We have recently finished our review of last year’s data and updated the seasonality and relative store prices for all of the stock classes we monitor. In terms of beef, our prime beef seasonality follows the pattern outlined in Table 1.
This is expressed as a percentage of our whole season average – for example, if our whole season average was $4.50/kg then we would expect our April price to be 94% of this, or $ 4.23/kg, and our peak September price to be 8% higher than the year average, so $4.86/kg.
This seasonality of pricing is relatively consistent although in recent years the relative price of mid-to-late spring has reduced and late winter increased. The hope is this reflects market demands.
Within the database we put a greater weighting on the most recent five years. We still use the older data but scale back the weighting on it.
When using the Farmax model you can simply enter your expected year-average schedule price and the model will outline expected prices each month. From this you can then quite quickly do a scenario test on whether you sell cattle earlier or later, and therefore the effect on the whole farm profitability.
Once these prime prices are established then we can look at the store prices as a ratio of the prime price. In Farmax jargon we call this the relativity. Taking R1 cattle for example, the store liveweight price for weaner steers have historically averaged 65% of the April prime steer schedule.
As an example, using our April schedule price of $4.23/kg we would expect medium weight weaner steers to have an average store price of $2.75/kg ($4.23 x 0.65). The buyer would need to add on freight to calculate a landed home price, and the seller to deduct selling costs such as yard fees and commissions. From early indications for this particular year the current market is offering store cattle at a lower relativity than the long run average.
It is important to note that the range in the store-to-prime relativity over the last 13 years has been from as low as 52% to as high as 75%. For the mathematicians reading this the coefficient of variation is quite high at 11%.
In other words it is quite variable and the current prime beef price is only one of the things that influences demand for store cattle. The farmer expectation for future beef prices, impact of feed supply, and competition from other enterprises also influences how farmers will pitch their prices for store stock.
The average relativity or predicted store price is very useful for doing long-term scenario testing on buying and selling strategies, and calculating what is likely to be the most profitable option for a farm over time.
However, for more tactical analysis of a particular year we can use these longer term relativities to give us some feedback on interpreting the current market. The canny traders have often recognised the subtleties surrounding store stock pricing and have been quick on their feet and able to make good use of the opportunities available. Technology and models won’t replace the need to make a gut feel decision on the risks and opportunities but can provide objective data to help support decisions.
For Farmax users accessing the Farmax bureau each month and getting the AgFirst price file, they will have the ability to quickly see whether current market values are above or below normal price relatively based on current schedule and the long-term relative average.
We say to our clients that if prices are above the long-term average then they just need to recognise that there is some heat in the market. It could still well be worth continuing to purchase at that level, but they need to think about why the prices are above what they normally would be.
The counterargument, of course, is when prices are significantly discounted. Then we need to consider whether there are ways of capitalising on that by possibly using some stored feed, dropping other less profitable stock, or looking at strategic inputs like nitrogen fertiliser to see if they are an economic opportunity to use a market when there is good buying available. For the breeder or store stock seller the same opportunity to do the calculations exists; they just wear the opposite hat.
I had a good example of this working in practice last year where a client was moving into a new enterprise of buying R1 cattle to be wintered on fodder beet and then sold in spring. With the widespread drought last autumn there was significant feed pressure on many farms and so this reflected on store stock prices. Weaner steers were at only 56% of the schedule last April.
This Farmax farmer was in a position to rapidly identify where the buying opportunities were, and be proactive about buying a significant number and feeding them well on the feed investment that had been developed. The end result was that we generated a gross margin of over $0.40c/kg of drymatter eaten from a combination of a good buying opportunity, feeding them well, and then selling them when the actual price was higher than the Farmax long term indicator. That kind of gross margin is probably very similar to the gross margin that a dairy business is earning after it deducts its variable costs relative to the $8.65 milk price.
Reserved decision
Another example of using the indicator price to help support longer-term decision making is where AgFirst analysed the payback from using stored supplementary feeds for a particular business.
Based on their cost of feed we decided that if the purchase prices were discounted by more than 20% then it would be worthwhile us opening up our feed reserves. By our sums this happens about one-year-in-five and so in this particular case we encouraged this client to hold on to their supplements so that they can use them in the most valuable years and keep their cost structures down in years where purchase costs were average or above.
So being in tune with where a market price sits relative to longer-term averages can be a powerful piece of information in farm decision making.
The AgFirst database covers monthly relativities for steers, heifers, cull cows, and bulls from weaners through to R3. Sheep and deer are also covered.
As you would expect we need to add the disclaimer that markets are not static things and history does not always repeat itself. If we had a crystal ball it certainly would be easy.
We believe that these support tools can help farmers weigh up the pros and cons in any decision making process. Ultimately they have to be comfortable with their decisions – any market risks taken need to be in the context of a farm business plan and financial resources.
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Phil Tither
