Stylized Facts of Financial Returns › Correlation Breakdown in Crises
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A final stylized fact concerns correlations between assets, which increase during market stress. The diversification benefits you count on in normal times partially evaporate precisely when you need them most.
Even after controlling for volatility, the underlying correlation structure shifts during crises. Assets that seemed uncorrelated become highly correlated when panic sets in.
# Define crisis and calm periods
crisis_periods = [
("2008-09-01", "2009-03-31"), # Financial Crisis
("2020-02-15", "2020-04-15"), # COVID Crash
]
calm_periods = [
("2013-01-01", "2013-12-31"),
("2017-01-01", "2017-12-31"),
]
def get_corr_matrix(returns, start, end):
mask = (returns.index >= start) & (returns.index <= end)
return returns[mask].corr()
# Calculate correlations for different periods
crisis_corr_2008 = get_corr_matrix(multi_returns, "2008-09-01", "2009-03-31")
calm_corr_2017 = get_corr_matrix(multi_returns, "2017-01-01", "2017-12-31")
crisis_corr_2020 = get_corr_matrix(multi_returns, "2020-02-15", "2020-04-15")Correlation Structure: Crisis vs. Calm Periods
============================================================
Financial Crisis (Sep 2008 - Mar 2009):
^GSPC GLD TLT EFA
^GSPC 1.000 0.394 -0.013 0.945
GLD 0.394 1.000 0.196 0.448
TLT -0.013 0.196 1.000 0.037
EFA 0.945 0.448 0.037 1.000
Calm Period (2017):
^GSPC GLD TLT EFA
^GSPC 1.000 0.063 -0.351 0.862
GLD 0.063 1.000 0.153 0.101
TLT -0.351 0.153 1.000 -0.310
EFA 0.862 0.101 -0.310 1.000
COVID Crash (Feb - Apr 2020):
^GSPC GLD TLT EFA
^GSPC 1.000 0.050 -0.156 0.928
GLD 0.050 1.000 0.178 0.088
TLT -0.156 0.178 1.000 -0.069
EFA 0.928 0.088 -0.069 1.000During the financial crisis and COVID crash, correlations between S&P 500 and other assets shift compared to calm periods. The correlation between US and international equities (EFA) typically spikes during crises, reducing the diversification benefit of global equity allocation exactly when losses are largest.
