Abstract

We examine the bipartite graphs of German corporate boards in 1993, 1999 and 2005, focusing on their projections onto directors (the “personal” network) and onto companies (the “institutional” network). The novel feature here is our focus on the temporal evolution of the two projections. The personal networks exhibit cores of highly central directors who are densely connected among themselves, while the institutional networks show a persistent core of large corporations whose identity remains mostly the same.
This results in the persistent presence of a core network of very large corporations, despite substantial turnover in the identity of directors and significant changes in Germany’s corporate governance during the investigated period. Our findings strongly suggest that core persistence originates from the board appointment decisions of the very largest corporations and is largely independent of personal destinies.

Persistence in corporate networks

with Laura Birg and Mishael Milaković
Journal of Economic Interaction and Coordination
in press
link

SSRN
2014, No. 184
link

Abstract

In an analysis of the US, the UK and German stock market, we find a change in the behaviour based on the stocks’ beta values. In the years 1995–2006, trades of stocks with high beta and large volume were concentrated in the IT and technology sector, whereas in 2006–2012 those trades are dominated by stocks from the financial sector.
We show that an agent-based model can reproduce such a transition. We further show that the initial impulse for the transition might stem from the increase of high-frequency trading at that time.

Transitions in the stock markets of the US, UK and Germany

with F. Wagner
Quantitative Finance
Volume 17, 2017 - Issue 2
link

Arxiv
arXiv:1504.06113
link

Abstract

We analyze the returns of stocks contained in the Standard & Poor’s 500 index from 1987 until 2011. We use covariance matrices of the firms’ returns determined in a time windows of several years. We find that the eigenvector belonging to the leading eigenvalue (the market) exhibits a phase transition. The market is in an ordered state from 1995 to 2005 and in a disordered state after 2005.
We can relate this transition to an order parameter derived from the stocks’ beta and the trading volume. This order parameter can also be interpreted within an agent-based model.

Phase transition in the S&P stock market

with F. Wagner
Journal of Economic Interaction and Coordination
October 2016, Volume 11, Issue 2, pp 229–246
link

Arxiv
arXiv:1306.2508
link

Abstract

We analyze cascades of defaults in an interbank loan market. The novel feature of this study is that the network structure and the size distribution of banks are derived from empirical data. We find that the ability of a defaulted institution to start a cascade depends on an interplay of shock size and connectivity. Further results indicate that the interbank loan network is structurally less stable after the financial crisis than it was before. To evaluate the influence of the network structure on market stability, we compare simulated cascades from the empirical network with results from different network models.
The results show that the empirical network has non-random features, which cannot be captured by randomized networks. The analysis also reveals that simulations that assume homogeneity for banks and loan size tend to overestimate the fragility of the interbank market.

Cascades in Real Interbank Markets

with F. Karimi
Computational Economics
January 2016, Volume 47, Issue 1, pp 49–66
link

Arxiv
arXiv:1310.1634
link

Abstract

We analyze the Italian interbank loan market from 1999 until 2010. The analysis of net trade flows shows a high imbalance caused by a few large net borrowers in the market. The trading volume shows a significant drop starting in 2007, which accelerates with the Lehman default in late 2008. The interbank loan network is very dense. Hence, we try to identify strong links by looking for preferential lending relationships expressed by discounts in the loan rate.
Furthermore, we estimate the dynamics of credit spreads for each bank and find that economically significant spreads for the overnight market developed only in 2010. The analysis of preferential loan relationships reveals that in the pre-Lehman era large net borrowers used to borrow at a slight discount. In the post-Lehman era borrowers with large net exposures paid more than the average market rate, which shows that the risk evaluation of market participants has changed considerably.

Structure in the Italian overnight loan market

Journal of International Money and Finance, 2014
Volume 41, March 2014, Pages 197–213
link

Kiel Working Paper
Kiel Working Papers 1772
link

Abstract

From a statistical point of view, the prevalence of non-Gaussian distributions in financial returns and their volatilities shows that the Central Limit Theorem (CLT) often does not apply in financial markets. In this article, we take the position that the independence assumption of the CLT is violated by herding tendencies among market participants, and investigate whether a generic probabilistic herding model can reproduce non-Gaussian statistics in systems with a large number of agents.
It is well known that the presence of a herding mechanism in the model is not sufficient for non-Gaussian properties, which crucially depend on the details of the communication network among agents. The main contribution of this article is to show that certain hierarchical networks, which portray the institutional structure of fund investment, warrant non-Gaussian properties for any system size and even lead to an increase in system-wide volatility. Viewed from this perspective, the mere existence of financial institutions with socially interacting managers contributes considerably to financial volatility.

A note on institutional hierarchy and volatility in financial markets

with Simone Alfarano, Mishael Milaković
The European Journal of Finance, 2013
Volume 19, Issue 6, 2013
link

Economics Working Paper, Kiel University (earlier version)
Economics Working Papers No 2009-09
link

Abstract

In the current era of strong worldwide market couplings the global financial village became highly prone to systemic collapses, events that can rapidly sweep throughout the entire village. We present a new methodology to assess and quantify inter-market relations. The approach is based on the correlations between the market index, the index volatility, the market Index Cohesive Force and the meta-correlations (correlations between the intra-correlations.) We investigated the relations between six important world markets—U.S., U.K., Germany, Japan, China and India—from January 2000 until December 2010.
We found that while the developed “western” markets (U.S., U.K., Germany) are highly correlated, the interdependencies between these markets and the developing “eastern” markets (India and China) are volatile and with noticeable maxima at times of global world events. The Japanese market switches “identity”—it switches between periods of high meta-correlations with the “western” markets and periods when it behaves more similarly to the “eastern” markets. The methodological framework presented here provides a way to quantify the evolvement of interdependencies in the global market, evaluate a world financial network and quantify changes in the world inter market relations.

Evolvement of Uniformity and Volatility in the Stressed Global Financial Village

with Dror Y. Kenett, Thomas Lux, Eshel Ben-Jacob
PlosOne, 2012
February 08, 2012 DOI: 10.1371/journal.pone.0031144
link

Abstract

The high degree of coupling between global financial markets has made the financial village prone to systemic collapses. Our approach is based on meta-correlations (correlations between the intra-market correlations), and a Dependency Network analysis. We investigated the relations between six important world markets — U.S., U.K., Germany, Japan, China and India from January 2000 until December 2010. Our findings show that while the developed Western markets, are highly correlated, the inter-dependencies between these markets and the Eastern markets are very volatile and with noticeable maxima at times of global world events.
Finally, using the Dependency network approach, we quantify the flow of information between the different markets, and how markets affect each other. We observe that German and U.K. stocks show a large amount of coupling, while other markets are more segmented. These and additional reported findings illustrate that this methodological framework provides a way to quantify interdependencies in the global market and their evolvement, to evaluate the world financial network, and quantify changes in inter-market relations. Such changes can be used as precursors to the agitation of the global financial village.

Correlations and Dependencies in the global financial village

with Dror Y. Kenett, Lior Zatlavi, Thomas Lux, Eshel Ben-Jacob
International Journal of Modern Physics: Conference Series, 2012
Int. J. Mod. Phys. Conf. Ser. 16, 13 (2012). DOI: 10.1142/S201019451200774X
link

Abstract

The thesis applies methods from network sciences to four economic topics: herding in financial markets; corporate board networks; contagion in global financial markets; the Italian overnight loan market.



V, 144 Bl. : Ill., graph. Darst., Kt. ; 30 cm
Contents

Networks in Financial Markets

Dissertation
Kiel, Christian-Albrechts-Universität, Diss., 2012
link