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This paper aims to examine the quantile-based frequency connectedness between cryptocurrencies and platinum returns across different market conditions and investment horizons. In this paper, it is also aimed to evaluate the asymmetric and time-varying spillover effects between cryptocurrency markets and platinum returns within short-, medium-, and long-term horizons. The study discussed the Heterogeneous Market Hypothesis together with the concepts of cryptocurrencies and platinum as part of the theoretical and conceptual foundations underpinning the analysis. The study adopted the positivist research paradigm, quantitative research approach, and explanatory research design. We employed a hybrid analytical framework combining Quantile Regression (QR), Quantile-on-Quantile Regression (QQR), and Ensemble Empirical Mode Decomposition (EEMD) to capture the non-linear and frequency-dependent dynamics between the selected variables. A dataset comprising daily prices of Cardano (ADA), Binance Coin (BNB), Bitcoin (BTC), Ethereum (ETH), TRON (TRX), Tether (USDT), Dogecoin (DOGE), Ripple (XRP), and platinum returns sourced from CoinMarketCap and the Bloomberg L.P. Terminal was analysed. The main findings of the study demonstrate that (i) the connectedness between cryptocurrencies and platinum returns is generally weak and predominantly inverse in the short term, indicating minimal immediate spillover effects between the two asset classes, (ii) medium-term relationships become significantly stronger with positive dependencies dominating across most quantiles, suggesting increasing integration driven by speculative investment flows and evolving investor sentiment, and finally (iii) long-run connectedness is highly asymmetric and predominantly positive, particularly from cryptocurrencies to platinum returns, although occasional negative dependencies at lower quantiles indicate limited hedging and safe-haven properties during extreme market downturns.  

This paper aims to examine the quantile-based frequency connectedness between cryptocurrencies and palladium returns across different market conditions and investment horizons. In this paper, it is also aimed to evaluate the asymmetric and time-varying spillover dynamics between cryptocurrency markets and palladium returns in order to determine their diversification, hedging, and safe-haven characteristics. The study discussed the Heterogeneous Market Hypothesis together with the concepts of cryptocurrencies and palladium as part of the theoretical and conceptual foundation of the analysis. We employed a hybrid analytical framework combining Quantile Regression (QR), Quantile-on-Quantile Regression (QQR), and Ensemble Empirical Mode Decomposition (EEMD) to capture the non-linear and frequency-dependent relationships between the selected variables. Daily time-series data on palladium prices and major cryptocurrencies, namely Cardano (ADA), Binance Coin (BNB), Bitcoin (BTC), Ethereum (ETH), TRON (TRX), Tether (USDT), Dogecoin (DOGE), and Ripple (XRP), sourced from CoinMarketCap and Bloomberg Terminal, were analysed over the study period. Main findings of the study demonstrate that (i) the connectedness between cryptocurrencies and palladium returns is generally weak in the short term, indicating limited immediate spillover effects between the two markets, (ii) medium- and long-term horizons exhibit stronger and predominantly positive connectedness across most quantiles, particularly from cryptocurrencies to palladium returns, suggesting increasing financial integration over time, and finally (iii) the cryptocurrency–palladium return nexus is asymmetric and state-dependent, with palladium occasionally displaying limited hedging and safe-haven properties during periods of market distress. The study concludes that cryptocurrencies primarily function as diversification instruments rather than consistent hedging assets against palladium market risks. Based on the findings, investors and portfolio managers are encouraged to adopt medium- to long-term investment strategies when integrating cryptocurrencies and palladium within diversified portfolios, while closely monitoring persistent cryptocurrency market trends that may influence palladium price dynamics over time.

This paper examined the connectedness between Copper returns and major cryptocurrency returns, with particular attention to their predictive ability and their roles in diversification and risk transmission across varying market conditions and investment horizons. In this study, it is also aimed to evaluate how these relationships evolve across different quantiles and frequency domains, thereby capturing both distributional asymmetries and time-dependent dynamics. We employed a hybrid analytical approach combining Ensemble Empirical Mode Decomposition and Quantile-on-Quantile Regression to decompose the return series and estimate dependence structures across multiple quantiles and time scales. A dataset comprising daily observations of copper and selected cryptocurrencies, Cardano (ADA), Binance Coin (BNB), Bitcoin (BTC), Ethereum (ETH), TRON (TRX), Tether (USDT), Dogecoin (DOGE), and Ripple (XRP), covering the period from 17 September 2014 to 17 April 2026 was analysed. The main findings of the study demonstrate that (i) short-term connectedness between copper and cryptocurrencies is generally weak, indicating limited immediate transmission of shocks; (ii) medium- and long-term results reveal stronger and more structured dependence, with certain cryptocurrencies, particularly Bitcoin and Binance Coin, exhibiting notable predictive influence on copper returns alongside time-varying co-movements; and finally (iii) the relationship is highly state-dependent, with stronger and asymmetric spillovers emerging during extreme market conditions, suggesting that cryptocurrencies primarily serve as diversifiers rather than consistent hedges. These results highlight the dynamic nature of the cryptocurrency–copper nexus and provide important implications for portfolio diversification, risk management, and financial market monitoring in increasingly interconnected global markets.

This paper examined the connectedness between silver returns and major cryptocurrencies, with particular attention to their predictive ability and their roles as hedging, safe-haven, and diversification instruments across varying market conditions and investment horizons. In this paper, it is also aimed to evaluate how these relationships evolve across different quantiles and frequency domains, thereby capturing both distributional asymmetries and time-dependent dynamics. We employed a hybrid analytical approach combining Ensemble Empirical Mode Decomposition and Quantile-in-Quantile Regression to decompose the return series and estimate dependence structures across multiple quantiles and time scales. A dataset comprising daily observations of silver and selected cryptocurrencies, Cardano (ADA), Binance Coin (BNB), Bitcoin (BTC), Ethereum (ETH), TRON (TRX), Tether (USDT), Dogecoin (DOGE), and Ripple (XRP), covering the period from 17 September 2014 to 17 April 2026 was analysed. The main findings of the study demonstrate that (i) the short-term connectedness between silver and cryptocurrencies is generally weak and statistically insignificant, suggesting limited immediate transmission of shocks between the two markets; (ii) the medium- and long-term results reveal stronger and more structured dependence, with cryptocurrencies, particularly Bitcoin and Binance Coin, exhibiting notable predictive influence on silver returns, alongside evidence of time-varying co-movements; and finally (iii) the nature of the relationship is markedly state-dependent, as certain cryptocurrencies display hedging or diversification benefits under specific market conditions, while others exhibit mixed or asymmetric effects, especially during periods of extreme market stress. The findings indicate that the cryptocurrency–silver nexus is dynamic and evolves across both time horizons and market states, offering delicate implications for portfolio diversification, risk management, and financial market monitoring in an increasingly interconnected global environment.

The aim of this study is to examine the dynamic relationships among alternative investment instruments in Turkey using advanced time-series methods. The findings indicate evidence of granger causal relationships among some of the variables. However, the direction and statistical significance of these relationships vary across the variables examined. The analysis employs monthly data covering the period from February 2010 to December 2018. The stationarity properties of the variables were examined using the Augmented Dickey–Fuller (ADF) test. Causal relationships among the variables were subsequently investigated using the Toda–Yamamoto causality test. The findings indicate that there are statistically significant short-term and long-term relationships among alternative investment instruments. It was determined that the exchange rate and gold prices have on the stock market. Furthermore, its interest rates play in both financial markets and housing prices. This study contributes to the literature by examining the relationships between alternative investment instruments using linear methods. Moreover, the results offer researchers and policymakers important implications for financial stability for investors' portfolio diversification strategies at both the national and international levels.

Technology, innovation, and economic shocks have transformed global financial markets. The latest global health pandemic has been compared to the 2008 global financial crisis, as investors, lawmakers, and regulators worldwide worried about economic collapse. Johannesburg Stock Exchange is Africa's largest. The JSE names SIFIs, whose failure would threaten SA's economy. Uncertainty increases failure risk, as seen in the GFC and COVID-19. This study examined how economic shocks affected investor confidence in South Africa's growing financial market, the JSE 15 Index. Analysis of data from January 1999 to December 2023 examined short- and long-term stock market impacts, the role of the South African Reserve Bank (SARB) in stability, and investor conduct during crises. The two economic shocks' effects on JSE 15 index stock prices were examined using Autoregressive Distributed Lags (ARDL) and correlation analysis. ARDL determines short- and long-term macroeconomic cointegration. Three macroeconomic variables—interest rates (T-Bills), inflation (CPI), and real effective exchange rate (REER)—are used to track their fluctuation during crises. The analysis shows a shift in investor confidence reflected in a considerable decline in financial performance throughout the crisis. As investors' risk tolerance differs, diversification benefits made abnormal returns unimportant. SARB's monetary and fiscal policies mitigated the pandemic. South African investors were also wary due to internal issues. The study shows that global commodity prices and currency rate volatility affect investor confidence more than domestic policy in emerging economies, adding to behavioural finance.

This article investigates the nature of the relationship and the effects of changes in oil prices on South Africa's exchange rate. It fills an essential gap in comprehending how oil price shocks influence emerging market economic dynamics. Through the use of a Bayesian Vector Auto-Regressive (BVAR) model, this study finds that the initial oil price shock to exchange rates is weakly positive in the short run, reflecting a 1% increase in oil prices, leading to a 0.08% exchange rate appreciation. The study also finds an asymmetrical relationship between oil prices and exchange rates. These effects become more pronounced when global uncertainty is at its peak. These findings have implications for shaping policies in South Africa. Exchange rate stability strategies could involve diversifying energy sources and introducing risk-hedging methods while striving for stability through flexible monetary and fiscal policies. This research also adds to the ongoing conversation about the susceptibility of emerging market currencies to external pressures, serving as a reference point for examining comparable economies. This research enriches the existing body of knowledge by addressing methodological gaps and providing a contemporary analysis of South Africa's exchange rate dynamics in a post-crisis global economy.

The pricing of six highly liquid futures commodity contracts is investigated using a Markov switching procedure. The data set spans an exceptionally turbulent period, characterized by a complex interplay of economic/financial and political shocks. Markov switching analysis exploits time series nonlinearity to identify the nature and the timing of the implicit changes of regime. Building on a HAM framework, we use the time varying parameterization of the transition probability estimates to link these shifts to exogenous variables. We provide in this way additional information on the co-movement of the time series and on their regime shifts, eventually conducive to herding pricing behaviour. The WTI oil futures price and DJIA stock index are used as proxies for global shocks as they turn out to be the main common drivers of the changes in regime of most futures commodity prices.   

This study investigates the relationship between inflation dynamics and retail energy prices across Nigerian states. The paper utilizes LSDV and SYS-GMM techniques for the estimation of the static and dynamic panel models. The research disaggregates energy prices into PMS, AGO, HHK and Gas, with CPI as the dependent variable. State Revenue per capita income, representing demand-pull factor of inflation, is used to capture excess liquidity's impact on inflation. Key findings reveal that PMS, AGO, and HHK have significant and distinct effects on inflation, with PMS and AGO driving the largest increases in CPI. Gas price also contribute to inflation, but its impact is moderated by a substitution effect, where consumers shift to gas in response to rising prices of HHK and other household cooking energy sources. This substitution effect reduces the inflationary pressure from gas, making its overall contribution to CPI less pronounced. Importantly, State Revenue per capita income is positively correlated with inflation, highlighting the role of federal transfers in exacerbating demand-pull inflation. For policymakers, these findings emphasize the importance of targeted interventions to stabilize energy prices, particularly PMS, AGO and federal transfers in shaping local economic dynamics and inflationary pressures. This targeted interventions to stabilize energy prices are vital for mitigating inflationary pressures in Nigerian states, as they account for regional economic differences, ensuring more effective and equitable economic stability across the country.

This study investigates the asymmetric impacts of retail energy prices on inflation in Nigeria, focusing on the period from Q1: 2010 to Q2: 2024. Utilizing secondary data sourced from the Central Bank of Nigeria (CBN) and the National Bureau of Statistics (NBS) e-library, we examine how fluctuations in petroleum prices (PMS and AGO) influence both food and headline inflation. The analysis employs a nonlinear ARDL approach to capture the distinct effects of rising versus falling energy costs, revealing significant asymmetries in their impact on inflation indices. Our findings indicate that increases in fuel prices exert a pronounced inflationary pressure, particularly on food prices, while decreases lead to muted deflationary effects. The results emphasize the need for comprehensive policy interventions to mitigate fuel-driven cost-push inflation. Specifically, we suggest revisiting the framework for fuel subsidy removal to prevent abrupt price shocks that could burden consumers. Additionally, establishing an Energy Price Stabilization Fund (EPSF) could help stabilize food prices during periods of high energy costs by providing targeted support to the food market. Moreover, managing the exchange rate to minimize extreme fluctuations could further alleviate inflation pressures associated with import costs. Finally, strengthening inflation monitoring systems will enhance the government's ability to respond proactively to inflationary trends, ensuring timely interventions. These policy recommendations aim to create a more stable economic environment, reducing the inflationary impact of volatile retail energy prices and improving overall economic resilience in Nigeria.

This paper explores the nonlinear dynamics relationship between petroleum product prices and inflation in Nigeria. By focusing on the role of exchange rate fluctuations in amplifying the relationships, the paper employs a multiplicative interaction approach to address the nonlinear effects of petroleum prices on inflation. Utilizing data from 2016: Q1 to 2024: Q2 from the National Bureau of Statistics and the Central Bank of Nigeria, the study introduces interaction terms to capture how petroleum prices and exchange rates interact to influence inflation. The methodology includes static and dynamic panel estimators, with a focus on the within effect model to account for unobserved state-specific factors. Key findings reveal that AGO and PMS prices significantly drive both headline and food inflation, while DPK's impact varies, and GAS shows minimal effect. The study highlights those geographical factors—proximity to seaports and fuel depots—significantly influence inflationary pressures. States closer to these facilities experience lower inflation due to reduced distribution costs. This suggests that policies aimed at partial subsidization for states farther from key infrastructure could mitigate regional inflation disparities. The findings contribute to the understanding of inflation dynamics, emphasizing the need for targeted policy interventions tailored to regional economic conditions in Nigeria.

This study examines the influence of global stock indices and macroeconomic conditions in Indonesia on the Jakarta Composite Index (JCI). The global stock indices analyzed in this study are the Dow Jones Industrial Average (DJIA), Nikkei 225 (N225), Shanghai Stock Exchange Composite (SSE), Strait Singapore index. The macroeconomic indicators that analyzed in this study are the inflation rate, the US dollar exchange rate against the Indonesian rupiah, and the BI rate. This study was conducted using secondary data. The research period was 3 years for 36 months from January 2018 to December 2020. The data used in this study are secondary data with a sample collection method using Purposive Sampling against JCI. Data analysis in this study was carried out using Microsoft Office Excel 2016, as well as hypothesis testing using panel data regression analysis with the Eviews program version 10.0 with a significance level of 5%. Research Results The results showed that in the short term, Index DJIA, Nikkei Index 225, Interest rates positively affect the movement of JCI. This suggests that an increase in the DJIA index, Nikkei 225 Index, and interest rates will result in an increase in the JCI, While Shanghai Index, STI, Inflation does not affect the JCI.

In the past 20 years, commodity markets have been examined under the hypothesis of whether the prices exhibit recurrent patterns or follow the stochastic processes. In this study, we analyze both global energy markets and food markets to detect the presence of multiple equilibria, which may lead to higher spikes in prices and to the occurrence of intermittency. This study focuses on daily prices in Brent petrol and Natural gas markets from 23 May 2017 to 23 May 2022. This time interval covers the period where extraordinary economic and financial policies have been preferred in countries worldwide amid the Covid-19 pandemic crisis. On the other hand, the study investigates global Food index monthly data from 2007M11 to 2022M4. Similarly, the time interval under examination points out the effects of the 2008 global crisis where expansionary monetary policies have been implemented both by the Federal Reserve of the U.S and the European Central Bank. We employed the phase-space reconstruction method for the Crude oil Brent Europe and spot Natural gas prices series, and global Food index data respectively. The main findings of the study demonstrate that commodity markets do not converge to a unique equilibrium level, instead multiple equilibria persist and chaotic behavior occurs. The presence of multiple equilibria leads to an increase in complexity and recurrently causes volatility in commodity markets, which may have spillover effects on other financial markets. Our results suggest that these effects simultaneously increase global inflationary pressures. From the perspective of policy making, it is crucial to establish a strategy to eliminate multiple equilibria and prevent high price spikes. Our findings have important implications for Central bank policies in emerging markets and portfolio and risk management.

This study investigates the impact of COVID-19 induced global panic on crude oil and natural gas volatility. The author uses the Structural Vector Auto Regression (SVAR) to examine the magnitude of shocks in global oil and gas prices caused by COVID-19 induced panic between 3rd January 2020 and 30th June 2021. The results show that shocks in oil and gas prices were negative and more severe in the first five (5) months of 2020 when the pandemic was spreading across the globe forcing countries' prices into lockdowns. The negative shocks gradually diminished in the following periods as the prices recovered courtesy of global economic recovery and vaccine rollouts. Furthermore, the panic was more pronounced in causing oil prices shocks as gas prices were already suffering amid mild temperatures during the 2020 winter season. The author stresses the need for swift actions during the early days of the crisis to adjust oil and gas supply to match demand shrinkage so as to stabilize their prices given their enormity to the global economy. The Russia-Saudi Arabia delays in agreeing on oil supply restrictions may have amplified the magnitude of negative shocks in oil prices. Existing studies have examined the country-level impacts of COVID-19 on energy prices focusing mainly on oil. However, oil and gas are among the most traded commodities in the world thus the stability of their prices is of global concern. This study examines this phenomenon on a global scale by utilizing the novel global coronavirus panic index.

This paper examines the impact of the September 11th attacks on the United States financial and non-financial sectors. The empirical analysis includes 5 financial and 28 non-financial sub-sector indices using the event study method, structural break test, and volatility analyses. The results of the estimation show that except for the short-lived impact on the real estate sector, the attacks had no significant impact on financial sector indices. Different reactions among non-financial sectors are observed. Travel and leisure and leisure goods sectors were the two industries that were mostly affected by the attacks due to the nature of their business. The outcomes of the analyses provide several diversification strategies and speculation opportunities for both portfolio managers and investors.

There is a pool of techniques and methods in addressing dynamics behaviors in higher frequency data, prominent among them is the ARCH/GARCH techniques. In this paper, the various types and assumptions of the ARCH/GARCH models were tried in examining the dynamism of exchange rate and international crude oil prices in Nigeria. And it was observed that the Nigerian foreign exchange rates behaviors did not conform with the assumptions of the ARCH/GARCH models, hence this paper adopted Lag Variables Autoregressive (LVAR) techniques originally developed by Agung and Heij multiplier to examine the dynamic response of the Nigerian foreign exchange rates to crude oil prices. The Heij coefficient was used to calculate the dynamic multipliers while the Engel & Granger two-step technique was used for cointegration analysis.  The results revealed an insignificant dynamic long-term response of the exchange rate to crude oil prices within the periods under review. The coefficient of dynamism was insignificantly in most cases of the sub-periods. The paper equally revealed that the significance of the dynamic multipliers depends greatly on external information about both market indicators which are two-way interactions. Thus, the paper recommends periodic intervention in the foreign exchange market by the monetary authorities to stabilize the market against any shocks in the international crude oil market, since crude oil is the main source of foreign exchange in Nigeria.

The aim of this study is to determine the causality relationship between energy prices, which are among the most important inputs of the economy, and selected stock market indices of developed countries. Crude oil and natural gas are used as energy variables. G7 countries were selected to represent developed countries. Stock indices used in the study are Dow & Jones (USA), DAX (Germany), CAC40 (France), FTSE250 (England), FTSE Italia All Share (Italy), NIKKEI225 (Japan), and S&P/TSX (Canada). In the study, Johansen (1988) cointegration test and Granger (1969) causality test were used to analyse the causality relationship between energy prices and selected stock market indices. The research could not find a long-term balance relationship between energy prices and developed country indices. Also, while the causality relationship was determined between crude oil prices and NIKKEI225, DAX, and CAC40 indices, a causal relationship between natural gas prices and Dow & Jones and FTSE250 indices was determined. In the study, it was found that energy prices can be used for diversification in investments to be made with stock market indices of developed countries. This study is one of the most comprehensive studies in the literature that examines the relationship between energy prices and the stock market indices of G7 countries. It is expected to contribute to the literature in this way.

This research work investigates the relationship between external macroeconomic shocks and stock price behavior in Nigeria. Variables such as exchange rate (EXR), US real interest rate (USRINTR), and world oil price (WOP) are adopted to capture external macroeconomic shocks while all share price index is used to proxy stock price. The research work uses Johansen cointegration and structural vector autoregressive model as the estimation method. Findings from the study confirm that no long-term co-movement exists between the stock price and the selected external shocks. Findings from the study equally show that both US real interest rate (USRINTR) and world oil price (WOP) are the major external shock predictors of the stock price in Nigeria.

This study aimed to perform a screening for economic interrelationships among market participants from the stock market, global stock indices, and commodities from fossil energy, agricultural, and the metals sector. Particular focus was put on the comovements of the light crude oil benchmarks West Texas Intermediate (WTI) and Brent crude oil. In finance research and the crude oil markets, identifying novel groupings and interactions is a fundamental requirement due to the extended impact of crude oil price fluctuations on economic growth and inflation. Thus, it is of high interest for investors to identify market players and interactions that appear sensitive to crude oil price volatility triggers. The price development of 14 stocks, 25 leading global indices, and 13 commodity prices, including WTI and Brent, were analyzed via data mining applying the hierarchical correlation cluster mapping technique. All price data comprised the period from January 2012 – December 2018 and were based on daily returns. The technique identifies and visualizes existing hierarchical clusters and correlation patterns emphasizing comovements that indicate positively correlated processes. The method successfully identified clustering patterns and a series of relevant and partly unexpected novel comovements in all investigated economic sectors. Although additional research is required to reveal the causative factors, the study offers an insight into in-depth market interrelationships.

Gold and oil price volatilities are thought to have an impact on financial markets. The main aim of this study is to examine the effects of changes in gold and oil prices on Turkish financial markets. For this purpose, the effects of gold and oil price volatilities on nominal US dollar/Turkish lira exchange rate, Borsa Istanbul 100 Index and Turkey 10-year bond interest rates are used to represent Turkish financial markets are analysed by Granger Casuality Test. The study comprises daily data over the period of June 1, 2010 - April 30, 2017. According to the results of the analysis, there is no causality relationship from gold and oil prices to Turkish financial markets. On the other hand, it is concluded that there is a one-way causality relationship from BIST100 index to Turkey 10-year bond interest rate and two-way causality relationship between BIST 100 index and nominal US dollar/Turkish lira exchange rate.