(CC image by Jullen Belli on Flickr)


Some say that long-term trends in the financial markets are impossible to predict.  Not so!  Markets follow cycles that, while not precisely predictable to the exact date, time, or price point, can be reasonably well-anticipated in advance.

If you’re a day-trader with a time horizon of minutes or hours, long-term trends won’t have any impact on your results at all.  But if your investing time horizon is multiple days, weeks or months as we recommend, then a good understanding of the long-term trend will enhance profits and reduce drawdowns.

If you have a long-term time horizon and you don’t like to make trades more than a few times a year, these long-term trends will be the single most crucial factor in deciding where to invest your money.


Don’t Invest Without a Long-Term Forecast

In my earliest foundational post, I introduced a framework for building wealth entitled “The Five Components of Successful Investing”.

The five components are the blue boxes in this flowchart, taken from that post (with the blue circle added to mark today’s focus):


For a longer-term investor, someone who can’t or does not want to make trades every week or every month, this simpler framework applies:

In the earlier post, I touched on how I make my long-term forecasts.  When I refer to the “long-term”, I mean cycles that generally last between 4 and 12 years, with an average of 8 years.  In another post, entitled “Want to Conquer the Investment Universe? First, Make a Map!”, I listed the asset classes and subclasses I forecast.  Now, I’ll explain my forecasting methodology in more detail.


Begin with a Baseline Trend (The “Very Long-Term”)

First, I make an assumption for what the trend will be across the next few long-term cycles.  This is the baseline trend that would best fit the long-term cycles, if we could knew them in advance.  To develop the baseline trends, I consider several factors:

  • Historical returns, in the form of risk premiums over the risk-free rate (the difference between the annual return and the risk-free interest rate).  This paper, by Aswath Damodaran of the Stern School of Business, explains the concept of equity risk premium in detail.  The author estimates the average annual risk premium for stocks as having been 4.10% (using geometric averages and the long-term risk-free rate) over the period from 1928 to 2010, albeit with a declining trend across that time period.  This means it is ok to make a choice that is slightly different than the longest average, because the risk premium may vary over the course of decades or a century.  Assuming that today’s 10-year US Treasury rate of 2.58% will be representative of the next few decades, the long-term baseline return for US stocks I’d derive from this approach would be 2.58% + 4.10% = 6.68%.
  • Inflation expectations.  In my post titled Inflation, Deflation, and Your Portfolio, I explain what inflation really means, as well as how essential it is to have a good forecast of inflation before making any long-term forecasts.  I expect deflationary pressures to continue to rule the day, up until the point where the massive amounts of unrepayable worldwide debt are either defaulted upon or renegotiated, as explained in my inflation forecast for 2016 and beyond.  Deflation depresses returns across all asset classes, but inflation tends to increase returns as long as there are not sudden shocks.  Because I expect deflation followed by an inflationary shock, it is hard to estimate what the overall impact of the two together will be, but it has to be considered.
  • Fundamental analysis, including political trends, demographics, social patterns, economic indices, and other factors that may impact a single sector or all financial markets over a very long period of time.

Here are the baseline long-term trends I am using as of today:

I also establish a range around each baseline trend value.  I do this by defining and measuring the depth of previous long-term cycles that have occurred in each asset subclass.  For example, the range of possible long-term annual returns I’ve established for gold mining stocks (“PM Stocks”) is -25.9% to +35.0%, but for consumer staples stocks it is only -11.1% to +12.5%.  [Technical note: The positive skew exists so we have symmetry across up and down cycles.  (1+.125) * (1-.111) = 1.000].  I use these ranges later in the process.


Determine Trend, Using a Long-Term Chart

Next, I look at a weekly or monthly chart to determine the direction and strength of the current long-term trend.  You can see countless examples of how I gauge trend direction and strength on my YouTube channel.  Recall that the definition of an uptrend is a series of higher lows, and the definition of a downtrend is a series of lower highs.  If there is not a clearly discernable trend, look at the prior trend direction.  Most likely, what is occurring is a flat correction and we would expect the prior trend to resume once the correction is complete.  For example, in the chart below, I have marked the rising yield cycle from 2003 to 2006 which appears as a flat correction when looking at the 30-year yield.

Long-term chart of US Treasury Bond yields, with long-term cycles marked by the blue lines.


This example also illustrates how price outweighs time when evaluating long-term cycles.  Often, cycles don’t follow regular lengths, so it is very dangerous to assume that major highs or lows will occur X months from now merely because that happened the last couple times around.  I’ll go more in-depth on this subject in later posts on intermediate-term cycles, another component of my framework for successful investing.

Besides examining the price action in a long-term chart, I also consider the following factors when forecasting the future trend direction:

  • Momentum: The rate at which prices are increasing or decreasing.  Technical indicators that measure momentum include the Stochastic Oscillator, RSI, % rate of change, and deviation from a long-term average.  If prices make a new long-term low or high, but momentum is weaker than another low or high that recently occurred, the odds favor a change in the long-term trend direction.
  • Intermarket analysis: The performance of other asset classes that tend to move in the same direction as, or opposite direction from, the asset class we’re examining.  For instance, the US dollar index and the price of gold (in dollars) tend to move in opposite directions.  When the typical relationship doesn’t hold, it is a warning sign that the trend may be changing.  John Murphy has written several excellent books on the subject, one of which is on my list of essential books for trading and investing.
  • Fundamental factors: shifts in political trends, demographics, social patterns, economic indices, or other factors that may impact a single sector or all financial markets.

Based on the long-term chart, I select an “Actual Long-Term Trend” and a “Forecasted Long-Term Trend” from one of the five choices below:

  • “Up” – representing a clear upward trend
  • “Up (?)” – representing a weak upward trend
  • “Down” – representing a clear downward trend
  • “Down (?)” – representing a weak downward trend
  • “??” – representing a situation where the trend cannot be determined


Translate the Trend into a Fearless Forecast

So far, we’ve selected a baseline long-term trend, defined a range within which the long-term forecast can fall, and assessed the current long-term market situation.  Now that we have assembled all the info we need, we can proceed to make our long-term forecasts.

I take the actual and forecasted long-term trends from the prior step and translate them into a percentage between -100% and +100%.  This percentage determines how much my long-term forecast will vary from the baseline trend.  A percentage of -100% represents the most bearish, or negative, stance on from a long-term standpoint, and would produce a long-term forecast at the absolute bottom of the range.  Conversely, a percentage of +100% represents the most bullish, or positive, stance on from a long-term standpoint, and would produce a long-term forecast at the absolute top of the range.  Anything in between will fall within the range, with higher percentages giving higher forecasts and lower ones giving lower forecasts.  A percentage of 0% puts us right in the center of the range.

I have a grid I use to define the percentage for every possible combination of actual and forecasted trend (5 x 5 = 25 combinations in total).  The grid is the same for all asset classes.  The forecasted trend carries much more weight than the actual trend, because the future trend will determine our profit or loss, not the past trend.  As legendary hockey player Wayne Gretzky famously said, “skate to where the puck is going, not to where it has been.”

When I am confident in the forecasted trend, and differs from the actual trend (e.g. actual trend is Down, forecasted trend is Up), the percentage will be positive but not too strongly positive.  We want to start getting on-board the new trend, but not too heavily in case the current trend extends longer.  As the new trend begins to emerge, we become more confident in the forecasted trend so the percentage goes up.  At an actual trend of “Up (?)” and a forecasted trend of “Up”, I am at a percentage of +100% which means I am as bullish on that asset class as I can be, and I’m putting a higher percentage of my assets into it.  In this case, I see the actual trend beginning to turn up, in line with my forecast, so I have more confidence that my forecast is indeed correct.

As another example, let’s continue the earlier case of gold mining stocks.  As of today, my assessment of the actual long-term trend is “Down (?)” and I have chosen “Down (?)” for the forecasted long-term trend.  This is a weak situation, and negative for the gold miners.  However, because both forecasts have low confidence, the percentage is -40% and not any lower.  Applying this percentage to the range we established, -25.9% to +35.0%, and the baseline trend of +6.5%, we get a long-term forecast of -6.5%.  Calculation: -6.5% = 6.5% + (-40%) * (6.5% – (-25.9%)).

This forecast applies to the stage of the long-term cycle that we are in.  For example, if a few months from now the downtrend seems to be exhausting, causing us to change our forecasted trend to “Up (?)”, the percentage would go to +35% (as defined for that combination of actual trend “Down (?)” and forecasted trend “Up (?)”) and the long-term forecast would increase to +16.5%.  This is a big move, but I don’t change my long-term forecasts very often, only when conditions warrant.

To see this in action, including loads of real-life examples, check out our live stream, YouTube channel, and free trading podcast.

Armed with a fearless long-term forecast, we can now take action.


Turn Forecasts into Profit

With forecasts on all areas of our investment universe, we are ready to face the market.

Long-term investors can stop here, allocating their wealth to the asset subclasses with the highest projected forecasts.  It’s still important to monitor the risk level of the portfolio to avoid overconcentration.  More about risk levels in Episode 2 and Episode 10 of my investing podcast.

Intermediate-term traders, or swing traders, will want to layer intermediate-term forecasts onto the long-term ones.  Here’s a link to another post with more details, as I continue my series on the Five Components of Successful Investing.

So get started today on your fearless forecasts, and be prepared for the volatile times that lie ahead for financial markets.