We investigate the effects of non‐synchronous trading on volatility spillover for the G‐7 equity markets during the Eurozone sovereign debt crisis (ESDC) and the Covid‐19 pandemic crisis. For data synchronisation we utilise ΜΑ(1) adjusted return series to estimate the Baba‐Engle‐Kraft‐Kroner (BEKK) and the dynamic conditional correlation (DCC) models. We also consider the use of realised kernels as explanatory variables in the variance equation. In this set up, the contagion effects during crises periods are more perceptible, as the spikes are easier to interpret. We also check the robustness of our main results by applying, wavelet coherence analysis to G‐7 major equity indices with realised kernels, as well as local Gaussian correlations (LGC). Our findings suggest the empirical significance of the synchronisation effects for the US and the other G‐7 equity markets. We also conclude that realised kernels is an effective tool for mitigating non‐synchronous effects. These results underline the significance of quantifying the synchronisation effects in equity markets as well as international portfolio diversification strategies.
{"title":"The implications of non‐synchronous trading in G‐7 financial markets","authors":"Dimitrios Dimitriou, Dimitris Kenourgios, Theodore Simos, Alexandros Tsioutsios","doi":"10.1002/ijfe.2936","DOIUrl":"https://doi.org/10.1002/ijfe.2936","url":null,"abstract":"We investigate the effects of non‐synchronous trading on volatility spillover for the G‐7 equity markets during the Eurozone sovereign debt crisis (ESDC) and the Covid‐19 pandemic crisis. For data synchronisation we utilise ΜΑ(1) adjusted return series to estimate the Baba‐Engle‐Kraft‐Kroner (BEKK) and the dynamic conditional correlation (DCC) models. We also consider the use of realised kernels as explanatory variables in the variance equation. In this set up, the contagion effects during crises periods are more perceptible, as the spikes are easier to interpret. We also check the robustness of our main results by applying, wavelet coherence analysis to G‐7 major equity indices with realised kernels, as well as local Gaussian correlations (LGC). Our findings suggest the empirical significance of the synchronisation effects for the US and the other G‐7 equity markets. We also conclude that realised kernels is an effective tool for mitigating non‐synchronous effects. These results underline the significance of quantifying the synchronisation effects in equity markets as well as international portfolio diversification strategies.","PeriodicalId":371613,"journal":{"name":"International Journal of Finance & Economics","volume":"9 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139870631","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This article examines how the COVID‐19 pandemic affected European trade patterns. Specifically, dynamic panel data models are estimated over the period 2019M1–2021M12 to assess the effects on exports and imports of various sectors and products (selected on the basis of their trading volume or strategic importance) of the restrictions and of other policy measures adopted by national governments during the crisis. The results suggest that the impact of the COVID‐19 pandemic was heterogeneous across sectors and product types, both the initial drop and the subsequent rebound being different depending on sectoral characteristics and the degree of resilience. In particular, trade flows of durable products were more significantly affected by the pandemic compared to those of non‐durable ones.
{"title":"The COVID‐19 pandemic and European trade patterns: A sectoral analysis","authors":"G. Caporale, A. Sova, Robert Sova","doi":"10.1002/ijfe.2943","DOIUrl":"https://doi.org/10.1002/ijfe.2943","url":null,"abstract":"This article examines how the COVID‐19 pandemic affected European trade patterns. Specifically, dynamic panel data models are estimated over the period 2019M1–2021M12 to assess the effects on exports and imports of various sectors and products (selected on the basis of their trading volume or strategic importance) of the restrictions and of other policy measures adopted by national governments during the crisis. The results suggest that the impact of the COVID‐19 pandemic was heterogeneous across sectors and product types, both the initial drop and the subsequent rebound being different depending on sectoral characteristics and the degree of resilience. In particular, trade flows of durable products were more significantly affected by the pandemic compared to those of non‐durable ones.","PeriodicalId":371613,"journal":{"name":"International Journal of Finance & Economics","volume":"53 9","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139871059","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Introduction to essays in modelling financial market dynamics","authors":"Fredj Jawadi","doi":"10.1002/ijfe.2187","DOIUrl":"https://doi.org/10.1002/ijfe.2187","url":null,"abstract":"","PeriodicalId":371613,"journal":{"name":"International Journal of Finance & Economics","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132979644","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-09-04DOI: 10.15847/DINAMIACET-IUL.WP.2020.06
Ana Romão, Ricardo Barradas
The objective of this paper is to perform a time series econometric analysis in order to empirically assess the macroeconomic determinants and the corresponding drivers of the Portuguese households’ indebtedness in the period 1988 to 2016. During that period, the Portuguese economy experienced a process of financialisation that contributed to an increase in Portuguese households’ indebtedness to unprecedented levels. The Portuguese households’ indebtedness played a crucial role in the recent sovereign debt crisis. Based on the existing literature, we hypothesize that Portuguese households’ indebtedness was due to seven macroeconomic determinants, notably housing prices, financial asset prices, the degree of personal income inequality, households’ labour income, the importance of welfare state expenditures, the fraction of the working-age population and the level of interest rates. Our findings reveal that financial asset prices, the degree of personal income inequality, households’ labour income and the fraction of the working-age population positively impact Portuguese households’ indebtedness, whereas the housing prices negatively impact Portuguese households’ indebtedness. Our findings also show that the increase in financial asset prices and the decline in housing prices were the main drivers of Portuguese households’ indebtedness in the last few decades.
{"title":"Macroeconomic Determinants of Households' Indebtedness in Portugal: What Really Matters in the Era of Financialisation?","authors":"Ana Romão, Ricardo Barradas","doi":"10.15847/DINAMIACET-IUL.WP.2020.06","DOIUrl":"https://doi.org/10.15847/DINAMIACET-IUL.WP.2020.06","url":null,"abstract":"The objective of this paper is to perform a time series econometric analysis in order to empirically assess the macroeconomic determinants and the corresponding drivers of the Portuguese households’ indebtedness in the period 1988 to 2016. During that period, the Portuguese economy experienced a process of financialisation that contributed to an increase in Portuguese households’ indebtedness to unprecedented levels. The Portuguese households’ indebtedness played a crucial role in the recent sovereign debt crisis. Based on the existing literature, we hypothesize that Portuguese households’ indebtedness was due to seven macroeconomic determinants, notably housing prices, financial asset prices, the degree of personal income inequality, households’ labour income, the importance of welfare state expenditures, the fraction of the working-age population and the level of interest rates. Our findings reveal that financial asset prices, the degree of personal income inequality, households’ labour income and the fraction of the working-age population positively impact Portuguese households’ indebtedness, whereas the housing prices negatively impact Portuguese households’ indebtedness. Our findings also show that the increase in financial asset prices and the decline in housing prices were the main drivers of Portuguese households’ indebtedness in the last few decades.","PeriodicalId":371613,"journal":{"name":"International Journal of Finance & Economics","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130354142","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-09-01DOI: 10.36095/banxico/di.2021.17
C. Alba, G. Cuadra, J. Hernández, Raul Ibarra
Este trabajo analiza los cambios recientes en la importancia relativa de los determinantes de los flujos de capital hacia las economías de mercados emergentes. Para ello, estimamos modelos de vectores autorregresivos (VAR) para el período 2009-2020. Con base en estos modelos, estimamos los efectos sobre los flujos de deuda de choques a sus determinantes. Posteriormente, cuantificamos la contribución de cada una de las variables incluidas en el modelo para explicar la evolución de estos flujos en cada mes de la muestra mediante un análisis de descomposición histórica. Los resultados principales indican que la contribución de la aversión al riesgo global para explicar la evolución de los flujos de deuda aumentó durante marzo de 2020 en comparación con el pasado, aunque su importancia relativa ha disminuido desde entonces, particularmente a medida que mejoró el desempeño de los mercados financieros.
{"title":"Capital Flows to Emerging Economies and Global Risk Aversion during the COVID-19 Pandemic","authors":"C. Alba, G. Cuadra, J. Hernández, Raul Ibarra","doi":"10.36095/banxico/di.2021.17","DOIUrl":"https://doi.org/10.36095/banxico/di.2021.17","url":null,"abstract":"Este trabajo analiza los cambios recientes en la importancia relativa de los determinantes de los flujos de capital hacia las economías de mercados emergentes. Para ello, estimamos modelos de vectores autorregresivos (VAR) para el período 2009-2020. Con base en estos modelos, estimamos los efectos sobre los flujos de deuda de choques a sus determinantes. Posteriormente, cuantificamos la contribución de cada una de las variables incluidas en el modelo para explicar la evolución de estos flujos en cada mes de la muestra mediante un análisis de descomposición histórica. Los resultados principales indican que la contribución de la aversión al riesgo global para explicar la evolución de los flujos de deuda aumentó durante marzo de 2020 en comparación con el pasado, aunque su importancia relativa ha disminuido desde entonces, particularmente a medida que mejoró el desempeño de los mercados financieros.","PeriodicalId":371613,"journal":{"name":"International Journal of Finance & Economics","volume":"33 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121183194","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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