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Econometric Analysis of Networks
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Econometric Analysis of Networks

A special issue of Journal of Risk and Financial Management (ISSN 1911-8074).

Deadline for manuscript submissions: closed (30 November 2017)

Special Issue Editor

Prof. Dr. Christian Brownlees

E-Mail Website
Guest Editor
Department of Economics and Business, Pompeu Fabra University, Ramon Trias Fargas 25-27, Office 2-E10, 08005 Barcelona, Spain
Interests: network analysis; nonlinear time series; forecasting; statistical computing; empirical finance; financial high frequency data

Special Issue Information

Dear Colleagues,

Over the last couple of years, network analysis has rapidly become an important area of research in economics and finance. Network techniques aim at providing tools to analyze the degree of interconnectedness in high dimensional multivariate systems and its implications. Following the 2007-2009 financial crisis, a number of authors have started to apply these tools to study interconnections in the financial system. One of the main objectives of this strand of the literature is to identify highly interconnected financial institutions which might pose systemic threats to entire financial system. This has been also motivated by the current financial regulation environment which focuses on identifying SIFIs (Systemically Important Financial Institution). This special issue is intended to reflect the current theoretical and empirical research on network analysis in econometrics with a focus on financial applications.

Among the general topics of research to be considered are:

  1. Network Estimation
  2. Models for Contagion
  3. Credit Risk Networks
  4. Market Risk Networks
  5. Connectedness Indices
  6. Interbank Liquidity Networks

Dr. Christian Brownlees
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Risk and Financial Management is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

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Further information on MDPI's Special Issue polices can be found here.

Published Papers (2 papers)

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Research

2826 KiB  
Article
Network Analysis of the Shanghai Stock Exchange Based on Partial Mutual Information
by Tao You, Paweł Fiedor and Artur Hołda
J. Risk Financial Manag. 2015, 8(2), 266-284; https://doi.org/10.3390/jrfm8020266 - 1 Jun 2015
Cited by 24 | Viewed by 8719
Abstract
Analyzing social systems, particularly financial markets, using a complex network approach has become one of the most popular fields within econophysics. A similar trend is currently appearing within the econometrics and finance communities, as well. In this study, we present a state-of-the-artmethod for [...] Read more.
Analyzing social systems, particularly financial markets, using a complex network approach has become one of the most popular fields within econophysics. A similar trend is currently appearing within the econometrics and finance communities, as well. In this study, we present a state-of-the-artmethod for analyzing the structure and risk within stockmarkets, treating them as complex networks using model-free, nonlinear dependency measures based on information theory. This study is the first network analysis of the stockmarket in Shanghai using a nonlinear network methodology. Further, it is often assumed that markets outside the United States and Western Europe are inherently riskier. We find that the Chinese stock market is not structurally risky, contradicting this popular opinion. We use partial mutual information to create filtered networks representing the Shanghai stock exchange, comparing them to networks based on Pearson’s correlation. Consequently, we discuss the structure and characteristics of both the presented methods and the Shanghai stock exchange. This paper provides an insight into the cutting edge methodology designed for analyzing complex financial networks, as well as analyzing the structure of the market in Shanghai and, as such, is of interest to both researchers and financial analysts. Full article
(This article belongs to the Special Issue Econometric Analysis of Networks)
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220 KiB  
Article
Firm Value and Cross Listings: The Impact of Stock Market Prestige
by Nicola Cetorelli and Stavros Peristiani
J. Risk Financial Manag. 2015, 8(1), 150-180; https://doi.org/10.3390/jrfm8010150 - 23 Mar 2015
Cited by 8 | Viewed by 8229
Abstract
This study investigates the valuation impact of a firm’s decision to cross list on a more (or less) prestigious stock exchange relative to its own domestic market. We use a network analysis methodology to derive broad market-based measures of prestige for 45 country [...] Read more.
This study investigates the valuation impact of a firm’s decision to cross list on a more (or less) prestigious stock exchange relative to its own domestic market. We use a network analysis methodology to derive broad market-based measures of prestige for 45 country or regional stock exchange destinations between 1990 and 2006. We find that firms cross listing in a more prestigious market enjoy significant valuation gains over the five-year period following the listing. In contrast, firms cross listing in less prestigious markets experience a significant valuation discount over this post-listing period. The reputation of the cross-border listing destinations is therefore a useful signal of firm value going forward. Our findings are consistent with the view that cross listing in a prestigious market enhances firm visibility, strengthens corporate governance, and lowers informational frictions and capital costs. Full article
(This article belongs to the Special Issue Econometric Analysis of Networks)
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