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Index/Chapter 03

Asset Correlations & Cointegration Guide (Asset Correlations)

Look beyond simple correlation coefficient limits and analyze long-term equilibrium vectors using Johansen Cointegration tests.

5 min read

1. Overview of Cointegration & Asset Correlations

Standard investors rely on Pearson correlation coefficients to assess the relationship between asset classes. However, correlation coefficients only trace short-term rate of changes. They cannot confirm long-term equilibrium and are highly vulnerable to spurious correlation errors.

This guide details the mathematical principles of Cointegration and how to leverage it for robust portfolio diversification.


2. Core Concepts & Statistical Metrics

① Pearson Correlation Coefficient

  • Definition: Measures the linear relationship between two variables, ranging from -1.0 (perfect inverse relationship) to 1.0 (perfect positive relationship).
  • Significance: Indicates whether daily price movements fluctuate in tandem under short-term sentiment cycles.

② Johansen Cointegration Test & p-value

  • Definition: Evaluates whether a linear combination of non-stationary time series assets yields a stationary, long-term equilibrium spread.
  • p-value Thresholds:
    • <= 0.05: Confirms a strong cointegrating relationship. Even if short-term spreads drift, the prices are bound by a structural connection that inevitably pulls them back to equilibrium.
    • > 0.10: No cointegration. Any perceived price alignment is temporary (spurious), and the asset prices can drift apart indefinitely.

3. Structural Dynamics: Correlation vs. Cointegration

  • Spurious Alignments:
    • High Correlation, No Cointegration: Two assets move together briefly due to macro shocks, but lack structural connections (e.g. mutual supply loops, identical interest spreads). Arbitraging their spread carries immense risks of catastrophic divergence.
    • Low Correlation, High Cointegration: Daily price changes look random, but their spread never exceeds a constant envelope because of business structures (e.g. parent-subsidiary links, oil vs. jet fuel costs).

4. Practical Institutional Application

  1. Detecting Decoupling Events:
    • If the p-value of Bitcoin and Nasdaq cointegration shifts from 0.02 to 0.15, the historical correlation has broken down. Valuation models must isolate their liquidity channels immediately.
  2. Pairs Trading Safety Nets:
    • When a structurally cointegrated pair (e.g., TSMC and ASML) experiences extreme spread divergence, investors sell the overvalued asset and purchase the undervalued asset. Profits are collected as the spread mean-reverts back to statistical equilibrium.
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