Regime switching模型下的幂式期权定价（英文）

研究了标的资产价格过程服从马尔科夫调节的几何布朗运动时的欧式幂型看涨期权的定价问题.特别是,市场利率,标的风险资产的预期收益率与波动率随着马尔科夫链的状态转移而变化.由于市场不完备,通过采用regime switching Esscher变换得到一个等价鞅测度并给出期权的定价公式.最后,考虑了所得结果的数值分析.

Barrier Option Pricing in Regime Switching Models with Rebates

This paper is concerned with the valuation of single and double barrier knock-out call options in a Markovian regime switching model with specific rebates.The integral formulas of the rebates are derived via matrix Wiener-Hopf factorizations and Fourier transform techniques,also,the integral representations of the option prices are constructed.Moreover,the first-passage time density functions in two-state regime model are derived.As applications,several numerical algorithms and numerical examples are presented.

Risk-minimizing Hedging Strategy for an Equity-indexed Annuity under a Regime Switching Model

The equity-indexed annuity （EIA） contract offers a proportional participation in the performance of a specified equity index, in addition to a guaranteed return on the single premium. How to manage the risk of the EIA is an important issue. This paper considers the hedging of the EIA. We assume that the parameters of the financial model depend on a continuous-time finite-state Markov chain and the Markov chain is observed, that is the Markov regime switching model. The state of the Markov chain can be interpreted as the state of an economy. Under the regime switching model~ we obtain the risk-minimizing hedging strategy for the EIA.

MULTI-PERIOD MEAN-VARIANCE PORTFOLIO SELECTION WITH MARKOV REGIME SWITCHING AND UNCERTAIN TIME-HORIZON

This paper investigates a multi-period mean-variance portfolio selection with regime switching and uncertain exit time. The returns of assets all depend on the states of the stochastic market which are assumed to follow a discrete-time Markov chain. The authors derive the optimal strategy and the efficient frontier of the model in closed-form. Some results in the existing literature are obtained as special cases of our results.

中国的粮价上涨在趋稳吗——基于Nonlinear Regime Switching模型的研究

长期以来,粮食价格作为'百价之基'对我国社会整体物价水平以及国民经济的平稳运行产生着极其重要的影响,正确把握和认识粮食价格的波动规律将有助于制定更加有效的宏观调控政策。近十年来,随着中国经济结构的发展以及外部经济环境的变化,中国的粮食价格波动特性与波动规律也发生了较大变化。本文通过运用结构性突变时态转换模型对中国三十年以来主要粮食品种价格波动特性进行研究,发现粮价的高低增长时态区间在显著缩小,粮食整体价格上涨在趋于稳定,趋稳拐点发生在2004年,其中粮食最低收购价政策通过提高农民整体收益预期成为熨平粮价上涨最主要的推动因素。

Evidence on the Effects of Money Growth on Inflation with Regime Switching

Since the latter half of 2010, a new round of inflation has gradually been manifesting in China. The debate regarding whether excess money supply is responsible for this inflation has attracted scholars to investigate the effects of money growth on inflation. In this paper, we use correlation analysis to confirm the comovement between growth of monetary aggregates and inflation. We explore the asymmetric effects of monetary policy on inflation using the Markov regime-switching model The empirical results show that monetary policy can be more effective in curbing inflation in a high inflation state than in boosting the price level in a low inflation state. However, simply tightening the money supply might not be sufficient to suppress the price level To this end, the Chinese Government should adopt other policies, such as supply stabilization policies, to help suppress the price level Our study can help policy-makers to determine the actual economic state and provides some policy implications for the current inflation.

Regime Switching Levy模型下的局部风险最小套期保值策略

本文假定风险资产的价格满足马尔可夫调制的几何Levy过程,其中市场利率、风险资产的平均回报率、波动率以及跳跃强度和幅度都依赖于市场的经济状态,这些经济状态由一连续时间马尔可夫链描述.由于该模型下的市场是不完备的,在本文中我们首先采用局部风险最小化方法获得了欧式未定权益的最优套期保值策略.接着,本文给出了一个具体的例子,得到了马尔科夫调制的几何布朗运动模型下的最优套期保值策略的数值结果.最后将该最优套期保值策略与Black-Scholes模型下Delta套期保值策略进行了比较,证实了不确定因素-马氏链的存在给风险管理者的投资决策带来了影响.

Time-Inconsistent Stochastic LQ Problem with Regime Switching

This paper investigates a time-inconsistent stochastic linear-quadratic problem with regime switching that is characterized via a finite-state Markov chain.Open-loop equilibrium control is studied in this paper whose existence is characterized via Markov-chain-modulated forward-backward stochastic difference equations and generalized Riccati-like equations with jumps.

Stochastic Maximum Principle for Forward-Backward Regime Switching Jump Diffusion Systems and Applications to Finance

The authors prove a sufficient stochastic maximum principle for the optimal control of a forward-backward Markov regime switching jump diffusion system and show its connection to dynamic programming principle. The result is applied to a cash flow valuation problem with terminal wealth constraint in a financial market. An explicit optimal strategy is obtained in this example.

A Markov Copula Model with Regime Switching and Its Application

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.

Markov repairable systems with stochastic regimes switching

Compared with the classical Markov repairable system, the Markov repairable system with stochastic regimes switching introduced in the paper provides a more realistic description of the practical system. The system can be used to model the dynamics of a repairable system whose performance regimes switch according to the external conditions. For example, to satisfy the demand variation that is typical for the power and communication systems and reduce the cost, these systems usually adjust their operating regimes. The transition rate matrices under distinct operating regimes are assumed to be different and the sojourn times in distinct regimes are governed by a finite state Markov chain. By using the theory of Markov process, Ion channel theory, and Laplace transforms, the up time of the system are studied. A numerical example is given to illustrate the obtained results. The effect of sojourn times in distinct regimes on the availability and the up time are also discussed in the numerical example.

A New Regime Switching Model with State-Varying Endogeneity

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.

Valuation of correlation options under a stochastic interest rate model with regime switching

We consider the valuation of a correlation option, a two-factor analog of a European call option, under a Hull-White interest rate model with regime switching. More specifically, the model parameters are modulated by an observable, continuous-time, finite-state Markov chain. We obtain an integral pricing formula for the correlation option by adopting the techniques of measure changes and inverse Fourier transform. Numerical analysis, via the fast Fourier transform, is provided to illustrate the practical implementation of our model.

PMCMC for Term Structure of Interest Rates under Markov Regime Switching and Jumps

A parameter estimation method,called PMCMC in this paper,is proposed to estimate a continuous-time model of the term structure of interests under Markov regime switching and jumps.There is a closed form solution to term structure of interest rates under Markov regime.However,the model is extended to be a CKLS model with non-closed form solutions which is a typical nonlinear and non-Gaussian state-space model(SSM)in the case of adding jumps.Although the difficulty of parameter estimation greatly prevents from researching models,we prove that the nonlinear and non-Gaussian state-space model has better performances in studying volatility.The method proposed in this paper will be implemented in simulation and empirical study for SHIBOR.Empirical results illustrate that the PMCMC algorithm has powerful advantages in tackling the models.

Bayesian Markov Regime-Switching Models for Cointegration

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.

Practical stability and instability of regime-switching diffusions

This work is devoted to practical stability of a class of regime-switching diffusions. First, the notion of practical stability is introduced. Then, sufficient conditions for practical stability and practical instability in probability and in pth mean are provided using a Lyapunov function argument. In addition, easily verifiable conditions on drift and diffusion coefficients are also given. Moreover, examples are supplied for demonstration purposes.

Goal Achieving Probabilities of Mean-Variance Strategies in a Market with Regime-Switching Volatility

In this paper, we establish properties for the switch-when-safe mean-variance strategies in the context of a Black-Scholes market model with stochastic volatility processes driven by a continuous-time Markov chain with a finite number of states. More precisely, expressions for the goal-achieving probabilities of the terminal wealth are obtained and numerical comparisons of lower bounds for these probabilities are shown for various market parameters. We conclude with asymptotic results when the Markovian changes in the volatility parameters appear with either higher or lower frequencies.

Dynamic Hedging Based on Markov Regime-Switching Dynamic Correlation Multivariate Stochastic Volatility Model

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.

A Markov-switching dynamic regression analysis of the asymmetries related to the determinants of US crude oil production between 1982 and 2019

The structural changes brought about by shale oil revolution have inspired this paper of which the aim is to analyze the potential asymmetries related to the determinants of crude oil production in the USA.Thus,using a Markov-switching dynamic regression model in which parameters change when oil production moves from one regime to the other,it is found that for both oil production and oil relative importance,the regime that was dominant during the 1980s and the early 1990s when oil production in the USA was substantially high is the same regime that has once again become dominant in the decade corresponding to the shale oil revolution.Furthermore,the study reveals the existence of asymmetries in the relationship between US crude oil production and both manufacturing production and the consumer price index.Asymmetries are also found in the relationship between the relative importance US crude oil and manufacturing production.Finally,it is found that the intercept and the variance parameter also vary from one regime to the other,thus justifying the use of regime-dependent models.

中国国债收益率曲线的混频周期机制研究——基于区制转移混频期限结构模型

文章在混频数据信息的现实条件下,为充分揭示我国国债收益率曲线的混频周期(非线性)特征及其与宏观经济的作用机制,提出了一种新的区制转移混频Nelson-Siegel期限结构(MS-MF-NS)模型。研究结果表明:与传统混频模型相比,MS-MF-NS模型因恰当引入经济周期行为而进一步提高了国债收益率的拟合效果;利率期限结构具有显著的周期行为特征,该特征受到期限结构斜率因子的逆经济周期行为的影响;在考虑经济周期因素后,斜率因子对宏观经济预测提供更多的前瞻性信息,基于通胀预期机制斜率因子对通货膨胀的预测作用也会显著增强;在非线性模型框架下,因合理刻画宏观经济对国债收益率作用机制的周期性差异,使得宏观基本面对收益率曲线及期限结构因子的贡献更加显著。货币政策调控需要考虑期限结构的非线性作用机制,基于统筹发展与安全的思想理念适度微调,同时需要关注货币政策跨周期和逆周期调节对期限结构的反馈效应。