AREC 412 Lec H – Motivation 1

Motivation for Fundamental and Technical Analysis What tools can we use to help us decide when to enter and when to exit a hedge? (Or, or for that matter, when to enter and exit any trade.) So, how do we know when to “pull the trigger” and make the decision at the top of the T-account? Evaluated forward price, often calculated costs, expected rates of return, rated risk and calculated probabilities of certain outcomes. But, while these steps support the decision, we need more tools to make the pricing decision. We need to expand on the decision-making process. We need a systematic way to make trading decisions. We need objective tools that say act: “Buy now” or “Sell now.” Fundamental Analysis: Price determination techniques used to establish the likely magnitude of future price movements and reasonable price-level objectives. Technical Analysis: Techniques used to understand patterns in the price discovery process. These patterns can be used to identify buy and sell signals. This is what commercial traders (large hedgers) and successful speculators do.

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Example) DEC 2021 Corn:

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Example) DEC 2021 Live Cattle:

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Example) NOV 2021 Feeder Cattle:

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Example) JUL 2022 KC Wheat:

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The process of the trading-public doing this work, this “analysis,” contributes to price discovery. It is the discovery and synthesis of existing supply and demand information into price. Correct trades are rewarded and incorrect are not... Informed traders make money at the expense of uninformed traders. Are we going to be able to trade and make greater than risk-adjusted profits? Not in the long term. That’s not what the purpose is. But we want to be informed and make good pricing decisions – as opposed to being reactionary and/or following emotions. The purpose is that these tools are better than what we would use without them. That is an important point: if you don’t do fundamental and technical analysis then what will determine, drive, or impact your trading?

AREC 412 Lec H – Fundamental Analysis: Nonstorables 11

Fundamental Analysis: Livestock (Nonstorable Commodities) The industry in question faces a demand curve which originates at the consumer level and is passed down to the farm-level through marketing firms. At any point in time, there is a fixed quantity supplied and future supplies are predetermined. We need to forecast the changes in supply and then forecast the changes in demand. The quantity supplied will be consumed. The quantity supplied equals the quantity demanded so that prices adjust to clear the market.

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Example) Assume it is 9/24/2021. We want to forecast the live cattle futures price for December 2021. Supplies will increase/decrease in 12/2021 compared to 12/2020? Live cattle futures price for DEC 2020 settled approximately @ $112.00/cwt. Currently, DEC 2021 @ $128.00 – Buy it or Sell it?

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$112.00

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Making use of predetermined supply numbers: Ex) Fed cattle – monthly Cattle on Feed reports On Feed(t) - Marketings(t) + Placements(t) - Other Dis(t) = On Feed(t+1) Think “stocks” and “flows.” Ex) Hogs – quarterly Hogs & Pigs reports Farrowing Intentions, Farrowings, Market Hogs @ Weights, and Market Hogs. All information is a point in time of “stocks.” Ex) Crops Planting Intentions, Acreage Planted, Crop Conditions, Crop Conditions, … Crop Yield Estimates, Crop Yields, and Acreage Harvested.

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Forecasting using elasticities. Steps 1) Estimate future supplies (%ΔS). 2) Estimate future shifts in demand (%ΔD). 3) Compare changes to base year within the same season and forecast price. 4) Qualitatively evaluate the forecast. From where do we get elasticities?

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Forecasting using elasticities. Steps 1) Estimate future supplies (%ΔS). 2) Estimate future shifts in demand (%ΔD). 3) Compare changes to base year within the same season and forecast price. 4) Qualitatively evaluate the forecast. From where do we get elasticities? 1) University research reports (Land Grant – Library) 2) USDA research reports (Economic Research Service) 3) Collect data and estimate

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ex) Farm-level beef cattle elasticities εbb = %ΔQb / %ΔPb = -0.85 εbp = %ΔQb / %ΔPp = +0.20 εbc = %ΔQb / %ΔPc = +0.10 εbI = %ΔQb / %ΔI = +0.55 From: Wohlgenant and Haidacher. Retail to Farm Linkage for a Complete Demand System of Food Commodities. USDA Economic Research Service Technical Bulletin Number 1775. December 1989. (You can find this research on the web.) These estimates describe consumer demand. Please be able to explain each: 1% and 10% changes.

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ex) Forecast DEC Live Cattle futures price Out Wt In Wt Gain @ Days on Feed 1300 850 450 3 150

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

31 28 31 30 31 30 31 31 30 31 30 31 The information we have with cattle are placements into feedlots. So, we are forecasting future marketings with placements. But there is also the need for more information than animal numbers – animal weights are also needed because numbers multiplied by weights are total production and it is pounds of beef that consumers purchase. (Now, you need to do something similar using the different information in the Hogs & Pigs report…)

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Ex) Problem Set 3 Hogs & Pigs Report released end of June and numbers as of 6/1 farrowed on 6/1 (# days?) 50# on 6/1 (# days?) 120# 180# 295#

Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May

30 31 31 30 31 30 31 31 28 31 30 31 So, if I was interested in the weight group that would be marketed during September then I would look at the 120-179 group…

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Supply information as of 9/1/2021, available 9/24/2021 Cattle placements from monthly 7-state Cattle on Feed report (9/24)

1000 Head

Month 2020 2021 21/20

May June July August

2,052 1,798 1,893 2,057

1,911 1,670 1,739 2,104

93.1 92.9 91.9 102.3

Steer carcass weights from monthly Livestock Slaughter report (9/23)

Month 2020 2021 Change

August 837 822 -1.8% We will make the assumption that the percentage increase/decrease in placements will materialize as the percent change marketings 150 days later. We will also make the assumption that the current increase/decrease in slaughter weights will persist.

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We need to generalize... Can you construct a better method to forecast future fed cattle numbers? ... and fed cattle slaughter weights? But what if you want to forecast supplies further than five months into the future?

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Total %ΔS = %Δ Numbers + %Δ Weight -8.1% + (-1.8%) = -9.9% Forecast DEC price based on supply information. εbb = -0.85 = %ΔQb / %ΔPb = (-9.9%) / %ΔPb -0.85 = (-9.9%) / %ΔPb %ΔPb = (-9.9%) / -0.85 = +11.6% $112.00 (1 + 0.116) = $125.04/cwt. ($2020) $125.04 (1.025) = $128.17/cwt. ($2021)

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DEC Live Cattle Price Forecast

P

$125.04

$112.00

Q Using only changes in supply. Careful, constant dollars on S&D graphs…

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The Demand Side... See the handout. Inflation rates and deflating example: Inflation rate = (CPI new)/(CPI old) = 273.0/259.5 = 1.052 (+5.2%) Deflate example: (Price new)/(Price old) = (CPI new)/(CPI old) (But!?) $97.56 (1.025) = $100.00 – inflate example $100 / (1.025) = $97.56 – deflate example

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DEC Live Cattle Price Forecast

P

$129.26

$125.04

$112.00

Q Using changes in supply and demand.

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Evaluating Price Forecasts (or why your price forecasts will be wrong) ● Supply flexibility or inaccurate supply projections. ● Inaccurate demand shift projections. ● Changes in retail or wholesale to farm margins. ● Changes in international trade. ● Changes in tastes and preferences (gradual or sharp). ● Inaccurate inflation projections. ● Changes in government programs. ● Survey errors – Rounding errors.

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International trade is a big uncertainty and hard to forecast… Need to ask what-if questions. What if fed cattle imports doubled? What if halved? What if beef imports doubled? Halved? What if beef exports doubled, halved, or were reduced to zero?

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The above are big picture impacts. What about this year compared to last? 2020 actual 2021 forecast

Beef Production (million pounds) 2327.4 -9.9% – 2097

Beef Imports (million pounds) 209.4 0% – 210

Beef Exports 285.0 335

Net Imports -75.7 -125

Net as % of Production -3.3% -6.0% so another -2.7% What are imports this year compared to last? What are exports this year compared to last? A negative Net Import is a Net Export. Net Imports/Exports essentially shift the supply curve. Production is removed from or added to the domestic market.

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Forecasting using derived demand. Steps 1) Forecast output price at the end of production 2) Estimate production costs (+ normal profits) during production 3) Forecast input price at the beginning of production 4) Evaluation forecast

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MAR Feeder Cattle Price Forecast

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MAR Feeder Cattle Price Forecast

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You also need to see the big picture... Forecasting with elasticities can be conducted at any level in the system – retail, wholesale, or farm. Once you have that level then levels below in the marketing system can be forecasted with derived demand. For example, we forecasted fed cattle and then used derived demand for feeder cattle. We could forecast boxed beef and then use derived demand for fed, feeder cattle, and calves…

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