crisis and crisis periods. While, MK Land Holdings was the main stock in the post-crisis network.

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“…Network-based methods are widely applied by researchers to study interdependency and the evolution of stock markets, such as minimum spanning tree (MST) (Mantegna 1999;Onnela et al 2003b;Zhao et al 2018;Yao and Memon 2019), threshold networks (CT) (Boginski et al 2005;Lee and Nobi 2018), planar maximally filtered graphs (PMFG) (Tumminello et al 2005;Yan et al 2015;Musmeci et al 2016), wavelet (Wang et al 2017), and multiple criteria decision making (MCDM) (Kou et al 2014). We have chosen MST, a main network mapping methodology extensively used to analyze various financial crisis (Wiliński et al 2013;Majapa and Gossel 2016;Coletti and Murgia 2016;Xia et al 2018;Memon and Yao 2019;Kou et al 2019), currency crisis (Jang et al 2011;Sultornsanee et al 2013), sovereign debt crisis events (Dias 2012), as well as macroeconomic phases (Zhang et al 2011). Therefore, this paper examines the interdependency and evolution of Pakistan's stock market by using MST before and after the general elections of 2018, 2013, and 2008. In the summary, our study has made two contributions.…”

Section: Introductionmentioning

confidence: 99%

General election effect on the network topology of Pakistan’s stock market: network-based study of a political event

2020

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To examine the interdependency and evolution of Pakistan's stock market, we consider the cross-correlation coefficients of daily stock returns belonging to the blue chip Karachi stock exchange (KSE-100) index. Using the minimum spanning tree network-based method, we extend the financial network literature by examining the topological properties of the network and generating six minimum spanning tree networks around three general elections in Pakistan. Our results reveal a star-like structure after the general elections of 2018 and before those in 2008, and a tree-like structure otherwise. We also highlight key nodes, the presence of different clusters, and compare the differences between the three elections. Additionally, the sectorial centrality measures reveal economic expansion in three industrial sectors-cement, oil and gas, and fertilizers. Moreover, a strong overall intermediary role of the fertilizer sector is observed. The results indicate a structural change in the stock market network due to general elections. Consequently, through this analysis, policy makers can focus on monitoring key nodes around general elections to estimate stock market stability, while local and international investors can form optimal diversification strategies.

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The network of the Italian stock market during the 2008–2011 financial crises

Cited by 10 publications

References 51 publications

The Impact of COVID-19 on the Dynamic Topology and Network Flow of World Stock Markets

The Impact of COVID-19 on the Dynamic Topology and Network Flow of World Stock Markets

A Network Analysis of Shariah-Compliant Stocks across Global Financial Crisis: A Case of Malaysia

General election effect on the network topology of Pakistan’s stock market: network-based study of a political event

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