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Correlations and Comovements in Financial Markets
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Correlations and Comovements in Financial Markets

A special issue of Journal of Risk and Financial Management (ISSN 1911-8074). This special issue belongs to the section "Mathematics and Finance".

Deadline for manuscript submissions: closed (31 October 2021) | Viewed by 10652

Special Issue Editors

Prof. Dr. Edoardo Otranto

E-Mail Website
Guest Editor
Department of Economics, University of Messina, 98122 Messina, Italy
Interests: time series; forecasting; models for volatility; models for conditional correlations in financial markets; structural changes; clustering
Special Issues, Collections and Topics in MDPI journals
Dr. Antonio Fabio Forgione

E-Mail Website
Guest Editor
Department of Economics, University of Messina, 98122 Messina, Italy
Interests: bank financial performance; bank efficiency; bank market power; environmental performance
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The increasing integration of financial markets across countries has favored the development of studies about the correlation, comovements, interdependence, and spillover effects between financial markets. The development of models studying the mechanisms of transmission of shocks from a so-called dominant market to other markets is a useful task to interpret and forecast the dynamics of financial variables, in particular in terms of volatility.

Similarly, the increased multiasset activity carried out by banks has amplified their exposure to correlation risk. In fact, the standard variance–covariance approach of value in risk models, such as the Montecarlo simulations, require, as a key element to be estimated, the correlation in the yield of market factors for the risky assets included in the market portfolio.

However, large-scale market corrections and market crashes call for the adoption of more and more sophisticated techniques to predict the magnitude of the movement of the assets.

Theoretical and empirical studies concerning financial econometrics, time-series analysis, risk management, and related issues, with original applications concerning the analysis of correlations or, more in generally, comovements between countries, markets, assets, and what are referred to as micro- or macroeconomic variables are welcome; in particular, studies focused on changes in correlations along time and forecasting are encouraged.

Similarly, contributions based on big data and machine learning with applications in the previous contexts are appreciated.

Prof. Dr. Edoardo Otranto
Dr. Antonio Fabio Forgione
Guest Editors

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.

Keywords

  • correlation models
  • spillover effects
  • comovements
  • risk models
  • financial econometrics

Published Papers (4 papers)

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Research

30 pages, 4700 KiB  
Article
Volatility Spillovers among Developed and Developing Countries: The Global Foreign Exchange Markets
by Walid Abass Mohammed
J. Risk Financial Manag. 2021, 14(6), 270; https://doi.org/10.3390/jrfm14060270 - 16 Jun 2021
Viewed by 2838
Abstract
In this paper, we investigate the “static and dynamic” return and volatility spillovers’ transmission across developed and developing countries. Quoted against the US dollar, we study twenty-three global currencies over the time period 2005–2016. Focusing on the spillover index methodology, the generalised VAR [...] Read more.
In this paper, we investigate the “static and dynamic” return and volatility spillovers’ transmission across developed and developing countries. Quoted against the US dollar, we study twenty-three global currencies over the time period 2005–2016. Focusing on the spillover index methodology, the generalised VAR framework is employed. Our findings indicate no evidence of bi-directional return and volatility spillovers between developed and developing countries. However, unidirectional volatility spillovers from developed to developing countries are highlighted. Furthermore, our findings document significant bi-directional volatility spillovers within the European region (Eurozone and non-Eurozone currencies) with the British pound sterling (GBP) and the Euro (EUR) as the most significant transmitters of volatility. The findings reiterate the prominence of volatility spillovers to financial regulators. Full article
(This article belongs to the Special Issue Correlations and Comovements in Financial Markets)
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19 pages, 2743 KiB  
Article
Information Spillover Effects of Real Estate Markets: Evidence from Ten Metropolitan Cities in China
by Junjie Li, Li Zheng, Chunlu Liu and Zhifeng Shen
J. Risk Financial Manag. 2021, 14(6), 244; https://doi.org/10.3390/jrfm14060244 - 31 May 2021
Cited by 2 | Viewed by 1964
Abstract
With the rapid development of information communication technology and the Internet, information spillover between cities in real estate markets is becoming more frequent. The influence of information spillover in real estate markets is becoming more and more prominent. However, the current research of [...] Read more.
With the rapid development of information communication technology and the Internet, information spillover between cities in real estate markets is becoming more frequent. The influence of information spillover in real estate markets is becoming more and more prominent. However, the current research of information spillover between cities is still relatively insufficient. In view of this research gap, this paper builds a research framework on the information conduction effect in the real estate markets of 10 Chinese cities by using Baidu search data, text mining and principal component analysis and analyzes the information interaction and dynamic influence of the real estate markets in each city by using the vector autoregressive model empirically. The results show that the information interaction among the real estate markets in each city has a network pattern and there is a significant two-way information spillover effect in most cities. When the “information distance” becomes closer, the information interaction between the markets of the cities becomes closer and it is easier for cities to influence each other. The results help to explain the information spillover mechanism behind the house price spillover and to improve the ability to predict and analyze the information spillover process in real estate markets. Full article
(This article belongs to the Special Issue Correlations and Comovements in Financial Markets)
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18 pages, 2650 KiB  
Article
The Incidence of Spillover Effects during the Unconventional Monetary Policies Era
by Demetrio Lacava and Luca Scaffidi Domianello
J. Risk Financial Manag. 2021, 14(6), 242; https://doi.org/10.3390/jrfm14060242 - 31 May 2021
Viewed by 2439
Abstract
In a context characterized by an increasing integration among financial markets, we aim to analyze whether the ECB unconventional monetary policy shields the Eurozone stock markets against spillovers of volatility from the US stock market. We augment the Markov switching Asymmetric Multiplicative Error [...] Read more.
In a context characterized by an increasing integration among financial markets, we aim to analyze whether the ECB unconventional monetary policy shields the Eurozone stock markets against spillovers of volatility from the US stock market. We augment the Markov switching Asymmetric Multiplicative Error Model (MS-AMEM) with exogenous variables to measure transmissions of volatility from the S&P500 index, on the one hand, and the announcement and implementation effects of unconventional policy, on the other hand. By estimating our model, the MS-AMEMX, on a sample of daily observations of the realized volatility of four Eurozone stock indices (CAC40, DAX30, FTSEMIB and IBEX35), we find how the increase in volatility brought about by volatility spillovers was mitigated by the implementation of unconventional policy, with a higher benefit for high-debt countries’ stock indices (FTSEMIB and IBEX35). Finally, the out-of-sample analysis certifies the suitability of our proxies also for forecasting purposes. Full article
(This article belongs to the Special Issue Correlations and Comovements in Financial Markets)
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15 pages, 515 KiB  
Article
Do the Determinants of Non-Performing Loans Have a Different Effect over Time? A Conditional Correlation Approach
by Mariagrazia Fallanca, Antonio Fabio Forgione and Edoardo Otranto
J. Risk Financial Manag. 2021, 14(1), 21; https://doi.org/10.3390/jrfm14010021 - 5 Jan 2021
Cited by 6 | Viewed by 2387
Abstract
Several studies have explored the linkage between non-performing loans and major macroeconomic indicators, using a wide variety of methodologies, sometimes with different results. This occurs, we argue, because these relationships are generally derived in terms of correlation coefficients evaluated in certain time spans, [...] Read more.
Several studies have explored the linkage between non-performing loans and major macroeconomic indicators, using a wide variety of methodologies, sometimes with different results. This occurs, we argue, because these relationships are generally derived in terms of correlation coefficients evaluated in certain time spans, which represent a sort of average level of correlations. However, such correlations are necessarily time-varying, because the relationships between bank loan indicators and macroeconomic variables could be stronger during particular periods or in correspondence with important economic events. We propose an empirical exercise using dynamic conditional correlation models, with constant and time-varying parameters. Applying these models to quarterly delinquency rates and an array of macroeconomic variables for the US, for the period 1985–2019, we find that the correlation is often negligible in this period except during periods of economic crises, in particular the early 1990 crisis and the subprime mortgage crisis. Full article
(This article belongs to the Special Issue Correlations and Comovements in Financial Markets)
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