Financial institutions and markets are highly interconnected, but only recently has literature begun to emerge that maps these interconnections and assesses their impact on financial risks and returns. The Journal of Network Theory in Finance is an interdisciplinary journal publishing academically rigorous and practitioner-focused research on the application of network theory in finance and related fields. The journal brings together research carried out in disparate areas within academia and other research institutions by policymakers and industry practitioners.
The Journal of Network Theory in Finance publishes data-driven or theoretical work in areas including, but not limited to:
- Empirical network analysis that enables better understanding of financial flows, trade flows, input-output tables, financial exposures or market interdependencies
- Modeling and simulation techniques for measuring interdependent financial risks
- New metrics and techniques for identifying central, vulnerable or systemically important institutions and markets in financial networks
- Network modeling of time-series data for financial risk management, asset allocation and portfolio management
- Social network analysis (SNA) in finance, such as using social network data for making credit and investment decisions
- Applied network visualization techniques that improve the communication of financial risks and rewards
- Analysis of counterparties and their risk exposure from interconnectivity with the financial system and regulatory strategies for improving financial stability
The Journal of Network Theory in Finance has been selected for coverage in the Clarivate Analytics Emerging Sources Citation Index.
This paper presents an evaluation of how risk interdependence affects the risk management process.
This paper extensively compares mutual-information-based networks with correlation-based networks on a stand-alone basis and in the framework of active investment strategies.
This paper proposes a framework to identify the structure of a financial network and its evolution over time, and presents an application to an interbank market with complete actual data.
In this paper, the author builds dynamic networks based on correlation and transfer entropy, using both the log returns and the volatilities of 97 stock market indexes from various parts of the world between 2000 and 2016
In this paper the authors study insolvency cascades in an interbank system, in which banks are permitted to insure their loans with credit default swaps sold by other banks.
The authors present a methodological framework for quantifying interdependencies in the global market and for evaluating risk levels in the worldwide financial network.
In this paper, the author provides an empirical analysis of the network characteristics of two interrelated interbank money markets and their effect on overall market conditions.
Through financial network analysis, this paper ascertains the existence of important causal behavior between certain financial assets, as inferred from eight different causality methods.
In this paper, the authors use information theory quantifiers to analyze the graphs generated by the VG method as applied to the return rate time series of stock markets from different countries.
In this paper, the authors use a topic-modeling approach to quantify the changing attentions of a major news outlet, the Financial Times, to issues of interest.
This paper deals with statistical measures based on high frequency data from stock markets, and in particular looks at how these measures changed according to time, with a focus on before and after the crisis of 2008.
How the interbank market becomes systemically dangerous: an agent-based network model of financial distress propagation
In this paper, the authors study the stability of the interbank market to exogenous shocks using an agent-based network framework.
The aim of this paper is to assess the effects of the reputation of the members of a group on any single member of the group using the concepts of social influence and convergence in belief.
Interbank network and regulation policies: an analysis through agent-based simulations with adaptive learning
The authors develop an agent-based model to study the impact of a broad range of regulation policies on the banking system.
This papers is the first to link bank liquidity performance and core–periphery network structures.
This paper presents a two-layer order book model.
This paper aims to build novel measures of systemic risk that take the multivariate nature of the problem into account by means of network models.
The authors explore the implications of directors' networks for company valuation in a concentrated ownership environment and in pyramidal control structures.
This paper provides a review of graphical modeling and describes potential applications in econometrics and finance.
The authors address the problem of how to capture the contributions of bank failures to systemic risk.