It is important to consider the changing states in hedging.The Markov regime-switching dynamic correlation multivariate stochastic volatility( MRS-DC-MSV) model was proposed to solve this issue. DC-MSV model and MRS-D...It is important to consider the changing states in hedging.The Markov regime-switching dynamic correlation multivariate stochastic volatility( MRS-DC-MSV) model was proposed to solve this issue. DC-MSV model and MRS-DC-MSV model were used to calculate the time-varying hedging ratios and compare the hedging performance. The Markov chain Monte Carlo( MCMC) method was used to estimate the parameters. The results showed that,there were obviously two economic states in Chinese financial market. Two models all did well in hedging,but the performance of MRS-DCMSV model was better. It could reduce risk by nearly 90%. Thus,in the hedging period,changing states is a factor that cannot be neglected.展开更多
Regime switching,which is described by a Markov chain,is introduced in a Markov copula model.We prove that the marginals（X,H^i）,i = 1,2,3 of the Markov copula model（X,H） are still Markov processes and have marting...Regime switching,which is described by a Markov chain,is introduced in a Markov copula model.We prove that the marginals（X,H^i）,i = 1,2,3 of the Markov copula model（X,H） are still Markov processes and have martingale property.In this proposed model,a pricing formula of credit default swap（CDS） with bilateral counterparty risk is derived.展开更多
In this paper,we propose a state-varying endogenous regime switching model(the SERS model),which includes the endogenous regime switching model by Chang et al.,the CCP model,as a special case.To estimate the unknown p...In this paper,we propose a state-varying endogenous regime switching model(the SERS model),which includes the endogenous regime switching model by Chang et al.,the CCP model,as a special case.To estimate the unknown parameters in the SERS model,we propose a maximum likelihood estimation method.Monte Carlo simulation results show that in the absence of state-varying endogeneity,the SERS model and the CCP model perform similarly,while in the presence of state-varying endogeneity,the SERS model performs much better than the CCP model.Finally,we use the SERS model to analyze Chinese stock market returns,and our empirical results show that there exists strongly state-varying endogeneity in volatility switching for the Shanghai Composite Index returns.Moreover,the SERS model can indeed produce a much more realistic assessment for the regime switching process than the one obtained by the CCP model.展开更多
Business cycle dynamics are determined by relatively large volatilities in output,consumption,and investment,which leads to cyclical fluctuations in interest rates.Using the Markov switching model,we model the nominal...Business cycle dynamics are determined by relatively large volatilities in output,consumption,and investment,which leads to cyclical fluctuations in interest rates.Using the Markov switching model,we model the nominal interest rate movements to explain the volatility regime shifts in a set of selected emerging Asian economies.The estimated results provide significant evidence of regime-dependent means,variances,and probabilities in both stable and volatile regimes in selected countries,confirming the existence of two distinct regimes in nominal interest rate movements.In addition,the smoothed probability results of switching autoregressive model show that the model is capable of capturing the two regimes for the corresponding nominal interest rate behaviors.Besides,the results reveal that the stables regimes have higher durations than the volatile regimes.This study also shows the advantage of Markov switching models over conventional regression models,allowing the identification of different regimes for the cyclical behavior of interest rates.展开更多
基金National Natural Science Foundation of China(No.71401144)
文摘It is important to consider the changing states in hedging.The Markov regime-switching dynamic correlation multivariate stochastic volatility( MRS-DC-MSV) model was proposed to solve this issue. DC-MSV model and MRS-DC-MSV model were used to calculate the time-varying hedging ratios and compare the hedging performance. The Markov chain Monte Carlo( MCMC) method was used to estimate the parameters. The results showed that,there were obviously two economic states in Chinese financial market. Two models all did well in hedging,but the performance of MRS-DCMSV model was better. It could reduce risk by nearly 90%. Thus,in the hedging period,changing states is a factor that cannot be neglected.
基金Supported by Jiangsu Government Scholarship for Overseas Studiesthe NNSF of China(Grant Nos.11401419,11301369,11371274)+1 种基金the CPSF(2014M561453)the NSF of Jiangsu Province(Grant Nos.BK20140279,BK20130260)
文摘Regime switching,which is described by a Markov chain,is introduced in a Markov copula model.We prove that the marginals（X,H^i）,i = 1,2,3 of the Markov copula model（X,H） are still Markov processes and have martingale property.In this proposed model,a pricing formula of credit default swap（CDS） with bilateral counterparty risk is derived.
基金The authors extend their sincere thanks to the editor and two referees for their insightful comments that helped improve the article substantially.This research is supported by the National Natural Science Foundation of China(Project 71803091)by the MOE(Ministry of Education in China)Project of Humanities and Social Sciences(Project 18YJC790015).
文摘In this paper,we propose a state-varying endogenous regime switching model(the SERS model),which includes the endogenous regime switching model by Chang et al.,the CCP model,as a special case.To estimate the unknown parameters in the SERS model,we propose a maximum likelihood estimation method.Monte Carlo simulation results show that in the absence of state-varying endogeneity,the SERS model and the CCP model perform similarly,while in the presence of state-varying endogeneity,the SERS model performs much better than the CCP model.Finally,we use the SERS model to analyze Chinese stock market returns,and our empirical results show that there exists strongly state-varying endogeneity in volatility switching for the Shanghai Composite Index returns.Moreover,the SERS model can indeed produce a much more realistic assessment for the regime switching process than the one obtained by the CCP model.
文摘Business cycle dynamics are determined by relatively large volatilities in output,consumption,and investment,which leads to cyclical fluctuations in interest rates.Using the Markov switching model,we model the nominal interest rate movements to explain the volatility regime shifts in a set of selected emerging Asian economies.The estimated results provide significant evidence of regime-dependent means,variances,and probabilities in both stable and volatile regimes in selected countries,confirming the existence of two distinct regimes in nominal interest rate movements.In addition,the smoothed probability results of switching autoregressive model show that the model is capable of capturing the two regimes for the corresponding nominal interest rate behaviors.Besides,the results reveal that the stables regimes have higher durations than the volatile regimes.This study also shows the advantage of Markov switching models over conventional regression models,allowing the identification of different regimes for the cyclical behavior of interest rates.
