Economics, Econometrics and Finance › Economics and Econometrics

Market Dynamics and Volatility

Works Count: 86871

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This cluster of papers focuses on the impact of oil price shocks on the global economy, including the stock market, volatility spillovers, commodity markets, and the macroeconomic effects of economic policy uncertainty. It explores the role of financialization, speculation, and monetary policy in shaping the response to oil price fluctuations.

Keywords

Oil Price Shocks; Economic Policy Uncertainty; Stock Market; Volatility Spillovers; Commodity Markets; Macroeconomic Effects; Financialization; Speculation; Global Economy; Monetary Policy

Statistical methods in cancer research. Vol. 1. The analysis of case-control studies

1983-02-01

N. E. Breslow , N. E. Day

Collapsing exchange-rate regimes

1984-08-01

Robert P. Flood , Peter M. Garber

THE IMPACT OF OIL PRICE SHOCKS ON THE U.S. STOCK MARKET*

2009-10-26

Lutz Kilian , Cheolbeom Park

It is shown that the reaction of U.S. real stock returns to an oil price shock differs greatly depending on whether the change in the price of oil is driven … It is shown that the reaction of U.S. real stock returns to an oil price shock differs greatly depending on whether the change in the price of oil is driven by demand or supply shocks in the oil market. The demand and supply shocks driving the global crude oil market jointly account for 22% of the long‐run variation in U.S. real stock returns. The responses of industry‐specific U.S. stock returns to demand and supply shocks in the crude oil market are consistent with accounts of the transmission of oil price shocks that emphasize the reduction in domestic final demand.

A Conditionally Heteroskedastic Time Series Model for Speculative Prices and Rates of Return

1987-08-01

Tim Bollerslev

Economic Forces and the Stock Market

1986-01-01

Nai‐Fu Chen , Richard Roll , Stephen A. Ross

This paper tests whether innovations in macroeconomic variables are risks that are rewarded in the stock market. Financial theory suggests that the following macroeconomic variables should systematically affect stock market … This paper tests whether innovations in macroeconomic variables are risks that are rewarded in the stock market. Financial theory suggests that the following macroeconomic variables should systematically affect stock market returns: the spread between long and short interest rates, expected and unexpected inflation, industrial production, and the spread between high- and low-grade bonds. We find that these sources of risk are significantly priced. Furthermore, neither the market portfolio nor aggregate consumption are priced separately. We also find that oil price risk is not separately rewarded in the stock market.

State-Space Models with Regime-Switching: Classical and Gibbs Sampling Approaches with Applications

2000-12-01

Sylvia Frühwirth‐Schnatter , Chang‐Jin Kim , Charles R. Nelson

Both state-space models and Markov switching models have been highly productive paths for empirical research in macroeconomics and finance. This book presents recent advances in econometric methods that make feasible … Both state-space models and Markov switching models have been highly productive paths for empirical research in macroeconomics and finance. This book presents recent advances in econometric methods that make feasible the estimation of models that have both features. One approach, in the classical framework, approximates the likelihood function; the other, in the Bayesian framework, uses Gibbs-sampling to simulate posterior distributions from data. The authors present numerous applications of these approaches in detail: decomposition of time series into trend and cycle, a new index of coincident economic indicators, approaches to modeling monetary policy uncertainty, Friedman's plucking model of recessions, the detection of turning points in the business cycle and the question of whether booms and recessions are duration-dependent, state-space models with heteroskedastic disturbances, fads and crashes in financial markets, long-run real exchange rates, and mean reversion in asset returns.

This is what happened to the oil price-macroeconomy relationship

1996-10-01

James D. Hamilton

Better to give than to receive: Predictive directional measurement of volatility spillovers

2011-05-26

Francis X. Diebold , Kamil Yılmaz

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Systematic Monetary Policy and the Effects of Oil Price Shocks

1997-01-01

Ben Bernanke , Mark Gertler , Mark W. Watson +2 more

OBJECTIVE of this paper is to increase our understanding of the role of monetary policy in postwar U. S. business cycles.We take as our starting point two common findings in … OBJECTIVE of this paper is to increase our understanding of the role of monetary policy in postwar U. S. business cycles.We take as our starting point two common findings in the recent monetary policy literature based on vector autoregressions (VARs).'First, identified shocks to monetary policy explain relatively little of the overall variation in output (typically, less than 20 percent).Second, most of the observed movement in the instruments of monetary policy, such as the federal funds rate or nonborrowed reserves, is endogenous; that is, changes in Federal Reserve policy are largely explained by macroeconomic conditions, as one might expect, given the Fed's commitment to macroeconomic stabilization.These two findings obviously do not support the view that erratic and unpredictable fluctuations in Federal Reserve policies are a primary cause of postwar U.S. business cycles; but neither do they rule out the possibility that systematic and predictable monetary policies-the Fed's policy rule-affect the course of the economy in an important way.Put more positively, if one takes the VAR evidence on monetary policy seriously (as we do), then any case for an important role of monetary policy in the business cycle rests on Thanks to Benjamin Friedman, Christopher Sims, and the Brookings Panel for helpful comments.

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Oil and the Macroeconomy since World War II

1983-04-01

James D. Hamilton

All but one of the U.S. recessions since World War II have been preceded, typically with a lag of around three-fourths of a year, by a dramatic increase in the … All but one of the U.S. recessions since World War II have been preceded, typically with a lag of around three-fourths of a year, by a dramatic increase in the price of crude petroleum. This does not mean that oil shocks caused these recessions. Evidence is presented, however, that even over the period 1948-72 this correlation is statistically significant and nonspurious, supporting the proposition that oil shocks were a contributing factor in at least some of the U.S. recessions prior to 1972. By extension, energy price increases may account for much of post-OPEC macroeconomic performance.

Further Evidence on the Great Crash, the Oil-Price Shock, and the Unit-Root Hypothesis

2002-01-01

Eric Zivot , Donald W. K. Andrews

Recently, Perron has carried out tests of the unit-root hypothesis against the alternative hypothesis of trend stationarity with a break in the trend occurring at the Great Crash of 1929 … Recently, Perron has carried out tests of the unit-root hypothesis against the alternative hypothesis of trend stationarity with a break in the trend occurring at the Great Crash of 1929 or at the 1973 oil-price shock. His analysis covers the Nelson–Plosser macroeconomic data series as well as a postwar quarterly real gross national product (GNP) series. His tests reject the unit-root null hypothesis for most of the series. This article takes issue with the assumption used by Perron that the Great Crash and the oil-price shock can be treated as exogenous events. A variation of Perron's test is considered in which the breakpoint is estimated rather than fixed. We argue that this test is more appropriate than Perron's because it circumvents the problem of data-mining. The asymptotic distribution of the estimated breakpoint test statistic is determined. The data series considered by Perron are reanalyzed using the test static. The empirical results make use of the asymptotics developed for the test statistic as well as extensive finite-sample corrections obtained by simulation. The effect on the empirical results of fat-tailed and temporally dependant innovations is investigated. In brief, by treating the breakpoint as endogenous, we find that there is less evidence against the unit-root hypothesis than Perron finds for many of the data series but stronger evidence against if for several of the series, including the Nelson–Plosser industrial-production, nominal-GNP, and real-GNP series.

Oil price shocks and stock market activity

1999-10-01

Perry Sadorsky

Oil and the Macroeconomy When Prices Go Up and Down: An Extension of Hamilton's Results

1989-06-01

Knut Anton Mork

Time-Varying Distributions and Dynamic Hedging with Foreign Currency Futures

1993-12-01

Kenneth F. Kroner , Jahangir Sultan

Most research on hedging has disregarded both the long-run cointegrating relationship between financial assets and the dynamic nature of the distributions of the assets. This study argues that neglecting these … Most research on hedging has disregarded both the long-run cointegrating relationship between financial assets and the dynamic nature of the distributions of the assets. This study argues that neglecting these affects the hedging performance of the existing models and proposes an alternative model that accounts for both of them. Using a bivariate error correction model with a GARCH error structure, the risk-minimizing futures hedge ratios for several currencies are estimated. Both within-sample comparisons and out-of-sample comparisons reveal that the proposed model provides greater risk reduction than the conventional models. Furthermore, a dynamic hedging strategy is proposed in which the potential risk reduction is more than enough to offset the transactions costs for most investors.

Some properties of time series data and their use in econometric model specification

1981-05-01

Clive W. J. Granger

THE ROLE OF INVENTORIES AND SPECULATIVE TRADING IN THE GLOBAL MARKET FOR CRUDE OIL

2013-04-10

Lutz Kilian , Daniel Murphy

SUMMARY We develop a structural model of the global market for crude oil that for the first time explicitly allows for shocks to the speculative demand for oil as well … SUMMARY We develop a structural model of the global market for crude oil that for the first time explicitly allows for shocks to the speculative demand for oil as well as shocks to flow demand and flow supply. The speculative component of the real price of oil is identified with the help of data on oil inventories. Our estimates rule out explanations of the 2003–2008 oil price surge based on unexpectedly diminishing oil supplies and based on speculative trading. Instead, this surge was caused by unexpected increases in world oil consumption driven by the global business cycle. There is evidence, however, that speculative demand shifts played an important role during earlier oil price shock episodes including 1979, 1986 and 1990. Our analysis implies that additional regulation of oil markets would not have prevented the 2003–2008 oil price surge. We also show that, even after accounting for the role of inventories in smoothing oil consumption, our estimate of the short‐run price elasticity of oil demand is much higher than traditional estimates from dynamic models that do not account for for the endogeneity of the price of oil. Copyright © 2013 John Wiley & Sons, Ltd.

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The Great Crash, the Oil Price Shock, and the Unit Root Hypothesis

1989-11-01

Pierre Perrón

We consider the null hypothesis that a time series has a unit root with possibly nonzero drift against the alternative that the process is «trend-stationary». The interest is that we … We consider the null hypothesis that a time series has a unit root with possibly nonzero drift against the alternative that the process is «trend-stationary». The interest is that we allow under both the null and alternative hypotheses for the presence for a one-time change in the level or in the slope of the trend function. We show how standard tests of the unit root hypothesis against trend stationary alternatives cannot reject the unit root hypothesis if the true data generating mechanism is that of stationary fluctuations around a trend function which contains a one-time break

Oil and the Stock Markets

1996-06-01

Charles M. Jones , Gautam Kaul

ABSTRACT We test whether the reaction of international stock markets to oil shocks can be justified by current and future changes in real cash flows and/or changes in expected returns. … ABSTRACT We test whether the reaction of international stock markets to oil shocks can be justified by current and future changes in real cash flows and/or changes in expected returns. We find that in the postwar period, the reaction of United States and Canadian stock prices to oil shocks can be completely accounted for by the impact of these shocks on real cash flows alone. In contrast, in both the United Kingdom and Japan, innovations in oil prices appear to cause larger changes in stock prices than can be justified by subsequent changes in real cash flows or by changing expected returns.

The Impact of Uncertainty Shocks

2009-01-01

Nicholas Bloom

Uncertainty appears to jump up after major shocks like the Cuban Missile crisis, the assassination of JFK, the OPEC I oil-price shock and the 9/11 terrorist attack. This paper offers … Uncertainty appears to jump up after major shocks like the Cuban Missile crisis, the assassination of JFK, the OPEC I oil-price shock and the 9/11 terrorist attack. This paper offers a structural framework to analyze the impact of these uncertainty shocks. I build a model with a time varying second moment, which is numerically solved and estimated using firm level data. The parameterized model is then used to simulate a macro uncertainty shock, which produces a rapid drop and rebound in aggregate output and employment. This occurs because higher uncertainty causes firms to temporarily pause their investment and hiring. Productivity growth also falls because this pause in activity freezes reallocation across units. In the medium term the increased volatility from the shock induces an overshoot in output, employment and productivity. Thus, second moment shocks generate short sharp recessions and recoveries. This simulated impact of an uncertainty shock is compared to VAR estimations on actual data, showing a good match in both magnitude and timing. The paper also jointly estimates labor and capital convex and non-convex adjustment costs. Ignoring capital adjustment costs is shown to lead to substantial bias while ignoring labor adjustment costs does not.

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Bitcoin, gold and the dollar – A GARCH volatility analysis

2015-11-11

Anne Haubo Dyhrberg

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Transmission of Volatility between Stock Markets

1990-01-01

Mervyn King , Sushil Wadhwani

Journal Article Transmission of Volatility between Stock Markets Get access Mervyn A. King, Mervyn A. King London School of Economics, Houghton Street, London, WC2A 2AE, UK Search for other works … Journal Article Transmission of Volatility between Stock Markets Get access Mervyn A. King, Mervyn A. King London School of Economics, Houghton Street, London, WC2A 2AE, UK Search for other works by this author on: Oxford Academic Google Scholar Sushil Wadhwani Sushil Wadhwani London School of Economics, Houghton Street, London, WC2A 2AE, UK Search for other works by this author on: Oxford Academic Google Scholar The Review of Financial Studies, Volume 3, Issue 1, January 1990, Pages 5–33, https://doi.org/10.1093/rfs/3.1.5 Published: 30 April 2015

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Oil price shocks and stock markets in the U.S. and 13 European countries

2008-04-19

Jung-Wook Park , Ronald A. Ratti

ON THE EFFICIENCY OF COMPETITIVE STOCK MARKETS WHERE TRADES HAVE DIVERSE INFORMATION

1976-05-01

Sanford J. Grossman

On the hedge and safe haven properties of Bitcoin: Is it really more than a diversifier?

2016-09-30

Elie Bouri , Péter Molnár , Georges Azzi +2 more

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COVID-Induced Economic Uncertainty

2020-04-01

Scott Baker , Nicholas Bloom , Steven J. Davis +1 more

Assessing the economic impact of the COVID-19 pandemic is essential for policymakers, but challenging because the crisis has unfolded with extreme speed.We identify three indicators -stock market volatility, newspaper-based economic … Assessing the economic impact of the COVID-19 pandemic is essential for policymakers, but challenging because the crisis has unfolded with extreme speed.We identify three indicators -stock market volatility, newspaper-based economic uncertainty, and subjective uncertainty in business expectation surveys -that provide real-time forward-looking uncertainty measures.We use these indicators to document and quantify the enormous increase in economic uncertainty in the past several weeks.We also illustrate how these forward-looking measures can be used to assess the macroeconomic impact of the COVID-19 crisis.Specifically, we feed COVID-induced first-moment and uncertainty shocks into an estimated model of disaster effects developed by Baker, Bloom and Terry (2020).Our illustrative exercise implies a year-on-year contraction in U.S. real GDP of nearly 11 percent as of 2020 Q4, with a 90 percent confidence interval extending to a nearly 20 percent contraction.The exercise says that about half of the forecasted output contraction reflects a negative effect of COVID-induced uncertainty.

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On the network topology of variance decompositions: Measuring the connectedness of financial firms

2014-04-24

Francis X. Diebold , Kamil Yılmaz

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Motivation Crowding Theory

2001-12-01

Bruno S. Frey , Reto Jegen

The Motivation Crowding Effect suggests that external intervention via monetary incentives or punishments may undermine, and under different identifiable conditions strengthen, intrinsic motivation. As of today, the theoretical possibility of … The Motivation Crowding Effect suggests that external intervention via monetary incentives or punishments may undermine, and under different identifiable conditions strengthen, intrinsic motivation. As of today, the theoretical possibility of motivation crowding has been the main subject of discussion among economists. This study demonstrates that the effect is also of empirical relevance . There exist a large number of studies, offering empirical evidence in support of the existence of crowding–out and crowding–in. The study is based on circumstantial evidence, laboratory studies by both psychologists and economists, as well as field research by econometric studies. The pieces of evidence presented refer to a wide variety of areas of the economy and society and have been collected for many different countries and periods of time. Crowding effects thus are an empirically relevant phenomenon, which can, in specific cases, even dominate the traditional relative price effect.

COVID-19 pandemic, oil prices, stock market, geopolitical risk and policy uncertainty nexus in the US economy: Fresh evidence from the wavelet-based approach

2020-05-15

Arshian Sharif , Chaker Aloui , Larisa Yarovaya

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Have Individual Stocks Become More Volatile? An Empirical Exploration of Idiosyncratic Risk

2001-02-01

John Y. Campbell , Martin Lettau , Burton G. Malkiel +1 more

ABSTRACT This paper uses a disaggregated approach to study the volatility of common stocks at the market, industry, and firm levels. Over the period from 1962 to 1997 there has … ABSTRACT This paper uses a disaggregated approach to study the volatility of common stocks at the market, industry, and firm levels. Over the period from 1962 to 1997 there has been a noticeable increase in firm‐level volatility relative to market volatility. Accordingly, correlations among individual stocks and the explanatory power of the market model for a typical stock have declined, whereas the number of stocks needed to achieve a given level of diversification has increased. All the volatility measures move together countercyclically and help to predict GDP growth. Market volatility tends to lead the other volatility series. Factors that may be responsible for these findings are suggested.

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Not All Oil Price Shocks Are Alike: Disentangling Demand and Supply Shocks in the Crude Oil Market

2009-05-01

Lutz Kilian

Shocks to the real price of oil may reflect oil supply shocks, shocks to the global demand for all industrial commodities, or demand shocks that are specific to the crude … Shocks to the real price of oil may reflect oil supply shocks, shocks to the global demand for all industrial commodities, or demand shocks that are specific to the crude oil market. Each shock has different effects on the real price of oil and on US macroeconomic aggregates. Changes in the composition of shocks help explain why regressions of macroeconomic aggregates on oil prices tend to be unstable. Evidence that the recent surge in oil prices was driven primarily by global demand shocks helps explain why this shock so far has failed to cause a major recession in the United States. (JEL E31, E32, Q41, Q43)

The Asset-Pricing Implications of Government Economic Policy Uncertainty

2015-01-01

Jonathan Brogaard , Andrew L. Detzel

Using the news-based measure of Baker et al. [Baker SR, Bloom N, Davis SJ (2013) Measuring economic policy uncertainty. Working paper, Stanford University, Stanford, CA] to capture economic policy uncertainty … Using the news-based measure of Baker et al. [Baker SR, Bloom N, Davis SJ (2013) Measuring economic policy uncertainty. Working paper, Stanford University, Stanford, CA] to capture economic policy uncertainty (EPU) in the United States, we find that EPU positively forecasts log excess market returns. An increase of one standard deviation in EPU is associated with a 1.5% increase in forecasted three-month abnormal returns (6.1% annualized). Furthermore, innovations in EPU earn a significant negative risk premium in the Fama–French 25 size–momentum portfolios. Among the Fama–French 25 portfolios formed on size and momentum returns, the portfolio with the greatest EPU beta underperforms the portfolio with the lowest EPU beta by 5.53% per annum, controlling for exposure to the Carhart four factors as well as implied and realized volatility. These findings suggest that EPU is an economically important risk factor for equities. This paper was accepted by Wei Jiang, finance.

Measuring the Frequency Dynamics of Financial Connectedness and Systemic Risk*

2018-01-01

Jozef Baruník , Tomáš Křehlík

We propose a new framework for measuring connectedness among financial variables that arise due to heterogeneous frequency responses to shocks. To estimate connectedness in short-, medium-, and long-term financial cycles, … We propose a new framework for measuring connectedness among financial variables that arise due to heterogeneous frequency responses to shocks. To estimate connectedness in short-, medium-, and long-term financial cycles, we introduce a framework based on the spectral representation of variance decompositions. In an empirical application, we document the rich time-frequency dynamics of volatility connectedness in U.S. financial institutions. Economically, periods in which connectedness is created at high frequencies are periods when stock markets seem to process information rapidly and calmly, and a shock to one asset in the system will have an impact mainly in the short term. When the connectedness is created at lower frequencies, it suggests that shocks are persistent and are being transmitted for longer periods.

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Is gold a safe haven? International evidence

2010-01-05

Dirk G. Baur , Thomas K. J. McDermott

Policy Uncertainty and Corporate Investment

2015-09-03

Huseyin Gulen , Mihai Ion

Using a news-based index of policy uncertainty, we document a strong negative relationship between firm-level capital investment and the aggregate level of uncertainty associated with future policy and regulatory outcomes. … Using a news-based index of policy uncertainty, we document a strong negative relationship between firm-level capital investment and the aggregate level of uncertainty associated with future policy and regulatory outcomes. More importantly, we find evidence that the relation between policy uncertainty and capital investment is not uniform in the cross-section, being significantly stronger for firms with a higher degree of investment irreversibility and for firms that are more dependent on government spending. Our results lend empirical support to the notion that policy uncertainty can depress corporate investment by inducing precautionary delays due to investment irreversibility. Received January 2, 2014; accepted July 27, 2015 by Editor David Denis.

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Measuring Financial Asset Return and Volatility Spillovers, with Application to Global Equity Markets

2008-12-09

Francis X. Diebold , Kamil Yılmaz

We provide a simple and intuitive measure of interdependence of asset returns and/or volatilities. In particular, we formulate and examine precise and separate measures of return spillovers and volatility spillovers. … We provide a simple and intuitive measure of interdependence of asset returns and/or volatilities. In particular, we formulate and examine precise and separate measures of return spillovers and volatility spillovers. Our framework facilitates study of both non‐crisis and crisis episodes, including trends and bursts in spillovers; both turn out to be empirically important. In particular, in an analysis of 19 global equity markets from the early 1990s to the present, we find striking evidence of divergent behaviour in the dynamics of return spillovers vs. volatility spillovers: return spillovers display a gently increasing trend but no bursts, whereas volatility spillovers display no trend but clear bursts.

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Fluctuations in Uncertainty

2014-05-01

Nicholas Bloom

Uncertainty is an amorphous concept. It reflects uncertainty in the minds of consumers, managers, and policymakers about possible futures. It is also a broad concept, including uncertainty over the path … Uncertainty is an amorphous concept. It reflects uncertainty in the minds of consumers, managers, and policymakers about possible futures. It is also a broad concept, including uncertainty over the path of macro phenomena like GDP growth, micro phenomena like the growth rate of firms, and noneconomic events like war and climate change. In this essay, I address four questions about uncertainty. First, what are some facts and patterns about economic uncertainty? Both macro and micro uncertainty appear to rise sharply in recessions and fall in booms. Uncertainty also varies heavily across countries—developing countries appear to have about one-third more macro uncertainty than developed countries. Second, why does uncertainty vary during business cycles? Third, do fluctuations in uncertainty affect behavior? Fourth, has higher uncertainty worsened the Great Recession and slowed the recovery? Much of this discussion is based on research on uncertainty from the last five years, reflecting the recent growth of the literature.

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Deutsche Mark–Dollar Volatility: Intraday Activity Patterns, Macroeconomic Announcements, and Longer Run Dependencies

1998-02-01

Torben G. Andersen , Tim Bollerslev

This paper provides a detailed characterization of the volatility in the deutsche mark–dollar foreign exchange market using an annual sample of five‐minute returns. The approach captures the intraday activity patterns, … This paper provides a detailed characterization of the volatility in the deutsche mark–dollar foreign exchange market using an annual sample of five‐minute returns. The approach captures the intraday activity patterns, the macroeconomic announcements, and the volatility persistence (ARCH) known from daily returns. The different features are separately quantified and shown to account for a substantial fraction of return variability, both at the intraday and daily level. The implications of the results for the interpretation of the fundamental “driving forces” behind the volatility process is also discussed.

Is Gold a Hedge or a Safe Haven? An Analysis of Stocks, Bonds and Gold

2010-04-16

Dirk G. Baur , Brian M. Lucey

Abstract Is gold a hedge, defined as a security that is uncorrelated with stocks or bonds on average, or is it a safe haven, defined as a security that is … Abstract Is gold a hedge, defined as a security that is uncorrelated with stocks or bonds on average, or is it a safe haven, defined as a security that is uncorrelated with stocks and bonds in a market crash? We study constant and time‐varying relations between U.S., U.K. and German stock and bond returns and gold returns to investigate gold as a hedge and a safe haven. We find that gold is a hedge against stocks on average and a safe haven in extreme stock market conditions. A portfolio analysis further shows that the safe haven property is short‐lived.

The Impact of Uncertainty Shocks

2007-09-01

Nicholas Bloom

Uncertainty appears to jump up after major shocks like the Cuban Missile crisis, the assassination of JFK, the OPEC I oil-price shock and the 9/11 terrorist attack.This paper offers a … Uncertainty appears to jump up after major shocks like the Cuban Missile crisis, the assassination of JFK, the OPEC I oil-price shock and the 9/11 terrorist attack.This paper offers a structural framework to analyze the impact of these uncertainty shocks.I build a model with a time varying second moment, which is numerically solved and estimated using firm level data.The parameterized model is then used to simulate a macro uncertainty shock, which produces a rapid drop and rebound in aggregate output and employment.This occurs because higher uncertainty causes firms to temporarily pause their investment and hiring.Productivity growth also falls because this pause in activity freezes reallocation across units.In the medium term the increased volatility from the shock induces an overshoot in output, employment and productivity.Thus, second moment shocks generate short sharp recessions and recoveries.This simulated impact of an uncertainty shock is compared to VAR estimations on actual data, showing a good match in both magnitude and timing.The paper also jointly estimates labor and capital convex and non-convex adjustment costs.Ignoring capital adjustment costs is shown to lead to substantial bias while ignoring labor adjustment costs does not.

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The Economic Effects of Energy Price Shocks

2008-11-01

Lutz Kilian

Large fluctuations in energy prices have been a distinguishing characteristic of the U.S. economy since the 1970s. Turmoil in the Middle East, rising energy prices in the United States, and … Large fluctuations in energy prices have been a distinguishing characteristic of the U.S. economy since the 1970s. Turmoil in the Middle East, rising energy prices in the United States, and evidence of global warming recently have reignited interest in the link between energy prices and economic performance. This paper addresses a number of the key issues in this debate: What are energy price shocks and where do they come from? How responsive is energy demand to changes in energy prices? How do consumer's expenditure patterns evolve in response to energy price shocks? How do energy price shocks affect U.S. real output, inflation, and stock prices? Why do energy price increases seem to cause recessions but energy price decreases do not seem to cause expansions? Why has there been a surge in the price of oil in recent years? Why has this new energy price shock not caused a recession so far? Have the effects of energy price shocks waned since the 1980s and, if so, why? As the paper demonstrates, it is critical to account for the endogeneity of energy prices and to differentiate between the effects of demand and supply shocks in energy markets when answering these questions.

Further Evidence on the Great Crash, the Oil-Price Shock, and the Unit-Root Hypothesis

1992-07-01

Eric Zivot , Donald W. K. Andrews

Recently, Perron has carried out tests of the unit-root hypothesis against the alternative hypothesis of trend stationarity with a break in the trend occurring at the Great Crash of 1929 … Recently, Perron has carried out tests of the unit-root hypothesis against the alternative hypothesis of trend stationarity with a break in the trend occurring at the Great Crash of 1929 or at the 1973 oil-price shock. His analysis covers the Nelson–Plosser macroeconomic data series as well as a postwar quarterly real gross national product (GNP) series. His tests reject the unit-root null hypothesis for most of the series. This article takes issue with the assumption used by Perron that the Great Crash and the oil-price shock can be treated as exogenous events. A variation of Perron's test is considered in which the breakpoint is estimated rather than fixed. We argue that this test is more appropriate than Perron's because it circumvents the problem of data-mining. The asymptotic distribution of the estimated breakpoint test statistic is determined. The data series considered by Perron are reanalyzed using this test statistic. The empirical results make use of the asymptotics developed for the test statistic as well as extensive finite-sample corrections obtained by simulation. The effect on the empirical results of fat-tailed and temporally dependent innovations is investigated, in brief, by treating the breakpoint as endogenous, we find that there is less evidence against the unit-root hypothesis than Perron finds for many of the data series but stronger evidence against it for several of the series, including the Nelson-Plosser industrial-production, nominal-GNP, and real-GNP series.

Facts and Fantasies about Commodity Futures

2006-03-01

Gary B. Gorton , K. Geert Rouwenhorst

For this study of the simple properties of commodity futures as an asset class, an equally weighted index of monthly returns of commodity futures was constructed for the July 1959 … For this study of the simple properties of commodity futures as an asset class, an equally weighted index of monthly returns of commodity futures was constructed for the July 1959 through December 2004 period. Fully collateralized commodity futures historically have offered the same return and Sharpe ratio as U.S. equities. Although the risk premium on commodity futures is essentially the same as that on equities for the study period, commodity futures returns are negatively correlated with equity returns and bond returns. The negative correlation is the result, primarily, of commodity futures' different behavior over a business cycle. Commodity futures are positively correlated with inflation, unexpected inflation, and changes in expected inflation.

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Long memory and regime switching

2001-11-01

Francis X. Diebold , Atsushi Inoue

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Political Uncertainty and Corporate Investment Cycles

2012-01-17

Brandon Julio , Youngsuk Yook

ABSTRACT We document cycles in corporate investment corresponding with the timing of national elections around the world. During election years, firms reduce investment expenditures by an average of 4.8% relative … ABSTRACT We document cycles in corporate investment corresponding with the timing of national elections around the world. During election years, firms reduce investment expenditures by an average of 4.8% relative to nonelection years, controlling for growth opportunities and economic conditions. The magnitude of the investment cycles varies with different country and election characteristics. We investigate several potential explanations and find evidence supporting the hypothesis that political uncertainty leads firms to reduce investment expenditures until the electoral uncertainty is resolved. These findings suggest that political uncertainty is an important channel through which the political process affects real economic outcomes.

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What is an oil shock?

2003-03-04

James D. Hamilton

Measuring Economic Policy Uncertainty*

2016-07-11

Scott Baker , Nicholas Bloom , Steven J. Davis

Abstract We develop a new index of economic policy uncertainty (EPU) based on newspaper coverage frequency. Several types of evidence—including human readings of 12,000 newspaper articles—indicate that our index proxies … Abstract We develop a new index of economic policy uncertainty (EPU) based on newspaper coverage frequency. Several types of evidence—including human readings of 12,000 newspaper articles—indicate that our index proxies for movements in policy-related economic uncertainty. Our U.S. index spikes near tight presidential elections, Gulf Wars I and II, the 9/11 attacks, the failure of Lehman Brothers, the 2011 debt ceiling dispute, and other major battles over fiscal policy. Using firm-level data, we find that policy uncertainty is associated with greater stock price volatility and reduced investment and employment in policy-sensitive sectors like defense, health care, finance, and infrastructure construction. At the macro level, innovations in policy uncertainty foreshadow declines in investment, output, and employment in the United States and, in a panel vector autoregressive setting, for 12 major economies. Extending our U.S. index back to 1900, EPU rose dramatically in the 1930s (from late 1931) and has drifted upward since the 1960s.

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Correlations in Price Changes and Volatility across International Stock Markets

1990-04-01

Yasushi Hamao , Ronald W. Masulis , Victor Ng

The short-run interdependence of prices and price volatility across three major international stock markets is studied. Daily opening and closing prices of major stock indexes for the Tokyo, London, and … The short-run interdependence of prices and price volatility across three major international stock markets is studied. Daily opening and closing prices of major stock indexes for the Tokyo, London, and New York stock markets are examined. The analysis utilizes the autoregressive conditionally heteroskedastic (ARCH) family of statistical models to explore these pricing relationships. Evidence of price volatility spillovers from New York to Tokyo, London to Tokyo, and New York to London is observed, but no price volatility spillover effects in other directions are found for the pre-October 1987 period.

Measuring Geopolitical Risk

2022-03-31

Dario Caldara , Matteo Iacoviello

We present a news-based measure of adverse geopolitical events and associated risks. The geopolitical risk (GPR) index spikes around the two world wars, at the beginning of the Korean War, … We present a news-based measure of adverse geopolitical events and associated risks. The geopolitical risk (GPR) index spikes around the two world wars, at the beginning of the Korean War, during the Cuban Missile Crisis, and after 9/11. Higher geopolitical risk foreshadows lower investment and employment and is associated with higher disaster probability and larger downside risks. The adverse consequences of the GPR index are driven by both the threat and the realization of adverse geopolitical events. We complement our aggregate measures with industry- and firm-level indicators of geopolitical risk. Investment drops more in industries that are exposed to aggregate geopolitical risk. Higher firm-level geopolitical risk is associated with lower firm-level investment. (JEL C43, E32, F51, F52, G31, H56, N40)

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Further Evidence on the Great Crash, the Oil-Price Shock, and the Unit-Root Hypothesis

1992-07-01

Eric Zivot , Donald W. K. Andrews

Investment under Uncertainty

1994-12-31

Robert K. Dixit , Robert S. Pindyck

Shockwaves of Political Leadership: The Impact of Trump’s Second Presidency on Global Oil Prices

2025-06-25

Mesbah Fathy Sharaf , Abdelhalem Mahmoud Shahen , Elhussien Ibrahim Mansour +1 more | International Journal of Energy Economics and Policy

This study explores how Donald Trump’s 2024 re-election affected Brent crude oil prices using an Interrupted Time Series (ITS) model. Given the importance of U.S. political shifts on global markets, … This study explores how Donald Trump’s 2024 re-election affected Brent crude oil prices using an Interrupted Time Series (ITS) model. Given the importance of U.S. political shifts on global markets, the study tests for a structural break in oil prices following the election. Using daily data from January 2022 to March 2025, it controls for key macro-financial factors: the Economic Policy Uncertainty (EPU) Index, Dow Jones Industrial Average (DJIA), and the 10-year U.S. Treasury Yield. Findings show a significant 5.25% drop in Brent oil prices immediately after Trump’s re-election, indicating initial market uncertainty. However, the trend reversed in the days after, suggesting that investor sentiment adjusted over time. A placebo test found no such effect before the election, strengthening causal claims. Additionally, a Distributed Lag ITS model revealed the decline unfolded gradually. These results echo past research linking political uncertainty to oil price volatility, highlighting the short-term sensitivity of oil markets to leadership shocks. Still, the later price recovery points to longer-term resilience. This research adds to the literature on political impacts on commodity markets, offering useful insights for investors, energy economists, and policymakers navigating politically driven market risks.

Carbon Intensity, Volatility Spillovers, and Market Connectedness in Hong Kong Stocks

2025-06-25

Eddie Lam , Yiuman Tse , Joseph K. W. Fung | Journal of risk and financial management

This paper examines the firm-level carbon intensity of 83 constituent stocks in the Hang Seng Index, constructs two distinct indexes from the 20 firms with the highest and lowest carbon … This paper examines the firm-level carbon intensity of 83 constituent stocks in the Hang Seng Index, constructs two distinct indexes from the 20 firms with the highest and lowest carbon intensities, and analyzes the connectedness of their annualized daily volatilities with four key external factors over the past 15 years. Our findings reveal that low-carbon stocks—often represented by high-tech and financial firms—tend to exhibit higher volatility, reflecting their more dynamic business environments and greater sensitivity to changes in revenue and profitability. In contrast, high-carbon companies, such as those in the utilities and energy sectors, display more stable demand patterns and are generally less exposed to abrupt market shocks. We also find that oil price shocks result in greater volatility spillovers for low-carbon stocks. Among external influences, the U.S. stock market and Treasury yield exert the most significant spillover effects, while crude oil prices and the U.S. dollar–Chinese yuan exchange rate act as net volatility recipients.

Artificial Intelligence-Driven Business Intelligence for Strategic Energy and ESG Management: A Systematic Review of Economic and Policy Implications

2025-06-25

Amineh A. Khaddam , Amro Alzghoul | International Journal of Energy Economics and Policy

This literature review examines how artificial intelligence (AI)-powered business intelligence (BI) platforms are being leveraged to advance energy management and sustainability (ESG) goals in corporations. A systematic search of recent … This literature review examines how artificial intelligence (AI)-powered business intelligence (BI) platforms are being leveraged to advance energy management and sustainability (ESG) goals in corporations. A systematic search of recent studies from Scopus, IEEE, Web of Science, and other databases yielded ~65 relevant peer-reviewed sources. We synthesized findings into five thematic areas: (1) AI applications in ESG reporting and automation, (2) BI systems for energy data visualization and monitoring, (3) predictive analytics for carbon and utility forecasting, (4) real-time dashboards for corporate sustainability decision-making, and (5) risks, biases, and ethical considerations of ESG technology. The review finds that AI-driven BI tools are streamlining sustainability reporting and assurance, enabling real-time energy monitoring and analytics, and improving forecasting of carbon footprints and energy consumption. These technologies have helped organizations identify efficiency opportunities and inform strategic sustainability decisions, with reported energy savings and emissions reductions in various cases. However, challenges persist, including data integration issues, algorithmic biases, and the need for ethical frameworks to govern AI in ESG. We identify critical research gaps such as (under-studied sectors and the social and governance dimensions of ESG tech) and propose directions for future investigation.

Oil Price Volatility and its Effects on Macroeconomic Stability in Jordan: A Structural VAR Approach

2025-06-25

Khaled Mohammed Al-Sawaie , Suleiman Ibrahim Shelash Mohammad , Khaleel Ibrahim Al-Daoud +5 more | International Journal of Energy Economics and Policy

This study examines the dynamic effects of global oil price fluctuations on key macroeconomic indicators in Jordan, including inflation, real GDP growth, fiscal deficit, and exchange rate stability, over the … This study examines the dynamic effects of global oil price fluctuations on key macroeconomic indicators in Jordan, including inflation, real GDP growth, fiscal deficit, and exchange rate stability, over the period 2000-2023. As an energy-importing economy, Jordan remains vulnerable to external oil price shocks, which influence domestic price levels, fiscal performance, and growth dynamics. Using quarterly data and a Structural Vector Auto Regression (SVAR) framework, the analysis identifies and quantifies the transmission of oil price shocks through impulse response functions and forecast error variance decomposition (FEVD). The Augmented Dickey-Fuller (ADF) test was applied to ensure stationarity, and optimal lag length was selected based on Akaike and Schwarz criteria. Results reveal that oil price shocks significantly increase inflation and widen the fiscal deficit, with inflation reacting immediately and fiscal imbalances persisting over several quarters. GDP growth shows a delayed negative response, while exchange rate effects are minor due to the fixed peg regime. FEVD results indicate that oil shocks explain up to 18% of inflation variance and around 9% of fiscal deficit variance. The findings suggest that oil price shocks are a key driver of macroeconomic volatility in Jordan. The study highlights the need for fiscal reform, energy diversification, and improved macroeconomic forecasting tools to mitigate the adverse effects of external energy shocks.

Energy-Related Uncertainty and Tourism Stock Markets: New Insights from Time-Varying Relationship with TVP- VAR Approach

2025-06-25

Zоkir Mamadiyarоv , Otabek Saidov , Nargiza Abdurazakova +5 more | International Journal of Energy Economics and Policy

In this study, a time-varying parameter vector autoregressive (TVP-VAR) model is estimated to examine the effects of energy-related uncertainty, geopolitical risk and global economic activity on tourism stock prices in … In this study, a time-varying parameter vector autoregressive (TVP-VAR) model is estimated to examine the effects of energy-related uncertainty, geopolitical risk and global economic activity on tourism stock prices in the United States (US) over the period February 1996-September 2022. The time-varying responses reveal that tourism stocks are negatively affected by energy-related uncertainty, particularly during financial crisis and COVID-19. Moreover, geopolitical risk shocks also negatively influence tourism stocks. Global economic activity exhibits both positive and negative shocks in tourism stocks. The results highlight the importance of considering sector-specific dynamics of energy-related uncertainty on tourism stocks in US.

Asymmetric Relationship between Oil Prices, Agricultural Production, and Industrial Production in Kazakhstan: Application of the NARDL Method

2025-06-25

Karlygash Baisholanova , Aida Mazhidovna Dauzova , Halim Kazan +5 more | International Journal of Energy Economics and Policy

Two important factors contributing to oil revenues in Kazakhstan are the agricultural and industrial production sectors. This study examines the asymmetric effects of variability in these sectors on oil revenues. … Two important factors contributing to oil revenues in Kazakhstan are the agricultural and industrial production sectors. This study examines the asymmetric effects of variability in these sectors on oil revenues. The analysis was conducted using the Nonlinear Autoregressive Distributed Lags (NARDL) model. In this model, oil revenues are represented as a ratio of oil revenues to GDP, while industrial and agricultural productions are represented by the industrial production index and the agricultural production index, respectively. The asymmetric effect refers to the differing impacts that positive or negative shocks in industrial or agricultural production have on oil revenues. Using annual data from 1992 to 2023, the study found that industrial production had statistically significant effects on oil revenues in the short term; however, this effect did not persist in the long term. In contrast, agricultural production demonstrated significant effects on oil revenues in both the short and long term, with notable seasonal differences in the impacts of short-term positive and negative shocks. Additionally, the error correction model indicated that both production sectors had asymmetric effects that led to deviations from expected oil revenues. In conclusion, the findings of this research highlight the significant role that production sectors play in explaining fluctuations in oil revenues.

Global Crude Oil Prices: A Blessing, a Curse, or a Crisis-Driven Force? A New Analysis for Turkey

2025-06-25

Ferhat Oztutus | International Journal of Energy Economics and Policy

This paper examines the relationship between global crude oil price volatility (COP) and industrial production (IP) in Turkey, using monthly data from 1986:02 to 2023:12 and applying the time-varying Granger … This paper examines the relationship between global crude oil price volatility (COP) and industrial production (IP) in Turkey, using monthly data from 1986:02 to 2023:12 and applying the time-varying Granger causality (TV-GC) analysis. The empirical results indicate that the causal relationship is highly dynamic, changing over time rather than remaining constant. Specifically, while the FE window results primarily detects causality at the beginning and end of the sample period, the RO and RE windows outcomes suggest a more sustained cause-and-effect relationship. The findings also highlight the importance of diversifying energy sources and adopting economic strategies to mitigate the impact of oil price volatility on industrial production. Turkish policymakers should focus on enhancing energy efficiency, promoting renewable energy investments, and strengthening industrial resilience to external shocks. A deeper understanding of these dynamics can help design new strategies to stabilize industrial output and support sustainable economic growth in Turkey.

Modeling the Dynamic Relationship between Inflation, Oil Price, and Macroeconomic Variables: Evidence from Saudi Arabia

2025-06-25

Mohamed Sharif Bashir , Ahlam Abdelhadi Hassan Elamin | International Journal of Energy Economics and Policy

This paper investigates the dynamic relationship between inflation, economic growth, oil price, money supply, and current account in Saudi Arabia for the period 1980–2023. It employs the autoregressive distributed lag … This paper investigates the dynamic relationship between inflation, economic growth, oil price, money supply, and current account in Saudi Arabia for the period 1980–2023. It employs the autoregressive distributed lag (ARDL) approach and error correction model (ECM) to examine the short-run and long-run dynamics. The bounds test of cointegration analysis confirms the existence of a long-term relationship between targeted variables. The ARDL model estimates suggested that gross domestic product (GDP), oil price, and money supply are negatively related to inflation. They also indicated that current accounts have a positive effect on price levels, GDP, and money supply, and a negative effect on oil prices and inflation levels. Therefore, enhancing regulatory quality and mobilizing more domestic resources can reduce inflation and accelerate economic growth.

Economic uncertainty and renewable energy investment

2025-06-24

Linus Nyiwul , Zhining Hu , Niraj P. Koirala +1 more | International Economics and Economic Policy

Does U.S. Financial Instability Matter on Clean, Green, and Sustainable Investment Indices? Evidence from TVP-VAR and Wavelet Coherence Approaches

2025-06-24

Hayet Soltani , Mouna Boujelbène Abbes | Asia-Pacific Financial Markets

Sustainable Factor Augmented Machine Learning Models for Crude Oil Return Forecasting

2025-06-24

Lianxu Wang , Xu Chen | Journal of risk and financial management

The global crude oil market, known for its pronounced volatility and nonlinear dynamics, plays a pivotal role in shaping economic stability and informing investment strategies. Contrary to traditional research focused … The global crude oil market, known for its pronounced volatility and nonlinear dynamics, plays a pivotal role in shaping economic stability and informing investment strategies. Contrary to traditional research focused on price forecasting, this study emphasizes the more investor-centric task of predicting returns for West Texas Intermediate (WTI) crude oil. By spotlighting returns, it directly addresses critical investor concerns such as asset allocation and risk management. This study applies advanced machine learning models, including XGBoost, random forest, and neural networks to predict crude oil return, and for the first time, incorporates sustainability and external risk variables, which are shown to enhance predictive performance in capturing the non-stationarity and complexity of financial time-series data. To enhance predictive accuracy, we integrate 55 variables across five dimensions: macroeconomic indicators, financial and futures markets, energy markets, momentum factors, and sustainability and external risk. Among these, the rate of change stands out as the most influential predictor. Notably, XGBoost demonstrates a superior performance, surpassing competing models with an impressive 76% accuracy in direction forecasting. The analysis highlights how the significance of various predictors shifted during the COVID-19 pandemic. This underscores the dynamic and adaptive character of crude oil markets under substantial external disruptions. In addition, by incorporating sustainability factors, the study provides deeper insights into the drivers of market behavior, supporting more informed portfolio adjustments, risk management strategies, and policy development aimed at fostering resilience and advancing sustainable energy transitions.

Forecasting Crude Oil Prices with a Structural Machine Learning Model

2025-06-24

Minho Lee , Chang Sik Kim | International Economic Journal

Analysis of global stock market development—Integration of clustering, classification, and shapley values

2025-06-24

Marcin Stawarz | PLoS ONE

This study aims to analyze the development of global stock exchanges by integrating clustering, classification, and Shapley Values to identify growth patterns and understand the differences in market characteristics and … This study aims to analyze the development of global stock exchanges by integrating clustering, classification, and Shapley Values to identify growth patterns and understand the differences in market characteristics and dynamics. The research applies the K-means algorithm for clustering, which enables the segmentation of exchanges based on their similarities. This is followed by using the random forest algorithm to classify these clusters and evaluate the importance of various features. Shapley Values are employed to interpret the contribution of individual variables to the model’s predictions, considering all possible combinations of features. The empirical analysis is based on data from 82 stock exchanges worldwide, sourced from organizations such as the World Federation of Exchanges and the International Monetary Fund. Key variables used include market capitalization, trading value, the number of listed companies, and share turnover velocity. The results highlight the significant heterogeneity among exchanges, with major markets like those in China and the United States forming distinct clusters due to their size, capitalization, and high trading activity. This distinction underscores their dominant position in the global financial landscape. Moreover, exchanges that have emerged from mergers, such as Euronext and NASDAQ Nordic, demonstrate superior characteristics compared to their peers, indicating that consolidation can be an effective strategy for competing with larger markets and enhancing global competitiveness. The study’s findings show that integrating clustering, classification, and Shapley Values is a robust approach for uncovering complex structures within financial markets. This approach provides deeper insights for market participants and policymakers into the growth patterns and strategic positioning of stock exchanges, offering valuable implications for future market development and competition strategies.

Oil price and financial markets contagion in Pacific Alliance economies during the first two decadesof the 21st century

2025-06-24

Julio César Alonso Cifuentes , Julián Benavides Franco , Irwin Taype Huaman | Estudios Gerenciales

Esta investigación estudia si las fluctuaciones en los precios del crudo Brent se propagaron a los mercados cambiarios y de acciones de la Alianza del Pacífico (Chile, Colombia, México, Perú) … Esta investigación estudia si las fluctuaciones en los precios del crudo Brent se propagaron a los mercados cambiarios y de acciones de la Alianza del Pacífico (Chile, Colombia, México, Perú) entre 2000-2019. Este periodo incluye la formación del bloque y excluye el cambio estructural provocado por la pandemia de COVID-19. Se emplean modelos VAR estructurales por país para filtrar los rendimientos mensuales, y se aplican ocho pruebas de contagio: correlaciones de Pearson, Spearman y Kendall; correlación ajustada de Forbes-Rigobon; estadística de arranque gaussiana local; prueba de covolatilidad X²; y dos pruebas de co-sesgo de tercer orden. Los regímenes de calma y crisis se identifican mediante el algoritmo alcista/bajista de Lunde-Timmermann y el clasificador de volatilidad realizada de Mohaddes-Pesaran. Las pruebas se replican excluyendo la crisis financiera global de 2007-2009. Los resultados muestran una marcada asimetría: el contagio cambiario es fuerte y persistente en México y Chile, moderado en Colombia y esporádico en Perú. En contraste, el contagio bursátil es significativo solo en Colombia y Perú. Estos hallazgos indican que las respuestas políticas homogéneas dentro de la Alianza podrían no ser efectivas, y que los inversionistas deben cubrir riesgos cambiarios y bursátiles de forma diferenciada.

FLUCTUATIONS IN MACROECONOMIC NEWS AND THEIR IMPACT ON THE STOCK MARKET: EVIDENCE FROM THE TUNISIAN TURBULENT PERIODS

2025-06-24

Fathi Nakai , DONIA ROUIHEM | Global economy journal

This paper investigates the impact of a broad set of economic and non-economic news on stock prices during the most stressful period of Tunisia’s multidimensional crisis (2011–2015). Using a two-stage … This paper investigates the impact of a broad set of economic and non-economic news on stock prices during the most stressful period of Tunisia’s multidimensional crisis (2011–2015). Using a two-stage econometric framework — Vector Autoregression (VAR) to isolate unanticipated shocks and Autoregressive Distributed Lag (ARDL) to analyze their effects — the research finds that traditional macroeconomic variables (e.g. interest rates, inflation, industrial production) lack significant long-term influence on stock returns. However, short-term dynamics reveal that unexpected monetary policy changes, inflationary shocks, and negative political events significantly affect market returns, with investors reacting more strongly to adverse political news. Sovereign credit rating downgrades also show persistent negative effects. The findings highlight the dominance of short-term volatility and political instability over long-term fundamentals in Tunisia’s fragile financial market, underscoring the decoupling of equity returns from macroeconomic conditions during crises. For crisis-hit emerging markets, policymakers must prioritize political stability and transparent monetary communication over traditional macroeconomic fixes, as short-term shocks and sovereign downgrades disproportionately drive market volatility compared to long-term fundamentals.

Geopolitical turbulence and market dynamics: analyzing the impact of the Israeli–Hamas conflict on global market volatility

2025-06-24

Imen Khemakhem , Salma Gallas | China Finance Review International

Purpose This study investigates the evolving connections, risk transmission and volatility spillovers between commodities and global financial markets. It offers an in-depth analysis of shifting relationships, tail risk exposure and … Purpose This study investigates the evolving connections, risk transmission and volatility spillovers between commodities and global financial markets. It offers an in-depth analysis of shifting relationships, tail risk exposure and market dynamics over time. Design/methodology/approach To achieve these objectives, this study employs the time-varying parameters vector autoregression (TVP-VAR) framework, the conditional autoregressive value-at-risk (CAViaR-TVP-VAR) model and the time-varying parameter vector autoregressive Barunik–Krehlik (TVP-VAR-BK) model to analyze daily data from January 2, 2023 to August 5, 2024. Findings Our empirical findings show that the Israeli–Hamas conflict considerably increased risk spillovers, tail risk transmission and the overall interconnectedness between global commodities and financial markets. Energy and agricultural assets emerged as key sources of volatility, while major financial indices, including the US dollar, TA All-Share and MSCI World, played pivotal roles in spreading shocks across sectors. The frequency-domain analysis highlights that crude oil and wheat were dominant in the short term, gold and Bitcoin acted as effective hedging tools over the medium term and over longer horizons, commodity-linked risks remained prominent. Research limitations/implications This study has some limitations, such as its focus on the period from January 2023 to August 2024 and its narrow scope, which does not include markets like bonds and real estate. Additionally, the models used may not account for nonlinear dynamics or intraday fluctuations and the conflict is analyzed as a singular event. Practical implications These findings have several important insights for financial markets. By highlighting the sectors most vulnerable to shocks, our study emphasizes the importance of being proactive in addressing potential market disruptions. For investors, our results suggest that both commodities and financial markets can be effective channels for transmitting risks. Additionally, commodities offer diversification benefits during times of market distress, helping to absorb economic shocks and reduce potential losses. For portfolio managers, this study underscores the value of diversifying investments across different sectors, exhibiting strong risk transmission mechanisms. By strategically allocating risk, investors can balance exposure and reduce the impact of adverse market movements. Thus, the findings emphasize the need for assigning appropriate risk allocations to mitigate negative spillovers and maintain portfolio stability. Originality/value This study explores the influence of the Israeli–Palestinian conflict on various financial sectors, including commodities, financial markets, fixed-income markets, global stock indices and the cryptocurrency market. It examines two key periods: the timeframe before the conflict and the period during the conflict itself. This study examines the impact of conflict on the interconnectedness and risk transmission between commodities and global financial markets. It explores how these relationships evolve, focusing on time-varying dynamics in market connectivity. The research provides a detailed analysis of risk spillovers, highlighting how risk contagion characteristics shift during periods of war instability. This work contributes to the existing literature by offering a deeper understanding of how geopolitical events influence the interactions among different asset classes, enhancing the traditional analysis of risk transmission and market connectivity.

Are oil price shocks driving India’s sustainable sector? A closer look at crisis-induced dynamics

2025-06-23

Neenu Chalissery , T. Mohamed Nishad , P. Milinth | Sustainability Accounting Management and Policy Journal

Purpose In the quest for a sustainable future, comprehending the interaction between conventional energy sources such as crude oil and the expanding realm of sustainable investments is essential, especially in … Purpose In the quest for a sustainable future, comprehending the interaction between conventional energy sources such as crude oil and the expanding realm of sustainable investments is essential, especially in emerging economies like India, where energy dependence and climate commitments exist in a fragile equilibrium. In particular, this paper aims to explore return co-movement and asymmetric volatility spillover between oil price uncertainty and green stocks in India and analyze how the market crises shape this dynamic relation. Design/methodology/approach This study used the Oil Volatility Index and green stock indices, specifically BSE GREENEX, BSE CARBONEX and BSE ESG 100, within the Bombay Stock Exchange of India from 2019 to 2023, including COVID-19 and the Russia–Ukraine war, and uses two sophisticated methods: wavelet coherence and asymmetric time-varying parameter vector autoregression. Findings The findings indicate that green investments are not entirely shielded from oil price uncertainty. Instead, their response to oil uncertainty is contingent upon prevailing market sentiment, which tends to be heightened during global events such as the COVID-19 pandemic. Furthermore, the result confirms the existence of asymmetry in oil shock spillover. Practical implications The reliance compromises the stability and attractiveness of green investments, posing a constraint to the attainment of Sustainable Development Goals (SDGs), particularly concerning climate action and clean energy objectives. Enhancing energy diversity and safeguarding green financing from oil fluctuations are essential for sustainable financial resilience. Social implications This study presents a social risk by potentially restricting the involvement of socially responsible investors in green finance, hindering the transition to a low-carbon economy. Thus, ensuring the stability of green financial markets is essential for building public trust and facilitating broader societal changes toward the achievement of the SDGs. Originality/value This study uniquely contributes to the literature by analyzing the dynamic relationship between crude oil price uncertainty and green stocks in the Indian market, where the interaction between traditional energy reliance and sustainable financing remains underexplored.

Convergence Bias in Lean Hog Futures

2025-06-23

Kyoungin Choe , Barry K. Goodwin | Journal of Agricultural and Applied Economics

Abstract We examine the convergence of lean hog futures and cash prices, focusing on the thinning of negotiated cash markets. Using daily Livestock Mandatory Reporting data from 2001 to 2024, … Abstract We examine the convergence of lean hog futures and cash prices, focusing on the thinning of negotiated cash markets. Using daily Livestock Mandatory Reporting data from 2001 to 2024, we confirm significant non-convergence between negotiated and futures prices over the past two decades. Regression results show that as the share of negotiated transactions declines, the absolute basis increases, emphasizing the critical role of negotiated markets in ensuring convergence. These findings highlight concerns about the reliability of negotiated prices as a benchmark for contracts and offer valuable insights for price risk management in the hog industry.

Firms’ subjective political uncertainty: survey evidence of Egypt’s Arab Spring

2025-06-23

Ahmed Hamed | Applied Economics Letters

Futures Options Pricing in the Indian Commodity Market Using Univariate GARCH Models and Particle Swarm Optimization

2025-06-23

S. Sapna , Biju R. Mohan | SN Computer Science

Shaping Investment Decisions: The Role of Investor Sentiment and its Antecedents in Indian Capital Market Investment Decisions

2025-06-23

M. Savithri , D. Rajakumari | International Review of Management and Marketing

This study sought to determine how working individuals in India felt about risk tolerance, financial health, financial literacy, overconfidence bias, herding behaviour, and social interaction in relation to their desire … This study sought to determine how working individuals in India felt about risk tolerance, financial health, financial literacy, overconfidence bias, herding behaviour, and social interaction in relation to their desire to participate in and engagement in the stock market. Using a cross-sectional methodology, this study gathered quantitative data via an online survey distributed via a Google form link to 343 participants from a variety of social media sites. The hypothesis in this study were tested using the partial least squares structural equation modelling (PLS-SEM) method. The results of this study demonstrated the strong benefits of social connection, herding behaviour, and risk tolerance on the desire to engage in the stock market. Participation in the stock market was significantly impacted by stock market investing intention as well. It was also shown that the intention to engage in the stock market effectively mediates the associations between stock market involvement and risk tolerance and overconfidence bias. Regarding stock market investing, the government and relevant authorities have to concentrate on formulating laws and programs that offer investors a financial safety net and encourage investment-related social media platforms. Risk tolerance, financial well-being, financial literacy, overconfidence bias, herding behaviour, social interaction, desire to participate in the stock market, and stock market involvement were all associated in this study. This is one of the few early initiatives to address difficulties of working people' involvement in stock market investments in underdeveloped nations.

Multifractal Carbon Market Price Forecasting with Memory-Guided Adversarial Network

2025-06-23

Na Li , Mingzhu Tang , Jingwen Deng +2 more | Fractal and Fractional

Carbon market price prediction is critical for stabilizing markets and advancing low-carbon transitions, where capturing multifractal dynamics is essential. Traditional models often neglect the inherent long-term memory and nonlinear dependencies … Carbon market price prediction is critical for stabilizing markets and advancing low-carbon transitions, where capturing multifractal dynamics is essential. Traditional models often neglect the inherent long-term memory and nonlinear dependencies of carbon price series. To tackle the issues of nonlinear dynamics, non-stationary characteristics, and inadequate suppression of modal aliasing in existing models, this study proposes an integrated prediction framework based on the coupling of gradient-sensitive time-series adversarial training and dynamic residual correction. A novel gradient significance-driven local adversarial training strategy enhances immunity to volatility through time step-specific perturbations while preserving structural integrity. The GSLAN-BiLSTM architecture dynamically recalibrates historical–current information fusion via memory-guided attention gating, mitigating prediction lag during abrupt price shifts. A “decomposition–prediction–correction” residual compensation system further decomposes base model errors via wavelet packet decomposition (WPD), with ARIMA-driven dynamic weighting enabling bias correction. Empirical validation using China’s carbon market high-frequency data demonstrates superior performance across key metrics. This framework extends beyond advancing carbon price forecasting by successfully generalizing its “multiscale decomposition, adversarial robustness enhancement, and residual dynamic compensation” paradigm to complex financial time-series prediction.

The South African Fear and Greed Index and Its Connectedness to the U.S. Index

2025-06-23

Deevarshan Naidoo , Peter Moores‐Pitt , Paul‐Francois Muzindutsi | Journal of risk and financial management

This study investigates the cross-country spillover effects of investor sentiment, specifically Fear and Greed, between the United States and South Africa, within the broader context of increasing global financial integration … This study investigates the cross-country spillover effects of investor sentiment, specifically Fear and Greed, between the United States and South Africa, within the broader context of increasing global financial integration and behavioral finance. Using monthly data from June 2007 to June 2024, this research constructs and tests the validity of a South African Fear and Greed Index, adapted from CNN’s U.S.-centric index, to better capture the unique dynamics and contribute to an alternate sentiment index for an emerging market. Employing the Diebold and Yilmaz (DY) connectedness framework, this study quantifies both static and dynamic spillover effects via a vector autoregression-based variance decomposition model. The results reveal significant bidirectional sentiment transmission, with the U.S. acting as a dominant net transmitter and South Africa as a net receiver, along with notable cross-country effects closely linked to the global economic trend. Spillover intensity escalates during periods of global economic stress, such as the 2008 financial crisis and the COVID-19 pandemic. The findings highlight that the USA significantly influences South Africa and that the adapted SA Fear and Greed Index better accounts for South African market conditions.

A sentiment-driven three-stage approach for multi-scale carbon price prediction

2025-06-23

Yongliang Liu , Chunling Tang , Aiying Zhou +2 more | Discover Sustainability

A new elite safe haven asset: Rolex watches

2025-06-23

Dimitrios Dimitriou , Georgios Garafas , Dimitris Kenourgios +1 more | Applied Economics

Impact of the energy commodity global prices on the disaggregated inflation: the case of Poland

2025-06-23

Piotr Palac , Justyna Tomala | Polityka Energetyczna – Energy Policy Journal

Dynamic Persistence of Shocks to Stock Prices in Emerging Markets: Non‐Normal Distributions, Structural Changes and Asymmetry

2025-06-23

Şaban Nazlıoğlu , İlhan Küçükkaplan , Şevket PAZARCI +2 more | International Journal of Finance & Economics

ABSTRACT This study examines the persistence of shocks to stock prices in emerging markets, with accounting for non‐normal distributions, structural changes and asymmetry by means of the recent developments in … ABSTRACT This study examines the persistence of shocks to stock prices in emerging markets, with accounting for non‐normal distributions, structural changes and asymmetry by means of the recent developments in the quantile autoregression models. The results, from the data covering the January 1988–January 2025 period for the stock price index of 24 emerging markets, show the importance of simultaneously accounting for these data properties in analysing the effects of shocks to stock prices. We find that the shocks tend to be temporary, demonstrating a mean‐reversion in stock prices of emerging markets, which provides implications for trading strategies, portfolio investment and risk management.

STATISTICAL ASSESSMENT OF THE IMPACT OF GLOBAL OIL PRICE VOLATILITY ON SUSTAINABLE DEVELOPMENT

2025-06-23

Ramiz Javad Javadov | AUDIT

Analyzing Systemic Risk Spillover Networks Through a Time-Frequency Approach

2025-06-22

Zheng Li-ping , Ziwei Liang , Jennifer Wang Yi +1 more | Mathematics

This paper investigates the spillover effects and transmission networks of systemic risk within China’s national economic sectors under extreme conditions from both time and frequency domain perspectives, building upon the … This paper investigates the spillover effects and transmission networks of systemic risk within China’s national economic sectors under extreme conditions from both time and frequency domain perspectives, building upon the spillover index methodology and calculating the ∆CoVaR index for Chinese industries. The findings indicate the following: (1) Extreme-risk spillovers synchronize across industries but exhibit pronounced time-varying peaks during the 2008 Global Financial Crisis, the 2015 crash, and the COVID-19 pandemic. (2) Long-term spillovers dominate overall connectedness, highlighting the lasting impact of fundamentals and structural linkages. (3) In terms of risk volatility, Energy, Materials, Consumer Discretionary, and Financials are most sensitive to systemic market shocks. (4) On the risk spillover effect, Consumer Discretionary, Industrials, Healthcare, and Information Technology consistently act as net transmitters of extreme risk, while Energy, Materials, Consumer Staples, Financials, Telecom Services, Utilities, and Real Estate primarily serve as net receivers. Based on these findings, the paper suggests deepening the regulatory mechanisms for systemic risk, strengthening the synergistic effect of systemic risk measurement and early warning indicators, and coordinating risk monitoring, early warning, and risk prevention and mitigation. It further emphasizes the importance of avoiding fragmented regulation by establishing a joint risk prevention mechanism across sectors and departments, strengthening the supervision of inter-industry capital flows. Finally, it highlights the need to closely monitor the formation mechanisms and transmission paths of new financial risks under the influence of the pandemic to prevent the accumulation and eruption of risks in the post-pandemic era. Authorities must conduct annual “Industry Transmission Reviews” to map emerging risk nodes and supply-chain vulnerabilities, refine policy tools, and stabilize market expectations so as to forestall the build-up and sudden release of new systemic shocks.

Interest Rate Marketization and Asset Prices Transmission Channel: Dynamic Impacts on the Chinese Economy

2025-06-22

Meng Chen , Haslindar Ibrahim , Zhenrui Chen +1 more | Business and Economic Research

This empirical study uses the TVP-VAR model to analyze the dynamic impacts of asset price transmission channels (stock price and real estate price channels) on China’s macroeconomic indicators (GDP and … This empirical study uses the TVP-VAR model to analyze the dynamic impacts of asset price transmission channels (stock price and real estate price channels) on China’s macroeconomic indicators (GDP and CPI) at three stages of interest rate marketization: the deepening stage (1996–2003), the improvement stage (2004–2015), and the comprehensive promotion stage (2016–2024). It explores how M2 influences these asset price channels and their effects on GDP and CPI. The results show that M2 has a stable negative impact on the stock price channel, while its short-term impact on the real estate price channel is positive and becomes consistently positive in the medium and long term. The effects of both channels on GDP are complex and unstable across different time spans: the stock price channel exhibits high volatility in its impact on CPI, whereas the real estate price channel has a strong short-term positive impact that weakens in the long term. The study connects its findings to theoretical frameworks such as Tobin’s Q theory and Modigliani’s wealth effect, providing insights for monetary policy formulation, financial market regulation, and investor decision-making.

Risk-Sensitive Deep Reinforcement Learning for Portfolio Optimization

2025-06-22

Xinyao Wang , Lili Liu | Journal of risk and financial management

Navigating the complexity of petroleum futures markets—marked by extreme volatility, geopolitical uncertainty, and macroeconomic shocks—demands adaptive and risk-sensitive strategies. This paper explores an Adaptive Risk-sensitive Transformer-based Deep Reinforcement Learning (ART-DRL) … Navigating the complexity of petroleum futures markets—marked by extreme volatility, geopolitical uncertainty, and macroeconomic shocks—demands adaptive and risk-sensitive strategies. This paper explores an Adaptive Risk-sensitive Transformer-based Deep Reinforcement Learning (ART-DRL) framework to improve portfolio optimization in commodity futures trading. While deep reinforcement learning (DRL) has been applied in equities and forex, its use in commodities remains underexplored. We evaluate DRL models, including Deep Q-Networks (DQN), Proximal Policy Optimization (PPO), Advantage Actor-Critic (A2C), and Deep Deterministic Policy Gradient (DDPG), integrating dynamic reward functions and asset-specific optimization. Empirical results show improvements in risk-adjusted performance, with an annualized return of 1.353, a Sharpe Ratio of 4.340, and a Sortino Ratio of 57.766. Although the return is below DQN (1.476), the proposed model achieves better stability and risk control. Notably, the models demonstrate resilience by learning from historical periods of extreme volatility, including the COVID-19 pandemic (2020–2021) and geopolitical shocks such as the Russia–Ukraine conflict (2022), despite testing commencing in January 2023. This research offers a practical, data-driven framework for risk-sensitive decision-making in commodities, showing how machine learning can support portfolio management under volatile market conditions.

Hedging Climate Change News With Commodity Futures: An Index‐Tracking Approach

2025-06-22

Fang Tong , Libo Yin | Journal of Futures Markets

ABSTRACT We propose and implement a trading strategy based on the index‐tracking approach to build portfolios that hedge climate risk using commodity futures. We consider the climate change news index … ABSTRACT We propose and implement a trading strategy based on the index‐tracking approach to build portfolios that hedge climate risk using commodity futures. We consider the climate change news index of Engle et al. to derive the hedge target. The empirical results suggest that the index‐tracking approach performs well in constructing climate change hedge portfolios. The short‐selling constraint enhances the out‐of‐sample hedge performance due to the alleviation of overfitting. The hedge performance indicates that commodity futures could be effective tools for hedging climate risk. We further reveal the heterogeneous roles of commodity futures in hedging climate risk. Our work provides an effective strategy for constructing climate change hedge portfolios and highlights the important and potential role of commodity futures in the era of climate change.

Modelling emotional contagious effect between US and BRICS-5

2025-06-22

Rajat Kumar Soni | Journal of Economic Studies

Purpose This study aims to examine how the stock market of Brazil, Russia, India, China and South Africa (BRICS) is reacting against the fear and greed mood of US investors. … Purpose This study aims to examine how the stock market of Brazil, Russia, India, China and South Africa (BRICS) is reacting against the fear and greed mood of US investors. For that purpose, the author used the CNN US Fear and Greed Index (F&G Index) as an independent variable to examine its impact on the stock prices of BRICS countries. Design/methodology/approach The author has applied a combination of methods supporting each other to decipher the unfolded interrelation between the US stock market and the BRICS stocks, especially related to the current time scenario. First, the DCC GARCH model is estimated to examine volatility transmission and conditional correlation between the same. Wavelet coherence plots were also used to intercept interaction between the F&G index and BRICS stocks. Quantile-and-quantile regression are also applied to examine the asymmetrical causal impact of the US F&G index on the stock prices of BRICS countries. Findings The US F&G Index acts as a global sentiment driver, with varying degrees of influence on the stock of BRICS countries. Brazil, South Africa and India have significant dynamic associations with the US F&G Index, whereas China and Russia exhibit weaker or negligible coherence. Fear in the US market has a more pronounced and significant impact on the BRICS stock markets compared to greed, and this asymmetry underscores the vulnerability of BRICS economies to negative US market sentiment. These findings highlight the asymmetric and heterogeneous impact of US market sentiment on BRICS economies, with implications for portfolio diversification, risk management and policy strategies in emerging markets. Originality/value The F&G index comprises seven different aspects of the stock market and may provide robust information on how the overall behaviours of US investors affect BRICS stocks. A comprehensive indicator like the CNN US Fear and Greed Index has not been explored previously in the given context, as per the best knowledge of the author. Therefore, the author gets the motivation to examine the impact of the US Fear and Greed Index on the stock prices of BRICS countries.

Price Forecasting of Crude Oil Using Hybrid Machine Learning Models

2025-06-21

Jyoti Choudhary , Haresh Kumar Sharma , Pradeep Malik +1 more | Journal of risk and financial management

Crude oil is a widely recognized, indispensable global and national economic resource. It is significantly susceptible to the boundless fluctuations attributed to various variables. Despite its capacity to sustain the … Crude oil is a widely recognized, indispensable global and national economic resource. It is significantly susceptible to the boundless fluctuations attributed to various variables. Despite its capacity to sustain the global economic framework, the embedded uncertainties correlated with the crude oil markets present formidable challenges that investors must diligently navigate. In this research, we propose a hybrid machine learning model based on random forest (RF), gated recurrent unit (GRU), conventional neural network (CNN), extreme gradient boosting (XGBoost), functional partial least squares (FPLS), and stacking. This hybrid model facilitates the decision-making process related to the import and export of crude oil in India. The precision and reliability of the different machine learning models utilized in this study were validated through rigorous evaluation using various error metrics, ensuring a thorough assessment of their forecasting capabilities. The conclusive results revealed that the proposed hybrid ensemble model consistently delivered effective and robust predictions compared to the individual models.

“Geopolitical crises and economic policy uncertainty: Time series analysis from the United States”

2025-06-21

İsa Çamyar , Bahar Ulupinar | Research in Economics

US-China tensions, US partisan conflict, and global oil prices: scapegoating?

2025-06-21

Yifei Cai , Jamel Saadaoui | Applied Economics Letters

Quantile-time-frequency risk spillover between investor attention, clean, and dirty cryptocurrency returns

2025-06-21

Fatma Ben Hamadou , Taicir Mezghani , Mouna Boujelbène Abbes | Risk Management

How Does the Stock Market React to the Carbon Policy? The Chinese Experience During 2014–2022

2025-06-21

Steven Bai , Cheol‐Won Yang | Asia & the Pacific Policy Studies

ABSTRACT As countries around the world move towards carbon neutrality, firms are facing new challenges of policy uncertainty. China is an interesting place to explore this, as it is the … ABSTRACT As countries around the world move towards carbon neutrality, firms are facing new challenges of policy uncertainty. China is an interesting place to explore this, as it is the largest carbon emitter and is taking strong steps towards carbon neutrality after the Paris Agreement. We investigate the impact of 28 Chinese carbon neutral policies on the stock return and systematic risk during 2014–2022. Event study methodology and modified CAPM (capital asset pricing model) with dummy variable for announcement date are employed. The results show that the electricity & heating, finance, and health sector experiences negative effects, while the mining industry has positive returns. Industries with mixed impacts initially experience negative impacts in the early stages, but turn positive later. Moreover, there is a noticeable trend of decreasing systematic risk in high‐energy‐consuming industries. This suggests that consistent policy enforcement can reduce the risks stemming from policy uncertainty, which in turn can benefit both firms and investors.

Does price discovery efficiency benefit from internationalization in China’s oil and oilseed futures market?——evidence from a quasi-natural experiment

2025-06-20

Xin Luan , Ronghua Ju | Asia-Pacific Journal of Accounting & Economics

Geopolitical Risk and the Risk Spillover on the US Technology Firms: A Quantile Perspective

2025-06-20

WANG Deyong , SUN Yizhong , WANG Yishuo +1 more | ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH

Machine learning heating oil price forecasts

2025-06-20

Bingzi Jin , Xiaojie Xu | New Mathematics and Natural Computation

Dynamic spillover and connectedness between Fintech and Islamic banking markets: evidence from country-level data with portfolio implications

2025-06-20

Mabruk Billah , Huson Joher Ali Ahmed , Muhammad Muazzem Hossain +1 more | International Journal of Islamic and Middle Eastern Finance and Management

Purpose This paper explores the interactive link between Islamic banking and Fintech indices, emphasizing their functions for portfolio x-diversification. This study aims to investigate the contagion and decoupling hypotheses and … Purpose This paper explores the interactive link between Islamic banking and Fintech indices, emphasizing their functions for portfolio x-diversification. This study aims to investigate the contagion and decoupling hypotheses and the extent to which specific Islamic banking indices act as a safe-haven. Applying the Time-Varying Parameter Vector Auto Regression (TVP-VAR) approach, the study aims to investigate return spillovers, directional connectivity and the overall influence of these indices in improving portfolio returns under varying economic mechanisms. Design/methodology/approach This paper uses Chatziantoniou et al. (2021) TVP-VAR model to examine the dynamic interconnectedness of Islamic Banking and Fintech indices. Findings The analysis shows a low correlation in terms of return transmission between Islamic banking indices and Fintech indices and positive net spillover from Fintech indices on Islamic banking. This indicates that while there is a weak coupling between Fintech and Islamic banking, there can be enhancements in returns on changes in Fintech. Also, the study uncovers that Islamic banking indices can act as a safe hedge during testing times and provide helpful information for improving portfolio efficiency and diversification plans. These results highlight the significance of future research in studying the links and the hedging and diversification benefits of these financial sectors Originality/value This research contributes to the existing literature by examining the untapped possibility of using Islamic banking and Fintech indices for portfolio diversification. This study uses the TVP-VAR model to examine their relationship and the use of the Islamic banking index as a portfolio hedge. The success reproductions show a limited return transmission from Islamic banking to the Fintech indices. However, a positive cross-backward effect exists in the opposite direction of the assumed relationship, giving helpful information for investors aiming at diversification free from the Marzipan effects.

Connectedness and hedging strategies between European sustainability and conventional stock markets

2025-06-20

Abdullah AlGhazali , Walid Mensi , Bruce Morley +1 more | Journal of Sustainable Finance & Investment

Central bank communication of uncertainty

2025-06-20

Pietro Fadda , Rayane Hanifi , Klodiana Istrefi +1 more | Journal of International Money and Finance

The Connectedness between Bitcoin, Stock Market, Gold, Oil, Bond and Exchange Rate: Evidence from Quantile VAR Approach and Portfolio Strategies

2025-06-20

Zekai ŞENOL , Bahri Fatih Tekin | Central European Business Review

Exploring Stock Returns Volatility of Select NSE – Listed Pharmaceutical Companies: An Empirical Study

2025-06-19

Siddhartha Saha | INTERNATIONAL JOURNAL OF INNOVATIONS & RESEARCH ANALYSIS

Volatility of a financial time series has become a fertile area for research during last decades. Global financial meltdowns have massive shock on different sectors as well as on scripts … Volatility of a financial time series has become a fertile area for research during last decades. Global financial meltdowns have massive shock on different sectors as well as on scripts returns. The current study empirically explores the volatility pattern of NSE listed pharmaceutical companies considering daily closing adjusted stock price from 2001-02 to 2015-16. The objective of the paper is to study the volatility design of daily stock returns. The application of GARCH, and T-GARCH models provides the evidence of the persistence of time varying asymmetric volatility. Main findings suggest that time varying volatility behaviour of Indian stock market may be due to recent global financial meltdown, which is originated from US sub-prime crisis. Likewise, effect captured by different models show that negative shocks have significant effect on conditional volatility.

Economic policy uncertainty, investor sentiment and IPO underpricing

2025-06-19

Mengting Zhang , William W. Du | International Review of Financial Analysis

Can the Oil Price Stabilisation Fund Reduce the Volatility of Domestic Prices?

2025-06-19

The Anh Pham | Asia & the Pacific Policy Studies

ABSTRACT This paper has two primary objectives. First, it contributes to the literature on oil stabilisation funds and price controls by examining how such a fund is used to regulate … ABSTRACT This paper has two primary objectives. First, it contributes to the literature on oil stabilisation funds and price controls by examining how such a fund is used to regulate market prices in the developing country of Vietnam. Second, it employs descriptive statistics and a standard GARCH methodology to investigate whether the fund, which operates as a form of price control, can effectively reduce domestic price volatility. The results show that the oil price stabilisation fund failed to achieve its intended goal. Considering the administrative costs and other negative impacts associated with the fund, a more market‐oriented approach, potentially combined with a price‐elastic tax system, is recommended for determining domestic oil prices.

Spillover network of tourism stocks, metaverse, artificial intelligence, and traditional assets: Do oil-related and volatility shocks matter?

2025-06-19

Oktay Özkan , Ojonugwa Usman , Anthony Ladis Komba +1 more | Tourism Economics

The rapid proliferation of technology-based assets in the presence of global shocks can deepen the relationship between financial assets and tourism stocks. This study investigates the spillover network of tourism … The rapid proliferation of technology-based assets in the presence of global shocks can deepen the relationship between financial assets and tourism stocks. This study investigates the spillover network of tourism stocks, metaverse, artificial intelligence, and traditional assets under oil-related volatility shocks. To this end, a Bayesian time-varying parameter vector autoregressive (TVP-VAR) method is applied. The empirical results suggest that tourism stocks are a net shock receiver. These results remain unchanged under oil-related and volatility shocks, indicating that oil-related and volatility shocks primarily reflect broader market dynamics rather than driving systemic risks. Our findings, therefore, provide insights into risk management and hedging strategies for tourism stocks.

Economic policy uncertainty, coal price, and industrial output: Evidence from China

2025-06-19

Boqiang Lin , Zhijun Wang | Energy