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Stochastic Volatility and Seasonality in ... - Interconti, Limited

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a seasonality feature the long-run level for the convenience yield process would thus be 0.0751<br />

(= α 0 /β); we <strong>in</strong>terpret this as the “normal” level of the convenience yield when adjusted for<br />

seasonality.<br />

The seasonal pattern of the mean-revert<strong>in</strong>g level of the convenience yield is also illustrated<br />

<strong>in</strong> Figure 3. The seasonal variation <strong>in</strong> α(t) is very similar to the seasonal variation <strong>in</strong> ν(t),<br />

though amplitudes are different. However, it is much more clear that α(t) has two local maxima<br />

<strong>and</strong> two local m<strong>in</strong>ima. 16 Aga<strong>in</strong>, the global maximum is achieved <strong>in</strong> July about two months<br />

prior to the beg<strong>in</strong>n<strong>in</strong>g of the US harvest<strong>in</strong>g while the global m<strong>in</strong>imum is achieved <strong>and</strong> the end<br />

of the US harvest<strong>in</strong>g. While the US soybean production accounts for 50-60% of world soybean<br />

production other key producers are Argent<strong>in</strong>a <strong>and</strong>, especially, Brazil which are both located<br />

<strong>in</strong> the Southern Hemisphere. These countries account together for 20-30% of world soybean<br />

production. The Brazilian soybean harvest<strong>in</strong>g takes place <strong>in</strong> March <strong>and</strong> April <strong>and</strong> the local<br />

maximum <strong>in</strong> Figure 3 is reached about two months earlier, while the local m<strong>in</strong>imum is reached<br />

dur<strong>in</strong>g the end<strong>in</strong>g of the Brazilian soybean harvest<strong>in</strong>g. The seasonal pattern <strong>in</strong> convenience<br />

yields is thus related to the supply of soybeans. When supplies are low convenience yields are<br />

high, <strong>and</strong> vice versa. This is consistent with the theory of storage which predicts a negative<br />

relationship between <strong>in</strong>ventories <strong>and</strong> convenience yields. The basic idea is that the hold<strong>in</strong>g of<br />

physical <strong>in</strong>ventory of soybeans gives rise to a convenience yield from be<strong>in</strong>g able to profit from<br />

temporary soybean supply shortages or keep a production process runn<strong>in</strong>g especially when<br />

<strong>in</strong>ventories are low. Furthermore, the parameter estimates suggest that the soybean spot price<br />

<strong>and</strong> the convenience yield are positively correlated with a correlation coefficient of 0.3979.<br />

Follow<strong>in</strong>g the above k<strong>in</strong>d of reason<strong>in</strong>g, this is also consistent with the observation that when<br />

supplies <strong>and</strong> <strong>in</strong>ventories are scarce the equilibrium soybean spot price <strong>and</strong> the convenience<br />

yield are simultaneously high; <strong>and</strong> vice versa when supplies <strong>and</strong> <strong>in</strong>ventories are plenty.<br />

On the other h<strong>and</strong>, supporters of the theory of storage often view the convenience yield as<br />

an option to profit from temporary shortages of the particular commodity. This would suggest<br />

a positive correlation between the convenience yield <strong>and</strong> the volatility; however, this view is<br />

not supported by the parameter estimate of ρ 23 which is not significantly different from zero<br />

<strong>and</strong> even estimated negative.<br />

16 The global maximum of the seasonal function α(t) is reached on July 15 where the function value is 0.746,<br />

while the global m<strong>in</strong>imum is reached on October 30 where the function value is -0.723. A local maximum is<br />

reached on February 7, <strong>and</strong> a local m<strong>in</strong>imum is reached on April 16.<br />

20

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