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
- Complex systems
- Machine Learning
Abstracting and indexing: Clarivate Analytics Emerging Sources Citation Index; EconLit; EconBiz; and Cabell’s Directory
Here, we address the more general problem of how shock propagation dynamics depend on the topological details of the underlying network. To this end, we consider different realistic network topologies, all consistent with balance sheet information…
The author models interactions between financial transactions and expectations and describe asset pricing and return disturbances.
This work studies contagion risk through the portfolio investment channel using network analysis and simulation on bilateral cross-country data.
This paper provides insight into how the collected data pursuant to the EMIR can be used to shed light on the complex network of interrelations underlying the financial markets.
In this paper, the authors present new evidence on the structure of euro area securities markets using a multilayer network approach.
In this paper, the authors show how to exploit the available data to build portfolios that better fit the risk profiles of investors. This is made possible, on the one hand, by constructing groups of homogeneous risk profiles based on user responses to…
In this paper, the authors investigate a credit rating problem based on the network of trading information (NoTI).
This paper examines the relationship between the topology of interbank networks and their ability to propagate localized, idiosyncratic shocks across the banking sector via banks’ interbank claims on one another.
This paper investigates the effects of contagion in interbank-lending networks, with a special focus on the theoretical grounding of centrality measures.
Structural changes in the interbank market across the financial crisis from multiple core–periphery analysis
In this work, the authors employ the KM–ER algorithm to characterize the internal organization of eMID.
This paper quantifies the interrelations induced among financial institutions by common asset holdings.
This paper surveys the use of networks and network-based methods to study economy- related questions.
This paper contributes to the financial networks literature by providing evidence that well-connected bankers on the boards of directors of nonfinancial firms reduce information asymmetry between credit markets and firms.
This paper defines an algorithm for measuring sentiment-based network risk, to understand the relationship between news sentiment and company stock price movements, and to better understand connectivity among companies.