Explore publications.

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.