The rapid expansion of Financial Technology (FinTech) is fundamentally reshaping financial systems, yet its role as a source of systemic risk and its dynamic connectedness with traditional energy and macroeconomic markets remain critically underexplored. This paper employs an integrated time-frequency framework to model financial spillover networks and demonstrates its utility in analyzing the connectedness between emerging FinTech sub-sectors, energy markets, and macroeconomic uncertainty. Using the Diebold and Yilmaz (2012) spillover index in the time domain and the BarunĂk and KĹehlĂk (2018) spectral decomposition in the frequency domain, we uncover a highly interconnected system: total connectedness reaches 43.62% for returns and 40.65% for volatility, showing that price shocks propagate more strongly than risk shocks. During the COVID-19 period, interconnectedness surged above 70%, highlighting how external shocks intensify contagion. We find that key FinTech indices such as Kensho Future Payments, KBW FinTech, and Kensho Alternative Finance act as major net transmitters, while the Distributed Ledger index, geopolitical risk, U.S. policy uncertainty, Brent oil, and U.S. 10-year Treasury yields are net receivers, signaling that within the financial network, shock propagation is now led by FinTech rather than emanating primarily from traditional macroeconomic indicators. Frequency results add important insight: volatility spillovers are mainly short-term (44.57%), reflecting transient fear contagion, while return spillovers are more persistent. Overall, our findings challenge the macro-driven spillover view and offer a time-sensitive framework for effective hedging and regulation. FinTech emerges as a key short-term shock transmitter, with clear implications for investorsâ hedging strategies and regulatorsâ systemic risk monitoring.
This study investigates directional causality between Bitcoin and gold across different market conditions. Rather than relying on mean-based dependence, we examine how causal effects vary across return quantiles, investment horizons, and market regimes. To address this question, we apply a CausalâFrequencyâQuantileâRegime (CFQR) framework. The approach combines frequency-domain Granger causality, quantile-based non-causality tests, and endogenous regime classification within a unified setting. Macroeconomic controls are included to reduce omitted variable bias. Statistical inference relies on bootstrap procedures with false discovery rate correction to account for multiple testing. Using daily data from 2013 to 2025, we find that the full-sample directional dominance between Bitcoin and gold is generally weak after multiple testing adjustments. However, under stress regimes, the causal relationship of gold to Bitcoin becomes more pronounced at longer investment horizons. Under normal conditions, causal effects remain unstable and fragmented. Economic effects are modest. Variance-based hedging gains are limited, while downside risk measures show moderate improvement during stress periods. Overall, the evidence suggests that gold does not serve as a universal hedge for Bitcoin, but may exert conditional informational influence during high-uncertainty states. The CFQR framework provides a structured way to identify such state-dependent causal patterns.
Understanding how Bitcoin mining is distributed across countries is important for evaluating both the sustainability and resilience of the network. In this study, we examine the evolution of total Bitcoin electricity consumption alongside the geographic distribution of Bitcoin mining. Data are provided by the Cambridge Centre for Alternative Finance (Licensed under CC BYâNCâSA 4.0): Annual data from the Cambridge Bitcoin Electricity Consumption Index (2010â2025) and a monthly panel of country-level Bitcoin hashrate shares for 105 countries (September 2019âJanuary 2022). To assess the degree of decentralization in the global mining network, we employ entropy-based measures, inequality indices, and panel convergence tests. The results indicate that total electricity consumption grew exponentially during the early years of Bitcoin, but later transitioned to a more stable and approximately linear path. Country-level permutation entropy reveals highly volatile and dynamic mining trajectories. The Theil index shows that cross-sectional inequality declines over time, while increasing symbolic entropy reflects a progressively more even cross-country distribution of mining activity. Further evidence from Ď-convergence supports a statistically significant reduction in cross-country dispersion of mining shares. Dynamic panel fixed-effects estimates reveal mean-reverting behavior in relative country shares, consistent with stochastic convergence. Finally, PhillipsâSul analysis points to heterogeneous early transition paths but ultimately supports convergence toward a single global club. The gradual geographical decentralization occurs alongside persistent coreâperiphery asymmetries in long-run mining shares. Overall, our findings suggest that Bitcoin mining behaves as a globally integrated industry in which computational capacity reallocates rapidly across countries in response to economic and regulatory conditions.
Samet GĂźnay, Kata VĂĄradi, NĂłra FelfĂśldi-SzĹącs
Abstract This study examines bubble dynamics in the S&P 500 Index and Bitcoin, with particular emphasis on the role of gold as a proxy for market-wide stress. We apply the GSADF bubble test, time-varying Granger causality, and multifractal detrended fluctuation analysis to both original and gold-filtered price series. The results reveal a pronounced asymmetry between equity and cryptocurrency markets. Bitcoin exhibits statistically significant and persistent bubble behavior in both raw and filtered data, accompanied by multifractal persistence consistent with self-reinforcing speculative dynamics. In contrast, the S&P 500 shows no consistent evidence of sustained bubble behavior, and its multifractal properties remain aligned with short memory and rapid information absorption. The causality analysis indicates a stable, state-dependent predictive relationship from gold to equity prices, suggesting sensitivity to global risk sentiment, while no comparable persistent linkage is observed for Bitcoin. Overall, the findings suggest that equity price dynamics remain connected to market-wide stress conditions, whereas Bitcoinâs behavior appears to be driven primarily by asset-specific speculative forces.
Aleksandar Ĺ eviÄ, Ĺ˝eljko Ĺ eviÄ, Athanasios Fassas, Panayiotis Tzeremes
There is a strong impetus to make cryptocurrencies more environmentally friendly, and in our study it is has been analyzed whether commodity price shocks have varying impacts on clean and dirty cryptocurrency interconnectedness before, during and after the COVID-19 pandemic. Using the decomposed and partial connectedness measure we evaluate the connectedness of oil price shocks, demand, supply and risk, as well as five clean and five dirty cryptocurrencies from October 2017 until April 2024. The spikes in demand and disruptions in oil supply lead to price increases. Oil shocks have the largest impact on sampled crypto products during the COVID-19 period, as opposed to pre- and post-pandemic years, and they demonstrate a stronger influence on selected cryptocurrencies than internal crypto-to-crypto dynamics. During the crisis, the difference between clean and dirty cryptocurrencies becomes less relevant when compared to no-crisis periods. We also find that clean cryptocurrencies are net recipients of shocks, while dirty counterparts, dominated by Bitcoin and Ethereum, are net transmitters, especially during the recovery phase. Our findings are relevant for supporting the transition to clean cryptocurrencies and contribute to a better understanding of dynamic interconnectedness. ⢠Examines the decomposed and partial connectedness ⢠Uses time-varying parameter vector autoregression (TVP-VAR) models ⢠Highlights the heterogeneity in cryptosâ responses to oil price fluctuations ⢠Total Connectedness Index peaks during the COVID-19 pandemic ⢠The distinctions between clean and dirty cryptocurrencies reemerged post-COVID
This study aims to compare the investment performance of Decentralized Finance (DeFi), equities (IHSG), and gold during the 2021â2024 period, which represents a full market cycle characterized by high volatility and economic uncertainty. The research objective is to evaluate differences in return, risk (volatility), risk adjusted performance, and inter asset correlations to assess portfolio diversification potential. A quantitative comparative approach is employed using monthly secondary data, analyzed through descriptive statistics, non-parametric difference tests, and correlation analysis. The findings indicate statistically significant differences among the three investment instruments. Gold demonstrates the highest risk efficiency and consistently performs as a safe haven asset. Equities show moderate stability but relatively lower risk adjusted performance. In contrast, DeFi records the highest average returns, accompanied by extreme volatility and low efficiency. Correlation results reveal a strong positive relationship between gold and equities, while DeFi exhibits significant negative correlations with both assets, indicating diversification potential despite elevated systemic risk. This study concludes that gold remains the most resilient investment asset, equities serve as a balanced growth instrument, and DeFi should be positioned as a high risk speculative asset rather than a core portfolio component.
Abstract This paper investigates whether Bitcoin serves as a safe haven and a diversification tool for both developed and emerging stock markets during the COVID-19 crisis, in comparison with gold. The analysis covers daily data from June 18, 2012, to May 25, 2020, across a representative set of developed (S&P500, FTSE100, DAX, CAC40, Nikkei225, Ibex35) and emerging (Shanghai, Nifty50, Ibovespa, MOEX) equity markets, providing a comprehensive view of asset interactions in different financial environments. Methodologically, we employ a two-step approach: an EGARCH model to estimate time-varying volatility, followed by a copula-based framework to capture nonlinear and asymmetric dependence structures. This combination allows for a nuanced assessment of asset behavior under both tranquil and crisis conditions. The results show that Bitcoin maintains weak dependence on developed equity markets during the COVID-19 period but fails to display consistent safe-haven characteristics under extreme stress. Gold, by contrast, continues to act as a reliable hedge, confirming its traditional role in protecting portfolios against market downturns. Overall, these findings suggest that while Bitcoin may provide diversification benefits under normal circumstances, it cannot yet replace gold as a robust safe-haven asset. For portfolio managers, this highlights the importance of gold in risk management, while underscoring Bitcoinâs evolving yet still uncertain role in global financial markets.
Financial assets are central to economic stability, yet the macroeconomic sensitivity and predictability of emerging digital assets, particularly non-fungible tokens (NFTs), remain unclear. This study evaluates the responsiveness of NFTs, cryptocurrencies, and traditional assets to interest rate and inflation fluctuations using time series forecasting and sensitivity analysis. ARIMAX, Partial Least Squares, Ridge Regression, and Long Short-Term Memory (LSTM) models are employed to capture linear and nonlinear dynamics across asset classes. Using daily data from July 2017 to November 2024, results indicate that LSTM achieves superior predictive accuracy for highly volatile and nonlinear assets, although forecast reliability is limited by structural breaks and thin trading. Traditional assets such as bonds and gold display stable sensitivities to macroeconomic variables, reinforcing their hedging role. In contrast, digital assets exhibit higher volatility and weaker, less stable macroeconomic linkages. NFTs show low correlations with traditional assets, suggesting diversification potential, but low forecast error variance does not imply low risk. Cryptocurrencies demonstrate stronger macroeconomic sensitivity alongside greater instability. Overall, the findings reveal a trade-off between diversification benefits and forecast reliability when integrating digital assets into portfolios.
Abstract This paper investigates the time-varying dynamics of the Bitcoin price by examining its relationship with key global factors, including the VIX, the interest rate, the US dollar index, the oil price, and the gold price. The empirical analysis employs a state-space model, the Kalman filter method, and a TVP-VAR-SV. The findings from the state-space model indicate a significant negative association between the Bitcoin price and the VIX, while identifying a positive relationship with the gold price. Further analysis using instantaneous time-varying impulse response functions reveals that the negative response of Bitcoin to the VIX intensified significantly during the pandemic period. A similar negative impact was observed regarding the US dollar index and the oil price. In contrast, the interest rate exhibited a positive connection with the Bitcoin price. Notably, the relationship between Bitcoin and gold, which was negative prior to the pandemic, became statistically insignificant as the crisis escalated. This underscores that Bitcoinâs hedging capabilities and safe haven characteristics are not intrinsic fundamental qualities, but rather conditional behaviors that evolve with shifting global economic landscapes. The evidence suggests that Bitcoinâs defensive properties are structural rather than fundamental, emerging primarily during specific volatility regimes. Additionally, the inverse relationship between the oil price and Bitcoin suggests that rising energy costs may dampen the cryptocurrencyâs appeal due to its substantial energy consumption. These results offer significant implications for scholars, investors, and portfolio managers regarding the management of digital assets during periods of systemic instability.
ABSTRACT The study examines interconnectedness among categories of cryptocurrencies, healthcare cryptocurrencies, decentralized finance indices (DeFi), and nonâfungible tokens using TVPâVAR extended joint connectedness, based on daily data from September 4, 2019, to July 31, 2024. The outcomes indicate that DeFi is the return shock and leading net transmitter, while healthcare cryptocurrencies are the net receivers. Secondly, we also analyze the effect of four newsâbased global uncertainties on total returns using the BVAR model. The outcomes reveal that geopolitical risk (GPR) does not significantly influence global connectedness; however, some individual DeFi protocols, such as Chain Link, Tezos, and Maker, respond positively to GPR. Conversely, economic policy uncertainty reduces the total connectedness index, while infectious disease equity market volatility increases it. Using weekly data covering cryptocurrency uncertainty indices, exerts a positive effect on total return connectedness. The findings underline the influential crypto assets and should be monitored by investors and policymakers.
Amro Saleem Alamaren, Korhan K. GĂśkmenoÄlu, Nigar TaĹpÄąnar
Abstract This study investigates the volatility spillover and connectedness networks among renewable energy sources (Biofuel, Fuel cell, Geothermal, Solar), green bonds, and cryptocurrencies (Bitcoin, Ethereum, Tether, and BNB coin) in the U.S. market. To accomplish this objective, we analyzed data from November 15, 2017, to May 31, 2024, via the methods introduced by Diebold and Yilmaz (Int J Forecast 28:57â66, 2012) and BarunĂk and KĹehlĂk (J Financ Econometr 16:271 296, 2018). Our findings reveal that major global disruptionsâincluding the COVID-19 pandemic, the RussiaâUkraine war, the collapse of Silicon Valley Bank, and the Credit Suisse crisisâhave intensified volatility spillovers and financial contagion across markets, exacerbating their outcomes. The findings suggest that the effectiveness of green finance depends on its allocation across these sectors, highlighting the importance of examining each sector to understand the success of these financial initiatives. The influence of COVID-19 on the U.S. economy has increased transmission risk across markets. Renewable energy is less volatile than green bonds and cryptocurrencies are, with these indices reacting more quickly to short-term shocks. Investors should focus on short-term impacts to manage market risk effectively. By providing insights into how financial shocks propagate across sectors, emphasizing the need for a sector-specific approach to assessing financial sustainability, and underscoring the importance of short-term risk management strategies, this research offers valuable contributions to decision-makers and investors.
This study explores the key determinants influencing cryptocurrency in Indonesia, focusing on macroeconomic variables including inflation, money supply, gold prices, and crude oil prices over the period from 2013 to 2023. It investigates the dynamic relationships between these variables and Bitcoin, the most widely recognized cryptocurrency globally. The research offers a novel contribution by integrating both domestic economic indicators and external commodity prices into a comprehensive framework for cryptocurrency pricing tailored specifically to the Indonesian market context. This innovative and comprehensive approach significantly enhances the understanding of how macroeconomic factors interact with cryptocurrency behavior, which is crucial for various stakeholders and policymakers alike. The findings aim to provide valuable insights to support the formulation of effective monetary policies in an evolving, increasingly complex financial landscape. Future studies are encouraged to build upon this framework by examining the connections between cryptocurrency and other components of the broader financial system.
Nourhaine Nefzi, A. Melki, Sahar Loukil, Ahmed Jeribi
Abstract This study investigates the dynamic connectedness within the cryptocurrency market by analyzing four distinct cryptomarket blocks: Bitcoin and Ethereum (conventional cryptocurrencies); PAXG, DGX, and GLC (gold-backed cryptocurrencies); LINK and MNK (decentralized finance); and THETA and MANA (nonfungible tokens). Using the time-varying parameter quantile vector autoregressive (TVP-Quantile VAR) model for the period 2019â2023, our analysis reveals significant insights into the risk transmission dynamics among cryptocurrencies. Both conventional cryptocurrencies exhibit a consistent net transmitter effect in extreme periods, whereas decentralized finance (DeFi) and nonfungible tokens (NFTs) shift between a net shock transmitter and a net shock receiver over time and quantiles. Moreover, our results shed light on the hedging and safe haven properties of these assets. By linking the dynamic connectedness findings with established literature on hedging and safe haven functions, we elucidate how these cryptocurrencies perform under varying market conditions. Specifically, we report that the role of LINK, MNK, THETA, and MANA as reliable safe-haven assets is contingent upon the observed period. We also observe the hedge and safe haven properties of selected gold-backed cryptocurrencies within the network. Overall, our findings suggest that, despite the dynamic connectedness of the cryptocurrency market, investors have the flexibility to diversify across these digital assets.
Necati Altemur, Ä°brahim Halil EkĹiĚ, Rizky Yudaruddin
Purpose This study aims to provide a comprehensive examination of the nonlinear and asymmetric relationships between global uncertainty indicators, namely, gold (GOLD), the US Dollar Index (DXY) and the Volatility Index (VIX), and major cryptocurrencies, including Bitcoin (BTC), Ethereum (ETH), Ripple (XRP), Cardano (ADA) and Binance Coin (BNB). It particularly focuses on how these dynamics evolve across different market conditions and the extent to which certain cryptocurrencies function as alternative safe-haven assets. Design/methodology/approach The analysis uses weekly data from January 2018 to June 2025, covering five major cryptocurrencies (BTC, ETH, XRP, ADA and BNB). To capture the dynamic and nonlinear relationships between global uncertainty indicators and cryptocurrency markets, the Quantile-on-Quantile Regression (QQR) approach is applied. Furthermore, the Quantile-on-Quantile Kernel-Based Regularized Least Squares (QQKRLS) technique is used as a robustness check to validate the findings. Findings The results demonstrate that the relationship between global uncertainty indicators and cryptocurrencies is neither linear, stationary nor unidirectional. Instead, it exhibits complex and asymmetric interactions that vary across quantiles and market conditions. Significant and predominantly inverse relationships are identified between the DXY, the VIX and cryptocurrencies, particularly at lower (0.05â0.30) and higher (0.70+) quantile levels. These findings suggest that investor behavior is influenced not only by economic fundamentals but also by uncertainty, market dynamics and risk perceptions. Originality/value This study is the first to apply QQR and QQKRLS methods to analyze the nonlinear and asymmetric linkages between global uncertainty indicators and major cryptocurrencies. It provides novel evidence on how these relationships shift across market conditions, offering fresh insights into the potential safe-haven role of cryptocurrencies.
Abstract This study explores the higher-order moments of connectedness among cryptocurrency, commodity, bond, and stock markets from April 19, 2017, to December 29, 2023, on the basis of the GARCH-SK and TVP-VAR models. The findings reveal that Bitcoin and Ethereum act as significant net shock transmitters, especially during major events such as the COVID-19 pandemic and the RussiaâUkraine conflict. After mid-2021, these cryptocurrencies transitioned from net receivers to net transmitters of volatility owing to rising economic and geopolitical risks. These insights assist in portfolio diversification strategies. By combining shock transmitters with shock-resilient cryptocurrencies, investors can enhance their risk profiles. Diversification opportunities shift during financial crises, making it crucial to focus on shock transmitters, which are less influenced by various risk factors. Additionally, the study highlights cryptocurrencies as potential safe havens compared with traditional assets such as gold, bonds, and stocks, which often maintain or appreciate value during market stress. TVP-VAR-informed dynamic portfolio reallocation can improve risk-adjusted returns and lower volatility, aiding in capital preservation during high TCI periods. Overall, our findings suggest that portfolios that include cryptocurrencies generally outperform those that do not, emphasizing their role as effective diversifiers in portfolio optimization and financial stability.
Abstract This study examines the dynamic connectedness that the innovative natural disasters index displays with major cryptocurrencies, decentralized finance assets (DeFi) and non-fungible tokens (NFTs) during the Russia-Ukraine conflict under intense inflationary pressures. Data spanning from 14 December 2021 to 31 January 2025 and three specifications of the Quantile Vector Autoregressive (Q-VAR) methodology at lower, middle and upper quantiles are adopted. Results indicate that natural disaster uncertainty has a larger footprint on DeFi assets in bear markets but is more influential on the NFTs in bull markets. So it acts as a hedge against medium risk digital currencies when pessimism prevails and motivates for investing in riskier assets in elevated investor optimism. The Ripple, Synthetic and Gala assets are the most tightly linked with natural disastersâ sentiment. Higher levels of geopolitical and monetary uncertainties fuel the switch of investorsâ decision-making criteria. This study provides valuable insights for the potential of modern cryptocurrencies to survive during crises when conventional currencies devaluate and offers a compass for monetary authorities and investors.
Open access
Market Dynamics and Volatility
Blockchain Technology Applications and Security
Environmental and Biological Research in Conflict Zones
This study explores the diversification potential of Bitcoin in a French investment portfolio comprising oil, currency, and gold across three distinct market regimes: a pre-crisis stable period, the COVID-19 pandemic, and the RussiaâUkraine conflict. The purpose is to assess whether Bitcoin can enhance portfolio efficiency and provide hedging opportunities under varying market conditions. The analysis is conducted using daily data for Bitcoin, gold, oil, currency, and the CAC40 index from January 1, 2019, to April 22, 2022. Portfolio performance is evaluated through the MeanâVariance (MV) framework and Stochastic Dominance (SD) analysis, allowing for a robust comparison of riskâreturn trade-offs and investor preferences. The MV results show that including Bitcoin consistently improves the portfolioâs riskâreturn profile, evidenced by an upward shift in the efficient frontier across all sub-periods. However, the SD analysis yields more nuanced insights. Before and during the COVID-19 crisis, the portfolio excluding Bitcoin dominates the Bitcoin-inclusive portfolio under second- and third-order stochastic dominance criteria, suggesting that risk-averse investors would prefer the traditional asset mix. In contrast, during the RussiaâUkraine war, no clear stochastic dominance is detected between Bitcoin-inclusive and Bitcoin-exclusive portfolios. These findings emphasize that Bitcoinâs diversification role is highly context- and framework-dependent.
Abstract We examine prospective classification of crypto currencies risks within the ISDA Standardized Initial Margin Model (SIMM) framework for calculation of initial margin on trades sensitive to cryptocurrenciesâ risk factors in the uncleared market. Consistent with the view that cryptocurrencies are digital assets that fundamentally rely on distributed ledger technology (DLT) and induce financial risks that are significantly different from those in traditional risk classes like commodities or FX, we find that cryptocurrencies are best classified into a distinct risk class within SIMM that is split into two buckets â pegged and floating (unpegged) crypto currencies as risk factors - and suggest risk weightsâ calibration methodology within the cryptocurrencies risk class that is consistent with the existing approaches adopted in SIMM.
Mobeen Ur Rehman, Neeraj Nautiyal, Xuan Vinh Vo, Muhammad Kashif ¡ 5 authors
Abstract Cryptocurrencies have regained mainstream attention, with Bitcoinxâ˛s recent rally renewing investor interest across the digital asset space. This study focuses on the connectedness and spillover effects among seven major digital assets to examine the asymmetric relationships conditional on market conditions and time horizons. To emphasize the significance of short- and long-term trading dynamics, we explore the state dependence of linkages during extreme upward and downward market movements. Our findings suggest a significant connectedness induced by Litecoin and Ethereum. Short-term fluctuations are the dominant drivers of crypto-market vulnerability across quantiles and frequencies. Pronounced upper-quantile connectedness emerges consistently across all markets. Interestingly, major currencies, such as Bitcoin, Ethereum, Ripple, and Dash, act as receivers during upside and median market conditions, whereas Ethereum and Litecoin exhibit transmission effects. Moreover, no connectedness is detected between Ethereum and Bitcoin at extreme quantiles. The findings highlight the need for careful monitoring and risk assessment of extreme events, demanding careful risk monitoring during periods of turmoil.
This study examines the joint influence of environmental factors and U.S. financial markets on the returns of Bitcoin (BTC) and Ethereum (ETH), shedding light on sustainability-driven crypto valuation. The analysis integrates COâ emissions, green innovations, ESG scores and financial indicators, including the S&P 500, NASDAQ, Dow Jones, gold and oil prices, using monthly data from January 2019 to February 2025. A robust econometric framework is employed to assess both the long-term cointegration and the short-term sensitivities of BTC and ETH returns. The findings suggest that BTC exhibits a strong positive correlation with environmental innovations and ESG scores, indicating an alignment with investors focused on sustainability. In contrast, ETH exhibits weaker sensitivity to environmental factors despite its adoption of a more energy-efficient Proof-of-Stake mechanism. Both cryptocurrencies respond positively to gold and oil prices, reinforcing their potential as alternative hedging assets. By jointly evaluating environmental and financial drivers, this study contributes to the fields of sustainable finance and digital asset research, bridging the gap between ESG studies and cryptocurrency market analysis.
Bintang Sahala Marpaung, Annaria Magdalena Marpaung, Petrosina Chece
Accurate stock price forecasting is vital for investors in formulating rational investment decisions within capital markets. This study analyzes the impact of Bitcoin, interest rates, and exchange rates on the stock prices of firms in the oil and gas mining sub-sector listed on the Indonesia Stock Exchange over the period 2018â2023. Employing a quantitative research design, the study utilizes secondary data and applies panel data regression analysis using EViews 9. The sample consists of eight firms selected from a population of eighteen companies through purposive sampling. The empirical results reveal that Bitcoin exerts a statistically significant partial effect on stock prices, whereas interest rates and exchange rates do not demonstrate a significant individual impact. Furthermore, the joint analysis indicates that Bitcoin, interest rates, and exchange rates collectively have no significant influence on stock prices. These findings suggest that investors should carefully assess stock price movements and broader market dynamics when making investment decisions, while firms are encouraged to enhance their financial performance to improve investment attractiveness.