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Enregistrement W211566519

A More Palatable Approach to Hedging

2006· article· en· W211566519 sur OpenAlexaboutno aff
Steve Cocheo

Notice bibliographique

RevueABA banking journal · 2006
Typearticle
Langueen
DomaineAgricultural and Biological Sciences
ThématiqueAgricultural risk and resilience
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésHedgeIgnoranceAppealBusinessSession (web analytics)EconomicsFinanceAdvertisingPolitical scienceLaw
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

One of farm bankers' challenges, for years, has been convincing their ag borrowers to get involved in pricing protection through hedging and other mechanisms that can save them from taking it in the neck when markets threaten to turn their season into a loss. This, of course, is not only out of concern for the farmer's neck, but for what the bank has on the line in lending to the farmer. If the farmer has a bad year, chances are the bank will also feel its share of pain. While more farmers than ever explore various hedging options today, many still won't touch them. But a new wrinkle in the market holds the promise of making price protection a great deal more palatable for producers, with advantages-beyond simple protection--to their lenders as well. Making hedging appeal to farmers The reticence of some producers to get involved with hedging isn't simply a matter of ignorance. Not every hedge provides the protection it is cracked up to do. Nor are all hedges created equal, and sometimes producers have been hurt by hedges--consider the hedge-to-arrive mess of the previous decade as an extreme example. There are a few good hedge brokers out there, and there are a whole lot of hedge brokers who aren't so good, said Dennis Everson, president for agri-business, First Dakota National Bank., Yankton, S.D., speaking during a session at last fall's North American Ag Lenders Conference, by the ABA and the Canadian Bankers Association. And hedging doesn't come for flee; consultants and brokers charge for their assistance. An alternative means of fixing a price, forward contracting, creates a specific relationship with a specific buyer prior to production, a commitment that not all producers care to make. Everson's $577.5 million-assets bank has been offering selected customers a special loan package since April 2005 that avoids some of this expense. The bank, one of the nation's largest community-bank farm lenders, is the first to team up with Cargill, Inc., to provide what the bank markets as the Extracense[TM] loan. Cargill has filed for patent protection on the concept. In time, other banks that work with Cargill will be able to adopt their own product names, and additional bank deals are in the works. Cargill first described the concept of Extracense loans at the 2002 ag conference, and has been working it through the practical and regulatory hurdles since. In essence, the idea revolves around a loan with a hedge contract built into it. With Cargill effectively providing the hedge to the bank, however, there is no fee or commission involved. A number of features make this choice particularly attractive to farmers. An example of how the hedge works The concept can work with various crops and livestock types, but for argument's sake, let's use corn, one of the examples demonstrated at the conference by Everson and Jeff Seeley, vice-president, risk management, Cargill. Under an ordinary lending relationship, the borrower would grow corn on 1,000 acres, with an estimated average yield of 150 bushels per acre. To produce this, the farmer would need to borrow $100 per acre at prime plus one percentage point for eight months (all rates mentioned in this article are annualized). Under the new concept, the producer would borrow at prime minus two. That will certainly bring the farmer in the door for a look. Here's the appeal of this concept, in its standard form, for borrowers: * They borrow at three percentage points below the market rate. * If the price of the producer's crop has fallen by an agreed-upon amount--say, corn falls by 25 cents per bushel on the Chicago Board of Trade--then the loan principal will be reduced. In the example of corn, a one percentage point reduction of the principal due at maturity would be made for every penny of price decline beyond 25 cents per bushel. (This is up to a limit of half of principal. …

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,003
score de la tête « metaresearch » (Gemma)0,005
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,057
Score d'incertitude au seuil0,191

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0030,005
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0010,001
Études des sciences et des technologies0,0040,008
Communication savante0,0130,013
Science ouverte0,0020,005
Intégrité de la recherche0,0060,014
Charge utile insuffisante (le modèle a refusé de juger)0,0570,010

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,009
Tête enseignante GPT0,199
Écart entre enseignants0,190 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2006
Routes d'admission1
Résumé présentoui

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