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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.

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.

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.