How do some farmers get a higher average revenue per acre than others? The most obvious answer is that some farmers have soil and weather conditions which naturally and consistently produce more bushels per acre. Some are located geographically where the average basis is consistently higher than others. Some have learned to take better advantage of the market pricing than others. The decision over which you have the most direct control within a geographical, weather, and soil type area is choosing when to lock in available prices.

Not everyone has an APH of 200 bushels for corn and a positive 50 cent basis per bushel, so there are an infinite number of combinations that can be generated when evaluating marketing potential and performance. If we use an APH of 200 and zero basis, everyone can (and should) compare their results to a standard baseline to really understand how well their marketing plan is performing.

Let’s start by taking a look at what was available for complete marketing period for the 2018-22 crops. The average high for the December contract was $5.47/bu or $1094/ac and the average low was $3.48/bu or $696/a, producing an average range of $1.99/bu or $398/ac that was at your discretion. The average “do nothing” contract expiration price was $4.84/bu, or $968/ac, 68% of the ranges that were available. If you decided not to take any pricing action with the December contract, you would leave $126/ac in the field. Many of you have been told this is the safe decision and you can make it up with basis improvement and carry above your storage costs.

For those who do not use December contracts for pricing, the average high for the July contract was $6.55/bu or $1310/ac and the average low was $3.52/bu or $704/ac, producing a range of $3.03/bu or $606/ac per acre that was at your discretion. The average “do nothing” contract expiration price was $5.52/bu or $1104/ac, 66% of the ranges that were available. If you decided not to take any pricing action with the July contract, you could have increased your gross revenue by $136/ac but left another $606/ac in the bin.

Using both December and July contracts to assist with the pricing, the December contract could have been priced at the average high and lifted at the average low for a hedging gain of $1.99/bu. Likewise, the July contract could have been priced at the average high and lifted at the average low for a hedging gain of $3.03/bu. Combined, the hedging gain of $5.02 could have delivered an average effective price of $10.54/bu or $2108/ac. Of course, I know it is not realistic to believe someone has a system that could have picked 10 tops and 10 bottoms correctly succession. But don’t kid yourself, if the “do nothing” plans generated an average price in the top one-third of the price range (68% and 66% respectively), then $7.50/bu or $1500/ac was available by only capturing 40% of the trading range that was available. Conservatively, that is $500/ac return above COP (including land and actual labor charges).

Is $500/ac return over COP (including land and actual labor charges) within reach for 2024 corn with APH 200 and basis zero using your current marketing plan?

Posted by Keith D. Rogers on 5 May 2024

The charts I am talking about are pure and simply the printed record of daily trades. Because I think moving averages are easy to understand, have certain mathematical characteristics that make them easy to work with and mine information, and because several posts have recently been about MA indicators, I will try to address the good, bad, and ugly as unbiased as I can.

The first glance at the charts clearly indicates that we have a short term bottom in corn, beans, and wheat. The question is how short is short or how much higher will the market go? To keep the discussion focused, I am going to use CN24 as an example. I have three MAs (5, 17, & 35) added to my data chart.
The reason that this is a great learning opportunity is because it is decision time – time to lift or offset hedges if the market is going to rally, or put protection in place if the market is going lower. Getting that call right is the single most cost effective decision any farmer can make. And it is the decision that every farmer can make in a few seconds. Through last Friday, it was absolutely clear that the long term trend was down. How can you reach that conclusion? When the price is less than MA5, MA5 is below MA17, and MA17 is below MA35, that is the condition the defines a sustained downward trend. To have a sustained rally, Price will have to get above MA5, MA5 above MA17, and MA17 above MA35. Just look at other areas of charts and look closely at the relative position of those variables while a rally was on or when the rally turned down. By logical deduction, the price and averages have to converge on each other at both the top and bottom of sustained market moves. Repeat, the condition of a sustained rally did not exist last Friday. This process repeats itself regardless of the price or time because it is a mathematical identity and not some made up marketing opinion.

Since Friday, prices have climbed above MA5, and that will happen with every internal short term correction and every major trend change. So, which is this? You can draw your own conclusions but here are some statistics to consider. For the last 300 days of the last ten CN charts, Price has crossed MA5 742 times (74 times a year), which resulted in 246 winning transactions, and 496 losing transactions. Seven of the years ended with transaction losses, and three with transaction gains, and an average loss over the 10 years of about $0.38 per bushel. Now the truly ugly, one year ended with a loss of $1.75/bu. and another $1.45/bu. Using price crossing MA35 as an entry and exit, there were 123 transactions in 10 years, 35 winners, and 88 losers. The average annual transaction gain was $0.41/bu. with four of the 10 years failing to produce a positive gain.

What other secrets is the chart hiding? On Friday, it was possible to calculate the price would have to close above 468.25 to turn MA5 up Monday, and above 498 to turn MA17 up, and above 504 to turn up MA35. As long as MA17 and MA35 are diverging, no sustained rally has been confirmed. Drop down to the hourly chart, and have a look at a sustained rally, but beware the hourly chart usually does not make

Posted by Keith D. Rogers on 24 January 2024

Chapter 9 Graphics

With Dec 2023 contracts expiring, it was time to move the models I look at daily to a new file and add 2025 contracts to the data set so they can be pulled up at will to look at specific market behavior in any of the last 15-20 years. All indicators need to be retested to verify that the move and additions were successful. Jumping forward in time, the BBQ fixings are now in the frig marinating and the computer is at 942 of 1,000 assigned task and will soon be preparing a report of every time each of those 1,000 conditions were met to trigger a signal in last 10 years, and what was the result of that decision.

Tomorrow, I am going to do a dry run on the BBQ with Judy to see if we like the new recipe I am trying, and we will be assessing if we think that is the one I should use when we host a dinner next week. Some of you will say “what the hell” and that is fine. If you said that directly to me, I would ask if it is any different to transfer the concepts of trusting previous taste tests of Korean BBQ to guide the dinner we will prepare, or trusting the previous seed or fertilizer trials to guide your next years’ production plans, or sorting out best strategies for market performance to guide your marketing plans for next year. You do some versions of the first two all the time, but I was told several times in the last few weeks that farmers don’t have time to look at marketing performance. Really?

The computer just reported in. The computer identified a strategy that made no losing trades in the last nine years (2,700 days), and has not done so on the first 48 days of the 2024 contract. Don’t rush to ask. None of the 1,000 strategies I suggested did better than a “do nothing and wait” strategy, so what I learned is that none of those 1,000 strategies for that particular indicator are acceptable to me even though some made some very good decisions based on a casual observations. I hope the BBQ tomorrow has a much better outcome, so I don’t have to search for better alternatives. And, for the market trigger, I will study the charts to see if I can see what needs to be fixed, and then run a test again. I think that is close to what you would do if the “snake oil” you tried did not produce results. Just a few observations from the lighter side.

Posted by Keith D Rogers on 16 December 2023.

To correct the errors, let me summarize how easy it is to switch from untested fundamental projections to probability based technical indicator strategies.  First, there are many technical indicators, but one of the easiest to understand and work with is moving averages.  While there are many to choose from, let’s settle on one pair, the 5-day (MA5) and 35-day (MA35) crossover.  If you want to sketch this out on paper, create three columns for the closing contract price, and the two moving average calculations.  That is the only input you need to get started – contract closing price, 5-day average, and 35-day average.

Next we need a specific goal and decision rule.  I suggest the goal be to maximize the revenue over multiple time periods by protecting price when the price trend turns down and lifting or offsetting the hedge when the price trend turns up.  There are more details in the corn, soybean, and wheat articles on the SelectiveHedging.com website, but a down trend is defined by MA5<MA35 and an up trend is defined by MA5>MA35.  Obviously, that simplifies the search for a trend change signal to when MA5 crosses down through MA35 or when MA5 crosses up through MA35.  Add two more conditions and the basic decision rule is complete. MA5 must be less than MA35, and MA35 must be down to go short, or up to go long.

If you are using the three column paper version, record the contract closing price, calculate the two moving averages, search for where MA5 and MA35 are both down and both lower than yesterday.  Confirm that MA5 is less than MA35 and you have the trigger for a trend change from up to down.  If you prefer a spreadsheet, it will do the MA calculations automatically so you can go directly to determine if all the conditions of the decision rule are met.  If you prefer using charts, the price will already be entered, and the MAs will be calculated.  Check directly for the crossing and confirm if the other rules are met.  That is all that is needed to trigger an action signal. The articles on the website go on to describe how to record the hedging gain or loss at each signal, and to accumulate the total for the year, but that information is not needed to trigger a signal.

I have been asked many times to show graphic solutions of the decisions.  The easiest way is to look at a chart at the point specific signals were triggered and verify that the conditions of the decision rule were met.  Here are specific examples from each of the last five years to check out when sell signals were triggered for the 5/35 indicator:  WZ20 2/11/20, WZ21 11/15/20, WZ22 12/15/21, WZ23 11/25/22, and WZ24 11/27/23.  What condition or conditions existed the day all five of these signals triggered? What will the conditions be when the next short signal triggers?

Posted by Keith D. Rogers on 14 December 2023

Indeed, all of those players have some effect on the market prices.  Speculators and fund managers are in the market to “buy low and sell high,” or vice versa, and make a profit.  They do not care whether the price is high or low, so you do not need to look farther for their motives.  The government, through USDA, has responsibility for many functions in agriculture, but monthly reporting of U.S. and world Supply and Demand estimates is the one most farmers focus on throughout the year.  USDA’s responsibility is to present the most accurate estimates possible for the end of marketing year balance sheet using multiple sources, technology, and statistical estimates.  The fact that the USDA estimates do not match those of farmer “experts” does not prove either bias or intent to manipulate the markets.  It could be they are just doing their job as laid out in standard procedures  developed over many years.  In the end, the markets decide which numbers are most accurate, and all farmers are free to use them or not.

If you want to believe volatility and low prices are about conspiracy and manipulation, I can’t help you.  What I can do is share some of the economic and statistical logic that explains a major portion of the volatility.  Think about the S&D framework.  We still don’t have an acceptable consensus number for the 2023 crop production, and we apparently don’t have demand functions for either domestic use or exports.  It is not necessary to look any farther for an explanation for volatility.  It is not a mystery or manipulation; it is the markets adjusting to new and conflicting information on a daily and weekly basis until we do have firm estimates for carryout.

Let’s take a good look at the WASDE reports and isolate potential sources of errors.  There are 14 or 15 lines in the reports, and they are all best “statistical” estimates at a point in time for a balance sheet at the end of the marketing year.  NOT ONE LINE is known for certain, even when the reports say “final.”  What does that mean?

Let’s back up further.  The reports have two basic goals – - to estimate Ending Stocks (ES) which will be left at the end of the marketing year, and the price equilibrium value that will be established by the markets.  ES is normally determined by simply subtracting Use from Total Supply.  Therefore, if there is an error in any of the lines used to calculate Supply or Use, the errors feed into the ES estimate.  The conclusion is straight forward that the ES number is likely the least accurate line in the report because it has the most cumulative errors.  No manipulation here; just how the numbers are generated.

Next, how are the price estimates generated?  Traditionally, market analysts take a short cut and calculate Stock:Use ratios to project price change expectations because there is an economical logic.  The accuracy of this short cut depends on the accuracy of the Supply and Use estimates and many assumptions about variables which are buried out of sight in the estimates of the 10 or 11 lines going into the calculation.  By default, price appears to become a projection of previous price patterns and NOT an equilibrium calculation for Supply and Use.

If so, it appears to be glaring violations of basic economics principles.  Price discovery equilibrium can be written in a simplified version as a series of three equations.  S=f(P,x,y,z), D=f(P,a,b,c),  and S=D where the quantity supplied is a function of  Price and other factors, quantity demanded is function of Price and other factors, and Supply equals Demand at a specific price.  Graphically, the equilibrium at a specific price looks like this sample.

In reality, the first short cut is taken when Planted Acres, Harvested Acres, Yield, Beginning Stocks, and Imports appear to be projections of previous trends that are only loosely related to price, or not related at all.  In short the supply estimate becomes a quantity number and not a function of price so that the actual representation of a Supply Curve is often a vertical or near vertical line, on the graph.

The potential price estimate errors begin to compound.  Supply includes Beginning Stocks (BS) and later Use will include ES.  Stop and ask yourself why anyone was holding any stocks at the end of last marketing year and why will there be ES at the end of this marketing year.  There are many reasons farmers hold stocks during or at the end of the marketing year, but it usually is because they believe the price will rally.  By definition, that makes BS and ES both a function of price.  By calculating stocks as a residual (subtraction) in the report, it is implied that they are not a function of price.  By default, that calculation alone can introduce an error in the area of 5-10% of Supply even if the calculation has a very small confidence interval.  Simply said, if equilibrium price  is not used to determine the Supply components, then a second major source of volatility is introduced.

The most glaring error shows up on the Demand side.  Specifically, everyone who has had Econ 101 knows how significant the demand curve is in determining price equilibrium.  I am going to step on some toes, but to the best of my knowledge, no one has ever seen a demand curve for corn or soybeans!  If that is true, every line in the Use section is a projection of some trend and not a function of price or price equilibrium at all.  The potential error is huge.

I can’t say if the folks who produce the price estimates for USDA do or don’t use an equilibrium model or even have basic demand curves, but I can point to some things that suggest we don’t know what the soybean demand curves look like.  Back to basics.  If the price is determined by an S&D equilibrium model, and Supply is assumed to be a function of price, then it follows that every price reported in the WASDE reports is the intersection of the Supply with the implied demand curve.  Domestic demand curves are very stable over time with a bias to shift right as the number of consumers increase over time.  Thus, it should be very easy to construct a proxy demand curve from the WASDE reports.  In theory, the reported price points are the intersection of the Demand function which is price sensitive with the Supply function that is not price sensitive so the monthly price points should all be along a single function that traces out the demand curve.  We know the demand curve is not linear so that it flattens out at low prices and high quantity and turns up sharply at high prices and low quantities.  Regardless of the precise functional relationship with price, we know that demand theory says the demand function should be downward sloping from the upper left corner of S&D chart to the lower right corner.

Look carefully at the chart for the 2022 soybean crop with the USDA prices graphically presented from the preliminary estimate in April 2022 through August 2023.  The chart violates two major economic assumptions.  It does not conform to a systematic functional form  and the regression is upward sloping rather than downward.

This is not meant to say that USDA is using inappropriate price estimation methodology.  It is meant to point out a major source of volatility if the true demand estimates are not consistent.  The only line in the Use section that is normally subject to major demand changes is Exports.  The demand function for exports is a composite of the demand curves for all countries using soybeans.  The quantity demanded for U.S. exports slides up and down the U.S. demand curve as well as the demand curve of each country all the time just like quantity of soybeans used domestically, but there is a whole new set of factors that can shift the entire demand curve for exports over very short periods.  Once domestic Supply and Use have been determined, the major source of volatility is a shift in export demand and the direct impact on ES and Price.

Volatility is about the unknown and rumors about the unknown future.  Regretfully, farmers will never have all the information about the future between harvest and the time they have to convert the crops to cash flow.  Being integrally involved in world markets as our grain markets are, means marketing decisions will always have to be made within a context of even less stability than our own domestic markets.

Posted by Keith D. Rogers on 16 September 2023

Today, many folks want to deal in soundbites, which leads to partial information that is only a little better than misinformation – actually, it often is misinformation when taken out of context.  One thing I am sure about is that most soundbites are not comprehensive enough to either identify the real problems or options to solve the apparent problems.

If you have ever worked with me, you know my approach is to identify problems that need to be fixed and options that will fix the problem, or ways to live with the problem.  I would like to start with “my plan is not working” but that may get too close to home until a lot of frustration is vented about “data sources.”

By “data sources,” I am talking about USDA monthly and quarterly estimate reports, private estimates, fundamental and technical information that flashes across the screen every day, market advisors, and street estimates.   USDA estimates – Straight up, I believe the published estimates are produced according to processes developed and reviewed constantly over many years to produce the most accurate estimates available at the time they are scheduled for release.  If the process is not working , farmers need to work with their national farm organizations to enlist the strength of many.  Individuals venting accomplishes very little.  If there is a problem, this is a case of having to live with it until it is fixed so you can focus your energy on where it will have an impact.

Private estimates – Use them instead of USDA numbers if you can get your hands on objective written documentation that verifies that the private source has a consistent performance record of more accurately predicting price and price movement.  It doesn’t matter how fancy the “cherry picked” results look if the price prediction accuracy is not going to improve your bottom line.

Fundamentals and technical information – Many pieces are generated every day and they play well as soundbites for media editors without an agricultural background.  Markets are based on fundamental and technical information with little or no translation to price expectation or movement, and the media is good at flooding our minds with fluff and distracting us from thinking about what it really means.

Marketing advisors – While I disagree with some advisors because I believe they lack the educational background and experience to recognize why some marketing systems are unlikely to work, there are very few that I believe intentionally deal in deception.  If the advice is not working, it is the advisor and not the market.  Learn to recognize the difference between excuses and logical explanations.   Use advisors who can provide you with written documentation of actual performance to predict prices and price action.  Ask your advisor what their core strategies are based on.   Ask your advisor if he/she can show you the demand curves they are using to estimate corn, beans, and wheat prices.  I will leave it there.

Street estimates – Very few farmers use the same methods to estimate their yields for budgets and the banker that they use to report yields to USDA or the coffee shop.  Most farmers can do a pretty accurate job of estimating their yield, but the numbers tend to be weighted one way or the other depending on whether the guy across the table is bragging or crying the blues.

To summarize the data source estimates, of course there will be variation by everyone that touches the fundamental and technical information.  Every farmer knows, or should have known, data sources and price risk management challenges existed when they entered farming.  Many entered as apprentices and are just now learning that the experts released them without completing the training.  The data issues are not going away, so the options are to learn to use the tools that will allow you to live with the data issues or accept reality that your competition is using the tools successfully and have a significant advantage.

Now moving on to the marketing plan.  In the intro for the article, I intentionally did not use “marketing plan.”  Success of a marketing plan depends heavily on whether the assessment of fundamental and technical information about production and price estimates are accurate.  If your price projection system is not working effectively, then you are faced with protecting against price either rising, falling, or doing both over time.  The fact that the market is likely to do both is not a data problem as discussed above.  It is now time to entertain the possibility and accept responsibility that it is “your marketing” system that is not working. After many years as a formal and/or informal educator, I can tell you that “why isn’t my system working” is normally one of the easiest questions to answer. “A working system requires several parts to all work together, and there are hundreds of ways to get off track with the wrong parts and/or the wrong assembly as you apparently have done.”

Normally I hear a lot of novices saying something like “this worked last year or the year before.”  That is great for a soundbite but fails miserably to recognize the “all other things being held constant” assumption.  What concerns me the most is that I have heard more reputable analysts use a similar quote the last few months than ever before, and then go on to raise questions about national data sources and conspiracy or conspiracy implications.  Obviously, “conspiracy” is playing well in rural communities as an alternative to true confession.

I don’t have a bone to pick with anyone, but it is a sign of professional weakness to start blaming others for missed calls before giving serious attention to the core economic assumptions that have been ignored or violated.  The first place to look for errors is whether “all other things equal” has changed.  There is a glaring error when analysts project individual lines in the WASDE format and then are surprised that the price does not reconcile with some time-honored shortcuts to price projections.  Don’t get me wrong.  There is an obvious value starting with last year as a base and projecting from there to shortcut projections for this year.  But there are huge potential errors taking shortcuts to complex economic projections.  If your marketing plan is not working, there is a high probability that you are overlooking some basic and critical assumptions.  Evaluating and revising your marketing plan has far greater potential to increase your net revenue than blaming external sources for intentional data errors.  Everything about the future is an estimate, accept it and learn to live with it.  Food for thought!

Posted by Keith D. Rogers on 16 August 2023

That would lead others to say the estimated average farm price for supply and demand equilibrium and sales targets is the most important.  For many, the price estimate is the number that will be used in many different ways to triggered delayed or forward pricing of production.  Estimate prices weigh heavily on the budget and lending discussions with most bankers.  Another report was issued Friday, August 11, and only a small percent of farmers is likely to make new decisions based on the average price estimates because they believe the estimates will change (be raised) in future reports.

All eyes were focused on estimated production (yields and HA) in the August report and most certainly will be focused there again in September.  Why?  For all practical uses, production is now more or less a “fixed” vertical supply curve on the chart which will move right or left as more fields data becomes available.  Fixed means that very little variation will be explained by price changes this late in the production season.  Beginning stocks are essentially in the same category, subject to re-estimation but only slightly affected by price levels.  Imports are so small and near to constant that they will contribute very little to total supply change.  So, in reality, beginning stocks and production are the dominant variables in total supply and should be the major focus of each WASDE report.

Note that the bottom portion of the report is not called Demand, but rather Use, and that is significant.  Feed, food, and exports all appear to be estimated quantities that will be purchased at an unspecified price, but until you see a demand curve, the price estimate lacks significant rigor.  There is no obvious demand curve (series of paired prices and quantities purchased), yet, ending stocks are accepted as a simple residual of loosely estimated sales subtracted from supply estimates. Without a true demand curve with sales simultaneously determined with price, one would expect a very stable domestic portion of the demand/use, leaving exports as the most significant factor in the use section of the table as adjustments are made from month to month.  More in depth analysis is required, but it appears that ending stocks are not just the residual of farmers dumping the harvest on the market when they get ready, but rather a “supply” factor or a “demand” factor based on farmers holding or releasing grain as a function of current and expected prices.  The export component is known to be a function of U.S. prices, but can also be a shift in international demand which would just shift the demand left or right, leaving the domestic demand curve unchanged.  More research is needed.

If the goal is to project price from the Supply and Use data, then the two most important pieces from the report are production that can shift the fixed supply curve right or left to slide up or down a stable domestic demand curve, and external political decisions to buy or sell U.S. product independent of the U.S. price and shift the demand curve right or left.

Below is a chart searching for price equilibrium using one line from the WASDE and a privately estimated proxy for demand.  It’s not perfect, but is consistent.  The chart estimates for average farm price are running about 10-20 cents or 2.0-4.0% above the USDA estimates.  Note that the proxy demand curve embraces both 22-23 and 23-24 marketing years.

Posted by Keith D. Rogers on 13 August 2023

Key reversals can be reversed as early as the next bar, so the question then is whether they are consistent and reliable. Different folks have different success with key reversal indicators, so it is useless to say it is or is not a reliable indicator.  Data tells all.

Let’s use CZ23 and start with the key reversal down on the weekly chart on 4/25/22, close at 696.00.  The next key reversal up was on 7/10/23, close 506.50. Potential 89.50 cent hedge gain. In between, it hid a selloff from 696 down to 554, a rally up to 643, a selloff down to 492, a rally to 624, and a selloff down to 479.  Before leaving the weekly chart, note that the key reversal up was possible because the week of 7/03/23 was relatively inactive.  Nonetheless, the signal is that the market is likely to move higher.  Major rally or minor correction?  Based on another technical indicator, a correction to 524-555 followed by another selloff to 400 or lower looks more likely before new highs. (Opinion, not a recommendation)

Looking at the daily chart for CZ23, there was no key reversal down until 12/30/22 and no other key reversals through today (7/18/23).  Dropping down to the hourly chart, there was a key reversal down on 1/30/23, reversal up on 1/31/23, reversal down on 2/2/23, reversal up on 2/3/23, etc.

In summary, key reversals do indicate a shift in relative strength between buyers and sellers but provide only limited information about the duration of that strength.

Posted by Keith D. Rogers on 18 July 2023

Before you can jump on the band wagon with any marketing plan, you need to see historical performance and look for consistency.  Looking back to beginning of 2020, there have basically been only three trend changes in three years.  On or about 5/15/2020, the major trend indicator turned up.  On or about 6/15/2022, the trend indicator turned down.  Finally, it appears that on or about 8/23/2022, the trend indicator turned up.

Independent of other restrictions such as risk avoidance, fear, or other non-economic issues, the message has been very clear and easy to implement a marketing plan.  In May 2020 it was to lift or offset any existing hedges and avoid pricing any more grain until forced into cash flow sales, and then to replace the sales with paper ownership.  In May 2021, the message for MY 21-22 was still the same, delay pricing until forced into cash flow sales, and replaces the sales with paper.  In May 2022, the message was the same, and remained the same until June 2022.  Price all MY21-22 crop for delivery, and price as much of MY22-23 as you risk tolerance would stand.  In August 2022, the indicator said the trend was turning up, and it was time to lift or offset hedges.

“But nobody could know.”  Partially correct.  Many people, including some very high powered analysts and companies did not know.  In that case, you  have to make decisions based on probabilities.  Because of the mathematical structure of the moving average, it was possible to do a simple calculation for every day of roughly a thousand day period and know if it was possible for the trend to turn up of down the next day, and in many cases for several days.  Bottom line, no one could know for sure that the market was going to rally for more than two years, but many knew on a day to day basis whether the trend was still going to be up or down for one or more days.

In short, no one knows how long the market will rally or sell off, but there are indicators that do a great job of identifying the direction of the long term trend.  This is just one of many indicators that help answer the questions about whether the market is going up or down.

Drafted by Keith D. Rogers, 20 September 2022