Cal Poly uses DecisionTools Suite to Examine Hedging Strategy of Agricultural Producers
California grows nearly half of the fruits, nuts, and vegetables
consumed in the United States – worth $46.4 billion – yet agriculture can be one of the highest risk economic activities.
Many California produce farm operations use an 80/20 rule of thumb as a hedge ratio for seasonal production.
The farms aim to contract 80% of their crop in advance (hoping to meet costs and make a reasonable margin), leaving the remaining 20% to be sold at spot prices in the open market (hoping to attract high prices and high profits).
Of course, spot prices might not be favorable, in which case it is hoped that losses could be absorbed by the forward sales.
Is this rule of thumb a good strategy? Steven Slezak, a Lecturer in the Agribusiness
Department at Cal Poly, and Dr.
Jay Noel, the former Agribusiness Department Chair, used the DecisionTools Suite to evaluate the 80% hedge strategy in use by a lettuce producer.
“The thinking is, when spot market prices are high, the grower can more than make up for any losses that might occur in years when spot prices are low,” says Slezak.
“We wanted to see if this is a reasonable assumption.
We wanted to know if the 80% hedge actually covers costs over the long-term and if there are really profits in the spot market sales.
We wanted to know if the return on the speculation was worth the risk.
We found the answer is ‘No.’”
Growers do not profit from spot market sales over the long run.
The analysis shows growers are better off in the long-term selling as much of their product as possible using forward contracts.
This is important because growers often rely on short-term borrowing to cover operational costs each year.
If free cash flows dry up because of operational losses, growers become credit risks, some cannot service their debt, agricultural lending portfolios suffer losses, and costs rise for everybody in the industry.
Slezak and his colleagues reach out to the agribusiness industry in California and throughout the Pacific Northwest to educate them on the importance of margin management in an
increasingly volatile agricultural environment.
“We’re trying to show the industry it’s better to manage both revenues and costs, rather than emphasizing maximizing revenue,” he says.
“While growers have to give up some of the upside, it turns out the downside is much larger, and there is much more of a chance they’ll be able to stay in business.”
» More details of the hedge case study and analysis
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Coupling Market Research and Financial Analysis
Excerpted from @RISK Bank Credit and Financial Analysis, Chapter 6 by Roy Nersesian, published by Palisade
Market research attempts to gauge market acceptance for a non-existent product.
Market acceptance must ultimately be defined in terms of potential sales volume for a suggested price.
This exercise in judging imponderables is necessary to justify continued management support for the development of a new product.
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In addition, management is interested in a new product’s potential profitability or lack thereof in terms of return on investment and its long-term contribution to a firm’s financial wellbeing.
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PrecisionTree Utility Functions
Q: What are PrecisionTree Utility Functions?
A: Most decision trees are about possible gains and losses in money units like dollars.
They assume that every dollar is as good as every other dollar, that your happiness from gaining $100 and your unhappiness from losing $100 would be equal.
When the amounts involved are small relative to your wealth (or your company's wealth), that's not a bad assumption.
But suppose your net worth is $200,000, including your home equity.
Losing $200,000 would wipe you out and put you on the street, whereas gaining $200,000 would make you somewhat more comfortable.
The negative utility of losing $200,000 is much greater than the positive utility of gaining $200,000.
In this example, it makes sense to be risk averse.
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A utility function translates branch values, such as money amounts, into utility.
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A Generic Rabies Risk Assessment Tool to Support Surveillance
by Ward, Michael P., and Marta Hernández-Jover.
"A generic rabies risk assessment tool to support surveillance." Preventive veterinary medicine 120.1 (2015): 4-11.
Rabies was likely introduced to Indonesia during the 1880s, and within 2–3 decades it spread throughout much of archipelago.
More recently, several islands that had historically been free of rabies have become infected.
The authors used scenario trees in Excel to represent the main pathways of rabies spread.
They employed Monte Carlo stochastic simulation modelling with @RISK 6 to validate the functionality of the model.
An @RISK sensitivity analysis with Monte Carlo simulation was used to identify the most influential input values and as such, priority areas for surveillance.
Read the paper here
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