Posts tagged with: Forecasts

Here’s How to See the Trend

(Part 9 of ten-part series on Financial Truths)

Section 1: Why Did Your Short-Term Pattern Fail?

Section 2: Follow the Money: Start with Inflation/Deflation

Section 3: Make a Long-Term Forecast

Section 4: Make an Intermediate-Term Forecast

Section 5: Identify & Trade the Best Opportunities

 

Sign up for FREE email updates to be notified right away when a new episode is available!

 

wide view

(CC image by Ulbrecht Hopper on Flickr)

 

Blog Post References:

An Active Management Plan for Self-Directed Investors

Inflation, Deflation, and Your Portfolio

Fearless Forecasting for Long-Term Investors

Fearless Forecasting for Traders

 

Section 1: Why Did Your Short-Term Pattern Fail?

  • Why do chart patterns fail?  Most often, it’s the higher-level trend – found in the sector, the broad market index, or longer-term stock chart.
  • SBUX looked bullish to a short-term trader on 11/3/15 …

    … but the sector was WAY overextended and at a key level …

    … and the S&P 500 had recovered as much as it could. Nowhere to go but down.

    Long-term chart looked bubbly! SBUX still hasn’t broken this level as of 2/6/17

  • Always study the sector and market (higher-level assets)
  • Always study the intermediate-term and long-term trends (higher-level trends)

Section 2: Follow the Money: Start with Inflation/Deflation

  • What inflation is
  • How we measure inflation
  • Why inflation matters so much
  • How to forecast inflation

Section 3: Make a Long-Term Forecast

  • I introduced this concept in Episode 4
  • Pull up a weekly chart, 25+ years of data
  • Examine the four dimensions of: Price, Pattern, Momentum, and Time (see Episode 7 for details)
  • Choose your baseline asset allocations
    • Best approach: Rank all the choices in your investment universe from highest to lowest Sharpe Ratio
    • Simpler approach: Just adopt my allocations (shown below as of February 2017), but adjust as needed for your risk tolerance, goals, and market outlook
    • More details coming up in Episode 10!
    • As of Feb 2017, I’m bearish on most financial markets over the long-term, so these are conservative allocations despite my relatively young age.

      The sector-by-sector view for serious traders. This shows how I divide my stock allocation across various sectors. They’re ideal targets, not something I try to exactly match my portfolio to. As of Feb 2017.

Section 4: Make an Intermediate-Term Forecast

  • Pull up a daily chart, 8+ years of data
  • Examine the four dimensions of: Price, Pattern, Momentum, and Time (see Episode 7 for details)
  • “Flex” your baseline allocations, going overweight the assets that you expect to rise in the intermediate-term, and underweight or short the ones you expect to fall (review Episode 4 for more details)
  • Overweight bonds, underweight stocks, and short the US dollar as of early Feb 2017. But I’m still diversified.

Section 5: Identify & Trade the Best Opportunities

  • You’re free to trade anything within the asset class or sector; just stay reasonably close to your asset allocation targets
  • Remember that options and futures are leveraged.  Don’t underestimate the exposure.
  • Update periodically
    • Re-evaluate the long-term trend every few months, or sooner if the intermediate-term trend has changed
    • Re-evaluate the intermediate-term trend every few weeks, or sooner if market conditions warrant
  • Learn more macro trading strategies and stay current on market news by viewing our online trading videos and live streams

 

Intro music by audionautix.com

Image credit: blog.uyora.com/author/george/

Find more episodes of the Torpedo Trading Podcast at this link

Continue Reading →

(CC image by Chase Lindberg on Flickr)

 

“Intermediate-term” market cycles – which I define as 6 to 14 months in length in most cases, with an average of 10 months – are the “sweet spot” of trading.  I make the most money trading these cycles, and you can too.

Shorter-term trends and cycles are more prone to unpredictable random noise.  Longer-term ones can be accurately forecasted, but because long-term cycles average around 8 years in length, it takes a long time to extract profits from them.  Good for a long-term investor, but not enough if you are serious about trading and you want to make a living from it or generate enough trading profits to meaningfully supplement your annual income.  Active traders must be aware of the long-term trends but will place trades according to the intermediate-term trends instead, even when those intermediate-term trends oppose a slower-moving long-term trend, because active traders have a shorter time horizon for holding positions.

 

Don’t Trade Without an Intermediate-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):

In the earlier post, I briefly touched on how I make my intermediate-term forecasts.  Again, when I refer to the “intermediate-term”, I mean cycles that generally last between 6 and 14 months, with an average of 10 months.  In another post, entitled “Want to Conquer the Investment Universe? First, Make a Map!”, I listed the asset classes and subclasses I forecast.  They include: the US dollar, major commodities, bonds, and each of the ten stock sectors.  Now, I’ll explain my forecasting methodology in more detail.

 

Start with Your Long-Term Forecast

Always consult a long-term chart (30+ years of data, if possible) before placing an intermediate-term trade.  In my post titled “Fearless Forecasting for Long-Term Investors”, I introduced my methodology for making long-term forecasts.  Here’s a high-level summary:

  1. Begin with a baseline trend, which you expect to observe over several long-term cycles.
  2. Establish a range around the baseline trend, based on the depth and length of prior long-term cycles.
  3. Determine the current long-term trend direction by looking for a series of higher lows (an uptrend) or a series of lower highs (a downtrend).  Also, determine whether this trend is strong or weak.  If there isn’t any 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 over.
  4. Forecast the long-term trend direction and strength based on: The current long-term trend direction and strength, momentum, intermarket analysis, and fundamental factors.  Look for more details on this in future posts, podcasts, and videos.
  5. Take the actual and forecasted long-term trends from steps 3 and 4 and translate them into a single percentage between -100% and +100%.  This percentage determines where your long-term forecast will fall within the range of possible forecasts we defined in step 2.

Let’s use the technology sector as our example for this post.  My long-term forecast for tech stocks is +1.4%.  Here’s how I got there:

The range of possible long-term forecasts is -15.3% to +18.0% with a baseline of +7.0%.  Technical note: The positive skew exists so we have symmetry across up and down cycles.  (1+.180) * (1-.153) = 1.000.  The percentage I apply to this range is -25%, which reflects that the current long-term trend is “Up” and the forecasted downtrend is “Down (?)”.  In other words, there is a strong uptrend now, but I expect a weak downtrend to emerge so I select a long-term forecast that is below the midpoint of my forecast range by 25%.  Calculation: 1.4% = 7.0% + (-25%) * (7.0% – (-15.3%)).

 

Study Prior Intermediate-Term Cycles

Using a daily or weekly chart with at least 10 years of history, identify past uptrends and downtrends.  Let the price be your guide – don’t assume that every single cycle will follow the same length of time.  It rarely works out that way.  But, although the duration of any two cycles may vary, their average duration is usually stable over time.  The half-cycles will average approximately 10.5 months from low-to-high or high-to-low.  Thus, the full cycles will average approximately 21 months (10.5 * 2) from low-to-low or high-t0-high.

Here’s how it shakes out for the tech sector (as tracked by the XLK exchange-traded fund):

Lots of variation in cycle length, indeed – but averaging 23 months apiece when examining the last 10 years of history.  Pretty close to our 21-month expectation.  It’s very helpful to know that the cycle lengths tend to revert to a mean over the long-term.  This knowledge helped us anticipate a couple quick turns in late 2015 and early 2016 following the extremely long uptrend that ran from August 2011 to July 2015.

The fourth column in the chart above shows the lag between the tech sector and the S&P 500.  This is part of the intermarket analysis framework I’ll mention later in the post.

Identifying the past trends is pretty simple and is done in just the same way as the long-term trends.  Look for a series of higher lows (an uptrend) or a series of lower highs (a downtrend), in alternating fashion.  If the price action looks choppy or flat, 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 over.

There are other nuances that make this both an art and a science.  Sometimes I select a cycle low or high that is not the precise low or high that was reached.  For example, the XLK hit 11.44 on 11/20/08, which is below the low of 11.53 I marked on 3/9/09.  But, I chose 3/9/09 instead because it coincided with the overall low in the S&P 500 and because the points immediately before and after the 3/9/09 extreme were lower, indicating the 11/20/08 low may have been a fluke.

A note on trading being both an art and a science: I’m always skeptical of trading schemes that claim to be purely quantitative, or algorithm-based.  There is simply no way to get around the fact that anytime you develop a trading system, whether it explicitly allows for the use of educated judgment or not, you ARE using judgment.  All mathematical models rely upon some sort of assumptions, such as: market returns following a given distribution, a random process being stationary, or the model having an error structure that follows a normal probability distribution with a mean of zero.  By using a mathematical model to make trading decisions, you’re making the judgment that those assumptions are valid.

Why do we record and study the prior cycle highs and lows?  Because, we need the following info for our forecast:

  • The depth of a typical low-to-high or high-to-low cycle: the percentage gain or loss that usually occurs.  This is one piece of evidence we use to determine whether the current trend is nearly exhausted or has more room to run.  First, select a depth of a low-to-high cycle, expressed as an annual return.  For the tech sector, I chose +40.0% as the annual return during an upward cycle after examining the data.  This seems like a very high return, but remember that it’s the return from the exact day of a cycle low to the exact day of a cycle high, with hindsight.  It’s not meant to be a real-life return.  For a downward cycle, I solved for -26.5% because this is the annual return that produces an annual return of +1.4% across an upward cycle and a downward cycle.  Recall that +1.4% is our long-term forecast for tech stocks from the section above.
  • How long the typical cycles are: do they average close to 21 months between highs and between lows?  Have recent cycles slowed, suggesting the current and next cycles will accelerate?  Or vice versa?
  • Is there another sector, market, or asset class that typically lags or leads this one?  In our example, the tech sector usually turns within a month or less of the S&P 500, so we’d look at any divergence between the two with great skepticism.  This is intermarket analysis – drawing connections between different sectors, markets, or asset classes.  The S&P 500 highs and lows should themselves be determined by considering highs and lows in bonds, for example.  Most traders fail to consider this big-picture view, focusing on narrow indicators or chart patterns instead.  Many of the best opportunities to rake in serious profits are found in scenarios where the asset you’re trading is out-of-line with similar stocks, sectors, or asset classes.  If you learn to spot these situations, you’ll start to capture those profits and avoid traps.

We will choose an actual trend (direction and strength) and a forecasted trend (direction and strength) for the intermediate-term, as we did for the long-term.  We’ll choose from one of the five options 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

Now that we’ve recorded and studied past cycles, the actual trend for tech falls right out of that analysis.  The last low was 2/11/16, so an uptrend is in place and it’s a clear one, as the below chart shows.  So we pick “Up” as the actual trend.

As far as the forecasted trend goes, we’ve already gathered some info that will help us make a prediction.  Yet there’s more we can and must consider.

 

Forecast the Intermediate-Term Trend

So far we’ve looked at the depth and the duration of the current cycle and we’ve seen how it compares with past cycles.  We’ve also brought in intermarket analysis as part of this process.

Next, let’s join this insight with some more technical analysis to select a trend forecast and to pinpoint entry and exit points for a potential short-term trading position.

I’ve organized this into categories of: Pattern, Price, Momentum, and Time in homage to Robert Miner’s outstanding book High Probability Trading Strategies: Entry to Exit Tactics for the Forex, Futures, and Stock Markets, which I selected as one of my ten most essential books for traders and investors.  Each of these categories deserves its own follow-up posts, so stay tuned for those.  I’ll simply introduce each for now.

Pattern

In general, a “trend” usually consists of five distinct sections or “waves”.  During a trend, as “trend” is defined here, the market is reaching successively higher or lower extremes.  A “correction”, during which the price moves in the opposite direction from the trend, usually consists of three distinct sections or “waves”.  The corrective waves will also usually be shorter in time than the trend waves.  These principles come from Elliott Wave theory.  Many well-known traders have integrated these principles into successful trading strategies.

How does this fit in with the framework we’ve defined?  I’ve called every cycle a “trend”, and haven’t used the term “correction.”  It’s simple!  Since we’re talking about the intermediate-term timeframe here, the trend (5-wave) direction is the direction of the long-term trend.  The corrective (3-wave) direction is the opposite of the long-term trend.

For the tech sector, the actual trend we’ve chosen is “Up” in both timeframes.  Therefore, we expect upward intermediate-term cycles like the one we’re currently in to have 5 waves.  We expect downward intermediate-term cycles to have only 3 waves, and to be shorter in time than the upward cycles.  This will hold until the long-term trend changes direction.

In the tech uptrend that began 2/11/16, there is a 5-wave pattern:

 

Consider also checking for other, more complex patterns.  I recently began incorporating harmonic patterns, as found in Scott Carney’s book Harmonic Trading, Volume One: Profiting from the Natural Order of the Financial Markets, into my technical analysis framework.  Simpler patterns like a head-and-shoulders top, double bottom, or wedge/triangle formations are also useful.

Price

The introduction of a wave structure also allows for the projection of price target points using Fibonacci principles.  This is a deep subject that I’ll tackle in a later series of posts.  Here, the most likely endpoints of Wave 5 are between 51.72 and 52.51, so we should expect a little further rally before this upward cycle ends.

Momentum

Many traders use momentum oscillators like the MACD, Stochastics, or RSI to measure how rapidly price is changing.  This is what momentum oscillators do well, but most new traders go too far with them.  They trade using very simple rules like MACD crossovers, and they aren’t successful.  Never, ever, trade based on one indicator or one simple rule in isolation!  A crossover, in which a more responsive momentum indicator crosses over a smoothed momentum indicator, may indeed signal an important reversal in momentum and may be a sign of an important trend change.  But, you need to look at all the other market conditions first before executing a trade based on this single factor.

I recommend looking at momentum across multiple time frames, as Miner teaches in his book.  As a general rule, you want to trade in the direction of the longer-timeframe momentum and execute your trades when the shorter-timeframe momentum reverses in the direction of the longer-timeframe momentum.  For instance, when momentum on a weekly chart is rising but not yet in the overbought area, you would want to look for an entry point to buy when the momentum on a daily chart makes a bullish crossover.  Again, don’t execute the trade unless you’ve first studied the overall market conditions.

In our tech example, the momentum on a monthly chart is positive but very overbought and starting to decline.  This reinforces my view that the high between 51.72 and 52.51 will represent a long-term high in tech stocks.  The momentum on a daily chart, shown in the screen capture above below the price chart, has risen into the overbought zone but has not yet reversed.  This reinforces the view that there is just a little more room to run in this intermediate-term cycle.

Volume (the number of shares traded) can also be a useful indicator of momentum, but has become far less reliable than it was in the past because many trades take place off the major market exchanges so they are not part of volume statistics.  Many of these are large block trades between institutions.

Time

The only thing I’ll add on time, besides what I already mentioned in the context of intermediate-term cycles, is that you can layer time projections onto a 3-wave or 5-wave price structure to identify dates where a wave is more likely to end.  Like Fibonacci price projections, it’s a deep topic that I’ll save for future posts.

Fundamentals

I added fundamental analysis as another crucial element to consider, although some traders will consider it anathema.  Fundamental analysis is a broad term for factors that aren’t viewable on a price chart.  It includes: 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.

Many technical analysts believe all information is reflected in the market price, so they’d say it’s merely a distraction to look at fundamentals.  I agree that much of the “market news and commentary” out there is distraction, but I strongly disagree that you can ignore the fundamentals.  They can provide clues that you’ll never find on a price chart.

I believe fundamental analysis is most valuable for spotting major extremes in price or bubbles.  In 2000, 19 online startups bought very expensive Super Bowl advertisements.  Certainly, this would add some evidence in favor of the dot-com bubble being about to burst, which it did shortly after.

The Verdict

Considering all the above info, I’ve chosen an intermediate-term trend of “Up (?)”, signifying that the uptrend is still in place but has weakened and is almost done.

 

Translate the Trend Into A Fearless Forecast

Like we did with the long-term trend, next we take the actual and forecasted long-term trends (“Up” and “Up (?)”, respectively) and translate them into a single percentage between -100% and +100%.  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).  Here, the percentage is +20%.  This indicates that although we still want to hold tech stocks (the percentage is positive), we are only slightly positive on the sector and we certainly don’t want to buy more of it.

When the XLK gets above $52, or breaks down from its current levels, I’ll mark the forecasted trend “Down”, the percentage will go negative to -50%, and I’ll be going short the tech sector.

We want to go long the sectors, markets, and asset classes that have the highest percentages (closest to 100%) and go short the ones that have the lowest percentages (closest to -100%).

If you have a baseline asset allocation, you’ll want to adjust it up or down based on the percentages in each asset class, but staying within a minimum and maximum for each asset class.  This is what I do to ensure that while I act on opportunities, I don’t get too carried away with a single asset class.  More on this in future posts.

Also, look forward to many more examples of this framework in action throughout future live streams, videos, and of course our free trading podcast.

I know this approach takes more time than the easy single-indicator “strategies” (advertised as such, but really a total fraud!).  But it works.  This is a winning approach for managing a large portfolio of assets or for swing trading a smaller account.  It is a comprehensive, time-tested, and successful strategic framework when it is used in conjunction with good risk management and a sound mental approach to trading.

Continue Reading →

(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.

Continue Reading →
(CC image by Mario Donati on Flickr)

(CC image by Mario Donati on Flickr)

 

We’ve seen relatively low and stable inflation levels for the last 30 years, so it’s easy to forget that it hasn’t always been this way.  What will the next 30 years bring?  More of the same, a return to the high inflation of the 1970s and early 1980s, or deflation as in the Great Recession of 2009-2010?  Or, could we experience all of the above?  Is your portfolio ready?

My prior post explains the real meaning of the terms “inflation” and “deflation” with several examples.  It also guides you towards making better forecasts of inflation, based on its three main drivers.

When the inflation rate shifts suddenly, it causes major damage to investors who haven’t prepared for these episodes.  Often, it’s the investors with the most conservative approach that are left worst-off once the dust settles.

If my forecast comes to pass, few investors will be spared from the damage.  That’s because the conditions today are ripe for BOTH deflation AND inflation, one after the other.  Only by taking specific steps now, and remaining alert as events unfold, will you emerge with your portfolio intact.

 

Historical Perspective

Prior to 1971, when the United States fully broke all ties between the dollar and gold, consumer prices in the United States underwent phases of high inflation and deflation.  However, when averaging across these cycles, prices maintained stability over the long run.   This happened because the dollar was backed by gold and the supply of gold grew only as quickly as it could be mined and processed.  Overall price levels stayed roughly the same from generation to generation, rather than increasing over time like everyone accepts as normal today.  (Look at how much prices have gone up from 1975 to 2015 – imagine if college was still that cheap today!)

Since 1971, the inflation rate has been less volatile, as the U.S. Federal Reserve has closely managed monetary policy in the United States.  The Fed’s objectives, as defined by the Federal Reserve Act, are to maximize employment, maintain stable prices, and moderate long-term interest rates.  These objectives existed long before 1971, but in the eyes of the Fed’s Board of Governors and the Federal Open Market Committee (FOMC) who are charged with carrying out these goals, “stable prices” now means something very different than it used to.  Today, they say that “stable prices” does not mean actually mean “stable prices” over the long run, but gradually rising prices!  If they really cared about stable prices, you’d still be able to buy a postage stamp for 13 cents or a car for $3,800, as in 1975.

The Fed has managed to keep prices rising gently for most of the last 45 years because it has responded swiftly and dramatically to any threat of falling prices in the economy, whether real or perceived.  By contrast, they react slowly when the economy is booming because they do not want to be blamed for the damage that would occur if they suddenly withdrew stimulus from the economy.  This behavior creates a strong bias towards rising prices rather than stable or falling prices, as we see below.

cpi_graph_70yr

The Fed’s focus has been on using monetary policy to smoothing out the boom-bust cycles that naturally occur in a free market economy.  When the economy starts to contract, the Fed expands the money supply through actions like buying US Treasury bonds (indirectly, because doing so directly would be illegal!), cuts key interest rates, or takes other actions to try to juice up the economy.

On the surface, this seems like a great thing for everyone.  Who cares if prices go up over time, as long as it’s gradual and predictable and there are no major shocks to the system?  If they’ve kept inflation tightly controlled for decades, certainly they can continue to do so?

Not so fast.  This “over-management” of the economy harms us all, especially savers and investors.  It allows bubbles to grow bigger and bigger over a longer period of time, rather than deflating on their own.  We saw massive bubbles burst in currencies (1997), real estate (2008), stocks (1987, 2000, 2008), banks (1980s S&L crisis), junk bonds (1989), and commodities (2008, 2014-15) to name just a few.  These bubbles would likely have still happened without misguided policy from the Fed and the U.S. government, they would just have been smaller and easier to recover from.

In summary, the Fed has kept the inflation rate moderate and positive for decades, but at the cost of pushing more volatility into asset markets.  This is wonderful news for alert traders and active investors, but bad news for savers and passive investors.

 

Current Conditions

Under a “lower-for-longer” interest-rate policy like we observe today, businesses respond by expanding debt, refinancing old debt that they’ll still never be able to pay back, and other financial engineering like massive stock buybacks, all of which are value-destroying in the long run.  They don’t deploy as much capital into real investment that would produce long-run growth and more jobs.  Furthermore, retirees, and savers have to set aside more money when interest rates are low, otherwise they won’t have enough interest and dividends to live on.  Pension funds and insurance companies must set aside more money to meet future obligations.  What does this all mean?  Money sits idle or chases bad investments instead of being invested into job creation, good technologies, or production plants.

We see this most clearly in the velocity of money: the rate at which money, credit, and liquid assets circulate in the economy.  Lower velocity means more money sitting idle instead of being used to purchase goods and services.

A similarly steep drop in velocity happened right before the Great Depression.

A similarly steep drop in velocity happened right before the Great Depression.

 

At the same time, the money supply is rapidly expanding:

m2-60yr

Most measures of credit I monitor are growing too.  Corporate debt, student loans, and auto loans are breaking records month after month.

Yet despite all this credit creation, and consumer prices that are nominally rising, I see deflationary pressures far outweighing any inflationary ones.  Neither government nor the Fed can stop it using their existing tools.

Commodity prices continue to trend downward:

These are two commonly-cited indexes of commodity prices I track. The Dow Jones-UBS index (purple line), has more weight in energy than the CCI (red line).

These are two commonly-cited indexes of commodity prices I track. The Dow Jones-UBS index (purple line), has more weight in energy than the CCI (red line).

 

Gold and gold stocks remain below their 2011 highs:

gold_2006

 

Investors’ inflation expectations keep falling:

infl_exp_5yr_2006

 

Lastly, actual realized inflation continues to fall short of investor expectations:

infl_dev_1_5_2009

 

These charts don’t look anything like what we’d expect to see if inflation were right around the corner.  This is deflation all the way.

 

What’s Next?

When debt builds up in the economy, all is well-and-good until enough borrowers become unable to service their debts.  Debt levels across households, corporations, and governments continue to grow far faster than incomes.  This is unsustainable.  Default rates will reach crisis levels in one area first – state and local governments are a likely starting point, but I cannot be certain which area will tip off the crisis.  It could even be a geopolitical crisis, natural disaster, or any number of events that could set the process in motion.  Timing is even more difficult to predict, but it’s hard to imagine we can go another 3-5 years on the path we’re on.

As default rates rise, the crisis will spread to other sectors of the economy with a speed and severity that will exceed politicians’ and the Fed’s abilities to respond.  Therefore, expect a sudden decrease in virtually all asset prices, with few places to hide.  Gold, income-producing real assets like land and some real estate, will be best protected.  This will be the deflationary phase of the crisis.  (I’d argue the deflationary pressures we see today are a sign that the crisis period has already started!).

But I don’t expect politicians or central bankers to accept this reality for long.  There will be too much pressure on them to act, and to act in ways we have not seen before.

As an example, I believe we are likely to see a large-scale debt forgiveness program for households accompanied by a revaluation of the U.S. dollar at a lower level.  I also think we’ll see a global renegotiation of debts, since a great deal of debt is owed to other governments.   U.S. President-Elect Trump, whether you like him or not, certainly is a man who understands how to renegotiate debt and emerge from bankruptcies.  To make these measures more effective, I also expect governments will initiate capital controls, restricting the movement of money across borders.  We may also see an attempt to introduce regional currencies or a global currency at this time.  These actions will represent the inflationary phase of the crisis.

The length of time we remain in the deflationary and inflationary phases will depend on how effective global policymakers are at achieving consensus during the crisis.  The more rapidly they are able to successfully “reset” the global economy, the faster we’ll move from deflation to inflation and then return to some semblance of normalcy.

 

How To Stay Safe, Or Even Profit, From These Events

If there is one thing all good traders love, it is volatility.  Even in times of crisis, markets remain open (with limited exceptions).  Many of the skills I teach will help you preserve your capital and even make money during both phases of the crisis.  For instance, shorting stocks, buying put options, and trading the VIX in a crisis environment can be immensely profitable!  Keep in mind that these strategies do carry risk, and should be used carefully as your own financial situation permits.

You should also consider owning some hard assets like gold, silver, and income-producing real estate if you are able.  Minimizing your own personal debt will benefit you in a crisis period as well.  Stay tuned for more on all these topics.

Above all else, it goes without saying that you’ll want to take steps to ensure your personal safety, diversify your skillsets, and overall become more self-sufficient.  I highly recommend Jack Spirko’s podcast, The Survival Podcast, for a rational and thoughtful discussion of preparedness topics.  I’ve been a listener and subscriber for many years.

Deflation and inflation don’t have to catch you off-guard.  By sharpening your trading skills, you can use volatility to your advantage.

 

Continue Reading →