Champagne as Market Indicator, from Bruno Ombreux
This is an occasion to repost my 2006 wine study:
I looked at the following time series:
- Champagne and Sparkling wines, a French CPI component from INSEE.
- 11° red wine, another French CPI component from INSEE.
- CAC40 index
In addition, I defined a "Feelgood index", which is the difference between champagne and red wine log-returns. The rationale is that when people are feeling good, they drink champagne rather than your average Joe's supermarket 11° red wine.
The CAC40 choice could be discussed. France is accounting for only 25% of champagne sales, the rest being exported. However, due to the correlations between world stock indices, this choice is not critical.
Data is monthly from 1998 to 2005 included.
The conclusion is that there is no correlation between champagne, red wine, feelgood and the CAC40 returns, either contemporaneous or lagged one month. Wine is a proper vehicle for diversification.
A second study, with different prices, those from the Association of Champagne Dealers, looking at yearly returns from 1990, also concludes that there is no correlation. Since there are only 16 yearly data points, the 95% confidence interval is huge:
-0.54 < correlation < +0.50 Then this second study can be ignored. However, it doesn't contradict the first one.
Champagne returned 22% over the period and 11° red wine 31%. These are poor returns, far below the stock market, even before storage costs. However, annualised volatilty of returns is very low: 1.3% for champagne et 1.9% for red wine.
Nota Bene:
1) This is not a study about returns from investing in top wines like Margaux or Haut Brion. This is a study of run-of-the-mill champagnes and red wines, who shouldn't commend any age, scarcity or snob-appeal premium.
2) It is neither a study about generating alpha from wine-picking. We are only looking at broad wine indices from INSEE.
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Results for contemporaneous series
(lagged series give similar results)
*CAC40 vs Champagne*
Residuals:
Min 1Q Median 3Q Max
-0.0107351 -0.0021576 -0.0002676 0.0019569 0.0105993
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.0020951 0.0003879 5.402 5.05e-07 ***
cac 0.0010887 0.0064082 0.170 0.865
—
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.003771 on 93 degrees of freedom
Multiple R-Squared: 0.0003103, Adjusted R-squared: -0.01044
F-statistic: 0.02886 on 1 and 93 DF, p-value: 0.8655
*CAC40 vs red*
Min 1Q Median 3Q Max
-0.025410 -0.001498 -0.001408 -0.001034 0.014695
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.0014074 0.0005554 2.534 0.0129 *
cac 0.0022486 0.0091757 0.245 0.8069
—
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.0054 on 93 degrees of freedom
Multiple R-Squared: 0.0006454, Adjusted R-squared: -0.0101
F-statistic: 0.06006 on 1 and 93 DF, p-value: 0.807
*CAC40 vs Feelgood Index*
Residuals:
Min 1Q Median 3Q Max
-0.0141041 -0.0032415 0.0001090 0.0033706 0.0277683
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.0006878 0.0006367 1.08 0.283
cac -0.0011599 0.0105198 -0.11 0.912
Residual standard error: 0.006191 on 93 degrees of freedom
Multiple R-Squared: 0.0001307, Adjusted R-squared: -0.01062
F-statistic: 0.01216 on 1 and 93 DF, p-value: 0.9124