92 research outputs found
A Note on institutional hierarchy and volatility in financial markets
From a statistical point of view, the prevalence of non-Gaussian distributions in nancial returns and their volatilities shows that the Central Limit Theorem (CLT) often does not apply in nancial markets. In this paper 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 sucient for non-Gaussian properties, which crucially depend on the details of the communication network among agents. The main contribution of this paper 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 nancial institutions with socially interacting managers contributes considerably to nancial volatility.Herding; financial volatility; networks; core-perifery
A Look at Financial Dependencies by Means of Econophysics and Financial Economics
This is a review about financial dependencies which merges efforts in
econophysics and financial economics during the last few years. We focus on the
most relevant contributions to the analysis of asset markets' dependencies,
especially correlational studies, which in our opinion are beneficial for
researchers in both fields. In econophysics, these dependencies can be modeled
to describe financial markets as evolving complex networks. In particular we
show that a useful way to describe dependencies is by means of information
filtering networks that are able to retrieve relevant and meaningful
information in complex financial data sets. In financial economics these
dependencies can describe asset comovement and spill-overs. In particular,
several models are presented that show how network and factor model approaches
are related to modeling of multivariate volatility and asset returns
respectively. Finally, we sketch out how these studies can inspire future
research and how they contribute to support researchers in both fields to find
a better and a stronger common language
Networks in Financial Markets
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
A Note on institutional hierarchy and volatility in financial markets
From a statistical point of view, the prevalence of non-Gaussian
distributions in nancial returns and their volatilities shows that the
Central Limit Theorem (CLT) often does not apply in nancial markets.
In this paper 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 sucient for non-Gaussian properties, which
crucially depend on the details of the communication network among
agents. The main contribution of this paper 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 nancial institutions with socially
interacting managers contributes considerably to nancial volatility
Advances in the Agent-based Modeling of Economic and Social Behavior
In this review we discuss advances in the agent-based modeling of economic and social systems. We show the state of the art of the heuristic design of agents and how behavioral economics and laboratory experiments have improved the modeling of agent behavior. We further discuss how economic networks and social systems can be modeled and we discuss novel methodology and data sources. Lastly, we present an overview of estimation techniques to calibrate and validate agent-based models and show avenues for future research
Reduction of systemic risk by means of Pigouvian taxation
We analyze the possibility of reduction of systemic risk in financial markets through Pigouvian taxation of financial institutions, which is used to support the rescue fund. We introduce the concept of the cascade risk with a clear operational definition as a subclass and a network related measure of the systemic risk. Using financial networks constructed from real Italian money market data and using realistic parameters, we show that the cascade risk can be substantially reduced by a small rate of taxation and by means of a simple strategy of the money transfer from the rescue fund to interbanking market subjects. Furthermore, we show that while negative effects on the return on investment (ROI) are direct and certain, an overall positive effect on risk adjusted return on investments (ROIRA) is visible. Please note that the taxation is introduced as a monetary/regulatory, not as a _scal measure, as the term could suggest. The rescue fund is implemented in a form of a common reserve fund
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