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Automated Data Analysis

FEBRUARY 25, 2013

Doing research lately I realized I was duplicating a lot of my efforts in terms of gathering and organizing data

for analysis. I decided to invest some time creating databases and macros that could do this for me and

make it easier to do analysis going forward.

I started with commodity futures data from Quandl.com which is a great data website. It also has an API for

calling specific date ranges and data.

First I created a list of the commodities I needed and made a macro in Excel that would download this. The

macro would go through the list of products I needed data for, and request them for the date ranges

specified in cells C1 and D1. It would then save them by symbol name in a folder.

So after running the macro the folder would contain the price data for the commodities requested. In this

case there was a small range downloaded so I have a number of small CSV files.

Next I used VBA in Access to import the CSV data into the

database tables for the related commodities.

As shown below there is now tables for each contract, and

each tables has OHLC data as well as volume and open

interest.

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In order to avoid pulling unnecessary amounts of data back into Excel to analyze I made a union query

which would return the data needed. In this case front and back month corn since 1/1/2013.

Once in excel I used to a pivot table to organize the data which made it easier to graph.

Lastly I created different charts. The following pages are the automated reports I had Excel generate for

corn, soy and wheat.

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RelationshipsbetweenUSDACropProgressReportsandCornYields.

2012

FromApriltoNovembertheUSDepartmentofAgriculturereleasesaweeklyreporttitledCropProgressand

ConditionswhichprovidesinformationonthegrowthcycleandconditionsofmajorgraincropsintheUS.These

reportsareanimportantsourceofinformationforcommoditymarketsandhavethepotentialtocauselargechanges

inprice.

Thereportisacompilationofsurveystakenfromapproximately4,000respondentswhoprovidesubjectiveratings

andcategorizecropsasVeryPoor,Poor,Fair,GoodorExcellent.TheUSDAthenprovidestheaggregatepercentageof

eachcrop,ineachstate,whichfallsintoeachcategory.

Whilebreadthoftheweeklysurveysandthemethodologyprovidesvaluabledata,theUSDAspresentationofthe

datamakesitdifficulttoanalyze.

Forexample,whentryingtocomparetwoweekstherearefivedifferentchangesthathavetobechecked.Inthis

hypotheticalscenariotheamountratedExcellenthasdropped5%,theamountratedPoorhasdropped10%and

theamountratedFairhasincreased15%.

Week1 Week2

Excellent 10% 5%

Good 20% 20%

Fair 30% 45%

Poor 30% 20%

VeryPoor 10% 10%

Althoughthisisvaluabledata,itishandicappedthroughpresentationandreporting,makingitdifficultrunstatistical

analysisortocomparetohistoricaldata.

Eveninthecurrentformvisualrepresentationdoesnotprovidemoreinsight.

InordertocondensetheweeklyreportoffivedifferentcategoriesandcorrespondingpercentagesIhavecreateda

numericalratingscalewithweightedcategoriestocomeupwithanaggregateratingwith1equalingVeryPoorand5

equalingExcellent.

Applyingthistotheprevioushypotheticalexampleweseethattheoverallchangesinthecategoriesleftthe

conditionsunchanged

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Week1 Week2

Excellent 5 10% =0.50 5% =0.25

Good 4 20% =0.80 20% =0.80

Fair 3 30% =0.90 45% =1.35Poor 2 30% =0.60 20% =0.40

VeryPoor 1 10% =0.10 10% =0.10

2.9

2.9

Inthisexample,theaverageratingforWeek1and2was2.9,whichismarginallybelowFair(3).

InordertoanalyzethisdataIranqueriesagainsttheUSDAsAgriculturalMarketingServicesdatabasewhichIthen

importedintoMicrosoftAccess.Cornratingsforeverystategoingbackto1986producedover55,000entriesinthe

database.

Icreatedqueriestopullspecificstatesandyears.IalsoutilizedcalculatedfieldsinAccesstoproducetheaggregate

foreachweekforeachstate.

RatingNumber:IIf([Corn]="Excellent",5,(IIf([Corn]="Good",4,(IIf([Corn]="Fair",3,(IIf([Corn]="Poor",2,(IIf([Corn]="Very

Poor",1)))))))))

Weighted:[RatingNumber]*[Rating]*0.01

Creatingthisaggregateallowsforeasycomparisonsacrossyears.Accessqueriescanbemadeforspecifiedstatesand

yearsandthenlinkedtoExcel.OnceinExcelitseasytoanalyzethedataorchartit.

Belowisanexampleoftheweeklyaggregatefrom2007-2012,with2012bolded.ThisdatawasfromWeek#25which

correspondedtotheJune11th

reportin2012.Althoughthischartshowstheconditionsweremarkedlypoorerthan

previousyears,themarketforSeptembercornfuturesclosedat$5.37onthedayofthereport.Thefollowingweek

futuresbegantheirrallywhichtoppedoutwithSeptembercornhitting$8.43

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TheJuly9th

reportshowedexcessivedeteriorationinIowaquality,withSeptembercornfuturesclosingat$7.31.

Theaggregatechartsmakeiteasytocomparestatesandalsovisualizetheconditionsrelativetopreviousyears.For

example,Indianawasespeciallyhardhitduringthedroughtof2012andthismethodputsitintoperspectivewith

otheryears.

Indroughtyearssuchas2012marketsoftenlookforanalogyearswithsimilarconditionsinordertohavehistorical

referencefortrading.For2012theoftencitedanalogyearswere1988and1993.IcreatedAccessqueriestopulland

comparethisdata.Additionally,Ialsocreatedanotherindexwhichcomparedaveragecropratingsfrombetween

2006-2011forcomparisonwithdroughtyears.

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Anotheradvantageforaggregatingtheratingsisthatitallowsforyearlyaveragesofconditions.Duringthecourseof

theyearfinalyieldestimatesfromtheUSDA,aswellasprivatecompanies,havemajorimpactsonmarketsas

participantsreadjustsupply/demandmodels.Giventhatcropconditionsthroughouttheyeararecloselylinkedtothe

finalofficialyieldIwantedtolookathowwelltheaverageyearlycropratingmatchedwiththefinalreportedyield.

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Icreatedascatterplotfrom2000to2012witheachstatesaverageratingandfinalrealizedyield.

Theseshowabroadcorrelationbetweenaverageyieldandaggregateannualcroprating.Oneinterestingoutlieris

SouthDakotawhoseratingstendtobemoreoptimisticthantheothereightmajorproducingstates.

Thiscanbethenanalyzedbyindividualstatesandlinearregressionlinescanbecreatedtoquantifythetrends.For

Iowa,duringthisperiodthelinearregressionequationisy=0.0129x+1.5717.IftheaveragecropconditionwasFair(3)

forayearthiswouldsuggestafinalendingyieldof110bushelsperacre,whileifitwereGood(4)thiswouldsuggesta

yieldof188bpa.

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Thiscanberunforotherstatesaswell.ForinstanceNebraskaslinearregressionisy=0.0199x+0.6353whichforaan

averageyearlyratingofFair(3)suggestionsa118bpayieldandforGood(4)suggestions169bpsyield.Thisflatter

relationshipimpliesthat,relativetoIowa,Nebraskacornyieldsfluctuatelessasreportedcropconditionschange.

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UsingtheequationforeachstateslinearregressionIcalculatedthedifferencebetweentheimpliedtrendlineyield

andthefinalrealizedyield.Thisshowstheaggregateyearlyaveragetobequiteaccuratewiththelargestpercentage

beinglessthan5bpaawayfromthefinalyield.

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Thisaccuracydatacananalyzedbystate

StateAvgdifference

Max Min Range

NE 0.35 13.89 -10.27 24.16

KS 0.23 14.39 -16.71 31.09

WI 0.1 14.39 -20.32 34.71

MN 0.37 11.42 -23.89 35.32

SD -0.12 17.67 -22.16 39.83

IN -0.34 13.79 -32.65 46.45

OH -0.1 22.46 -26.55 49.01

IA -0.1 27.27 -26.8 54.07

IL 0.01 33.72 -33.89 67.61

Andbyyear

StateAvg

difference Max Min Range

2000 -21.58 -2.33 -33.89 31.56

2001 -9.6 2.13 -19.59 21.72

2002 2.64 17.12 -6.67 23.79

2003 -1 10.66 -10.18 20.84

2004 1.01 8.85 -8.78 17.63

2005 7.77 33.72 -4.37 38.09

2006 0.31 17.63 -7.94 25.57

2007 0.89 15.11 -10.27 25.38

2008 3.96 13.39 -5.2 18.59

2009 7.86 17.67 -5.46 23.14

2010 -7.05 3.87 -23.14 27.01

2011 3.29 15.95 -3.23 19.18

2012 12.09 27.27 2.77 24.5

Oneinterestingtakeawayfromthisdataishowmuch2012exceededexpectations.BetweenJanuaryandthe

beginningofJune2012cornpricestradedbetween$5and$6.Duringmid-JunetoAugustpricesspikedto$8.43on

August10.Sincethen,priceshavefallenwithDecembercornfuturesreachingaSeptember29lowof$7.05.

The2012correlationdatashowsthatthefinalrealizedyieldwas12bpahigherthanthecropconditionsimpliedyield.

Thisisbiggestoutperformanceinthesampleseriesandsuggestedthemarketoverpricedriskearliertheyearbefore

readjustingafterharvest.Alsothataccuracyoftheimpliedyieldcalculationsdecreasesinextremeyearssuchas2012.

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Corn Update 1/29/13

JANUARY 30, 2013

Lately RBOB/Ethanol spread has been widening. However this is mostly due to the strength in the RBOB

market being greater than the strength in the ethanol market, rather than ethanol weakness.

The correlation between ethanol and corn has been weakening, as ethanol prices have been strong relative

to corn prices and thereby increasing margins for ethanol plants.

Given the low carryout number in the January WASDE we need old crop higher to ration demand and prior

to the report the prices werent high enough to do this. With margins increasing the demand reduction is

unlikely to come from ethanol. Its possible that feed usage with decrease, but it remains to be seen if that

will happen.

Technically there can be a case to be made for

the long side in March corn. Its broken through

the descending trendline and has been

consolidating after the last supply and demand

report. Its also above the rising 20, 50 and 200

day moving averages. And 710 has proved to

be an important level that has held as well.

However looking at linear regressions from the

August peak March corn has been selling off

and is now just back at the top of range.

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To grind or not to grind

JANUARY 29, 2013

Recently POET made headlines for idling its Macon, Missouri plant due primarily to a lack of available local

corn. Given that its a large operator and the announcement made many headlines, I felt it deserved a

closer look.

According to Ethanol Producer Magazine, Macon is one of the only plants POET runs that currently doesnt

do corn oil extraction. POET runs 27 plants, has their own corn oil extraction technology, and Macon is one

of the 2 plants that doesnt have this. Extracting co-product value has been especially important since the

tax credits expired, even more so after the drought.

POET is private company so for comparison I looked at the breakdown of operating profits for Green Plains

Renewable Energy on their most recent 10-Q for the impact of corn oil.

In this case GPRE has been losing money on ethanol production for the 9 months ending 9/31/2012 but co-

products like corn oil are becoming an important source of income that can help to offset losses.

Also, basis in northeastern Missouri has traded on the lower end of the range for Missouri according to data

from USDA AMS and doesnt seem high when comparing to other bids for the Midwest.

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Although the closure is attributed to lack of corn supply in the area it seems like adding corn oil extraction to

the plant before new crop could also be a major factor.

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National DDGS Price Comparisons

FEBRUARY 3, 2012

USDA AMS has a page for running custom reports from their data which is useful for DDGS data(http://marketnews.usda.gov/portal/)

Pulling data from around the country I created a national average price and looked at how 100 day moving

averages for different regions traded at premiums or discounts.

Of course Chicago and Iowa are trading at a discount. But I found the variability and seasonality of the

Kansas to be surprising. The Kansas prices usually bottom in the summer and then stay higher in the winter

when there is more feed demand.

With the amount of the DDGS that is still going to China, Kansas seems like a potential shipping point.

There is a large intermodal facility in Kansas City and a few ethanol plants nearby. However no plants in thearea have container-loading capacity and most can easily truck out their capacity. Given the large premium

Kansas is currently trading at it wouldnt make sense unless DDGS was sourced from Iowa, and by then any

comparative advantage would be gone due to transportation cost. Also intermodal shipping costs to China

are very similar if shipping from Kansas City or Chicago.

Taking another look at Chicago and California prices in one of the longer data series. The California

premium has really strengthened since 2008.

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Last thing I found interesting was how closely Western Iowa and Chicago traded. Given how much capacity

in Western Iowa I assumed it would be trading at a larger discount to Chicago. However for most of 2011

they have traded in lockstep. Possibly due to the production in Illinois as well large marketing firms being

able to transport huge quantities out of Western Iowa by rail.

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Chinese DDGS Imports

JANUARY 2, 2012

For a while the Chinese Commerce Ministry has been doing an anti-dumping investigation into US DDGS

exports to China. Recently they announced this investigation would continue until June 28th.

Admittedly China doesnt have a lot of choice when it comes to US export to China that it can limit, but an

investigation into DDGS is an obvious paper tiger. Reuters points out that last week China asked the US to

lift duties on Chinese-made tires so China is likely trying to use DDGS restrictions as leverage. The problem

is China would be hurting themselves more than the US if they imposed restrictions so this is an empty

threat.

1.Chinese ethanol producers requested the investigation but they are marginal players. Their total DDGS

output is 3.5m tonnes. Total US productions for marketing year 09-10 is ~39m tonnes. Total US exports to

China January to August 2011 is 805k tonnes. Chinese ethanol producers are also not going to be

increasing output given that Premier Wen said on October 22 that China needs to strictly control ethanol

production. Domestic demand is higher than their production can satisfy and they arent going to be able to

increase production.

2. Even if Chinese domestic production was enough to satisfy feed mill demand there would still be demand

for US DDGS. Growing conditions in China results higher level of mycotoxins and Chinese DDGS trades at

a discount to US DDGS. Containerized DDGS can be shipped closer to feedmills in southern China reducing

the need for slow and expensive inland transit from the ethanol plants in the north.

3. China doesnt have the luxury of limiting food imports. DDGS can only be used as animal feed so limiting

its import directly leads to meat inflation. If you are fining companies like Unilever for even talking about aprice increase for shampoo, you are not in position to do anything that could lead to actual food inflation.

4. Not exporting to China would hurt the US, but not that much. Even though China is the #2 export market

there werent sizeable exports until 2008. Most US DDGS can be used domestically. Even now 60% more

is being exported to Mexico than to China. Canada is the 3rd biggest market. Canada and Mexico also have

the advantage of being serviced by rail, making it much cheaper than containerized shipments to China.

Its hard to imagine China doing anything substantial given the it would lead to directly to food inflation, there

isnt a viable domestic alternative and the damage to the US ethanol industry would be limited.