← Correlation and diversification

Lesson 4 of 25 · 7 min

Two assets, one formula: the variance of a pair

Two of the three terms do not move when correlation moves, which is why the third one decides the whole answer.

The two-asset case contains the entire mechanism, and it is small enough to hold in one line. Everything later in this track is this formula with more terms.

variance = (w1 x s1)^2 + (w2 x s2)^2 + (2 x w1 x w2 x s1 x s2 x r)

variance
The pair's portfolio variance. Its square root is the volatility you would quote.
w1, w2
The two weights, as decimals summing to 1.
s1, s2
The two holdings' own volatilities.
r
The correlation between them. It appears once, in the third term, and nowhere else.

Put weights of 0.55 and 0.45 on holdings with volatilities of 31 and 22 percent. The first two terms are 0.55 squared times 0.31 squared = 0.02907025, and 0.45 squared times 0.22 squared = 0.00980100. They sum to 0.03887125 and they do not move for any value of the correlation. Only the third term moves. At a correlation of 0.15 it is 0.00506385, giving a variance of 0.04393510 and a volatility of 20.96 percent. At 0.65 it is 0.02194335, giving 24.66 percent. At minus 0.40 it is negative 0.01350360, giving 15.93 percent.

The boundary case is the one to memorise. At a correlation of exactly 1 the variance is 0.07263025 and the volatility is 26.95 percent, which is also 0.55 times 31 plus 0.45 times 22. A perfectly correlated pair's volatility is the plain weighted average of its parts. Every diversification benefit that exists anywhere is the gap between that weighted average and the actual answer, and the gap exists only because the correlation is below one.

That identity has a direct collateral consequence. A blended advance rate is a weighted average of per-asset advance rates, which is arithmetic that behaves as though every correlation were 1. Track 1 lesson 3 introduced lending value as market value times an advance rate; the blending step is linear, so it cannot represent diversification at all. Whatever credit a schedule gives for holding different things has to come from somewhere else, and lesson 24 shows where.

Key terms

Cross term
The third term in the pair formula, the only one containing the correlation. Its sign is the correlation's sign.
Sub-additivity
The property that a portfolio's volatility is less than the weighted average of its holdings' volatilities. It holds whenever correlation is below 1 and fails exactly at 1.
Weighted average volatility
Each holding's volatility times its weight, added up. It is the volatility a pair would have at perfect correlation, and therefore the ceiling.

Worked example

One pair, five correlations

Weights 0.55 and 0.45. Volatilities 31% and 22%. Only the correlation changes. Illustrative figures.

The two squared terms, at any correlation
0.03887125

0.3025 x 0.0961 plus 0.2025 x 0.0484.

Volatility at r = -0.40
15.93%

Cross term -0.01350360.

Volatility at r = 0
19.72%

Cross term nil.

Volatility at r = 0.15
20.96%

Cross term 0.00506385.

Volatility at r = 0.65
24.66%

Cross term 0.02194335.

Volatility at r = 1.00
26.95%

Equal to 0.55 x 31 + 0.45 x 22.

Eleven points of volatility separate the first and last rows, and the holdings, the weights and the volatilities were identical in every one of them.

Check yourself

Weights of 0.60 and 0.40 on holdings with volatilities of 26% and 18%, correlated 0.35. What is the pair's volatility, and how far is it below the weighted average of the two volatilities?

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Educational only. Nothing in this lesson is investment, legal or tax advice, or a recommendation to enter into any transaction. Figures are illustrative and computed from the inputs stated in the lesson.

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