Abstract
This study examines the transformative impact of blockchain technology and cryptocurrencies on the financial sector, analyzing their potential to revolutionize traditional systems through decentralized, secure, and transparent transaction models. Leveraging data from Kaggle (2017–2021), we employ ARIMA modeling to explore market trends, volatility, and participant behavior. Key findings underscore the role of regulatory frameworks in risk management and the potential of blockchain to reshape monetary policy.
Methodology
1. Data Source
- Dataset: Cryptocurrency metrics (e.g., Bitcoin’s opening/closing prices, trading volume) sourced from Kaggle.
- Analysis: Longitudinal data combined with advanced forecasting techniques.
2. ARIMA Model
- ARIMA(0,1,1): Predicts future transaction values.
- ARIMA(2,1,0): Forecasts active market participants.
- Validation: AIC/BIC criteria ensured optimal model fit.
Key Findings
1. Bitcoin Market Dynamics (2017–2021)
- Trends: High volatility post-2017 peak, gradual recovery by 2019.
- Forecasts: ARIMA models predict continued short-term volatility (Figures 1–4).
👉 Explore Bitcoin’s price trends
2. Regulatory Importance
- Challenges: Price volatility threatens macroeconomic stability.
- Opportunities: Blockchain enhances transparency and security.
Discussion
Cryptocurrencies disrupt traditional finance but introduce risks like market instability. Effective regulatory frameworks are critical to balance innovation and financial security.
Conclusion
Blockchain technology holds immense potential for financial innovation, yet its adoption requires addressing volatility and regulatory gaps. Future research should refine predictive models and policy strategies.
FAQs
Q1: How does blockchain improve financial transparency?
A1: By decentralizing transactions and creating immutable records, blockchain reduces fraud and enhances auditability.
Q2: What risks do cryptocurrencies pose?
A2: Volatility, regulatory uncertainty, and cybersecurity threats (e.g., exchange hacks).
Q3: Why use ARIMA for crypto forecasts?
A3: ARIMA effectively models non-stationary time-series data, capturing trends and volatility patterns.