The Engle-Granger two-step methodology is a statistical procedure used in econometrics to test for cointegration between two or more time series variables. Cointegration implies that even if individual series are non-stationary, a linear combination of them can be stationary, suggesting a long-term equilibrium relationship crucial for understanding correlated crypto asset movements.
Mechanism
The mechanism involves two primary steps: first, a long-run regression is estimated between the non-stationary time series to obtain the residuals. Second, these residuals are then tested for stationarity using a unit root test, such as the Augmented Dickey-Fuller (ADF) test. If the residuals are found to be stationary, it indicates that the original time series are cointegrated, implying they move together in the long term despite short-term deviations.
Methodology
The strategic application of the Engle-Granger method in crypto investing involves identifying long-term price relationships between different cryptocurrencies, or between digital assets and traditional financial instruments. This methodology aids in developing pairs trading strategies, where temporary deviations from an established equilibrium are exploited. It provides a robust framework for assessing the statistical validity of assumed relationships, allowing for the construction of more resilient arbitrage or relative value strategies in dynamic crypto markets.
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