Markov-switching Regression Research Articles

Optimal asset allocation and nonlinear return predictability from the dividend-price ratio

AbstractWe study non-linear predictability of stock returns arising from the dividend-price ratio and its implications for asset allocation decisions. Using data from five countries — U.S., U.K., France, Germany and Japan — we find empirical evidence supporting non-linear and time-varying models for the equity risk premium. Building on this, we examine several model specifications that can account for non-linear return predictability, including Markov switching models, regression trees, random forests and neural networks. Although in-sample return regressions and portfolio allocation results support the use of non-linear predictability models, the out-of-sample evidence is notably weaker, highlighting the difficulty in exploiting non-linear predictability in real time.

The Nonlinear Nexus of Climate Policy Uncertainty and Renewable Energy Consumption in the United States of America: A Markov-Switching Approach

We employ a Markov-Switching regression model using monthly US data from April 1987 to August 2022 to investigate the effect of climate policy uncertainty (CPU) on renewable energy consumption (REC). The main findings suggest the presence of a nonlinear relationship between CPU and REC. The baseline analysis using the CPU index reveals an adverse effect in regimes characterized by high levels of uncertainty. However, the effect is not statistically significant in a low uncertainty regime. To account for potential variations in the results, we perform a robustness analysis that considers the effect of CPU on REC, which may fluctuate based on the authorities' contextual perspectives (i.e., being in favor or against climate policy) and also the effect of CPU on REC by household. In addition, we incorporate a robustness check by utilizing the environmental policy uncertainty index developed by Noailly et al. (2022). The robustness test results confirm the results obtained from the baseline estimation.

Market Reactions to U.S. Financial Indices: A Comparison of the GFC versus the COVID-19 Pandemic Crisis

This study delves into the impacts of the 2008 global financial crisis (GFC) and the COVID-19 health crisis on U.S. financial indices, exploring the intricate relationship between economic shocks and these indices during downturns. Using Markov switching regression models and control variables, including GDP, consumer sentiment, industrial production, and the ratio of inventories-to-sale, it quantifies the effects of these crises on the CBOE Volatility Index (VIX), Standard & Poor’s 500 (S&P 500), and the Dow Jones Industrial Average (DJIA) from Q1 2000 to Q2 2023, covering crucial moments of both crises and stable periods (dichotomous variables). Results reveal that the 2008 crisis significantly heightened financial volatility and depreciated the valuation of S&P 500 and DJIA indicators, while the COVID-19 crisis had a diverse impact on market dynamics, particularly negatively affecting specific sectors. This study underscores the importance of consumer confidence and inventory management in mitigating financial volatility and emphasises the need for robust policy measures to address economic shocks, enhance financial stability, and alleviate future crises, especially during endogenous crises such as financial downturns. This research sheds light on the nuanced impact of crises on financial markets and the broader economy, revealing the intricate dynamics shaping market behaviour during turbulent times.

Interactive influence of house prices and the repo rate on household debt in South Africa

<p><big>The recent interest rate policy decisions of the South African Reserve Bank have been criticized significantly by left-leaning political parties and civic society organisations for being anti-poor, anti-labour, and pro-capital because of their implications for household debt. Existing literature has established that interest rates and house prices are insignificant determinants of household debt dynamics in South Africa. Taking advantage of additional data for the period 2013-2022, and contrary to the previous studies, the paper maintains that house prices and the central bank policy rate play a crucial role in household debt dynamics. Applying a Markov Switching regression to quarterly data for the period 1981Q1 to 2022Q1, the paper finds that house prices and the policy rate have a significant influence on household debt dynamics. It establishes the existence of a ‘house price boom, low policy rate burden’ regime and a ‘high policy rate burden, low house price’ regime. The coexistence of the ‘house price boom’ and the ‘low policy rate’ explains the debt euphoria characterised by significant household leveraging.</big></p>

Foreign investor portfolio flow and monetary policy response in the Indonesian stock market considering the COVID-19 pandemic

Foreign portfolio investment in developing countries, including Indonesia, plays a crucial role in the economy, where this fund flow can influence exchange rates and stimulate price increases in the stock market. During the COVID-19 pandemic, the volatility of foreign portfolio flows by investors has significantly increased. To anticipate these conditions, the monetary authorities in Indonesia have implemented various monetary policies to address the possibility of more adverse situations. This study examines the impact of the inflow or outflow of foreign portfolio investments and the monetary policies reflected in the 7-day repo rate of Bank Indonesia on the Indonesian stock market. The data were collected from April 4, 2016, to March 18, 2022. The research methodology involves the Non-Linear Autoregressive Distributed Lag and the Markov Switching Regression (MSR) model. The findings indicate that foreign investor portfolio flows influence the Jakarta Composite Index. There is a tendency for domestic investors to analyze the habits of foreign investors. The study also found that monetary policy is not proven to affect the Jakarta Composite Index, while the USD/IDR exchange rate has an impact on the Indonesian stock market. This indicates many companies listed on the Indonesia Stock Exchange have debt in dollars or are paid in US dollars, making them vulnerable to exchange rate fluctuations.

Asymmetric and Nonlinear Foreign Debt–Inflation Nexus in Brazil: Evidence from NARDL and Markov Regime Switching Approaches

This paper augments the sparse literature on the inflationary impact of foreign debt in Brazil while addressing methodological caveats in previous studies. We depart from the linearity assumption and employ two nonlinear techniques: the nonlinear autoregressive distributed lag (NARDL) model and a Markov Switching Regression (MSR) to investigate the connection between foreign debt and inflation within a multivariate framework. The analyses consider the presence of structural breaks via assessing variable stationarity using the Zivot and Andrew unit root test and incorporating a residual-based cointegration test proposed by Gregory and Hansen. Additionally, we apply a multiple structural breakpoints test by Bai and Perron to determine the presence of structural breaks in the impact of foreign debt on inflation. Our findings robustly indicate that the domestic money supply has a statistically significant positive effect, while the nominal effective exchange rate has a negative effect on inflation in both the short and long run. The NARDL model reveals that only positive changes in foreign debt have a statistically significant negative effect on inflation in the short run, whereas both positive and negative foreign debt changes significantly affect inflation in the long run. The results from the MSR model are generally consistent with those of the NARDL model.

Conditional macroeconomic and stock market volatility under regime switching: Empirical evidence from Africa

<abstract> <p>We used the Markov switching regression model to establish a relationship between the conditional stock market returns and macroeconomic volatilities. Monthly data from thirteen (13) African stock markets and macroeconomic variables (exchange rate, inflation, interest rate, money supply, and crude oil price) from 2003 to 2022 were employed. We confirmed the existence of two distinct regimes: An economic expansion or a "tranquil" state with less volatility and an economic decline or a "crisis" state with high volatility. Our findings indicated that macroeconomic variables significantly affect both expansion and crisis periods. However, the estimated coefficients were more significant in a tranquil than in a crisis state. The findings of the study were consistent with macroeconomic theory and pointed out policy implications.</p> </abstract>

The effect of gas and oil prices on economic confidence: An empirical analysis for euro area

Energy prices are determinants of economic confidence by directly affecting production, consumption, and transportation costs. Nevertheless, countries’ energy policies and macroeconomic and geopolitical developments may moderate the impact of energy prices on economic confidence. This study analyzes the effects of oil and gas prices on business and confidence in the Euro Area over the period 1994–2023. We employ non-linear correlation and regression models to investigate the spillover relationship between the variables. For this purpose, the Markov Switching Regression (MSR) model is employed to analyze the spillover effect of oil and gas prices on both consumer and business confidence. The empirical results show that oil and gas prices harm consumer confidence in all regimes. Oil prices have a positive effect on business confidence in a volatility regime. However, oil prices negatively affect business confidence in low volatility, but this effect is insignificant. The effect of gas prices on the business confidence index is negative and statistically significant during periods of high volatility. Besides, gas prices positively affect business confidence for low volatility.

Effects of Interest Rate Policy on Inflation

This paper analyzes the episodes of high inflation and the efficacy of raising interest rates in reducing inflationary pressures in the U.S. economy. Estimating a Markov-switching regression model, the results show that high inflation frequently occurred from 1975 to 1983 with the most prolonged duration. In the 2000s, there were merely two inflationary months in 2008, but this is too short to call it a period. Then, after a period of low inflation in 2020, inflationary pressure started to build up. From March 2021 to the present, a period of high inflation has been prevailing. The estimation results suggest that the period from 1976 to 1983 is one episode of the high inflation period, and the period from 2016 to 2022 is the second period, which is about equal in length to both periods. A simple sub-period analysis shows that an increase in the federal funds rate lowers future inflation in both periods. A vector autoregression model is then estimated to identify the monetary policy channel via the short-term interest rate together with other variables such as inflation expectations and real economic activity. A one standard deviation increase in the federal funds rate can reduce annual inflation by up to 1.6 percent in the first period and 0.74 percent in the second. The effects on expected inflation are also comparable. The results suggest that interest rate policy has been effective in controlling inflation.

Stock Returns and State-Dependent Effects of Changes in Exchange Rate and Money Supply from Central Banks

This study investigates the state-dependent effects of exchange rate movements and money supply shocks on stock market returns using daily stock returns, exchange rate, and variations in money supply data obtained from the databank.worldbank.org website from 1990 to 2022. The stock markets of ten emerging and developed countries were used in the study. The Markov-Switching regression methodology was utilized for this study. The results suggest that for the developed stock markets, in Regime 1, a positive shock to the money supply stimulated a significant rise in the stock returns while in Regime 2, a positive shock to the money supply induced a drop in returns. This suggests that for the developed stock markets, the effect of money supply shock on returns is state-dependent. In the developing stock markets, the coefficient for exchange rate was negative and significant in Regime 1, while it was insignificant in Regime 2. Therefore, the effect of exchange rate on returns is state-dependent in developing countries. Also, the coefficient for volatility in the exchange rate was negative and sizable in both regimes, indicating that the returns effect of volatility is not state-dependent. Basically, each day the exchange rate appreciates, stock returns rises in the developed stock markets while a devaluation policy executed in developing countries stimulated some decline in returns of emerging markets. In both regimes, a rise in money supply shock had positive and significant returns. The effect of money supply on stock returns is not state-dependent. Consequently, developing countries need flexible approaches to managing the variations in the exchange rates and money in circulation. While policymakers in developed markets may need to focus more on reducing volatility rather than adjusting exchange rates to influence stockpiling, those of emerging countries could benefit more from policies that stabilize exchange rates.

Gold and CoVid-19: Uncovering the safe haven hypothesis with dynamic MSR modeling

During the catastrophic Covid-19 era, numerous assets experienced a decline in their original values, leaving the financial community grappling with the implications of the pandemic. A significant concern arising from this context is whether gold emerged as the ultimate safe haven during the pandemic and whether there were any shifts in investor behavior between the two waves of the pandemic. To address these concerns, we employed relevant analytical approaches, utilizing a dynamic Markov-Switching Regression (MSR) model. Our findings indicate that during both waves of Covid-19, gold exhibited characteristics of a safe haven asset against bonds, providing a hedge against economic turmoil. However, when it comes to stocks, gold's role slightly changed. It acted as a diversifier, offering a different pattern of returns compared to equities. This highlights gold's ability to adapt to evolving market characteristics.These results emphasize the importance of conducting further research on this topic to gain deeper insights into the factors influencing gold's behavior during periods of crisis. By expanding our understanding, we can refine risk management strategies and enhance portfolio performance in turbulent market conditions.

PARTISANSHIP, REGULATION, AND VOLATILITY IN SOUTH KOREA'S HOUSING MARKET

South Korea's mortgage loan policy, which represents a regulatory policy for stabilizing the housing market, has changed significantly in accordance with changes in presidency and partisanship. Which partisan government's housing policy has been most effective in stabilizing the market? To answer this question, we discuss the different partisanships of Korea's conservative and progressive parties, their policy preferences, and the previous governments’ key housing policies. Thereafter, we concretize the research methodology and examine the housing volatility witnessed since 1987, using the Markov‐switching regression. The results reveal that the market was highly unstable when the progressive government actively promoted regulation in favor of “governmentalist” partisanship. Moreover, the policy was mostly effective in lowering apartment prices in Seoul, which was the regulation's primary target all along. Based on these findings, we conclude with some policy implications of the study. Given that governmentalist partisanship heightens volatility in the housing market, housing market policies should be designed to hedge the negative externalities of partisanship.

Testing Okun's Law Over the Business Cycle: The Case of South Africa

ABSTRACT: Understanding the relationship between output and unemployment (Okun's law) is important for policymakers, particularly during crises. One of the aspects of Okun's law that is commonly examined during crises is the structural stability and behavior of Okun's law over the business cycle. While this issue has been addressed empirically in developed countries, little is known about it in developing countries such as South Africa. Hence, this study examines the structural stability and behavior of Okun's law over the business cycle in South Africa. This study adopts both the difference and gap methods of formalizing Okun's law to implement its objectives. The recursive rolling window method was used to test the structural stability of Okun's law over time. The behavior of Okun's law over the business cycle is examined using the Markov-switching regression method. This study was conducted using the data from 1994Q1 to 2021Q1. The results of this study show that Okun's law varies over the business cycle because the response of unemployment to economic expansion is quite different from that of economic contraction. Okun's law holds during economic expansion but fails to hold during an economic recession. Evidence from this study also reveals that the coefficients of Okun's law vary over time. For instance, in the case of the difference method, Okun's coefficients range from 0.063 to 1.221 in absolute terms. For the gap method, especially when the H-P filtering method is applied, Okun's coefficients range from 0.509 to 9.412 in absolute terms. In summary, the findings from this study suggest that cyclical unemployment responds more significantly to cyclical output growth than the response of changes in unemployment to changes in output. In addition, this study proves that Okun's law is unstable over time in South Africa. These findings imply a high degree of variability between the labor and goods markets in the country. Hence, policies must be designed to harmonize the divergence between the two markets. This will require the implementation of macroeconomic policies such as fiscal and monetary policies. From a fiscal policy perspective, the government should reduce taxes or provide tax holidays to firms. The interest rate should be set low in the case of monetary policy.

Does Islamic banking reduce the risks of COVID-19 for SMEs? Novel evidence for SME financing in the pandemic period for an emerging market

This paper aims to examine the effect of COVID-19 on SME bank lending in the Islamic banking sector to small and medium-sized enterprises (SMEs) in an emerging market: Turkey. Understanding whether SME bank lending in the Islamic banking sector is procyclical or not is very important to reduce the impact of COVID-19 on SMEs. Interrupted time series analysis (ITSA), the Markov switching regression model, and vector autoregressive (VAR) methodologies are employed using novel weekly data for the pandemic period. The present study finds that the Islamic banking sector for SME financing has behaved countercyclically during COVID-19 in the Turkish economy. The paper thus sheds new light on the relationship between Islamic bank lending for SME financing and the COVID-19 shock in an important emerging market. The findings can provide insights into how Islamic banks mitigate the effect of COVID-19 on SMEs in an emerging market context. The present paper clearly shows differences between Islamic bank lending toward SMEs and deposit bank lending toward SMEs in the pandemic era. The willingness of Islamic banks to supply loans to SMEs during the pandemic plays a vital role in reducing SME firm failure in the Turkish economy.

Carbon emissions and sustainability in Covid-19's waves: evidence from a two-state dynamic Markov-switching regression (MSR) model.

Throughout the world, carbon emissions have decreased in an unprecedented way as a result of the Covid-19 pandemic. The purpose of this paper is to investigate whether a rebound effect in carbon emissions is anticipated following the extraction of information related to the beliefs of investors. A suitable Markov switching model is used in this paper to adapt the safe haven financial methodology to an environmental sustainability perspective. Analytically, the aforementioned situation is modeled by estimating a two-state dynamic Markov-Switching Regression (MSR), with a state-dependent intercept term to capture the dynamics of the series, across unobserved regimes. In light of the results of the research and the robustness checks, investors are anticipating a rebound effect on the total quantity of carbon emissions.

Dynamics of the gas retail market under China's price cap regulation

To stabilise gas prices and safeguard consumer interests, China introduced a new price cap regulation for the gas retail market in 2013. This study is the first to evaluate the impact of this price cap regulation on the dynamics of retail gas prices. By using an asymmetric error correction model and Markov-switching regression based on daily gas-station-level price data from Inner Mongolia, China, we establish that retail prices respond asymmetrically to price caps, rather than crude oil prices, implying that price caps may serve as focal points for gas stations to collude tacitly. Additionally, the cyclic nature of retail prices is not obvious under the price cap regulation, which provides some evidence for the buffering effect of price caps on price cycles. Finally, we establish that price cycle characteristics differ by gas station and brand. These results may provide a better understanding of retail price dynamics in a price-cap-regulated market and guide policymakers and planners in optimising regulatory policies.

The Lead-Lag Relationship Between International Food Prices, Freight Rates, and Trinidad and Tobago's Food Inflation: A Support Vector Regression Analysis

The objective of this study is to empirically investigate: i) the extent in which shipping costs can cause and predict the food inflation in Trinidad and Tobago (T and T); ii) the extent in which international food prices can drive food inflation in T and T; and iii) the impact of the Russia-Ukraine conflict on food prices in T and T. As a fourth sub-objective, this study seeks to provide policy recommendations to address the food price inflation in T and T. A structural model is sought as it can use information about the past prices of the international food prices and shipping rates to forecast T and T's food price inflation. this study used monthly data on T and T retail price index food subcategory, the FAO Food Price Index (FFPI), and the Freightos Baltic Index over the January 2015 to November 2022 period. the Support Vector Regression (SVR) model was applied and used the FFPI and Freightos Baltic Index as the leading indicators to forecast T and T's food price inflation. this study found that the FAO Food Prices does and the Freightos Baltic Index does have an impact on food prices in T and T. Secondly, based on the FAO index and the Freightos Baltic Index, T and T's food price inflation should be 14.91% lower than its present value. third, in a Markov Switching regression, the war dummy was only significant in the second regime, statistically suggesting that the Russia-Ukraine conflict only had a short term effect on T and T's food prices. this contributed to the literature as it introduced a new test to investigate predictive causality. Policy measures to increase the agriculture output and address the food price inflation in T and T include adopting sustainable farming practices such as integrated pest management T and The sustainable water management, and encouraging aquaponics.

A Markov Switching Approach in Assessing Oil Price and Stock Market Nexus in the Last Decade: The Impact of the COVID-19 Pandemic.

We revisit the oil price and stock market nexus by considering the impact of major economic shocks in the post-global financial crisis (GFC) scenario. Our breakpoint unit root test and Markov switching regression (MRS) analyses using West Texas Intermediate (WTI) oil price and Standard & Poor's 500 (S&P 500) market index show that among the major economic events, the recent coronavirus (COVID-19) pandemic is the most significant contributor to market volatilities. Furthermore, our MRS results show that the relationship between oil price and the stock market is regime-dependent; the stock market experiences substantial and positive shocks in a volatile oil price regime. Our results provide valuable insights to investors and policymakers regarding risk management and financial market stability during economic crisis periods, specifically during the COVID-19 pandemic.

Gelişmekte Olan Ülkelerde Kredi Temerrüt Takası (CDS) Primlerinin Belirleyicileri: Türkiye'den Kanıtlar

Turkey faces increasing CDS (Credit Default Swap) spreads. The level of CDS spreads shows the riskiness of a country in terms of credit default and countries can’t attract high foreign investment inflows when CDS spreads are high. In this context, countries need to identify the influential factors in order to decrease CDS spreads. In this study, ten independent variables classified in global, macro, and market factors are analyzed using monthly data between January 2004 and December 2019 with autoregressive distributed lag (ARDL), fully modified least square (FMOLS), dynamic ordinary least square (DOLS), and Markov Switching Regression (MSR) after applying principal component analysis (PCA). The results show that (i) market component has a greater effect than other components for all models, which indicates that it is the most important variable for Turkey’s CDS spreads; (ii) global and market components are positive and statistically significant for the ARDL, FMOLS, and DOLS models; (iii) macro component is negative for all models.

The Impact of ECB’s Unconventional Monetary Policy on the German Stock Market Volatility

Abstract This study investigated the reaction of German stock market volatility (Dax index) to the European Central Bank (ECB)’s unconventional monetary policy (UMP) announcements. The financial crisis of 2008 proved that the traditional monetary policy’s tool (the short -term interest rate) has lost its effectiveness to meet the new challenges. So, the key central banks, ECB included, had to implement the new, untested and nonstandard monetary policy which so called unconventional monetary policy. In this study, we used the ECB’s shadow policy rate approach to extract unconventional monetary policy. Also, We employed GJR GARCH (p,o,q) model to estimate the volatility in the German stock market. Then we calibrated both OLS (linear regression) and Markov-switching (probability-matrix of regime changes) models to examine the reaction of German stock returns volatility to UMP announcement by ECB for a period from January 2006 to December 2019. The results delivered by both models showed that the ECB’s UMP had a strong and negative effect on the volatility of the German stock market. Also, both models showed that the past German stock volatility has a significant and negative effect on the dependent variable, while the volatility of the German stock returns is a function of the global volatility estimated by the VIX index. Moreover, the results showed that the Markov-switching regression model provides a better illustration of the stock market volatility impact of UMP than the OLS model because it can represent the changes into the two different regimes named ordinary regime and quantitative easing (crisis) regime. Furthermore, under the Markov-switching regression model, we can see how the output gap and the inflation gap influence the volatility of the Dax index, while the results of the OLS regression model showed that there is no significant relationship between the output gap and the inflation gap with the German stock market volatility.