Markov Switching Model Research Articles

Common and idiosyncratic components of Latin American business cycles connectedness

ABSTRACT This paper investigates the evolution of business cycles synchronization in Latin America since the 1990ʹs. To do so, a Vector Autoregressive model is fed, alternatively, with the countries’ Industrial Production Indexes and with these series filtered by the US financial conditions index, which is considered a common component affecting business cycles in the region. Additionally, a Markov switching model is estimated to identify regional recessions. Our findings indicate that business cycles connectedness rise significantly during regional recessions and that the common factor plays an important role. The evidence supports the usefulness of policy coordination among Latin American economies to cushion the spillover effects of exogenous shocks, and helps to identify subgroups of countries for which such coordination is recommendable.

Geopolitical risk and oil price volatility: Evidence from Markov-switching model

This study explores the predictability of geopolitical risk (GPR) on oil market volatility using autoregressive Markov-regime switching model, and obtains several remarkable findings. First, in-sample results show that high GPR can lead to high fluctuations in oil market. Considering different market states, GPR has different effects. Second, out-of-sample results indicate that GPR has useful information to forecast oil market volatility. Compared to expansions, GPR has a more powerful ability for forecasting oil price volatility during recessions, which are robust to different robustness tests. Third, GPR is effective in long-term forecast horizons. Moreover, geopolitical risk threats and acts are helpful in forecasting oil price volatility, especially geopolitical risk threats.

Cheap Talk in a New Keynesian Model

This paper shows that the stance of fiscal policy does have significant impact on the conduct of monetary policy in the United States. Further, we document that the implied fiscal-monetary policy interactions are subject to regime instability, using a Markov-switching model. Then, we develop a microfoundation of regime switches using a cheap talk game between central bank and government. As a case study, we simulate the effects of regime switches within an otherwise standard New Keynesian model using the cheap talk game in the state-space of our model.

Economic policy uncertainty and commodity market volatility: implications for economic recovery.

As a consequence of the COVID-19 pandemic outbreak, most commodities experienced significant price drops, which were expected to continue well into 2020. As a result, the Markov switching model is used to study the influence of policy uncertainty and the COVID-19 pandemic on commodity prices in the USA. Commodity markets are stimulated by economic policy uncertainty, according to results from a two-state Markov switching model. In both high and low regimes, economic policy uncertainty (EPU) influences the commodity market, according to the study’s findings. However, in the high regime, EPU has a greater influence on the energy and metal sectors. EPU has different influences on commodity markets in high- and low-volatility regimes, according to this study. There is a wide range of correlations between COVID-19 outcomes and EPU and how the prices of natural gas, oil, corn, silver, soybean, copper, gold, and steel respond to these tremors, in both high- and low-volatility tenure. Oil and natural gas, on the other hand, are unaffected by shifts in COVID-19 death rates under either regime. Results show that in both high- and low-volatility regimes, the demand and supply for most commodities are responsive to historical prices.

Financial stability and monetary policy of the Central Bank of West African Countries: a Markov-Switching model

Purpose This paper aims to examine the response of monetary policy to financial instability in the West African Economic and Monetary Union.Design/methodology/approach Through annual aggregated data from 1970 to 2019, the empirical strategy is based on the Markov regime-switching model with fixed probabilities.Findings The results revealed that the monetary policy of the central bank of the West African Economic and Monetary Union is characterized by two regimes (calm and distress) with respect to the trend of financial stability. The authors also found that the occurrence of the calm regime was likely greater than that of the distress regime. In addition, the calm regime is longer than the distress regime. The authors finally revealed that the central bank reacts to financial instability risk by increasing its short-term interest rate when financial instability reaches a threshold.Research limitations/implications The limitation of this study is the unavailability of monthly or quarterly data that are more suitable for the methodological approach adopted.Originality/value This study is the one to estimate the response of the Central Bank of West African Countries to financial stress using a novel approach based on the Markov-Switching regression.

Using Markov-Switching Models in US Stocks Optimal Portfolio Selection in a Black–Litterman Context (Part 1)

In this study, we tested the benefit of using Markov-Switching (M-S) models to forecast the views of the 26 most traded stocks in the US in a Black–Litterman (B–L) optimal selection context. With weekly historical data of these stocks from 1 January 1980, we estimated and simulated (from 7 January 2000, to 7 February 2022) three portfolios that used M-S views in each stock and blended them with the market equilibrium views in a B–L context. Our position was that the B–L optimal portfolios could generate alpha (extra return) against a buy-and-hold and an actively managed portfolio with sample portfolio parameters (à la Markowitz, SampP). Our results suggest that the outperformance of the B–L managed portfolios holds only in the short term. In the long-term, the performance of the B–L portfolios, the SampP, and the market portfolio are statistically equal in terms of returns or their mean–variance efficiency in an ex-ante or ex-post analysis.

Systematic Literature Review With Bibliometric Analysis on Markov Switching Model: Methods and Applications

This study involved a systematic literature review using bibliometric analysis to examine the evolution and current trends of Markov switching studies. The bibliometric analysis was used for the descriptive, intellectual, social, and conceptual network analyses, while systematic reviews were used to identify the application of the Markov switching model. A total of 449 articles were selected and extracted from the Web of Science (WoS) between 1992 and 2021. The publication trends, most influential countries and articles, leading journals, collaboration networks, research hotspots, research fronts, coupling networks, and application of the model in various disciplines were described. This study summarized the research agenda of the Markov switching field, which would be helpful for researchers and funding agencies.

Portfolio Performance of Islamic Versus Conventional Market Indices and Regime Shift Behavior: Empirical Evidence from Asian Emerging Markets

Purpose: The main objective of this study is to examine the performance analysis of Islamic and conventional portfolio of emerging market of Asia and to investigate whether Islamic indices outperform the conventional indices or not. Moreover, to investigate the regime shift behavior of these markets.
 Design/Methodology/Approach: Emerging markets of Asia like China, India, Indonesia, Malaysia, Pakistan and Thailand are taken. Data is taken for the period January 2010 to December 2019. Data frequency is on monthly closing prices basis for both markets. Risk adjusted measures like Sharpe ratio, Treynor ratio and Jensen alpha are used for performance evaluation. Markov switching model is used to investigate the performance of both indices. Morgan Stanley capital international risk- free rate is used as risk proxy.
 Findings: Sharpe ratio is outperformed in Islamic markets while Treynor ratio is outperformed in conventional markets. Jensen alpha is outperformed in Islamic market so result proved that mostly Islamic markets is outperformed. The Markov switching model divide the MSCI returns into two parts recession and expansion. Results indicated that the presence of regime in both recession and expansion period so investor can diversify the international portfolios. Mix portfolio strategy is indicated that investor behavior is indifferent. There is a change in both regime in recession and expansion period so investor consider the international portfolio diversification with regime shifts.
 Implications/Originality/Value: This study is important for global investor as well as local investor for portfolio diversification. This study is also important for academic scholars, Regulatory authorities and for those who is interested in Islamic funds by their religious views.

Regime shifts in equity risk premium: international evidence

Introduction. The academic discussion dedicated to the specific features of financial crises is focused on the analysis of historical volatility patterns. Most researchers point out that strong long-term fluctuations on stock markets are typical for financial crises. Similar reactions to economic crises can be found throughout financial history. Both academic communities and stock markets participants are interested in the search for driving forces that stimulate such kind of behaviour. Purpose. Studying the influence of the scale of national stock markets and various economic crises on the risk level of operations with financial instruments. Methods. Latent modes were identified using Markov switching models. The determination of latent market states was based on the ratio of the components of financial turbulence that characterise the isolated changes in correlated risks and volatility. The influence of the scale of stock markets on the profitability and risk of operations with financial instruments was assessed using the vector autoregression model. Results. The influence of economic crises on the quantitative characters of the excess returns of the world’s largest stock markets was assessed using two-mode Markov switching models and revealed significant differences in the behaviour of stock markets at different time intervals. It was established that the high volatility regime dominates the market during the periods accompanied by economic crises. Through the combination of typical and atypical values of the financial turbulence components we identified four latent market states that provide additional information on the further changes in the current market regimes or lack thereof. Unilateral causal connections are typical for markets with high capitalisation. Markets adapt to the USA market shocks almost twice as slower as compared to the shocks of developing markets. Conclusions. The identified dependences allow increasing the explanatory and prognostic potential of statistical risk analysis in national stock markets.

SOME REGIME-SWITCHING MODELS FOR ECONOMIC TIME SERIES: A COMPARATIVE STUDY

This paper mainly discusses some regime-switching models and explore their usefulness in modeling the economic time series. In recent years, several time series models have been proposed which shape the idea of the existence of different regimes produced by a stochastic process. Especially, nonlinear time series models have gained more attention because linear time series models faced various limitations. The purpose of this study is to establish the methodology of the Self-Exciting Threshold Autoregressive (SETAR) model, Smooth Transition Autoregressive (STAR) model and Markov-Switching (MSW) model from parametric nonlinear time series models in the mean and to compare these models with each other through two financial data sets. For this purpose, some theoretical information on the subject models are given without going into too much detail. In the light of the obtained theoretical information, all models are modeled by using two financial data sets. The obtained models are compared with the help of some performance criteria, measurement of relative efficiency and graph showing the relation of the actual-fitted values of the models.

FINANCIAL LIBERALIZATION, DEMOCRATIC INSTITUTIONS, AND INCOME INEQUALITY: NEW INSIGHTS FROM PAKISTAN

This study investigates the relationship between financial liberalization, democratic institutions, and income inequality in Pakistan by using a two-state Markov switching (MS) methodology for the period 1972–2017. The dynamic factor modelling approach is used to construct the financial liberalization index. The impact of the Global Financial Crisis (GFC) of 2007–2008 on financial liberalization–institutions–inequality nexus was checked using the Chow breakpoint test. The result reveals no significant effect of GFC on Pakistan’s economy. Results from the MS model divulge that financial liberalization lessens income inequality in the high-income inequality regime as well as in the low-income inequality regime. The result further discloses that democratic institutions enhance income inequality in high-income inequality regimes while reduce income inequality in the low-inequality regime. While studying the joint role of democratic institutions and financial liberalization, it is observed that the weak role of democratic institutions offsets the benefits of financial liberalization in the high-income inequality regime; however, institutions and financial liberalization are supportive in reducing income inequality in the low-inequality regime. Besides, the results also confirm the existence of Kuznets hypothesis in Pakistan. Therefore, there is a need for further reforms to revamp institutions to reduce income inequality in Pakistan.

Consumption- and speculation-led change in demand for oil and the response of base metals: A Markov-switching approach

We examine how base metal returns respond to various oil shocks applying Markov-switching models. We find that both consumption-led and speculation-led increase in demand for oil increase metal returns while an increase in oil supply decreases metal returns. However, the effects of oil supply shocks and speculation-led oil demand shocks are statistically significant mostly in the high volatility regimes indicating a stronger link between oil and base metals in the volatile markets. Our novel finding of regime-dependent relation between oil and metal markets has important implications for both investors and policy makers.

Predictability of bull and bear markets: A new look at forecasting stock market regimes (and returns) in the US

The empirical literature of stock market predictability mainly suffers from model uncertainty and parameter instability. To meet this challenge, we propose a novel approach that combines dimensionality reduction, regime-switching models, and forecast combination to predict excess returns on the S&P 500. First, we aggregate the weekly information of 146 popular macroeconomic and financial variables using different principal component analysis techniques. Second, we estimate Markov-switching models with time-varying transition probabilities using the principal components as predictors. Third, we pool the models in forecast clusters to hedge against model risk and to evaluate the usefulness of different specifications. Our weekly forecasts respond to regime changes in a timely manner to participate in recoveries or to prevent losses. This is also reflected in an improvement of risk-adjusted performance measures as compared to several benchmarks. However, when considering stock market returns, our forecasts do not outperform common benchmarks. Nevertheless, they do add statistical and, in particular, economic value during recessions or in declining markets.

Financialization, natural resources rents and environmental sustainability dynamics in Saudi Arabia under high and low regimes

In light of increasing environmental degradation, a body of research has studied the role that financialization and natural resources endowments can play as an emergency lever for the achievement of a sustainable environment. The previous studies on the factors leading to environmental degradation have followed a restrictive approach as they have resorted mainly to CO2 emissions and ecological footprint. Few existing studies have referred to more globalizing indicators of environmental degradation such as the ecological gap and its dynamics. This study focuses not only on environmental sustainability, but also on its dynamics as proxies of environmental degradation. The aim of our paper is to identify the dynamic impacts on environmental sustainability caused by financial development and natural resources rents in low and high sustainability regimes. Therefore, the objective of this paper is to verify if the provision of a developed financial sector and the endowment of abundant natural resources for a country like Saudi Arabia makes it possible to ensure a sustainable environment. Results based on the Markov switching model in the case of Saudi Arabia spanning the period 1985–2017 revealed that financialization promotes environmental sustainability, but not its dynamics, in high sustainability regime. Our findings reported also that natural resources rents are beneficial for the achievement of environmental sustainability both in low and high sustainability regimes, but do not constitute a means to preserve the dynamics of environmental sustainability. Biomass energy consumption has negative effects on ecological gap and its dynamics under high sustainability regime. Economic growth is beneficial for reducing the ecological gap, but harmful for maintaining a dynamic of environmental sustainability in low sustainability regime. The effects of economic growth are reversed in high sustainability regime. The results found in this study not only offer decision-makers the appropriate policies to achieve a sustainable environment, but also some recommendations to preserve its dynamics.

Volatility spillover analysis between stocks and exchange rate markets in short and long terms in East European and Eurasian countries

PurposeThis paper researches a bidirectional volatility transmission effect between stocks and exchange rate markets in the six East European and Eurasian countries.Design/methodology/approachResearch process involves creation of transitory and permanent volatilities via optimal component generalized autoregressive heteroscedasticity (CGARCH) model, while these volatilities are subsequently embedded in Markov switching model.FindingsThis study’s results indicate that bidirectional volatility transmission exists between the markets in the selected countries, whereas the effect from exchange rate to stocks is stronger than the other way around in both short-term and long-term. In particular, the authors find that long-term spillover effect from exchange rate to stocks is stronger than the short-term counterpart in all countries, which could suggest that flow-oriented model better explains the nexus between the markets than portfolio-balance approach. On the other hand, short-term volatility transfer from stock to exchange rate is stronger than its long-term equivalent.Practical implicationsThis suggests that portfolio-balance theory also has a role in explaining the transmission effect from stock to exchange rate market, but a decisive fact is from which direction spillover effect is observed.Originality/valueThis paper is the first one that analyses the volatility nexus between stocks and exchange rate in short and long term in the four East European and two Eurasian countries.

Spatial dependence in regional business cycles: evidence from Mexican states

This study investigates how regional business cycles are spatially dependent in Mexico by developing a Markov switching model with a spatial autoregressive process. The Markov switching model with two regimes distinguishes business cycles between expansion and recession phases (i.e., high- and low-growth rate regimes). The objective of this study is twofold. First, this study aims to identify which states transitioned from expansion to recession during the Great Recession in 2008–2009. Second, it numerically examines the extent to which states that experienced this transition caused a deterioration in neighboring states’ economies. Employing Bayesian inference for the Markov switching model with quarterly data of state economic activity during the period 2003:Q1–2015:Q4, this study finds that Mexican states with higher manufacturing sector shares tended to be in recession during the Great Recession. Although some states experienced economic downturns in this period, they were not in a recessionary regime. This study also finds that business cycles across states were spatially dependent during the Great Recession. The numerical simulations of spatial spillover effects suggest that states that regime-switched from expansion to recession during the Great Recession caused a reduction in the quarterly growth rate of their neighboring economies by an average of 0.39 percentage points.

Empirical analysis of asymmetry phenomenon in the public debt structure of Sub-Saharan Africa's five biggest economies: A Markov-Switching model

This study examined the sustainability of the future path of public debts in sub-Saharan Africa's five biggest economies.In light of the COVID 19 outbreak, the study adopts the Markov-switching model (MSM) to analyse the un(sustainability) of public debt in sub-Saharan Africa's five biggest economies (namely Nigeria, South Africa, Angola, Ghana and Ethiopia). The MSM approach is motivated by the idea that a country might be solvent in the short term but may face fiscal shocks which may violate sustainability in future. More importantly, the Markov-switching model provides us with the unusual advantage of estimating precise answers as to the probabilities of a regime switch as well as the time they would occur.Using the log-likelihood and information criteria, the result supports a two-state regime for all the 5 countries selected in this study. State 1 is the low-debt ratio state (sustainable debt) with a standard deviation lower than state 2, while the high-debt ratio state (unsustainable debt) is the regime with the higher standard deviation (State 2). The result also indicates that the probability of transitioning between both regimes are highly persistent. One economic implication of the forecast result is that future public debt levels in sub-Saharan African countries might not aid Africa Union's 2063 development targets.

Impact of oil demand and supply shocks on food-grain prices: a Markov-switching approach

ABSTRACT This study examines the impact of structural oil demand and supply shocks on the prices of four food-grains: corn, rice, soybean and wheat. We first derive two oil demand shocks-one is due to the change in the global economic condition and the other is oil-market-specific-and an oil supply shock that reflects the change in global oil production. The structural shocks are then used in the linear, and nonlinear Markov-switching models to examine their effects on the four food-grain prices. The results show that an unanticipated oil supply shock does not affect price of any of the four food-grains significantly. An increase in the demand for oil, which is not induced by the change in global economic condition, increases only the corn price in the less volatile corn market. An improvement of global economic condition impacts wheat and corn prices in high volatility regimes. However, oil shocks that are older than one month usually do not affect the food-grain prices.

The Impact of Global Economic Policy Uncertainty, Geopolitical Risk and Oil Price on Stock Market: Evidence From Asean Countries

Using monthly data from January 1997 to July 2020, this study examines the impact of Global Economic Policy Uncertainty (GEPU), Geopolitical Risk (GPR), and oil price (WTI) on ASEAN stock exchanges such as the Jakarta Stock Exchange (JSE), Kuala Lumpur Composite Index (KLCI), Philippine Stock Exchange (PSI), Stock Exchange of Thailand (SET), and Vietnam Stock Index (VNI). We use a two-stage Markov switching model to model market returns as a time-varying transition probability Markovian process. The findings reveal some fascinating new information, such as the fact that global policy uncertainty has a strong negative impact on the bulk of ASEAN stock returns during periods of high volatility. Another finding shows that, contrary to assumptions, geopolitical concerns had no effect across all samples. We also discovered that, in both the low and high volatility regimes, oil price changes have a considerable impact on all ASEAN stock markets.

Explaining Aggregated Recovery Rates

This study on explaining aggregated recovery rates (ARR) is based on the largest existing loss and recovery database for commercial loans provided by Global Credit Data, which includes defaults from 5 continents and over 120 countries. The dependence of monthly ARR from bank loans on various macroeconomic factors is examined and sources of their variability are stated. For the first time, an influence of stochastically estimated monthly growth of GDP USA and Europe is quantified. To extract monthly signals of GDP USA and Europe, dynamic factor models for panel data of different frequency information are employed. Then, the behavior of the ARR is investigated using several regression models with unshifted and shifted explanatory variables in time to improve their forecasting power by taking into account the economic situation after the default. An application of a Markov switching model shows that the distribution of the ARR differs between crisis and prosperity times. The best fit among the compared models is reached by the Markov switching model. Moreover, a significant influence of the estimated monthly growth of GDP in Europe is observed for both crises and prosperity times.