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Network structure, portfolio diversification and systemic risk

Journal of Management Science and Engineering 2021年第2期6卷 235-245页

作者： Shouwei Li Chao Wang School of Economics and Management Southeast UniversityNanjing211189China College of Finance Nanjing Agricultural UniversityNanjing210095China

We investigate the effect of portfolio diversification on banking systemic risk,where the network effect is *** analyze three kinds of interbank networks,namely,random networks,small-world networks and scale-free *** show that the effect of portfolio diversification on banking systemic risk depends on interbank network structures and shock ***,systemic risk increases first and then reduces with the increase of the level of portfolio diversification in the case of the individual ***,in the case of the systemic shock,systemic risk reduces with the increases of the level of portfolio ***,banking systems with scale-free network structures are the most stable,and those with small-world network structures are the most vulnerable.

关键词： portfolio diversification Network structure System risk Banking system

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International portfolio diversification: A Cluster Analysis Approach

International Portfolio Diversification: A Cluster Analysis ...

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The Fifth International Conference on Information and Management Sciences

作者： Kok-Sun Mak Tak-Kee Hui School of BusinessMonash University Malaysia Department of Decision SciencesNUS Business School

＜正＞One of the critical aspects of modern portfolio theory is to deal with the merits of international diversification, which is closely linked with the co-movements and interdependence between stock markets. This paper aims to investigate the potential of diversifying into U.S. and some Asia Pacific markets by studying the co-movements of the monthly returns of the markets between July 1997 and Dec 2004. The markets considered are: Australia, China, Hong Kong, India, Japan, Malaysia, Singapore, South Korea, Taiwan, Thailand and the U.S. Cluster analysis is first used to classify the markets into groups such that markets within the same group move quite closely in tandem with each other while movements of markets from different groups are not quite closely related. The correlation coefficients between the monthly returns of the markets are used as the measures of similarity between the markets. Then from each group the market with the highest monthly return per unit risk is selected to form a portfolio. An optimum investment strategy is then derived using the Markowitz algorithm, i.e. weight of investment in each market in the portfolio is determined so that the risk is minimized for a given rate of return. We will also look at the stability of the cluster structure by applying the same technique over three sub-periods.

关键词： portfolio diversification cluster analysis correlation coefficient Markovvitz algorithm

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Is a correlation‑based investment strategy beneficial for long‑term international portfolio investors?

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Financial Innovation 2023年第1期9卷 1739-1764页

作者： Seema Wati Narayan Mobeen Ur Rehman Yi‑Shuai Ren Chaoqun Ma Asia Pacific Applied Economics Association MelbourneAustralia Shaheed Zulfikar Ali Bhutto Institute of Science and Technology(SZABIST) IslamabadPakistan South Ural State University 76 Lenin ProspektChelyabinskRussian Federation School of Public Administration Hunan UniversityChangshaChina Research Institute of Digital Society and Blockchain Hunan UniversityChangshaChina Centre for Resource and Environmental Management Hunan UniversityChangshaChina The Energy Centre University of AucklandAucklandNew Zealand Business School Hunan UniversityChangshaChina

Using negative to low-correlated assets to manage short-term portfolio risk is not uncommon among investors,although the long-term benefits of this strategy remain *** study examines the long-term benefits of the correlation strategy for portfolios based on the stock market in Asia,Central and Eastern Europe,the Middle East and North Africa,and Latin America from 2000 to *** strategy is as *** develop five portfolios based on the average unconditional correlation between domestic and foreign assets from 2000 to *** yields five regional portfolios based on low to high *** the presence of selected economic and financial conditions,long-term diversification gains for each regional portfolio are evaluated using a panel cointegration-based testing *** across all portfolios and regions,our key cointegration results suggest that selecting a low-correlated portfolio to maximize diversification gains does not necessarily result in long-term diversification *** empirical method,which also permits the estimation of cointegrating regressions,provides the opportunity to evaluate the impact of oil prices,*** market fluctuations,and investor sentiments on regional portfolios,as well as to hedge against these ***,we extend our data to cover the years 2017–2022 and find that our main findings are robust.

关键词： portfolio diversification portfolio mix Asia Central and Eastern Europe Middle East North Africa Latin America

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