This research investigates whether cryptocurrencies have significant long-term connections with traditional financial assets, demonstrating stable relationships despite their volatility. Various tests were conducted to analyze these relationships and interactions.
- Initial Data Analysis: The stationarity test on the original data indicated a price level trend, a common characteristic of financial data.
- Differencing Data: By differencing the original datasets, we focused on returns or changes in prices rather than levels. The Augmented Dickey-Fuller (ADF) test confirmed that the differenced data is stationary.
- Assets Analyzed: Bitcoin (BTC), Ethereum (ETH), Gold, and S&P 500 (SP500).
- Results: The cointegration tests revealed a long-term equilibrium relationship among BTC, ETH, Gold, and SP500. Despite short-term fluctuations, these assets' prices tend to move together over the long term.
- Purpose: The VAR model was employed to capture the short-term interactions between the analyzed assets.
- Findings: The model effectively described the dynamic interdependencies and interactions over short periods.
- Cryptocurrencies and Gold: Tests indicated that both cryptocurrencies and Gold exhibit homoscedasticity (constant variance) and lack serial correlation.
- S&P 500: In contrast, the SP500 data demonstrated heteroscedasticity (variable variance) and serial correlation.
- Objective: To verify the correctness of the model used for analysis.
- Outcome: The Ramsey RESET test confirmed that the model accurately represents the true underlying relationship between the analyzed assets.
Based on the conducted tests and analysis, we conclude that our main hypothesis—cryptocurrencies have significant long-term connections with traditional financial assets, showing stable relationships despite their volatility—cannot be rejected. While there are short-term differences, the long-term connections are evident.