1. Seasonal Variance in Corn Futures
Caleb Seeley
4/16/08

2. Motivation
Does the seasonal nature of corn production have an impact on corn futures prices?
Will jumps in corn prices be impacted by the seasonal production cycle?

5. Motivation
Corn is planted in the spring and harvested in the early October. The crop is stored in October, and used over the course of the next year.
Prior to the harvest of corn, the remaining stocks from the previous year have almost been completely used up.
Will examine corn futures prices at 5 minute intervals over 25 years ( ) to see how this impacts volatility of corn futures prices.

6. Background Mathematics
Realized Variation:
Realized Bi-Power Variation:

7. Background Mathematics Part 2
The relative jump is defined:
RJt = (RVt – BVt) / RVt
In order to studentize the RJt one needs to estimate the integrated quarticity
Jump Test from BN-S (2005)

8. Background Mathematics Part 3
Tri-Power Quarticity
Z-statistic – used .999 significance level (3.09)

9. Realized Semi-Varience
Semi-variance taken from Barndorff-Nielsen, Kinnebrock, Shephard (2008)
Realized semi-variance is the sum of squared negative returns (where 1 is the indicator function that the return is negative) :

11. Results Average RV = .0001002 Average BV = .000151
Annualized RV = 17.03%
Annualized BV = 15.89%
Jump Days: 372 (5.8%)

13. Standard Error:

15. Both monthly and weekly realized variance and bipower-variation exhibit same pattern.
Likely causes of increased volatility may also cause price increases eg: drought, crop disease
Does Semi-Variance suggest this is the case?

16. Monthly RSV

17. Weekly RSV

18. Results
No, SV and Upward-Variance exhibit an identical pattern to RV and BV
Do the patterns in RV and BV impact jumps on a seasonal basis?

20. RV-BV/RV

21. Standard Error:

23. RV-BV/RV

24. Conclusions Distinct pattern in yearly volatility:
As corn stocks dwindle and in preparation for next years harvest corn price volatility rises to a peak in July.
This pattern is observed in both RV and BV suggesting that it is part of the continuous portion of volatility, NOT the jump portion.

25. Seasonal Jumps Winter Jumps: 105 (28.2%) Spring Jumps: 78 (20.97%)
Summer Jumps: 101(27.15%)
Fall Jumps: 88 (23.66%)
Warm Weather Jumps: 193 (51.88%)
Cold Weather Jumps: 179 (48.12%)

26. Jumps By Month Jan: 38 Feb: 32 Mar: 34 Apr: 26 May: 22 June: 29
July: 37
Aug: 34
Sep: 23
Oct: 27
Nov: 29
Dec: 34

27. Conclusions
Jumps are not much more prevalent in the summer than any other season.
Suggests that the volatility rises due to known, predicted events.
Weather catastrophes and low corn stocks are known to occur during summer months.
Thus the continuous volatility increases as the corn stocks dwindle as prices become more susceptible to any shock