This paper introduces a Bayesian Markov regime-switching model that allows the cointegration relationship between two time series to be switched on and off over time. Unlike classical approaches for testing and modeli...This paper introduces a Bayesian Markov regime-switching model that allows the cointegration relationship between two time series to be switched on and off over time. Unlike classical approaches for testing and modeling cointegration, the Bayesian Markov switching method allows for estimation of the regime-specific model parameters via Markov Chain Monte Carlo and generates more reliable estimation. Inference of regime switching also provides important information for further analysis and decision making.展开更多
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
This study examines a novel relationship between volatility and dynamic herding behavior during COVID-19 by examining the relationship of oil market volatility,Global volatility and Infectious disease equity market vo...This study examines a novel relationship between volatility and dynamic herding behavior during COVID-19 by examining the relationship of oil market volatility,Global volatility and Infectious disease equity market volatility with time-varying herding behavior in energy stock of Developed markets.Using country level data,this study observes that market switch between anti-herding to herding state during pandemic and all three volatility measures have significant impact on dynamic herding state under high dispersion regime.However,in low dispersion regime only global volatility has significant impact on time-varying herding behavior.This study suggests that the level of speculation in energy sector affect investor behavior;therefore,policy makers should monitor and model possible signals related to health crisis that can be transformed in to financial market crisis.展开更多
In this paper,we consider the price of catastrophe options with credit risk in a regime-switching model.We assume that the macroeconomic states are described by a continuous-time Markov chain with a finite state space...In this paper,we consider the price of catastrophe options with credit risk in a regime-switching model.We assume that the macroeconomic states are described by a continuous-time Markov chain with a finite state space.By using the measure change technique,we derive the price expressions of catastrophe put options.Moreover,we conduct some numerical analysis to demonstrate how the parameters of the model affect the price of the catastrophe put option.展开更多
目的基于Markov模型评价肺结节低剂量螺旋CT(LDCT)筛查的卫生经济学。方法利用2021年—2023年北京市某三甲医院的肺结节LDCT筛查数据和部分国外临床研究数据,采用成本效用分析方法,通过增量成本效用比(ICUR)确定优势筛查策略;使用R语言...目的基于Markov模型评价肺结节低剂量螺旋CT(LDCT)筛查的卫生经济学。方法利用2021年—2023年北京市某三甲医院的肺结节LDCT筛查数据和部分国外临床研究数据,采用成本效用分析方法,通过增量成本效用比(ICUR)确定优势筛查策略;使用R语言获得转移概率参数,利用TreeAge Pro 2011软件构建Markov模型。假设以我国10万名55岁及以上人群为肺结节筛查对象,模拟其疾病发展情况,并通过敏感性分析评价该模型的稳定性。结果成本效用分析显示,该模型经20次循环后,LDCT筛查策略的总成本为3543088618元,相较于不筛查策略的总成本增加了784130651元,额外获得了7996个质量调整生命年(QALY),每获得一个QALY需多花费98059.77元。采用WHO卫生经济学评价标准,LDCT筛查策略的ICUR大于1倍人均国内生产总值(GDP)但小于3倍人均GDP,为优势策略。敏感性分析显示,各变量在其敏感性分析范围内无论如何变化,都不会对ICUR产生较大影响,表明该模型具有较好的稳定性。结论在55岁及以上人群中开展每年一次肺结节LDCT筛查的ICUR小于3倍人均GDP,具有一定的经济学效用,该筛查策略有利于肺癌的“早发现、早诊断、早治疗”。展开更多
目的:基于中国卫生服务体系角度评价血塞通软胶囊对比安慰剂治疗缺血性中风患者的经济性。方法:基于血塞通软胶囊的Ⅲ期对照试验和已发表的文献数据构建markov模型,模拟患者终身的质量调整生命年(quality-adjusted life year,QALY)和增...目的:基于中国卫生服务体系角度评价血塞通软胶囊对比安慰剂治疗缺血性中风患者的经济性。方法:基于血塞通软胶囊的Ⅲ期对照试验和已发表的文献数据构建markov模型,模拟患者终身的质量调整生命年(quality-adjusted life year,QALY)和增量成本效果比(Incremental cost-effectiveness ratio ICER),并进行单因素敏感性分析和概率敏感性分析检验模型的不确定性。结果:基础分析结果显示,与安慰剂组相比,血塞通软胶囊在获得0.32个QALY且节约医疗成本,具有绝对优势,单因素敏感性分析和概率敏感性分析验证了模型的稳健性。单因素敏感性分析显示对模型结果影响程度最大的4个因素分别是mRS3-5首次住院成本、mRS0-2首次住院成本、mRS0-2的状态效用值及贴现率;概率敏感性分析显示在我国的意愿支付值之下血塞通软胶囊具有经济性的概率为100%。结论:与安慰剂相比,血塞通软胶囊在提升QALY的同时降低了相应的成本,对治疗我国缺血性中风患者具有经济性。展开更多
为研究设备可用度对列车控制中心(TCC,Train Control Center)的影响和预测TCC的剩余使用寿命(RUL,Remaining Useful Life),降低TCC的故障发生率,确保车辆安全运行,构建TCC动态故障树模型。通过引入Markov理论,将其转化为Markov模型,设计...为研究设备可用度对列车控制中心(TCC,Train Control Center)的影响和预测TCC的剩余使用寿命(RUL,Remaining Useful Life),降低TCC的故障发生率,确保车辆安全运行,构建TCC动态故障树模型。通过引入Markov理论,将其转化为Markov模型,设计了TCC可用度评估与RUL预测方法;考虑了TCC的失效率和共因失效,利用D-S(Dempster-Shafer)证据理论对失效数据作数据融合处理,得到TCC设备初始故障区间概率;在此基础上,采用超椭球模型约束设备初始故障区间概率,得到更加精确的底事件故障区间概率;画出Markov状态转移图,用矩阵推导出TCC可用度和RUL的函数关系式,且对可用度的计算还考虑了维修因素。以兰州—乌鲁木齐客运专线某TCC数据作为分析案例,用该方法计算TCC及其各设备的可用度,并预测TCC的RUL。结果表明:与通用方法相比,评估结果相同,但评估信息更丰富。展开更多
文摘This paper introduces a Bayesian Markov regime-switching model that allows the cointegration relationship between two time series to be switched on and off over time. Unlike classical approaches for testing and modeling cointegration, the Bayesian Markov switching method allows for estimation of the regime-specific model parameters via Markov Chain Monte Carlo and generates more reliable estimation. Inference of regime switching also provides important information for further analysis and decision making.
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.
文摘This study examines a novel relationship between volatility and dynamic herding behavior during COVID-19 by examining the relationship of oil market volatility,Global volatility and Infectious disease equity market volatility with time-varying herding behavior in energy stock of Developed markets.Using country level data,this study observes that market switch between anti-herding to herding state during pandemic and all three volatility measures have significant impact on dynamic herding state under high dispersion regime.However,in low dispersion regime only global volatility has significant impact on time-varying herding behavior.This study suggests that the level of speculation in energy sector affect investor behavior;therefore,policy makers should monitor and model possible signals related to health crisis that can be transformed in to financial market crisis.
基金supported by the Jiangsu University Philosophy and Social Science Research Project(Grant No.2019SJA1326).
文摘In this paper,we consider the price of catastrophe options with credit risk in a regime-switching model.We assume that the macroeconomic states are described by a continuous-time Markov chain with a finite state space.By using the measure change technique,we derive the price expressions of catastrophe put options.Moreover,we conduct some numerical analysis to demonstrate how the parameters of the model affect the price of the catastrophe put option.
文摘目的基于Markov模型评价肺结节低剂量螺旋CT(LDCT)筛查的卫生经济学。方法利用2021年—2023年北京市某三甲医院的肺结节LDCT筛查数据和部分国外临床研究数据,采用成本效用分析方法,通过增量成本效用比(ICUR)确定优势筛查策略;使用R语言获得转移概率参数,利用TreeAge Pro 2011软件构建Markov模型。假设以我国10万名55岁及以上人群为肺结节筛查对象,模拟其疾病发展情况,并通过敏感性分析评价该模型的稳定性。结果成本效用分析显示,该模型经20次循环后,LDCT筛查策略的总成本为3543088618元,相较于不筛查策略的总成本增加了784130651元,额外获得了7996个质量调整生命年(QALY),每获得一个QALY需多花费98059.77元。采用WHO卫生经济学评价标准,LDCT筛查策略的ICUR大于1倍人均国内生产总值(GDP)但小于3倍人均GDP,为优势策略。敏感性分析显示,各变量在其敏感性分析范围内无论如何变化,都不会对ICUR产生较大影响,表明该模型具有较好的稳定性。结论在55岁及以上人群中开展每年一次肺结节LDCT筛查的ICUR小于3倍人均GDP,具有一定的经济学效用,该筛查策略有利于肺癌的“早发现、早诊断、早治疗”。
文摘目的:基于中国卫生服务体系角度评价血塞通软胶囊对比安慰剂治疗缺血性中风患者的经济性。方法:基于血塞通软胶囊的Ⅲ期对照试验和已发表的文献数据构建markov模型,模拟患者终身的质量调整生命年(quality-adjusted life year,QALY)和增量成本效果比(Incremental cost-effectiveness ratio ICER),并进行单因素敏感性分析和概率敏感性分析检验模型的不确定性。结果:基础分析结果显示,与安慰剂组相比,血塞通软胶囊在获得0.32个QALY且节约医疗成本,具有绝对优势,单因素敏感性分析和概率敏感性分析验证了模型的稳健性。单因素敏感性分析显示对模型结果影响程度最大的4个因素分别是mRS3-5首次住院成本、mRS0-2首次住院成本、mRS0-2的状态效用值及贴现率;概率敏感性分析显示在我国的意愿支付值之下血塞通软胶囊具有经济性的概率为100%。结论:与安慰剂相比,血塞通软胶囊在提升QALY的同时降低了相应的成本,对治疗我国缺血性中风患者具有经济性。
文摘为研究设备可用度对列车控制中心(TCC,Train Control Center)的影响和预测TCC的剩余使用寿命(RUL,Remaining Useful Life),降低TCC的故障发生率,确保车辆安全运行,构建TCC动态故障树模型。通过引入Markov理论,将其转化为Markov模型,设计了TCC可用度评估与RUL预测方法;考虑了TCC的失效率和共因失效,利用D-S(Dempster-Shafer)证据理论对失效数据作数据融合处理,得到TCC设备初始故障区间概率;在此基础上,采用超椭球模型约束设备初始故障区间概率,得到更加精确的底事件故障区间概率;画出Markov状态转移图,用矩阵推导出TCC可用度和RUL的函数关系式,且对可用度的计算还考虑了维修因素。以兰州—乌鲁木齐客运专线某TCC数据作为分析案例,用该方法计算TCC及其各设备的可用度,并预测TCC的RUL。结果表明:与通用方法相比,评估结果相同,但评估信息更丰富。
