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Article

Bitcoin Halving: How Effective Is It in Driving Cryptocurrency Market Dynamics?

by
Nyoman Sri Subawa
1,
Caren Angellina Mimaki
1,*,
I Made Oka Mahendra
1 and
Made Srinitha Millinia Utami
2
1
Department of Management, Universitas Pendidikan Nasional, Denpasar 80224, Indonesia
2
School of Nursing and Midwifery, Edith Cowan University, Perth 6027, Australia
*
Author to whom correspondence should be addressed.
J. Risk Financial Manag. 2026, 19(1), 2; https://doi.org/10.3390/jrfm19010002
Submission received: 14 November 2025 / Revised: 15 December 2025 / Accepted: 16 December 2025 / Published: 19 December 2025
(This article belongs to the Section Financial Technology and Innovation)
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Versions Notes

Abstract

Bitcoin halving is a quadrennial event that halves mining rewards and is believed to influence cryptocurrency prices and cryptocurrency market dynamics. This study examines the effect of Bitcoin halving on Cryptocurrency Prices, with Government Regulations, Market Sentiment, and Cryptocurrency Performance as mediating variables. A quantitative research approach was employed, gathering original data via survey instruments from 294 participants within the cryptocurrency community in Bali, which were analyzed using PLS-SEM. The findings indicate that Bitcoin halving exerts a favorable and statistically meaningful influence on Government Regulations, Market Sentiment, Cryptocurrency Performance, and Cryptocurrency Prices. Market Sentiment fully mediates the influence of Government Regulations and Cryptocurrency Performance on Cryptocurrency Prices, while Government Regulations and Cryptocurrency Performance partially mediate the effect of Bitcoin halving. These findings highlight that Cryptocurrency Prices are shaped by the interplay of technical, policy, and psychological factors, with strategic implications for investors, regulators, and developers.

1. Introduction

In today’s digital age, widespread digitization has driven the rapid integration of digital products and services into various aspects of economic and social activities (Agarwal & Pradhan, 2019; Hariguna et al., 2023; Subawa et al., 2020). One of the most transformative innovations is blockchain technology, a specialized form of database architecture designed to overcome the limitations of traditional banking databases (Paul, 2021; Silva & Mira da Silva, 2022; Tripathi et al., 2023). Cryptocurrencies represent the primary applications of blockchain technology (Krain et al., 2025), functioning as digital currencies whose transactions are securely recorded on a distributed ledger (Gupta et al., 2023; Javaid et al., 2022; Mattke et al., 2019). Within this ecosystem, Bitcoin remains dominant, particularly due to its programmed halving mechanism, which occurs approximately every four years and reduces miner block rewards (Liu et al., 2025). The 2024 Bitcoin halving has become a major focus of attention, as many analysts predict it will significantly impact the cryptocurrency market, with potential spillover effects on emerging technology sectors such as artificial intelligence (AI) (Jiménez et al., 2024; Sedlmeir et al., 2024).
According to Grossman (2019), traditional currencies, or fiat money, will eventually be replaced by Bitcoin, as it operates on a peer-to-peer internet protocol system that eliminates the need for third-party intermediaries, allowing transactions to occur transparently and in real time (Soin et al., 2025). Halving events have also been identified as potential catalysts for increased institutional participation, as they reinforce Bitcoin’s scarcity and its perception as a hedge against inflationary pressures (Fabus et al., 2024; Lashkaripour, 2024; Stensås et al., 2019). Therefore, halvings also serve as strategic factors influencing long-term valuations (Cho et al., 2025).
Investor sentiment is another critical determinant of cryptocurrency prices movements (Anamika et al., 2023; Güler, 2023). Positive sentiment among investors, analysts, the media, or companies can drive substantial price appreciation (Almeida & Gonçalves, 2023; Kim et al., 2022). Prior studies explained that investor sentiment is the result of irrational speculation regarding the future value of assets driven by market participants (Kamath et al., 2024). Similarly, Vanderkooi et al. (2024) found that emotional fluctuations in public attention can significantly impact market volatility, a factor that market participants should anticipate (Caferra, 2022).
Currently, government regulation also plays a crucial role in shaping the cryptocurrency landscape globally (Motsi-Omoijiade, 2022; Schaupp et al., 2022). Many governments remain skeptical of cryptocurrencies, often considering them a potential scam due to the prevalence of fraudulent schemes and money laundering activities in the crypto market. In the Indonesian context, Widhiasthini et al. (2024) emphasized the urgency of cryptocurrency regulation, particularly in regions with complex economic ecosystems. Frederiks et al. (2024) and Cumming et al. (2025) also noted that from a resource-based perspective, new technology-based firms (NTBFs) are more likely to adopt cryptocurrency technology amid regulatory uncertainty, as limited regulation can create opportunities to secure competitive resources.
Despite the extensive literature on Bitcoin, empirical studies examining halving events have primarily focused on price reactions, market efficiency, mining economics, or long-term supply effects. Far less attention has been paid to the psychological and behavioral channels through which halvings may influence market outcomes. The majority of previous studies have investigated halving events through quantitative market data, but rarely have they considered whether investor perceptions, sentiment formation, or regulatory expectations mediate the halving’s broader impact on cryptocurrency markets. Furthermore, much of the existing literature centers on Bitcoin alone, with only a few investigating other digital assets such as altcoins, remains limited (Peng et al., 2024). This gap highlights the need for a comprehensive understanding of the cryptocurrency ecosystem, particularly the interdependence between Bitcoin and alternative digital currencies. While theoretical models suggest that halving reduces supply and may exert upward pressure on prices (Chan et al., 2023), real-world outcomes are much more complex, influenced by macroeconomic conditions, project fundamentals, market sentiment, and the regulatory environment.

The Present Study

This study addresses these gaps by developing an integrated model that examines the influence of the 2024 Bitcoin halving on cryptocurrency prices through the mediating roles of market sentiment, government regulation, and cryptocurrency performances. It offers valuable contributions in various fields. For investors, it provides insight into the optimal timing for cryptocurrency investment decisions. For governments and regulators, it offers empirical evidence to support the formulation of an effective and adaptive regulatory framework for the cryptocurrency industry. For academics, it deepens understanding of how the Bitcoin halving affects the increasingly complex price dynamics of the cryptocurrency market. Furthermore, this study can serve as a theoretical reference for future academics investigating the relationship between Bitcoin and alternative cryptocurrencies (Altcoins). From a theoretical perspective, this study contributes to the advancement of financial theory, particularly in understanding the dynamics of digital asset markets. By analyzing the impact of the Bitcoin halving, this study extends existing financial modeling approaches by integrating behavioral and sentiment dimensions of the cryptocurrency market. This study also contributes to a deeper understanding of investor behavior, particularly among novice investors, in response to significant events in the cryptocurrency market. Ultimately, these findings are expected to open new research avenues in both financial psychology and cryptocurrency market studies.

2. Method

This research was conducted in Bali Province, Indonesia, a region with international recognition and a relatively active digital asset user community. The study population included individuals belonging to cryptocurrency-related organizations and communities who were currently actively investing in crypto assets. These communities were identified through Indonesian crypto forums and social media groups (Discord, Telegram, or Instagram) related to trading, blockchain associations, and local crypto meetup communities in Bali. Community selection was conducted based on three main criteria: (1) Respondents were active in crypto investment activities, particularly those with practical experience in trading and holding digital assets; (2) Communities were willing to accept and distribute the research questionnaire, including obtaining permission from the group admin or manager; and (3) Communities had sufficient activity and membership to provide a variety of perspectives and ensure the collected data was more representative.
The sample was determined using a simple random sampling method, ensuring that each member of the population had an equal chance of being selected as a respondent. To maintain randomness and minimize self-selection bias, the questionnaire link was widely distributed within these communities, and respondents included in the final dataset were randomly selected from the initial participant pool. The sample size was determined using the ten-times rule formula commonly used in PLS-SEM. Given that 25 indicators are used in the research model (Appendix A), the minimum sample size was determined by multiplying the number of indicators by ten (25 × 10 = 250 respondents). This number meets the requirements to ensure the stability of the model estimates and the adequacy of data in the PLS-SEM analysis. Furthermore, to ensure the relevance of the collected data, this study employed a mandatory screening question at the beginning of the questionnaire designed to verify that only individuals with active crypto investment experience could participate.
This study uses a perception-based survey approach aimed at capturing how individual investors interpret and react to the halving event, which in turn influences investment decisions. Furthermore, this approach is used because it recognizes that market prices are influenced by investor expectations and sentiment, particularly for highly volatile assets including cryptocurrencies. The research instrument used a 10-point Likert scale ranging from “Strongly Disagree—(1)” to “Strongly Agree—(10)” to measure respondents’ perceptions of each construct. In this study, all research constructs were treated as reflective constructs, meaning their indicators were viewed as manifestations of underlying latent variables. Data analysis was performed using Structural Equation Modeling (SEM) techniques with the Partial Least Squares (PLS) algorithm, implemented using SmartPLS version 4.0 software. This analytical approach was chosen due to its robustness in handling complex, predictive-oriented models and its suitability for studies with relatively small to moderate sample sizes (Hair et al., 2022; Richter et al., 2022).

Respondents Demographic Profile

The questionnaire distribution process resulted in 303 responses. After conducting a data eligibility check, 9 questionnaires were found to be invalid. Therefore, a total of 294 valid responses were retained for further analysis, all of which were provided by individuals who are active cryptocurrency investors. Based on gender distribution, 159 respondents (54.1%) were male, while 135 respondents (45.9%) were female. This finding indicates that male participants are more dominant within cryptocurrency organizations, suggesting that gender dynamics may influence participation levels in digital investment activities. Furthermore, socio-cultural factors may also contribute to shaping investment preferences across genders. In terms of age distribution, 257 respondents (87.4%) were between the ages of 17 and 27, while 37 respondents (12.6%) were between the ages of 28 and 38. This indicates that the majority of individuals actively participating in cryptocurrency organizations and investments are young investors, reflecting the strong appeal of cryptocurrency investment among the younger generation, who are generally more receptive to technological innovations and digital financial instruments.
The research model shown in Figure 1 is based on behavioral finance and signaling theory, which explains how the Bitcoin halving affects market outcomes through investor perceptions. Specifically, the Bitcoin halving influences government regulation, as changes in supply and market activity can attract regulators’ attention and prompt policy adjustments. These regulatory actions then act as signals to investors, shaping their perceptions of market credibility and risk, which in turn influence market sentiment. Positive sentiment increases trading activity and liquidity, improving crypto asset performance, and these changes in asset performance subsequently influence Bitcoin price through shifts in investor demand and capital flows. By integrating objective market events with perception-based measures, this framework captures the fundamental and behavioral mechanisms underlying price dynamics in cryptocurrency markets.

3. Results of Partial Least Square (PLS) Analysis

To analyze the proposed research model, the Partial Least Squares (PLS) method was used using SmartPLS version 4.0. The analysis consisted of two basic stages: evaluation of the measurement model (outer model) and the structural model (inner model). Testing of the internal model was conducted through a bootstrapping resampling procedure, and the detailed results are presented below (Hair et al., 2022).
Table 1 shows the results of the first stage PLS analysis, which involves the evaluation of the outer model, including validity, reliability, and multicollinearity. The convergent validity test results indicate that all indicator outer loadings exceeded the threshold of 0.70, with values ranging from 0.796 to 0.881, confirming that all indicators have adequate validity. Furthermore, the Average Variance Extracted (AVE) values for all constructs were above 0.50, with a range of 0.672 to 0.731, indicating that each construct explained more than half of the variance in its indicator and was considered valid. Furthermore, the discriminant validity test results indicated that all constructs in the model met the required criteria. This is demonstrated by the HTMT values, which were all below 0.90 (Table 2), and the Fornell–Larcker criterion results, which showed that the square root of the AVE for each construct was higher than its correlation with the other constructs (Table 3). The reliability test results in Table 1 also indicate that all constructs have excellent reliability, with Cronbach’s alpha values ranging from 0.878 to 0.908 and composite reliability values between 0.911 and 0.931. All values exceed the minimum threshold of 0.70, indicating a high level of internal consistency. Finally, the multicollinearity assessment using the Variance Inflation Factor (VIF) showed that all indicators had VIF values below 10, thus concluding that the model is free from multicollinearity issues (Hair et al., 2022; Ringle et al., 2014).
The inner model evaluation indicates that the structural relationships among the constructs demonstrate strong and consistent explanatory power. As shown in Table 4, the R2 values for Government Regulation, Cryptocurrency Performance, Market Sentiment, and Cryptocurrency Price are 0.571, 0.489, 0.742, and 0.690, respectively. These findings suggest that the exogenous variables explain between 48.9% and 74.2% of the variance in the corresponding endogenous constructs, indicating that the proposed model possesses moderate to substantial explanatory power. Furthermore, the predictive relevance (Q2) values were also within the moderate range. 0.340 for Government Regulation, 0.304 for Cryptocurrency Performance, 0.434 for Market Sentiment, and 0.452 for Cryptocurrency Price, indicating that the model has adequate predictive accuracy and relevance.
Moreover, the f2 results as shown in Table 4 indicate that bitcoin halving has a very large effect on government regulations (f2 = 1.329) and cryptocurrency performance (f2 = 0.956), while its direct effects on market sentiment (f2 = 0.076) and cryptocurrency prices (f2 = 0.028) are small. Government regulations and cryptocurrency performance exert small-to-medium effects on cryptocurrency prices (f2 = 0.115; 0.067) and market sentiment (f2 = 0.083; 0.115), whereas market sentiment has a small effect on cryptocurrency prices (f2 = 0.046). Overall, these results suggest that Bitcoin halving strongly influences regulatory and performance variables, while its impact on prices is primarily indirect through mediating factors. Model fit was assessed using the Standardized Root Mean Square Residual (SRMR), with values of 0.059 for the saturated model and 0.081 for the estimated model, indicating a good to acceptable level of overall model fit. In conclusion, the PLS analysis results confirm that the measurement and structural models meet the recommended criteria for reliability, validity, and predictive quality, thus supporting the robustness of the proposed research framework.

3.1. Direct Effect Analysis

The path analysis results, as shown in Table 5, indicate that all hypotheses proposed in the model are positive and statistically significant. These findings are supported by t-statistic values exceeding 1.65 and p-values below 0.05.
Specifically, the Bitcoin Halving has a positive effect on Government Regulation (β = 0.755; t = 23.539; p < 0.001), Market Sentiment (β = 0.240; t = 2.247; p = 0.025), Cryptocurrency Performance (β = 0.699; t = 18.964; p < 0.001), and Cryptocurrency Prices (β = 0.136; t = 2.280; p = 0.023). Furthermore, Government Regulations positively impacted Market Sentiment (β = 0.318; t = 3.002; p = 0.003) and Cryptocurrency Prices (β = 0.356; t = 4.046; p < 0.001). Similarly, Cryptocurrency Performance exhibited a significant positive effect on Market Sentiment (β = 0.344; t = 4.475; p < 0.001) and Cryptocurrency Prices (β = 0.253; t = 3.294; p = 0.001). Finally, Market Sentiment exhibited a positive and significant relationship with Cryptocurrency Prices (β = 0.195; t = 2.088; p = 0.037). Overall, these findings confirm that Bitcoin Halving directly and indirectly increases cryptocurrency market prices through the mediating role of government regulations, asset performance, and market sentiment.

3.2. Indirect Effect Analysis

Indirect path analysis in Table 6 shows that the Bitcoin halving significantly impacts cryptocurrency prices through various mediation pathways, specifically, government regulation, cryptocurrency performance, and market sentiment. These findings suggest that the Bitcoin halving’s effect on price dynamics operates not only through direct mechanisms but also through institutional and behavioral channels, highlighting the multi-layered nature of cryptocurrency market movements.
Mediation in this study was assessed based on the significance value of the structural path coefficients that had been implemented through a bootstrapping procedure. Specifically, four criteria were applied. First, when the paths X → M (C) and M → Y (D) were significant, but the indirect effect X → M → Y (A) was not significant, full mediation was supported. Second, when the paths X → M (C), M → Y (D), and the indirect effect X → M → Y (A) were all statistically significant, partial mediation was supported. Third, when the coefficient of the indirect effect (A) was approximately equal to the direct effect (X → Y; B), mediation was considered not supported. Finally, if the paths X → M (C) or M → Y (D) were not significant, mediation was also considered not supported. This approach ensured that the mediation classification was based on causal structure and statistical significance.
The mediation analysis presented in Table 7 indicates that full mediation occurs when market sentiment mediates the relationship between government regulation and cryptocurrency prices, as well as between cryptocurrency performance and cryptocurrency prices. This conclusion is supported by the presence of a significant indirect effect accompanied by an insignificant direct effect, indicating that the influence of government regulation and cryptocurrency performance on cryptocurrency prices is transmitted entirely through market sentiment. Substantively, these findings indicate that a strengthening regulatory framework is associated with higher cryptocurrency prices if accompanied by positive investor sentiment, and that improved cryptocurrency performance reflected in price appreciation primarily through changes in market sentiment.
In contrast, three relationships exhibit partial mediation, as both direct and indirect effects remain statistically significant. First, market sentiment partially mediates the relationship between Bitcoin halving and cryptocurrency prices, indicating that halving events contribute to price increases both directly and indirectly through shifts in investor sentiment. Second, government regulation partially mediates the relationship between Bitcoin halving and cryptocurrency prices, indicating that effective regulatory oversight amplifies the positive impact of halving events on price movements. Finally, cryptocurrency performance also partially mediates the relationship between Bitcoin halving and cryptocurrency prices, indicating that the impact of Bitcoin halving on prices is conveyed directly and through an increase in overall cryptocurrency performance.

4. Discussion

This research makes a significant contribution, particularly in understanding how the Bitcoin halving is an important factor in regulatory transformation, market sentiment, and strengthen cryptocurrency performance. Furthermore, the study confirms that all four components have a significant influence on cryptocurrency price increases. These findings suggest that market sentiment serves as a dominant behavioral transmission mechanism, linking the Bitcoin halving, regulation, and cryptocurrency performance to price dynamics. These findings also strengthen the relevance of behavioral finance theory and sentiment-based asset pricing, which argue that in highly speculative markets characterized by information asymmetry, such as the cryptocurrency market, prices are strongly shaped by investor expectations, emotions, and narratives than by traditional fundamentals alone. In this context, cryptocurrency valuation can be understood as a socially constructed process, influenced by collective beliefs, perceptions of legitimacy, and future-oriented speculation.
The significant relationship between Bitcoin halving and market sentiment and government regulation reflects the dual technical and institutional nature of halving events. Although Bitcoin halving is a technical mechanism specific to Bitcoin’s protocol, their impact on the broader cryptocurrency market is largely indirect, operating through investor sentiment, shared market narratives, and spillover effects across crypto assets rather than through direct supply changes. From a technical perspective, halving tightens supply and reinforces the logic of scarcity as the basis for price expectations. From an institutional perspective, the surge in volatility and speculative activity post-halving heightens regulatory attention to financial system stability. These findings align with previous studies showing that halving events intensify market speculation, increasing regulatory enforcement and oversight in response to protect investors and ensure market stability (Fabus et al., 2024; Xiong & Luo, 2024). At the same time, halving serve as symbolic narrative triggers, reinforcing investor optimism and speculative momentum, consistent with the narrative economics framework (Almeida & Gonçalves, 2023; Ben Osman et al., 2024; Ramadhani & Andrianingsih, 2024). In other words, the impact of halving on the market is not merely mechanical, but is also mediated by investors’ narrative and psychological constructions (Chan et al., 2023).
The strong link between regulation, cryptocurrency performance, and market sentiment further confirms that regulatory clarity, along with technological and market strength, are key drivers of investor confidence. Transparent regulation plays a role in reducing uncertainty, while network and market performance shape perceptions of the credibility and sustainability of crypto assets (Hamza, 2020; Savero et al., 2024). Consistent with Dwyer (2015) view, cryptocurrency valuations in this context react more strongly to perceived credibility, network strength, and institutional acceptance than to conventional fundamental metrics. Consequently, fundamental analysis of cryptocurrency projects remains crucial for understanding how performance dynamics shape investor sentiment and influence subsequent market behavior. In this context, supportive regulation not only provides legal certainty but also acts as a signal of legitimacy, strengthening investor participation and supporting market stability (Bonaparte & Bernile, 2023; Manurung & Paath, 2020; Schaupp et al., 2022; Stupak, 2025).
The literature also confirms that market sentiment is a crucial element in cryptocurrency price formation. Positive sentiment not only reflects individual optimism but also represents collective expectations that is followed by buying pressure and shape short-term trends (Abdul Karim et al., 2022; Naeem et al., 2021). Optimism generated by positive news, influencers, and community dynamics creates a psychological feedback mechanism, where price increases strengthen sentiment, and sentiment, in turn, strengthens price increases. Conversely, negative sentiment tends to trigger panic and herd behavior, accelerating price corrections. Therefore, crypto market volatility can be understood as a reflection of fluctuations in investors’ collective emotions. (Pratama, 2023; Ti & Husodo, 2024). Cryptocurrency performance also plays a major role as a cognitive foundation in shaping investor confidence. Market capitalization growth, increased liquidity, transaction efficiency, and network stability foster the perception that crypto assets have utility, durability, and long-term prospects. Investors respond to performance not as purely numerical information, but as a signal of technological legitimacy and ecosystem sustainability. Perceptions of strong performance lower psychological barriers to risk and broaden market participation. This process explains why the relationship between performance and price is not mutually exclusive but rather intertwined with how performance is interpreted by market participants (Jegerson et al., 2025; Momtaz, 2021).
Mediation analysis offers important theoretical insights, particularly regarding the price formation mechanisms in crypto markets. Full mediation through market sentiment in some relationships suggests that regulatory improvements and improved cryptocurrency performance affect prices only after shaping investors’ expectations and emotional responses (Ben Osman et al., 2025). This supports sentiment-based valuation models, which emphasize that objective signals require psychological interpretation before being capitalized on in prices. (Liu et al., 2025; Wang et al., 2025). In contrast, the partial mediation effect detected in the relationships involving Bitcoin halving reflects the halving’s hybrid nature as both a mechanical supply-side shock and a speculative market narrative. Halving directly affect prices through changing supply dynamics, while simultaneously amplifying optimism and speculative behavior through sentiment-based channels (Ballis & Verousis, 2022; Gurdgiev & O’Loughlin, 2020; de Salis & dos Maciel, 2023).
These findings also explain why a perception-based approach through surveys is a relevant empirical method for capturing the effects of halving. Although halving are technical protocol events, their impact on prices is more anticipatory than reactive. In practice, price movements often occur well before the halving, reflecting investor expectations, media coverage, and investor speculative positions. Therefore, investor confidence, optimism, and fear are the primary channels for transmitting the impact of halving, which cannot be fully captured through historical price data alone (Alfina et al., 2023; Jiménez et al., 2024). In this context, survey instruments are an effective tool for mapping the latent psychological mechanisms underlying price formation, in line with behavioral approaches in contemporary crypto market studies. This study’s findings are generally consistent with evidence that sentiment, social signals, and narrative framing exert a strong influence on cryptocurrency prices (Abdul Karim et al., 2022; Almeida & Gonçalves, 2023; Naeem et al., 2021). However, this study extends previous research by explicitly demonstrating that market sentiment is not simply a contributing factor but rather a dominant mediating channel that transmits the effects of regulation, performance, and halving into price movements. This suggests that investor psychology plays a more structurally embedded role in crypto asset valuations than is often acknowledged in technically oriented market models. From a macro-financial perspective, these findings also suggest that cryptocurrencies increasingly behave as financial-social hybrids, where valuations emerge from the interaction of technology, institutions, and mass investor psychology. Government regulation enhances perceived legitimacy, performance strengthens technological trust, and halving intensify scarcity narratives. However, none of these forces fully translate into price formation without investor interpretation.

5. Conclusions

This research demonstrates that the Bitcoin halving plays a significant role in shaping cryptocurrency price dynamics through its interaction with market sentiment, government regulation, and crypto asset performance. Key findings emphasize that price movements are not solely determined by technical supply mechanisms, but are strongly shaped by investor expectations, psychological responses, and institutional legitimacy. In this context, market sentiment appears to function as a key channel transmitting technical and regulatory signals into price formation. Theoretically, this research contributes to the development of complexity theory and behavioral finance in digital asset markets by demonstrating that cryptocurrency valuations are shaped by the interaction of technical, psychological, and regulatory factors. This study also enriches the regulatory literature by highlighting its dual role as both a source of stability and potential uncertainty. Furthermore, the findings regarding the halving’s spillover effect on altcoins broaden our understanding of cross-asset interconnections within the crypto ecosystem.
From a practical and policy perspective, the findings provide important insights at both local and global levels. For Indonesia and Bali, they suggest the need for clear regulatory guidance for cryptocurrency investors, including licensing frameworks for exchanges, enhanced investor protection measures, and public education on digital asset risks. At the global level, transparent and credible regulatory practices are likely to support investor confidence and market stability. These results highlight that investors should combine fundamental analysis, sentiment monitoring, and an understanding of regulatory dynamics when formulating strategies, while portfolio managers can leverage cyclical patterns surrounding halving events to inform timing and asset diversification decisions. For policymakers, the study undescores the importance of maintaining a transparent, adaptive, and innovation-supportive regulatory framework to promote long-term market confidence. Future research is recommended to examine long-term dynamics across multiple halving cycles, expand cross-country analysis in differing regulatory regimes, integrate large-scale behavioral data such as real-time social media sentiment, and investigate heterogeneous responses across altcoin types to better understand systemic risk and spillover effects in digital asset markets.

6. Limitations

This research was limited to a single country, with a relatively short research period, and focused solely on the impact of Bitcoin Halving on cryptocurrency prices, considering the role of market sentiment, government regulation, and cryptocurrency performance. In addition, this study relies on perception-based survey data, where investor sentiment may vary according to respondent characteristics such as age, investment experience, risk tolerance, and level of market exposure. These demographic differences may influence how market signals are interpreted, and therefore the findings should be interpreted with caution when generalizing to broader or more diverse investor populations. Although this research makes a significant contribution to understanding cryptocurrency market dynamics, there are still several aspects that can be further explored to enrich understanding and provide more comprehensive solutions. The following are recommendations for future research: First, Expanding the Scope of Variables and Context. Additional variables: Future research could include other variables such as institutional adoption, blockchain technology development, or global macroeconomic factors (e.g., inflation, interest rates) to examine their impact on cryptocurrency prices. Cross-country comparison: Comparative studies of the impact of Bitcoin Halving in various countries with different regulations could provide insight into how government policies moderate the halving effect. Second, a more in-depth methodological approach: Longitudinal analysis: Research with a longer time span (e.g., spanning multiple halving cycles) could reveal long-term patterns and stability of the halving impact. Further research could employ qualitative methods. In-depth interviews with market participants, regulators, or cryptocurrency developers could provide a more holistic understanding of their motivations and perceptions of the halving. Experimental studies, market simulations, or investor behavior experiments could help test the causal relationship between the halving and market sentiment.

Author Contributions

Conceptualization, N.S.S. and I.M.O.M.; methodology, N.S.S., C.A.M. and I.M.O.M.; software, C.A.M. and M.S.M.U.; validation, N.S.S., C.A.M., I.M.O.M. and M.S.M.U.; formal analysis, C.A.M. and M.S.M.U.; investigation, N.S.S., C.A.M. and I.M.O.M.; resources, I.M.O.M.; data curation, N.S.S., C.A.M., I.M.O.M. and M.S.M.U.; writing—original draft preparation, N.S.S., C.A.M., I.M.O.M. and M.S.M.U.; writing—review and editing, N.S.S., C.A.M., I.M.O.M. and M.S.M.U.; visualization, M.S.M.U.; supervision, N.S.S.; project administration, N.S.S., C.A.M., I.M.O.M. and M.S.M.U.; funding acquisition, N.S.S. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki, and approved by the Ethics Committee of The Universitas Pendidikan Nasional (protocol code 036A/KO.IN.UNID/VI/2025 and 25 June 2025).

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

Raw data for the non-financial analyses reported in this paper are available from the corresponding author on request.

Conflicts of Interest

The authors declare no conflicts of interest.

Appendix A. Questionnaire Items

  • Bitcoin Halving (BIH).
    • Active Bitcoin miners have a positive impact on the cryptocurrency market.
    • Bitcoin prices will definitely increase after a Bitcoin halving occurs.
    • Market sentiment is always positive before a Bitcoin halving takes place.
    • The halving protocol increases investor confidence and contributes to greater cryptocurrency stability.
    • Bitcoin halving can cause the prices of other cryptocurrencies to increase tenfold after the event.
  • Government Regulations (GR).
    • Regulations regarding cryptocurrency are clear and easy to understand.
    • The institutions overseeing cryptocurrency are overly strict.
    • Through the established regulations on cryptocurrency, the government ensures public protection from cryptocurrency-related fraud.
    • The existing cryptocurrency regulations need to be re-evaluated.
    • Government regulations can significantly increase cryptocurrency prices after a halving occurs.
  • Market Sentiment (MS).
    • News about cryptocurrency influences investors’ investment decisions.
    • Professional statements affect investors’ psychology.
    • Global events, such as wars or pandemics, negatively impact cryptocurrency.
    • Developer news can serve as an important signal in buy or sell decisions.
    • Positive market sentiment can significantly increase cryptocurrency prices.
  • Cryptocurrency Performance (CPER).
    • The success of a cryptocurrency in achieving strong performance enhances its positive image in the eyes of the public.
    • Positive cryptocurrency performance strengthens investor confidence in the asset’s growth potential.
    • Strong performance of a cryptocurrency can serve as evidence of the development team’s commitment and capability.
    • Government policies have a significant influence on cryptocurrency performance.
    • Cryptocurrency performance can significantly increase its market price.
  • Cryptocurrency Prices (CP).
    • Closing price can provide information on the appropriate timing to buy or sell an asset.
    • High trading volume during a certain period may indicate strong market interest.
    • High volatility can signal the need to sell an asset.
    • Network hash rate can be used as an indicator of security.
    • The launching price can influence the extent of price increases during a Bitcoin halving.

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Jrfm 19 00002 g001
Figure 1. Research Framework.
Figure 1. Research Framework.
Jrfm 19 00002 g001
Table 1. Outer Model Result.
Table 1. Outer Model Result.
IndicatorsLoadingsAVEαCRVIF
Bitcoin Halving
BIH10.8520.6720.8780.9112.654
BIH20.7972.748
BIH30.8462.330
BIH40.8042.833
BIH50.7962.090
Cryptocurrency Price
CP10.8510.6940.8900.9192.627
CP20.8462.541
CP30.8402.311
CP40.8372.496
CP50.8322.403
Cryptocurrency Performance
CPER10.8280.7070.8970.9242.131
CPER20.8302.168
CPER30.8542.381
CPER40.8142.026
CPER50.8402.268
Government Regulation
GR10.8460.7310.9080.9312.395
GR20.8712.979
GR30.8482.483
GR40.8282.207
GR50.8813.202
Market Sentiment
MS10.8530.6960.8910.9202.370
MS20.8482.359
MS30.8332.272
MS40.8062.065
MS50.8302.174
Table 2. HTMT Result.
Table 2. HTMT Result.
BIHCPERCPGRMS
BIH
CPER0.767
CP0.8180.839
GR0.8310.8420.877
MS0.7120.7200.7710.726
Note: BIH = Bitcoin halving; CPER = Cryptocurrency performance; CP = Cryptocurrency price; GR = Government Regulation; MS = Market sentiment.
Table 3. Fornell-Larcker Criterion Result.
Table 3. Fornell-Larcker Criterion Result.
BIHCPERCPGRMS
BIH0.820
CPER0.6840.833
CP0.7300.7530.841
GR0.7480.7580.7930.855
MS0.6360.6440.6920.6550.834
Note: BIH = Bitcoin halving; CPER = Cryptocurrency performance; CP = Cryptocurrency price; GR = Government Regulation; MS = Market sentiment.
Table 4. Goodness of Fit Result.
Table 4. Goodness of Fit Result.
CPERCPGRMS
R-Square0.4890.6900.5710.742
Q-Square0.3040.4520.3400.434
f-Square
    BIH0.9560.0281.3290.076
    GR 0.115 0.083
    MS 0.046
    CPER 0.067 0.115
Model FitSRMR SaturatedSRMR Estimated
0.0590.081
Note: BIH = Bitcoin halving; CPER = Cryptocurrency performance; CP = Cryptocurrency price; GR = Government Regulation; MS = Market sentiment.
Table 5. Results of Direct Effect Testing.
Table 5. Results of Direct Effect Testing.
Hypothesis PathsCoefficientsT Statisticp ValueResults
H1BIH → GR0.75523.5390.000 **Supported
H2BIH → MS0.2402.2470.025 *Supported
H3BIH → CPER0.69918.9640.000 **Supported
H4GR → MS0.3183.0020.003 *Supported
H5CPER → MS0.3444.4750.000 **Supported
H6GR → CP0.3564.0460.000 **Supported
H7MS → CP0.1952.0880.037 *Supported
H8CPER → CP0.2533.2940.001 **Supported
H9BIH → CP0.1362.2800.023 *Supported
Notes: * p-value < 0.05, ** p-value < 0.001, BIH = Bitcoin Halving, GR = Government Regulation, CPER = Cryptocurrency performance, MS = Market Sentiment, CP = Cryptocurrency Prices.
Table 6. Results of Indirect Effect Testing.
Table 6. Results of Indirect Effect Testing.
Hypothesis PathsCoefficientsT Statisticp ValueResults
H10BIH → MS → CP0.0472.3580.018 *Supported
H11GR → MS → CP0.0621.3110.190Rejected
H12CPER → MS → CP0.0671.5950.111Rejected
H13BIH → GR → CP0.2694.0810.000 **Supported
H14BIH → CPER → CP0.1773.2410.001 **Supported
Notes: * p-value < 0.05, ** p-value < 0.001, BIH = Bitcoin Halving, GR = Government Regulation, CPER = Cryptocurrency performance, MS = Market Sentiment, CP = Cryptocurrency Prices.
Table 7. Examination of Mediating Variables.
Table 7. Examination of Mediating Variables.
Mediation PathwaysCoefficients and SignificanceResults
(A)(B)(C)(D)
BIH → MS → CP0.047
(Sig. 0.018)		0.136
(Sig. 0.023)		0.240
(Sig. 0.025)		0.195
(Sig. 0.037)		Partial
Mediation
GR → MS → CP0.062
(Non-Sig. 0.190)		0.356
(Sig. 0.000)		0.318
(Sig. 0.003)		0.195
(Sig. 0.037)		Full
Mediation
CPER → MS → CP0.067
(Non-Sig. 0.111)		0.253
(Sig. 0.001)		0.344
(Sig. 0.000)		0.195
(Sig. 0.037)		Full
Mediation
BIH → GR → CP0.269
(Sig. 0.000)		0.136
(Sig. 0.023)		0.755
(Sig. 0.000)		0.356
(Sig. 0.000)		Partial
Mediation
BIH → CPER → CP0.177
(Sig. 0.001)		0.136
(Sig. 0.023)		0.699
(Sig. 0.000)		0.253
(Sig. 0.001)		Partial
Mediation
Notes: BIH = Bitcoin Halving, GR = Government Regulation, CPER = Cryptocurrency performance, MS = Market Sentiment, CP = Cryptocurrency Prices.
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Subawa, N.S.; Mimaki, C.A.; Mahendra, I.M.O.; Utami, M.S.M. Bitcoin Halving: How Effective Is It in Driving Cryptocurrency Market Dynamics? J. Risk Financial Manag. 2026, 19, 2. https://doi.org/10.3390/jrfm19010002

AMA Style

Subawa NS, Mimaki CA, Mahendra IMO, Utami MSM. Bitcoin Halving: How Effective Is It in Driving Cryptocurrency Market Dynamics? Journal of Risk and Financial Management. 2026; 19(1):2. https://doi.org/10.3390/jrfm19010002

Chicago/Turabian Style

Subawa, Nyoman Sri, Caren Angellina Mimaki, I Made Oka Mahendra, and Made Srinitha Millinia Utami. 2026. "Bitcoin Halving: How Effective Is It in Driving Cryptocurrency Market Dynamics?" Journal of Risk and Financial Management 19, no. 1: 2. https://doi.org/10.3390/jrfm19010002

APA Style

Subawa, N. S., Mimaki, C. A., Mahendra, I. M. O., & Utami, M. S. M. (2026). Bitcoin Halving: How Effective Is It in Driving Cryptocurrency Market Dynamics? Journal of Risk and Financial Management, 19(1), 2. https://doi.org/10.3390/jrfm19010002

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