We investigate the effect of portfolio diversification on banking systemic risk,where the network effect is incorporated.We analyze three kinds of interbank networks,namely,random networks,small-world networks and sca...We investigate the effect of portfolio diversification on banking systemic risk,where the network effect is incorporated.We analyze three kinds of interbank networks,namely,random networks,small-world networks and scale-free networks.We show that the effect of portfolio diversification on banking systemic risk depends on interbank network structures and shock types.First,systemic risk increases first and then reduces with the increase of the level of portfolio diversification in the case of the individual shock.Second,in the case of the systemic shock,systemic risk reduces with the increases of the level of portfolio diversification.Third,banking systems with scale-free network structures are the most stable,and those with small-world network structures are the most vulnerable.展开更多
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 unclear.This study examines the long-term benefits of...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 unclear.This 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 2016.Our strategy is as follows.We develop five portfolios based on the average unconditional correlation between domestic and foreign assets from 2000 to 2016.This yields five regional portfolios based on low to high correlations.In the presence of selected economic and financial conditions,long-term diversification gains for each regional portfolio are evaluated using a panel cointegration-based testing method.Consistent 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 gains.Our empirical method,which also permits the estimation of cointegrating regressions,provides the opportunity to evaluate the impact of oil prices,U.S.stock market fluctuations,and investor sentiments on regional portfolios,as well as to hedge against these fluctuations.Finally,we extend our data to cover the years 2017–2022 and find that our main findings are robust.展开更多
Market efficiency is based on efficient market hypothesis(EMH).EMH claims that market totally contains the available information.In case of EMH,valid investors who take position will not gain abnormal profits.If the e...Market efficiency is based on efficient market hypothesis(EMH).EMH claims that market totally contains the available information.In case of EMH,valid investors who take position will not gain abnormal profits.If the efficiency can not be established,that is,if markets are not efficient,investors will have the opportunity of abnormal profits.This paper investigates the causality relations to determine validity of EMH among G7(Canada,France,Germany,Italy,Japan,United Kingdom,and United States)countries'stock exchange markets for the period from July 2003 to October 2014.To find out whether the variables cause each other or not provides knowledge about the market efficiency.The implication of this analysis is twofold.One implication is that if the markets are informationally efficient,the possibility of abnormal returns through arbitrage is ruled out and investors can reduce the risk of their investment for the same expected returns,if they establish portfolios that consist of both markets rather than consisting of only one market.Based on this,Hacker-Hatemi-J.bootstrap causality test that is newer and has many advantages contrary to other tests was used.Results showed that EMH is valid among each G7 countries'stock exchange markets.Also portfolio diversification benefits exist among these markets.展开更多
This paper investigates the time-frequency dependence,return and volatility connectedness,dynamic linkages,and portfolio diversification gains among oil and China’s sectoral commodities,namely,Petrochemicals(CIFI),Gr...This paper investigates the time-frequency dependence,return and volatility connectedness,dynamic linkages,and portfolio diversification gains among oil and China’s sectoral commodities,namely,Petrochemicals(CIFI),Grains(CRFI),Energy(ENFI),Non-ferrous metals(NFFI),Oil&Fats(OOFI),and Softs(SOFI),utilizing a proposed research framework that contains the wavelet coherence,novel TVP-VAR based connectedness,and the cDCC-,DECO-FIAPARCH(1,d,1)model.The empirical results demonstrate that global oil market exhibits a relatively higher(lower)coherence with ENFI,NFFI,and OOFI(CRFI)on the long-term time horizon and the oil market leads China’s sectoral commodities during most sample periods.The crude oil market transmits significant connectedness to China’s sectoral commodities,especially the energy commodity sector(ENFI).The dynamic return and volatility total spillovers tend to intensify and exhibit significant fluctuations during the GFC and the oil price collapse.Further,the time-varying linkages among oil and China’s sectoral commodities are positive and fluctuant,mainly at a relatively low level.The dynamic return and volatility connectedness,multi-view linkages,optimal portfolio weights,and hedging ratios display significant time-varying features.The oil-commodity nexus offers diversification benefits and the optimal-weighted portfolio presents the best variance and downside risk reduction performance.Furthermore,risk management effectiveness is market-condition-dependent and heterogeneous across different commodity sectors and sub-samples.This paper can not only help investors and market regulators to capture the complex interconnectedness and risk transmission trajectory among oil and China’s sectoral commodities but also benefits for investors and portfolio managers to construct optimal portfolios and hedging strategies.展开更多
基金supported by National Natural Science Foundation of China(71671037,71971055)The 16th Batch of“Six Talents Peak”High-level Talent Projects in Jiangsu Province(JY-004)Social Science Fund Project of Jiangsu Province(19GLC005)
文摘We investigate the effect of portfolio diversification on banking systemic risk,where the network effect is incorporated.We analyze three kinds of interbank networks,namely,random networks,small-world networks and scale-free networks.We show that the effect of portfolio diversification on banking systemic risk depends on interbank network structures and shock types.First,systemic risk increases first and then reduces with the increase of the level of portfolio diversification in the case of the individual shock.Second,in the case of the systemic shock,systemic risk reduces with the increases of the level of portfolio diversification.Third,banking systems with scale-free network structures are the most stable,and those with small-world network structures are the most vulnerable.
基金supported by the National Natural Science Foundation of China(No.72104075,71850012,72274056)the National Office for Philosophy and Social Sciences Fund of China(No.19AZD014),Natural Science Foundation Project of Hunan Province(No.2022JJ40106)the Hunan University Youth Talent Program.
文摘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 unclear.This 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 2016.Our strategy is as follows.We develop five portfolios based on the average unconditional correlation between domestic and foreign assets from 2000 to 2016.This yields five regional portfolios based on low to high correlations.In the presence of selected economic and financial conditions,long-term diversification gains for each regional portfolio are evaluated using a panel cointegration-based testing method.Consistent 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 gains.Our empirical method,which also permits the estimation of cointegrating regressions,provides the opportunity to evaluate the impact of oil prices,U.S.stock market fluctuations,and investor sentiments on regional portfolios,as well as to hedge against these fluctuations.Finally,we extend our data to cover the years 2017–2022 and find that our main findings are robust.
文摘Market efficiency is based on efficient market hypothesis(EMH).EMH claims that market totally contains the available information.In case of EMH,valid investors who take position will not gain abnormal profits.If the efficiency can not be established,that is,if markets are not efficient,investors will have the opportunity of abnormal profits.This paper investigates the causality relations to determine validity of EMH among G7(Canada,France,Germany,Italy,Japan,United Kingdom,and United States)countries'stock exchange markets for the period from July 2003 to October 2014.To find out whether the variables cause each other or not provides knowledge about the market efficiency.The implication of this analysis is twofold.One implication is that if the markets are informationally efficient,the possibility of abnormal returns through arbitrage is ruled out and investors can reduce the risk of their investment for the same expected returns,if they establish portfolios that consist of both markets rather than consisting of only one market.Based on this,Hacker-Hatemi-J.bootstrap causality test that is newer and has many advantages contrary to other tests was used.Results showed that EMH is valid among each G7 countries'stock exchange markets.Also portfolio diversification benefits exist among these markets.
基金supported by the National Natural Science Foundation of China under Grant No.71573042the Natural Science Foundation of Fujian Province under Grant No.2017J01794。
文摘This paper investigates the time-frequency dependence,return and volatility connectedness,dynamic linkages,and portfolio diversification gains among oil and China’s sectoral commodities,namely,Petrochemicals(CIFI),Grains(CRFI),Energy(ENFI),Non-ferrous metals(NFFI),Oil&Fats(OOFI),and Softs(SOFI),utilizing a proposed research framework that contains the wavelet coherence,novel TVP-VAR based connectedness,and the cDCC-,DECO-FIAPARCH(1,d,1)model.The empirical results demonstrate that global oil market exhibits a relatively higher(lower)coherence with ENFI,NFFI,and OOFI(CRFI)on the long-term time horizon and the oil market leads China’s sectoral commodities during most sample periods.The crude oil market transmits significant connectedness to China’s sectoral commodities,especially the energy commodity sector(ENFI).The dynamic return and volatility total spillovers tend to intensify and exhibit significant fluctuations during the GFC and the oil price collapse.Further,the time-varying linkages among oil and China’s sectoral commodities are positive and fluctuant,mainly at a relatively low level.The dynamic return and volatility connectedness,multi-view linkages,optimal portfolio weights,and hedging ratios display significant time-varying features.The oil-commodity nexus offers diversification benefits and the optimal-weighted portfolio presents the best variance and downside risk reduction performance.Furthermore,risk management effectiveness is market-condition-dependent and heterogeneous across different commodity sectors and sub-samples.This paper can not only help investors and market regulators to capture the complex interconnectedness and risk transmission trajectory among oil and China’s sectoral commodities but also benefits for investors and portfolio managers to construct optimal portfolios and hedging strategies.
