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 →

Don’t Let Mental Mistakes Sink You

(Part 8 of ten-part series on Financial Truths)

Section 1: We Are All Human

Section 2: Play Devil’s Advocate

Section 3: Forget Your Cost Basis

Section 4: You Can’t Tell the Market What to Do, So Let the Market tell YOU What to Do

Section 5: Stop-Loss Orders Are Only For the Lazy

Section 6: Know When to Take a Break

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

 

trophy case

(CC image by Ben Sutherland on Flickr)

 

Section 1: We Are All Human

  • No ‘bot’ or ‘algorithm’ can come close to what a good investor/trader can achieve
  • Some high-speed trading firms do succeed, but have to spend many millions of dollars on computers and network connections to do it
  • ‘Flash crashes’ highlight the problems with pre-programmed trading algorithms
  • 2016 British Pound Flash Crash

    New Market Wizards by Jack D. Schwager

Section 2: Play Devil’s Advocate

  • Before placing a trade: visualize the market moving against you, what would that look like?
  • Could you construct a plausible alternative scenario around this?

Section 3: Forget Your Cost Basis

  • It doesn’t matter where you entered the trade
  • Don’t hang on to a losing trade because you want to “get back to even”
  • One exception: a “time-out” level based on total losses

Section 4: You Can’t Tell the Market What to Do, So Let the Market Tell YOU What to Do

  • Examine a chart without bias
  • Markets aren’t tradable 100% of the time

Section 5: Stop-Loss Orders Are Only For the Lazy

  • Stops often don’t work the way they’re supposed to
  • Other traders will exploit your stop-loss orders for their profit – “running the stops”
  • Don’t react too quickly to a breach: Watch the action around the price level
  • “Fake-outs” around commonly-known price levels

Section 6: Know When to Take a Break

  • Thinking too much about past mistakes
  • Being tempted to “double-down”
  • Exceeding a pre-defined risk tolerance

 

Intro music by audionautix.com

 

Find more episodes of the Torpedo Trading Podcast at this link

Continue Reading →

The Right Way to Read a Chart

(Part 7 of ten-part series on Financial Truths)

 

Section 1: What is Technical Analysis?

Section 2: Identifying the Higher-Level Trend

Section 3: Pattern

Section 4: Price

Section 5: Momentum

Section 6: Time

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

 

Section 1: What is Technical Analysis?

Section 2: Identifying the Higher-Level Trend

  • Uptrend: Series of rising lows
  • Downtrend: Series of falling highs
  • Diagnosing trend during choppy periods

Section 3: Pattern

  • Trends (same direction as the higher-level trend): typically consist of 5 waves (3 trend waves and 2 corrective waves)
  • Corrections (opposite direction as the higher-level trend): typically consist of 3 waves (2 trend waves and 1 corrective wave)
  • Basic patterns
  • Advanced patterns: Harmonic (e.g. Bat, Butterfly, Gartley)

Section 4: Price

  • Identify high-probability price targets and zones for trade entry/exit
  • Depth of past trends & corrections
  • Fibonacci retracements and projections
  • Pattern completion targets

Section 5: Momentum

  • Stochastics, MACD, or RSI
  • Examine multiple timeframes

Section 6: Time

  • Less precise than the other dimensions, but don’t ignore it
  • Correction periods should be shorter than trend periods
  • Length of past trends & corrections (e.g. 180 months for long-term cycles, 10 months for intermediate-term cycles)
  • Cycle compression/decompression
  • Fibonacci ratios can work on time as well as price
  • Pattern symmetry

 

Real-Life Examples:

Chart 1: Technical Framework in Action

Chart 2: Profitable Harmonic Pattern Set-Up

 

Intro music by audionautix.com

 

Find more episodes of the Torpedo Trading Podcast at this link

Continue Reading →

(Part 6 of ten-part series on Financial Truths)

Section 1: Intro to Options

Section 2: Professionals Sell More Options Than They Buy

Section 3: Sell a Covered Call Against a Long-Term Holding

Section 4: Sell a Naked Option

Section 5: Sell a Spread

Section 6: It’s Got Options, But Should You Really Trade It?

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

 

Section 1: Intro to Options

  • Calls and Puts
  • Options are defined by: Type (call or put), ticker symbol, strike price, and expiration date
  • Intrinsic value vs. time value
  • Constructing a profit graph
  • Long Call

    Long Put

    Short Call

    Short Put

    Long Strangle

  • Certainty vs. Probability: If you can eliminate a certain range of prices from the range of likely outcomes, OR isolate a couple scenarios that are most likely to occur, you can set up a trade with options that captures that hypothesis

Section 2: Professionals Sell More Options Than They Buy

  • Options are a form of leverage
  • Do you want to be the bank or the borrower?
  • Buying time costs money

Section 3: Sell a Covered Call Against a Long-Term Holding

Section 4: Sell a Naked Option

    • Collect premium up-front
    • Hold cash or margin reserves to back the position until expiry
    • It’s possible to lose several times the premium you took in
    • Importance of position management
    • Example:

Section 5: Sell a Spread

  • Same as selling a naked option, except you also buy an option having the same expiration date and a more extreme strike price
  • Position has a net credit (premium in your pocket)
  • Advantages and disadvantages

Section 6: It’s Got Options, But Should You Really Trade It?

  • Bid-ask spread: don’t get ripped off
  • If premiums are very rich, ask why

 

Intro music by audionautix.com

Find more episodes of the Torpedo Trading Podcast at this link

Continue Reading →

(Part 5 of ten-part series on Financial Truths)

Section 1: The Efficient Market Hypothesis

Section 2: Who Is Your Competition?

Section 3: What Is Your Edge?

Section 4: The Wrong Ways to Use Technical Analysis

Section 5: Certainty vs. Probability

Section 6: The Winning Way = Big-Picture View + Timing Tools

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

 

Section 1: The Efficient Market Hypothesis

  • Definition and forms: Weak-form, Semistrong-form, Strong-form
  • Why the efficient market hypothesis does NOT hold in the real world

Section 2: Who Is Your Competition?

  • The vast majority of shares are held by institutions or individuals who cannot or do not transact frequently
  • Paper by Edward Wolff of NYU – chart on top of page 15
  • Active vs Passive: Approx. 2/3 of US equity fund assets are classified as “actively managed”, 1/3 passive – statistic from Bloomberg article – but are they really “active?”
  • Who’s actually trading, reacting to new information that should affect prices?

Section 3: What Is Your Edge?

Section 4: The Wrong Ways to Use Technical Analysis

  • Ignoring one or more of the dimensions: Price, Pattern, Momentum, and Time (credit to Robert Miner – I recommend his book)
  • Magic indicators
    • Overbought and oversold indicators ARE NOT trading signals
    • Trading on momentum signals (e.g. Stochastic or MACD crossovers) by themselves will generate losses
    • “Bearish crossovers” marked by red lines would have produced large losses and significant trading costs, if used as signals to go short.

  • Trend-following: generates huge losses at major highs and lows, and repeated small losses in choppy markets
    • A simple method of trading moving average crossovers (20-day over 50-day) produced 6 wins, 11 losses, and lots of trading costs. Awful!

  • Failing to make a trading plan
  • Failing to make a risk management plan or to adhere to your plan
  • Ignoring trading costs and the cost of leverage

Section 5: Certainty Vs. Probability

  • You can never know for certain what the market will do
  • Technical analysis, when used correctly, identifies high-probability zones

Section 6: The Winning Way = Big-Picture View + Timing Tools

 

Intro music by audionautix.com

Find more episodes of the Torpedo Trading Podcast at this link

Continue Reading →

(Part 4 of ten-part series on Financial Truths)

Section 1: What Is Diversification, and How Do You Measure It?

Section 2: Determine Your Personal Risk Tolerance

Section 3: Set a Baseline Asset Allocation

Section 4: Define Ranges (Min/Max) Around Your Baseline Asset Allocation

Section 5: Trade and Invest, Staying Within the Ranges

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

 

Section 1: What Is Diversification, and How Do You Measure It?

  • Diversification = Owning a variety of assets that are less than 100% correlated with one another
    • Every pair of assets has a correlation coefficient, a statistic (between -1 and +1) that measures how likely they are to move in the same direction over a given period of time
    • Example: A portion of the correlation matrix I use, calculated from historical data:
  • If the standard deviation (volatility) of your overall portfolio is significantly lower than the standard deviations of most of the individual assets inside it, you are well-diversified
  • Owning a few stocks in the same sector, or the S&P 500, isn’t enough diversification
  • For options (puts and calls), calculate the true underlying exposure (number of contracts * underlying share price * delta)

 

Section 2: Determine Your Personal Risk Tolerance

 

Section 3: Set a Baseline Asset Allocation

  • Map your investment universe
    • Long-term investors: use the short list of six major asset classes
    • Traders & active investors: use the longer list of asset subclasses, which includes the ten stock sectors
  • Start with your personal balance sheet (introduced in Episode 3); set Cash % = Cash Requirement / Total Assets
  • Divvy up the rest between stocks and bonds according to your age
  • Carve out a little for precious metals and commodities
  • Adjust up or down for long-term market conditions (prospective 6-14 years).  Learn how to make long-term forecasts here.
    • Traders & active investors: steer your stock allocation towards the sectors with the highest forecasted returns
    • Can use individual stocks, just make sure to account for the higher volatility

 

Section 4: Define Ranges (Min/Max) Around Your Baseline Asset Allocation

  • First, choose the following parameters:
    • Maximum permissible loss on a single position
    • Typical stop-loss
  • Calculate minimum and maximum in each asset class/subclass:
    • Max % = Max Permissible Loss Per Trading Position / (Asset SD * Stop-Loss Multiple)
    • Min % = (-1) * Max %, subject to any other restrictions on short positions
  • Make sure these allocations fit within your risk tolerance
    • Have us run your portfolio through our Trade Analytics Service – we do all these steps for you
    • If you want to do the math yourself: Estimate the expected return and standard deviation of returns, under different scenarios
    • Model with a lognormal probability distribution, and/or run a simulation
    • Sample:
    • Calculate the 1/N percentile of the loss distribution (the loss that occurs 1 in N years)
    • If greater than X, go back and change your baseline asset allocations until they fit within the risk tolerance you defined
  • Check out episode 10 for sample asset allocation ranges.  You’ll find a free, downloadable spreadsheet there.

 

Section 5: Trade and Invest, Staying Within the Ranges

 

Intro music by audionautix.com

Find more episodes of the Torpedo Trading Podcast at this link

Continue Reading →

(Part 3 of ten-part series on Financial Truths)

 

Section 1: Why You Must Not Trade Until You Can Set Aside $15,000

Section 2: Constructing a Personal Balance Sheet

Section 3: Figuring Out How Much You Can Afford to Risk

Section 4: Your Road to $15K

Section 5: How to Develop Your Trading Skills While on the Road to $15K

 

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

 

 

Section 1: Why You Must Not Trade Until You Can Set Aside $15,000

  • It’s way too tempting to use leverage
    • Many exchanges require as little as $2,000 to set up a new margin account.
    • Margin debt carries an interest rate almost as high as credit card debt.  E-Trade: 9.25% on balances below $10,000
    • Buying options?  This is another form of leverage, and often even more expensive than margin.  With more capital, you can sell options instead.
    • Futures have MASSIVE leverage: e.g. 18-to-1 for crude oil on the CME – you’ll blow up your account unless you’ve got a long track record of successful trading, either in a real money or paper account
  • Commissions and fees will eat you alive

 

Section 2: Constructing a Personal Balance Sheet

  • Assets
    • Bank accounts, investments, retirement accounts, businesses, home equity, vehicles, other property, etc.
    • Contra-Assets (reduction to assets): Example – taxes on tax-deferred retirement accounts, like 401(k) and IRA accounts.  Could be as much as 30% or more depending on tax rates when you retire
  • Liabilities
    • Home mortgage, auto loans, student loans, credit card debt, business debt, medical debt, personal loans, etc.
  • Net Worth = Assets – Liabilities

 

Section 3: Figuring Out How Much You Can Afford to Risk

  • Establish an emergency fund
    • Think of a scenario that would be devastating for you financially (but nothing far-fetched/crazy like the end of the world!).  For example, being out of work for 6 months and your family facing $3,000 of extra medical bills during the same time period
    • Account for ALL costs you’d face, including staying current on debt
  • Don’t plan to rely on outside sources of funding like credit cards, cash advances, personal loans, etc.
  • Consider going further – perhaps a 12-month emergency fund, or keeping a year’s worth of mortgage payments or rent set aside on top of a 6-month emergency fund
  • Keep all emergency funds safely invested in cash-equivalents
  • If you’ve got $15K left over to deposit, then go forward.  But be sure to establish a risk management plan and limits in advance.  I introduced this topic in Episode 2.
    • What is a “significant loss” to you?  10%?  20%?  Don’t mind if you lose it all?
    • Over what timeframe?
    • How often can you accept this loss?  1 in 10, 20, 30 years?  Or more often?  To determine this, imagine that loss occurred just now.  Think about what you would do.  A big reaction, like selling lots of assets or closing an account – or small reaction, just watch things a little more closely?

 

Section 4: Your Road to $15K

 

Section 5: How to Develop Your Trading Skills While on the Road to $15K

  • Absorb knowledge
  • Follow the financial news for 15 minutes a day: Start with Reuters
  • “Paper trade”, but pretend the numbers are real – celebrate wins, feel the pain of losses

 

Intro music by audionautix.com

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 →

(Part 2 of ten-part series on Financial Truths)

 

Section 1: What is Volatility?

Section 2: What is Risk?

Section 3: How to Profit from Volatility and Risk

 

 

Section 1: What is Volatility?

  • Volatility: the variation in asset prices or other financial indices over a given time horizon.
    • Changes in stock prices
    • Movements in interest rates, currency exchange rates
  • Some of this volatility is random and unpredictable, but some can be anticipated by savvy investors who are skilled in technical and/or fundamental analysis
    • I believe that as you expand the timeframe, from minute-by-minute to hourly, daily, weekly, and monthly charts, you get less random noise and more predictable trends and patterns
    • Others believe the shortest timeframes are the most predictable
    • Both perspectives are OK!
  • Actual volatility: can be calculated from historical prices
  • Implied volatility: is the volatility for a future period of time, as estimated by market participants
    • As implied volatility increases, the prices of options (calls and puts) increase along with it
    • The Volatility Index (VIX), calculated by the Chicago Board of Exchange, measures the market’s expectation of the 30-day volatility of S&P 500 Index options.  The VIX is commonly quoted in the media
    • Exchange-traded funds that track the VIX, for short-term speculative trades: VXX, XIV

 

Section 2: What is Risk?

  • Risk is a specific type of volatility: the probability of suffering a loss of a certain size
  • Rooted in probability and statistical concepts
    • A wide range of outcomes can happen over a given time period, from large losses to huge profits
    • The simplest illustration is a bell curve: height represents probability, width represents range of possible outcomes (left=bad, right=good).  Two sample curves below:
    • The market doesn’t follow a bell curve in reality, but it’s a simple illustration
  • Risk is defined differently for every investor and trader
    • 1- You choose the amount that represents a significant loss to you (percentage?  dollar amount?)
    • 2- You choose the timeframe over which to measure profit/loss
    • 3- You choose how often you can accept this amount of loss (there is NO WAY to trade with zero chance of a significant loss)
    • What will you do if/when the loss occurs?  This determines how often you can accept that significant loss (1 in 5 years?  1 in 30 years?)
  • Most trading books recommend limiting the risk of each trading position one-by-one.  Simple, but misleading
    • Common rule: set a stop-loss at 1%, 5%, or 10% of your trading capital
    • Far better to understand the risk level of the entire portfolio of investments and trading positions together.  It’s more complex, but our Trade Analytics and Coaching services will assist you
    • Calibrate the risk level of your portfolio so it matches up with your definition of risk, determined by the 3 components of the prior step.  (1-Amount, 2-timeframe, 3-how often)
  • Your personal risk tolerance determines how aggressively you can invest in the markets, and what kinds of financial instruments you can trade.

 

Section 3: How to Profit from Volatility and Risk

  • Most important: Stay within your own risk management plan
    • Keep enough cash reserves OUT of the markets for things like: job loss, adversity, major purchases or down payments
    • Define a maximum loss over a certain time horizon, and know what you’ll do if it’s reached
  • When implied volatility is too high, sell options (calls and/or puts) to put those fat option premiums in your pocket
  • Keep extra dry powder for crises, panics, downturns, buying “fallen angel” stocks & bonds
    • When the market is stricken by fear, but better times are around the corner, you’ll be able to load up on bargains and wait for normal conditions to return
    • Many institutions aren’t allowed to invest in stocks and bonds below a certain size or credit rating, so they’ll be forced to sell
    • As long as you’re within your overall risk management plan, buy from them at “fire sale” prices
    • Example: VanEck Vectors Fallen Angel High Yield Bond ETF (ANGL) vs. oil ETF

 

Intro music by audionautix.com

Find more episodes of the Torpedo Trading Podcast at this link

Continue Reading →

(Part 1 of ten-part series on Financial Truths)

 

Section 1: The old model of: go to school, get a stable job, get pension / save in your retirement accounts, buy-and-hold for the long run, retire with lots of money set aside – it’s dead, over, gone, buried in history.

Section 2: You can easily become over-concentrated in a few highly correlated asset classes; correlations rise in a crisis

Section 3: “Leaving it to the experts” is leaving money on the table

 

 

Section 1: The old model of: go to school, get a stable job, get pension / save in your retirement accounts, buy-and-hold for the long run, retire with lots of money set aside – it’s dead, over, gone, buried in history.

  • Employment/population ratio (data.bls.gov) – peaked at 65% around 2000, down to 60% now and will keep dropping
  • Shift towards part-time jobs, freelancing: A survey by Upwork and the National Freelancers Union suggests that 55 million people, or 35% of the US workforce, made money by freelancing in 2016 – up by 2 million in the last 2 years. The largest growth rate has been in “diversified workers” who combine different part-time and freelance gigs into a full-time income. http://www.citylab.com/work/2016/10/the-two-sides-of-the-freelance-workforce/502955/
  • Today, 27% of private sector workers have access to defined benefit plans, and 58% to defined contribution (Bureau of Labor Statistics) https://www.bls.gov/ncs/ebs/retirement_data.htm
  • IRAs only became popular starting in 1981; Roth IRA began in 1997, 401(k) in 1980; there isn’t a long track record of them working for people from start to finish
  • Need a diverse skill set and good financial literacy to be successful today – take charge of your life
  • Fortune: nearly two-thirds of Americans can’t pass a basic test of financial literacy, 5 point drop since 2009 (http://fortune.com/2016/07/12/financial-literacy/ ).  Example – calculating interest on a loan.
  • Dave Ramsey: “Growth stock mutual funds make 12%/year”; Suze Orman says to dollar-cost average, it’s nonsense. Past performance does not indicate future results.

 

Section 2: You can easily become over-concentrated in a few highly correlated asset classes; correlations rise in a crisis

  • What does diversification really mean?
  • Examples of alternative assets that offer real diversification
  • Diversification is NOT: (but these are a start)
    • Having more than one brokerage account or retirement account
    • Different stocks, like in an ETF, mutual fund, tracking a market or index
    • A bunch of ETFs or mutual funds, tracking different markets or indices; all paper assets
    • Having money denominated in various currencies
    • Different paper assets like bonds (beyond a certain point)

 

Section 3: “Leaving it to the experts” is leaving money on the table

  • If you need your savings to be there for you when you retire, you need to know what you’re invested in, and why
  • Very few of the real experts are managing public money
  • They cost too much, extract lots of fees out of you
  • Some are compensated based on revenue they bring to the firm
  • Narrow-minded thinking, limited skill/knowledge of these experts, not looking at big picture
    • Thomas Picketty on demographics: In Capital in the Twenty-First Century (2013/2014), he states that global output grew at an average annual rate of 1.6% from 1700 to 2012, 0.8% of which reflects population growth and 0.8% of which came from growth in output per person.  Growth averaged 3.0% from 1913 to 2012, but this was largely due to population growth and is not sustainable.
  • Robo-advisors are selling a lie
    • Same type of garbage mathematical models that were used to justify mortgage-backed securities before the 2008-2009 financial crisis
    • Short time horizon, static models, not accounting for enough inputs or qualitative factors
    • Might seem cheap but what are you getting?  They don’t offer anything other than a very short list of ETFs, like a 401(k) – no PMs, no digital currencies, no country- or region-specific ETFs, no way to use options to manage portfolio risk.
    • Wash sales – not integrated with other holdings outside of that robo-advisor – false sense of security.
  • More sophisticated strategies achieve better results
    • Hedge funds (before they grew too large) – http://www.businessinsider.com/hedge-funds-and-sp-500-nearly-identical-2013-8 Hedge funds outperformed the S&P 500 only slightly from 1993-2006, but with much less volatility and far smaller drawdowns.  Risk management matters.
    • Private equity – https://www.bloomberg.com/gadfly/articles/2016-05-11/private-equity-has-diminishing-returns – The Cambridge Associates US Private Equity Index returned 13.4% annually net of fees from 4/1986 to 12/2015, with a standard deviation of only 9.4% (vs. Russell 2000 at 9.9% return, 16.7% standard deviation)
    • Picketty research (Capital in the Twenty-First Century) – the largest university endowments consistently outperform the smaller ones.  These have the funds needed to employ sophisticated advisors and invest in alternative assets that improve portfolio returns and reduce volatility
    • You can learn and apply many of the same strategies these sophisticated investors use to manage multi-billion-dollar portfolios.  In fact, you have an advantage they don’t.

 

Intro music by audionautix.com

Find more episodes of the Torpedo Trading Podcast at this link

Continue Reading →