Regime-switching purchasing power parity in Latin America: Monte Carlo unit root tests with dynamic conditional score

We suggest a Monte Carlo simulation-based unit root test of the purchasing power parity theory for Latin American countries. Under the null hypothesis, we use a Markov regime-switching (MS) model with unit root in the conditional location and MS volatility dynamics. Under the alternative hypothesis, the proposed test incorporates Markov regime-switching autoregressive moving average (MS-ARMA) plus MS volatility dynamics. Under both the null and alternative hypotheses, one of the volatility models estimated is Beta-t-EGARCH, which is a recent dynamic conditional score volatility model. We use data on real effective exchange rate time series for 14 Latin American countries. For each country, we estimate by Monte Carlo simulation the critical values of the unit root test. We provide an economic discussion of the unit root test results and also study the robustness of MS-ARMA plus MS volatility with respect to smooth transition autoregressive models with Fourier function.     

Nonlinearity and nonstationarity in international art market prices: evidence from Markov-switching ADF unit root tests

This study investigates the presence (or lack thereof) of nonlinear dynamics and nonstationarity in international art market prices using quarterly data for the period 1990–2011. We first test whether art market price indices follow stochastic trends or whether they are stationary by means of linear unit root tests. Next, we estimate the Markov regime-switching ADF model and test whether the linear or the nonlinear regime-switching model provides a better characterization of the global art market price series. We find that all art market price indices (except for Drawings) exhibit nonlinearity. To our knowledge, our study is the first one in the literature to suggest that a nonlinear (Markov regime-switching) model provides a better characterization of the behavior of price dynamics in international art markets. In particular, our findings indicate that the market for the overall global art market, paintings, old masters, sculptures, photographs, prints, and contemporary art might indeed be stationary while exhibiting nonlinear regime-switching properties. On the other hand, the market for drawings and the Nineteenth century art are found to be nonstationary. Overall, despite the common ground of a regime-switching framework, we still find that the sub-segments of the art market have their own inner regime switching dynamics and hence they can evolve differently overtime.     

Financial crises and regime-dependent dynamics

Generalized with the regime-dependent beliefs and regime-switching dynamics, the simple market-maker framework established by Day and Huang (1990) is capable to model all types of crises, that is, sudden crisis, disturbing crisis and smooth crisis, and to offer economic and dynamic justifications on how and why these crises appear. Moreover, the model simulations verify the salient qualitative and statistical properties commonly observed in the real financial data such as fat tails, volatility clustering, long range dependence, leverage effect and other stylized facts. Additionally, the model replicates the various chart patterns widely applied in the technical analysis.     

A regime-switching approach to the study of speculative attacks: A focus on EMS crises

This paper implements a regime-switching framework to study speculative attacks against EMS currencies during 1979–1993. To identify speculative episodes, we model exchange rates, reserves, and interest rates as time series subject to discrete regime shifts between two possible states: “tranquil” and “speculative”. We allow the probabilities of switching between states to be a function of fundamentals and expectations. The regime-switching framework improves the ability to identify speculative attacks vis-à-vis the indices of speculative pressure used in the literature. The results also indicate that fundamentals (particularly budget deficits) and expectations drive the probability of switching to a speculative state. First Version Received: October 2000/Final Version Received: June 2001     

Interactions between real economic and financial sides of the US economy in a regime-switching environment

This objective of this study is to examine the linkages between real (economic) and financial variables in the United States in a regime-switching environment that accounts explicitly for high volatility in the stock market and high stress in financial markets. Since the linearity test shows that the linear model should be rejected, we employ the Markov-switching VECM to examine the same objective using the Bayesian Markov-chain Monte Carlo method. The regime-dependent impulse response function (RDIRF) highlights the increasing importance of the financial sector of the economy during stress periods. The responses and their fluctuations are significantly greater in the high-volatility regime than in the low-volatility regime.     

Heterogeneous expectations in the foreign exchange market

In this study a regime-switching approach is applied to estimate the chartist and fundamentalist (c&f) exchange rate model originally proposed by Frankel and Froot (1986). The c&f model is tested against alternative regime-switching specifications applying likelihood ratio tests. Nested atheoretical models like the popular segmented trends model suggested by Engel and Hamilton (1990) are rejected in favour of the multi-agent model. Our findings turned out to be relatively robust when assessing the models sub-sample estimates and out-of-sample performance.JEL Classification: F31, F37, G12, G15 Correspondence to: S. Reitz     

Asset allocation under stochastic interest rate with regime switching

We investigate an optimal asset allocation problem in a Markovian regime-switching financial market with stochastic interest rate. The market has three investment opportunities, namely, a bank account, a share and a zero-coupon bond, where stochastic movements of the short rate and the share price are governed by a Markovian regime-switching Vasicek model and a Markovian regime-switching Geometric Brownian motion, respectively. We discuss the optimal asset allocation problem using the dynamic programming approach for stochastic optimal control and derive a regime-switching Hamilton–Jacobi–Bellman (HJB) equation. Particular attention is paid to the exponential utility case. Numerical and sensitivity analysis are provided for this case. The numerical results reveal that regime-switches described by a two-state Markov chain have significant impacts on the optimal investment strategies in the share and the bond. Furthermore, the market prices of risk in both the bond and share markets are crucial factors in determining the optimal investment strategies.     

Another look at competition: a regime–switching aproach

Measuring the level of competition in an industry is an empirical task with a lengthy history. Many of the traditional measures offer a snapshot of the industry, where the distribution of market share is examined at a given point in time. The purpose of this inquiry is to utilize a regime-switching model which highlights the importance of intra-industry movement. The empirical results suggest that even in an environment where the distribution of market share is improving, an industry can still be persistently dominated by the same collection of leading firms.     

A regime-switching approach to estimating the nonlinear quantity-based monetary policy rule in China

This article focuses on the quantity-based monetary policy rule in China. The article applies a Markov regime-switching approach to estimate the nonlinear policy rule using quarterly data from 1997Q1 to 2015Q2. Overall, the performance of the estimated two-state rule is significantly better than the performance of the linear rule. The regime-switching estimation suggests that the quantity-based policy tool displays a countercyclical response to the inflation gap but a pro-cyclical response to the output gap during recessions. In addition, this article provides notable evidence of the fact that China’s central bank has been targeting inflation over the gradual course of financial liberalization.     

市场整合研究方法与传达的信息

本文从认识市场结构和运作效率的角度,分析和比较了近年市场整合研究文献中使用较多的两种方法——协整检验和状态转换模型,对市场的"完全整合"、"不完全整合"和"市场隔离"三种状况进行理论界定,并在此基础上系统比较两种方法在提供关于市场状况信息方面的功能。本文认为单纯的"价格整合"既不是"市场整合"的必要条件也非充分条件;状态转换模型有着全面考查市场效率所需的价格、交易成本和贸易量三方面信息的能力,但它在了解市场之间的相互影响及其调整过程等动态分析方面尚有一定局限。     

Pricing foreign equity options with regime-switching

In this paper, we investigate the valuation of two types of foreign equity options under a Markovian regime-switching mean-reversion lognormal model, where some key model parameters in the dynamics of the foreign equity price and the foreign exchange rate are modulated by a continuous-time, finite-state Markov chain. A fast Fourier transform (FFT) approach is applied to provide an efficient way to evaluate the option prices. Numerical analysis and empirical studies are provided to illustrate the practical implementation of the proposed pricing model.     

Responses of international stock markets to oil price surges: a regime-switching perspective

We propose an enhanced regime-switching model to investigate the relationships between oil price surges and stock market cycles in five oil-dependent countries. Our model accounts for the joint effects of the West Texas Intermediate (WTI) and Brent oil markets and simultaneously captures asymmetry, volatility persistence and regime shifts contained in the underlying financial data. We find that stock market returns strongly exhibit a regime-switching behaviour, but they react differently to the increases in the price of oil. More precisely, the conditional volatility of studied stock markets during the bear market phases is found to be less affected by oil price surges than during the bull market phases. Whether the effects of oil shocks are positive or negative depends greatly on the degree of reliance on imported oil, the share of the cost of oil in the national income and the degree of improvement in energy efficiency of a given country. Finally, the relatively opposite effects of the WTI and Brent oil markets suggest the potential of substitution between them as well as the necessity of a diversification strategy of oil supply sources.     

Household lending, interest rates and housing price bubbles in Korea: Regime switching model and Kalman filter approach

This study investigates whether interest rates and household lending caused housing price bubbles in Korea over the period of 1986 to 2003. Using a regime-switching model, we found evidence of the existence of housing price bubbles throughout the sample period, with the exception of 1998 when Korea suffered from a financial crisis. Using a Kalman filter technique, we estimated the size of housing price bubbles for the sample period. Finally, using generalized impulse response function analysis and variance decompositions, we found that housing price bubbles increased with household lending and industrial production, whereas they decreased with interest rate; this latter effect is relatively small, however. Policy implications include the importance of preemptive intervention on household lending in order to contain housing price bubbles, but interest rates appear to be a less effective policy tool.     

House price dynamics,conditional higher-order moments,and density forecasts

Most studies on housing price dynamics are only concerned with the conditional mean and variance, but overlook other higher-order conditional moments and the structural change characteristics inherent in housing prices. In order to take into account these two important issues, this study utilizes the generalized Markov switching GARCH model to explore house price dynamics and conditional distribution for US market over 1975Q1–2007Q4. The housing return follows two distinct dynamics: the bust regime and the boom regime. The volatility pattern is different in the bust and boom regimes. In addition, the conditional densities derived by the regime-switching model change dramatically over time and are significantly different from normal distribution. More importantly, the regime-switching model can detect in advance a weak US housing market such as the one that occurred in the middle of 2007. The in-sample fitting ability of regime-switching model, which incorporates higher-order moments, has significant improvements compared to the single-regime AR and AR-GARCH models. For the out-of-sample Value-at-Risk forecasting performance, the ability of regime-switching AR-GARCH model to forecast one-step-ahead density is better compared to the single-regime AR-GARCH model.     

Regime-switching in volatility and correlation structure using range-based models with Markov-switching

This study examines latent shifts in the conditional volatility and correlation for the U.S. stock and T-bond data using the two-state Markov-switching range-based volatility and correlation models. This paper comes up with clear evidence of volatility regime-switching in stock indices and T-bond over the crisis period. As regards the process of correlation, we also find evidence of regime changes in correlations between stock indices and T-bond over several financial crises. We conclude that the phenomena of both volatility and correlation regime-switching are triggered by these financial crises. In addition, the range-based volatility and correlation model with regime-switching method could explicitly point out the true date of structure changes in the data generating process for volatility and correlation variables.     

Private sector involvement in the resolution of financial crises: How do markets react?

To correct the disincentives of liquidity assistance during financial crises, the official sector attempts to involve the private sector in the resolution of debt crises. This paper empirically tests the reaction of investors to announcements of private sector involvement (PSI). For this purpose, we disentangle shifts in risk premia incorporated in excess returns on emerging market bonds into changes in risk and shifts in the price of risk. A regime-switching ARCH-M model is employed to separate two regimes with respect to the market price of risk. While PSI has no effect on risk, it is shown that the likelihood of switching to a state with a high price of risk rises in response to PSI announcements. Thus, the results indicate that burden sharing was credible and, hence, effective.     

China’s government finance and food security nexus: a regime switching analysis

This paper is an empirical assessment of the government finance and food security nexus in China from 1978 to 2016. Using autoregressive distributed lag for linear and threshold cointegration, the results suggest that China’s government finance and food security have reinforced each other throughout the reform era when a structural break was allowed in the model. However, the strength of cointegration and Granger causality in the government-led food security link is stronger, hence supporting the state interventionist view that a strong state has played a dominant role in fulfilling national food security in China. China’s government finance and food security changes indicate food sector reform probabilities under fiscal constraint, as regime-switching indicators have delineated the Chinese government’s difficult fiscal periods and the main reforms in the food sector. In practice, this result implies that further policy reforms can be effective for China’s future food security.     

Multivariate multiple regression modelling for technology analysis

Technology analysis is important for technology management areas such as research and development strategy and new product development. So many studies on technology analysis have been used across a diverse array of fields. Most of these were based on patent analysis, which analyses patent documents using text mining and statistics. The studies on conventional patent analyses constructed models consisting of various independent variables (technologies) and one dependent variable. But in reality, we have to consider a model that includes several dependent variables at the same time, because most technologies influence each other. In this paper, we propose a methodology for patent analysis that reflects the various response technologies simultaneously. We perform multivariate multiple regression modelling in order to efficiently conduct our technology analysis. To show how our modelling can be applied to realistic context, we carry out a case study using the patent documents related to three-dimensional printing technology.     

Evaluating currency crises: the case of the European monetary system

In this paper we examine the nature of currency crises. We ascertain whether the currency crises of the European Monetary System (EMS) were based either on fundamentals, or on self-fulfilling market expectations driven by extrinsic uncertainty. In particular, we extend previous work of Jeanne and Masson (J Int Econ 50:327–350, 2000) regarding the evaluation of currency crisis. We contribute to the existing literature proposing the use of Markov regime-switching with time-varying transition probability model. Our empirical results suggest that the currency crises of the EMS were not due only to market expectations driven by external uncertainty, or ‘sunspots’, but also to fundamental variables that help to explain the behavior of market expectations. We would like to thank Joseph Byrne, James Mitchell, Martin Weale and two anonymous referees for very useful comments and suggestions.