The impact of uncertainty on money demand in the UK, US and Euro area

We estimate money demand functions for the UK, the Euro area and the US using Divisia monetary aggregates and investigate the extent to which the uncertainty caused by Brexit and Covid have affected these relationships. Our cointegrated VAR analysis shows that for all three economies Brexit and/or Covid have had some impact on the stability of money demand functions. We find that including a measure of stock market volatility in the money demand specifications helps re-establish stability of the models, particularly for the UK and the Euro area. We also explore the uncertainty and money demand relationship in the context of a Markov-switching model. We find that the effect of uncertainty on the demand for money is more pronounced during periods of heightened uncertainty. The findings of this study lend support to studies calling for Divisia aggregates to be given a more prominent role in policymaking, especially when interest rates are in the zero lower bound environment and are less informative about the stance of monetary policy.

The euro to dollar exchange rate in the Covid‐19 era: Evidence from spectral causality and Markov‐switching estimation

In this paper, we analyse how the Covid‐19 pandemic changed the dynamics of the euro to dollar exchange rate. To do so, we make use of spectral non‐causality tests to uncover the determinants of the euro to dollar exchange rate, using data that cover the pre‐Covid‐19 and the actual Covid‐19 era, by considering the exchange rate movements of other currencies, the stock market index of S&P 500, and the price of oil and gold, as well as their realized volatilities. Based on our findings, the Covid‐19 pandemic has indeed significantly changed the determinants of the euro to dollar exchange rate. Also, to investigate the potential shifts in the regimes of the euro to dollar exchange rate, we formulate a Markov‐switching model with two regimes, based on the determinants that have been found in the previous step. Based on our findings, the duration of the high volatility state in the Covid‐19 era has doubled, from almost 3 to approximately 6 days, compared to the pre‐Covid‐19 era, whereas the high volatility state in the Covid‐19 era is characterized by a statistically significant higher range of volatility compared to the pre‐Covid‐19 era.

Synchronization in Cycles of China and India During Recent Crises: A Markov Switching Analysis.

We study the impact of recent crisis episodes viz. the Great Recession of 2007-09, the Euro Area crisis of 2010-12 and the COVID-19 pandemic of 2020-21 on the Emerging Market Economies (EMEs) of China and India using data from January, 1986 till June, 2021. A Markov-switching (MS) analysis is applied to discern economy-specific cycles/regimes and common cycles/regimes in the growth rates of the economies. We apply the univariate MS Autoregressive (MS-AR) model to characterize country-specific negative growth, moderate growth and high growth regimes of China and India. We examine the extent of overlap of the identified regimes with the Great Recession, the Eurozone crisis, and the COVID-19 pandemic. Thereafter, we study the regimes depicting common phases in growth rates of China-India and China-India-US by using multivariate MS Vector Autoregressive (MS-VAR) models. The multivariate analysis shows the presence of common negative growth during the turbulent periods during the study period. These results can be explained by the existence of strong trade and financial linkages between the two EMEs and the Advanced economies. The pandemic triggered a recession in the Chinese, Indian and U.S. economies and its impact on growth is much worse than the Great Recession and the Eurozone crises.

News-based uncertainty measures and returns on prices of precious metals: evidence from regime switching and time-varying causality approach

PurposeThe study aims to examine the relationship among economic policy uncertainty (EPU), geopolitical-risks (GPR), the interaction (EPGR) of EPU and GPR and the returns of gold, silver, platinum, palladium and rhodium using monthly data from January (1997) to May (2021).Design/methodology/approachThe paper employs the Markov-switching and the novel Shi et al. (2020) bootstrap time-varying Granger-causality approach.FindingsThough the Markov-switching shows variation in the responses of precious metals to EPU, GPR and EPGR across low and high states, the paper observes the safe-haven potential of the precious metals in the high regime while the hedging potency is also evident in the results. To further substantiate the safe-haven and hedging properties, the time-varying Granger-causality shows the causal effect of EPU on all the selected precious metal returns coinciding with global events. While the authors show that GPR Granger causes platinum, palladium and rhodium consistently under the rolling/recursive-evolving tests, the authors cannot find the causal effect of GPR on gold and silver returns across the algorithms. The paper also observes persistence in the causal effect of EPGR on palladium and platinum across all the algorithms, while gold and rhodium only show consistency in the responses under the rolling- and recursive-evolving algorithms given the conditions of homoscedasticity and heteroscedasticity.Practical implicationsThe authors' results are essential to investors and policymakers since both typically leverage the hedging and safe-haven characteristics of precious metals to obviate downside risks during highly uncertain periods.Originality/valueThe authors' techniques allow examining the hedging and safe-haven properties of precious metals across regimes and date-stamp critical periods of causation inherent in the relationship.

Exploring the Contagion Effect from Developed to Emerging CEE Financial Markets

The paper aims to analyze the contagion effect coming from the developed stock markets of the US and Germany to the emerging CEE stock markets of Romania, Czech Republic, Hungary, and Poland using daily data for the period April 2005–April 2021. The paper also captures the level of integration of these emerging stock markets by analyzing the volatility spillover phenomenon. The quantification of the contagion effect coming from the developed to the emerging stock markets consisted of an empirical analysis based on the DCC-GARCH (Dynamic Conditional Correlation) model. Through this multivariate model, the time-varying conditional correlations were analyzed, both in periods of normal economic development and in times of economic instability, when there was a significant increase in the correlation coefficients between developed and emerging stock market indices. Furthermore, the level of connectedness between these markets has been analyzed using the volatility spillover index developed by Diebold and Yilmaz. The empirical results surprised the high level of integration of the analyzed stock markets in Central and Eastern Europe, with the intensity of volatility transmission between these markets increasing significantly during times of crisis. All stock market indices analyzed show periods during which they transmit net volatility and periods during which they receive net volatility, indicating a bidirectional volatility spillover phenomenon. Mostly, the BET, PX, and WIG indices are net transmitters of volatilities, whereas the BUX index is net recipient, except during the COVID-19 crisis, when it transmitted net volatility to the other three indices. Finally, using a Markov switching-regime VAR approach with two regimes, we explored the contagion effect between emerging CEE and developed stock markets during the COVID-19 pandemic. The empirical results proved a shift around the outbreak of the health crisis, after which the high volatility regime dominates the CEE markets. The contagion effects from developed stock markets to emerging CEE markets significantly increased during the first stage of the health crisis. © 2023 by the authors.

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.

The policy response to COVID-19 pandemic and its impact on the equity market sentiment: The Indian experience.

We examine the dynamics of the impact of the evolving policy response during the COVID-19 pandemic on the equity market sentiment in India. We operationalise our study by examining the India VIX, the fear gauge of the Indian equity market as an indicator for the market sentiment, and the country level Government Response Index of the Blavatnik School of Government, Oxford University as an indicator for the policy response. The relation is examined through the Markov-switching model using high-frequency daily data from January 30, 2020, to May 31, 2021. The evidence suggests that the policy response has a positive impact on the market sentiment when the market is fearful. Further, the evidence suggests that both the high-fear state and the low-fear state of the market sentiment given by the model are short-lived indicating heightened volatility and possible speculation during the ongoing pandemic in the Indian equity market.

Do emerging art market segments have their own price dynamics? Evidence from the Chinese art market

This study examines the nonlinear dynamics in the price series of Chinese art market segments between 2000 and 2019. We employ a hedonic price model to construct price indices of Chinese art market segments and analyze the nonlinearities and regime-switching properties of the individual segment using a series of Markov switching model specifications. We argue that occasional shocks would only temporarily alter their data-generating processes and have transitory effects. Moreover, we investigate the impact of COVID-19 on Chinese art market segments. Our findings have implications for market participants in identifying the price characteristics and dynamic behavior of art market segments. © 2022 The Author

Are commodity futures a hedge against inflation? A Markov-switching approach

This study examines the inflation hedging ability of various commodity futures using Markov-switching vector error correction models (MS-VECM). We find that total commodity futures fail to provide a hedge against inflation over the sample period between January 1983 and December 2021. However, industrial metals and precious metals are able to hedge against inflation. Other sub-indexes, including energy, agriculture, and livestock, do not have a significant inflation hedging ability. The inflation hedging capacity of industrial metals exhibits substantial variation over time, with most of the inflation hedging power occurring during the relatively longer and more common regimes covering the Great Moderation, the post-subprime crisis, and the periods after the outbreak of the COVID-19 pandemic. We further evaluate the inflation hedge ability of commodity futures by including stocks and bonds in the model. Our results suggest that industrial metals are more reliable inflation hedges. © 2023 Elsevier Inc.

The impact of the Russian-Ukrainian war on global financial markets

On February 24, 2022, Russia invaded the Ukraine. In this paper, we analyze the response of European and global stock markets alongside a representative sample of commodities. We compare the war response against the recent Covid-19 pandemic and the not-too-distant 2008 global financial crisis. Applying a Markov-switching HAR model on volatility proxies, estimates are made of synchronization, duration and intensity measures for each event. In broad terms, stock markets and commodities respond most rapidly to the Russian invasion;and post-invasion crisis intensity is noticeably smaller compared to both the Covid-19 and the GFC. Wheat and nickel are the most affected commodities due to the prominent exporter status of the two countries.

Recessions and flattening of the yield curve (1960–2021): A two-way road under a regime switching approach

The one-way relationship that goes from the term spread to recessions has been widely studied. However, the relationship between term spread and the business cycle, in addition to being bidirectional, is conditioned by the cyclical phase itself. To demonstrate this, we have modelled the bidirectional relationship between term spread and the business cycle by extracting two interrelated latent Markov variables: the first, drawn from four activity indicators, replicates the phases of the US business cycle;the second, from the term spread of the yield curve, identifies two regimes: an ordinary regime (positive slope) and a flattening regime. By analyzing both the transition between these regimes and forecasted probabilities, we find that this bidirectional relationship is not symmetrical. That is, the term spread signals a change in the business cycle regime while the cyclical factor only signals the beginning of the ordinary regime of the term spread, not its ending. To illustrate the model, we confirm the beginning of the COVID-19 recession in March of 2020, and the corresponding start of the ordinary regime in the term spread. © 2022 The Author

INDONESIA'S FINANCIAL STRESS EVENTS AND MACROECONOMIC DYNAMICS

In this study, we use a Markov-Switching Bayesian Vector AutoRegression model to investigate the episodic relationship between financial stress and the key macroeconomic variables in the case of Indonesia. We find different nature of relationships among Indonesia's real sector variables (household consumption expenditure and consumer price index), financial sector variables (interbank money market rate) and the policy variable (broad money supply during the times of high and low financial stress). Regime changes occurred on several occasions, including during the 2008 global financial crisis period and at the beginning of the COVID-19 pandemic. © 2022 Authors. All rights reserved.

Impact of Inflation in Different States of Unemployment: Evidence with the Phillips Curve in South Africa from 2008 to 2022

This paper investigates the impact of inflation in different states of unemployment: evidence with the Phillips curve in South Africa. The contribution of this paper is to examine the impact of inflation on different states of unemployment in South Africa. The Paper employs Markov-switching dynamic regression and data from 2008 to 2022. It was found that there are 2 states of unemployment mean rates of 25.55% and 33.59%, expected to run for 67 and 7 quarters, respectively. There is a 98.51% and 86.99% chance of a move and then returning to the same state, respectively. In states 1 and 2, a 1% increase in inflation results in a 2.61% increase and a 0.06% decrease in unemployment, respectively. There are times when the Phillips curve rationale is not holding. The government needs to increase the channels of employment opportunities. There is a need to re-look at the trade-offs between inflation and unemployment in the economy.

Stock Market Liquidity during Periods of Distress and its Implications: Evidence from International Financial Markets

Traditional market pricing models assume frictionless markets with abundant liquidity. This traditional models also incorporate stock market liquidity as an exogenous cost. However, this paradigm has many shortcomings due to its inability to explain some of the problems associated with security market illiquidity. The aim of this study was to explore the concept of stock market liquidity during periods of financial distress. A Markov switching GARCH model was used to investigate market liquidity in the CAC 40, DAX, JSE, Nasdaq Index and the Nikkei-225 during the 2007-2008 financial crisis and the Covid-19 pandemic. The sample period was January 1, 2020 to December 31, 2021 and December 1, 2007 to June 30, 2009. From the findings, some financial markets where still liquid despite the financial crisis with the exception of the Nasdaq index. Conversely, all the financial markets under consideration displayed strong illiquidity during the covid-19 pandemic. In essence, the level of market depth has significantly decreased from the financial crisis to the covid-19 pandemic which may be attributed to increasing margin requirements and information asymmetry as well as price restrictions. There is an urgent need for regulatory authorities to review some of the trading regulations during financial distress.

Stock Market Performance of the US Hospitality And Tourism During the Covid-19 Pandemic

In this study, the stock market performance of the travel and leisure industry during the COVID-19 pandemic is investigated by use of the three-regime Markov switching model. The analysis employs daily data for six subsectors (airlines, gambling, hotels, leisure services, restaurants and bars, as well as travel and tourism) for the US from January 2018 to November 2021. Estimation results provide strong evidence of regime switching behavior with wide differences across subsectors during the course of the COVID-19 pandemic. A longer duration of high volatility characterizes the airline and leisure services indices. These sectors exhibit the most pronounced downturn that was not fully recovered in November 2021. In contrast, the period of high volatility in the restaurant, gaming, and hotel industries is relatively short, and stock market performance recovers almost to the general trend. Of all subsectors, restaurants and bars experience the shortest duration of high volatility, limited to the second quarter of 2020. The stock market indices for the travel and tourism industry (mainly car rentals) are also highly volatile, but this pattern was observed already before the pandemic.

Regime switching and the responsiveness of prices to supply: The case of the Irish housing market

Understanding the impact of housing supply on housing price inflation is a particularly important issue from a policy-maker's perspective. Notwithstanding the impact of the great financial crisis (GFC) in 2007/08, the past 25 years has seen a significant increase in housing prices across a number of western economies. More recently, across countries, a common characteristic observed in housing markets appears to be the increase in price inflation in the aftermath of the Covid-19 pandemic. A key question which arises is whether housing price inflation can be assuaged somewhat by greater levels of housing supply? In this paper, we seek to quantify the impact of additional supply on price inflation in the Irish property market. While residential property markets in many countries experienced substantial swings in activity since the early 1990s, the Irish market has demonstrated particular volatility. Given such a high degree of volatility, it is plausible that the relationship between housing prices and its fundamental drivers could have changed over time. Crucially, therefore, we address this question using both a multiple breakpoint model and a Markov switching model to allow for the presence of structural changes in the Irish residential market over the period 1981–2019. Our results indicate a complex relationship between additional supply and house prices, with the impact varying over time. © 2022 Board of Trustees of the University of Illinois

Are commodity futures a hedge against inflation? A Markov-switching approach

This study examines the inflation hedging ability of various commodity futures using Markov-switching vector error correction models (MS-VECM). We find that total commodity futures fail to provide a hedge against inflation over the sample period between January 1983 and December 2021. However, industrial metals and precious metals are able to hedge against inflation. Other sub-indexes, including energy, agriculture, and livestock, do not have a significant inflation hedging ability. The inflation hedging capacity of industrial metals exhibits substantial variation over time, with most of the inflation hedging power occurring during the relatively longer and more common regimes covering the Great Moderation, the post-subprime crisis, and the periods after the outbreak of the COVID-19 pandemic. We further evaluate the inflation hedge ability of commodity futures by including stocks and bonds in the model. Our results suggest that industrial metals are more reliable inflation hedges.

Recessions and flattening of the yield curve (1960-2021): a two-way road under a regime switching approach

The one-way relationship that goes from the term spread to recessions has been widely studied. However, the relationship between term spread and the business cycle, in addition to being bidirectional, is conditioned by the cyclical phase itself. To demonstrate this, we have modelled the bidirectional relationship between term spread and the business cycle by extracting two interrelated latent Markov variables: the first, drawn from four activity indicators, replicates the phases of the US business cycle;the second, from the term spread of the yield curve, identifies two regimes: an ordinary regime (positive slope) and a flattening regime. By analyzing both the transition between these regimes and forecasted probabilities, we find that this bidirectional relationship is not symmetrical. That is, the term spread signals a change in the business cycle regime while the cyclical factor only signals the beginning of the ordinary regime of the term spread, not its ending. To illustrate the model, we confirm the beginning of the COVID-19 recession in March of 2020, and the corresponding start of the ordinary regime in the term spread.

Quantifying China's financial reach up through the pandemic: The African experience

This study seeks to quantify the financial connections between China and Africa. China's increasing investments in Africa have inevitably strengthened the relationship between China and the majority of African countries over the past decade. We find consistent effects of the Shanghai Industrial Index on African stock markets together with some evidence that these relationships strengthened following the onset of the coronavirus pandemic. Markov-Switching analysis affirms these connections while also identifying intensifying effects as we move from periods of low market volatility to periods of high volatility. The African stock markets included in the sample encompass Egypt, Kenya, Morocco, Nigeria, South Africa, Tanzania, Uganda, and Zambia. © 2022 Elsevier Inc.

Do emerging art market segments have their own price dynamics? Evidence from the Chinese art market

This study examines the nonlinear dynamics in the price series of Chinese art market segments between 2000 and 2019. We employ a hedonic price model to construct price indices of Chinese art market segments and analyze the nonlinearities and regime-switching properties of the individual segment using a series of Markov switching model specifications. We argue that occasional shocks would only temporarily alter their data-generating processes and have transitory effects. Moreover, we investigate the impact of COVID-19 on Chinese art market segments. Our findings have implications for market participants in identifying the price characteristics and dynamic behavior of art market segments.