In the Market Tells – Part 1 blog, I introduced the concept of market tells as an enduring trading edge that can be used to enhance returns over the long term. Developing the ability to identify market tells and act on these signals takes practice. It’s important to keep track of trading results to get better and gain confidence to jump on these opportunities in size when they occur.

In this blog, I first clarify thoughts on a few instances when the market tell guidelines are not met. The most important guideline for identifying a market tell is the 80% rule, which states that to consider market action as unusual (and thus providing a market tell), the usual behavior must occur at least 80% of the time. Otherwise, it’s just too difficult to associate the unusual behavior with a market tell rather than normal market gyrations. Next, I’ll review three more market tell techniques that can be used to trade asset classes. I’ll close with some thoughts on crowded trades and implementation hints.

Initial Thoughts

On some days, one sector may be up while the rest of the market is down. If the behavior is explained by news, then this price action is totally normal. Even without news, this sort of divergence occurs often enough to consider it normal activity. If a security is illiquid, such as a closed-end fund, then this action might be correcting a stale price from the previous day, which is not unusual at all.

To contrast, if all risky assets are aggressively moving higher (such as when the S&P 500 is up 2%+ for the day), and one sector is flat, then this behavior is much more unusual and may be the basis of a market tell, especially if no news explains the behavior. However, we need to remember that the time scale of this edge is on the order of a day or two.

Watching how a stock or asset class reacts to news associated with a known announcement date (such as an earnings call or a central bank news release) is very difficult to use as a market tell. There is usually an enormous amount of trader attention to these known release dates, which probably means there’s no trading edge. Much of the news and all the probabilistic outcomes have been priced in before the announcement, which is another way of saying the pre-announcement price is set such that there is no edge in buying or shorting the security ahead of the announcement, or in fading or chasing the post-news reaction.

Finally, watch out for interpreting short-term market action when there’s a lot of unwinding of positions. For instance, at the first of the year, it’s best to wait a week before interpreting market action as hedge funds unwind their end-of-year trades. This sort of behavior can occur during bear markets also. This is a very chaotic time when a lot of unwinding is occurring – it’s a very difficult time to interpret market action versus any sort of playbook. Wait until the dust settles and stocks start moving in unison before interpreting market action.

Divergences and Market Tells

In discussing market tells, I’ve used the term “divergence” to describe local price action where an asset class’s price or relative strength line is diverging from normal expectations. Searching for divergences is a staple of technical analysis.1,2 In the past I have falsely interpreted a divergence as a market tell. These misinterpretations generally occurred during relatively quiet times in the market, usually during bull markets, when the 80% rule did not apply.

Ask a market strategist about divergences, and the first thing that comes to their mind is the case where the stock market is making new highs while some other risky asset class is moving lower. For instance, from mid-2014 to mid-2015, the S&P 500 was moving higher, while junk bond markets where moving lower. This isn’t supposed to happen, and such a divergence is often interpreted as a warning of future weakness in the S&P 500, leading to a convergence of the two markets.

A classic market timing approach based on divergences is the 100-year-old Dow theory, which compares price action of the Dow Jones Industrial Average (DJIA) and the Dow Jones Transportation Average (DJTA).1,2 When new highs in the DJIA are not confirmed by the DJTA, a divergence is formed by two markets that usually move in sync with each other. Dow theory suggests that this sort of divergence is a warning of future weakness in the DJIA. It hasn’t been a very reliable signal, but many analysts still take notice when this happens.

Divergences of this type can be watched with respect to all risky asset classes during bull markets. In 2015, there were many extreme divergences as the S&P 500 seemed to hold steady throughout the year, while international and emerging stock indexes, commodity prices and credit markets were all very weak.

Another example of this type of divergence is the underperformance of the Russell 2000 during a bull market. Do we interpret this behavior as a divergence, signaling future S&P 500 weakness, or as a tell that the Russell 2000 is acting weak when it should be strong? The market tell interpretation is incorrect, since the Russell 2000 often underperforms the S&P 500 during bull markets. It’s not unusual behavior.

The divergence interpretation implies future convergence, or a future trend change, while the market tell interpretation implies continued divergence. While there’s merit to both views, I want to emphasize that the market tell interpretation is not correct. Divergences of this sort occur too often during quiescent times such that there’s no unusual behavior to provide a basis of a market tell. As described in Market Tells – Part 1, we typically need a large sell-off before searching for market tells.

Market Tone

When the market tone for an asset class is positive, it seems to march higher day after day, relentlessly. No matter what the playbook says, the market seems to shrug off the “proper correlations” and all negative news. Sell-offs are very brief and mild in depth. Prices always seem to end the day higher no matter how the market opens.

At various times during the dramatic rise of the S&P 500 from its 666-bottom in 2009, it seemed to shift into this sort of “beast mode.” Often the chatter among portfolio managers was about how hated the rally was, that the market was due for a correction, yet that sentiment seemed to be an anecdotal tell that the path of least resistance was higher.

The time scale for each of these positive tells is brief, with a short half-life of a day or two. Yet, as more of these daily tells occur, the multitude of them within a weekly or monthly time frame creates a longer-duration market tell. An example of such a tell occurred in the last four months of 2010 when the Russell 2000 relentlessly outperformed the S&P 500 undeterred by multiple short-term sell-offs.

A negative market tone is the opposite of the above. When the market tone for an asset is negative, it seems to fall day after day no matter what the playbook says should happen. Good news is ignored; bad news is punished. Gold exhibited this behavior in 2013.

Emerging market stocks exhibited this behavior at various times during the five-and-a-half years they dramatically underperformed the S&P 500 since topping out in 2010. I overweighted emerging market stocks at various moments during this time period, but ultimately had to jettison the trade in the face of poor market tone.

A very recent example was the negative market tone associated with energy stocks at the beginning of 2017. In the face of a reigniting economy, bullish Trump election news, a positive seasonal period starting in February, and rising oil prices, energy stocks just seemed to want to go down every day versus the S&P 500. In January 2017, these stocks were not acting well day to day, as shown in Figure 1 with the SPDR Energy ETF (Symbol: XLE) in the orange bars versus the S&P 500 ETF (Symbol: SPY) with the purple line. The blue line in the bottom panel is the relative strength line of XLE versus SPY.

When oil prices and the S&P 500 were higher for the day, XLE would barely outperform. When oil prices were lower for the day, XLE dramatically underperformed SPY. In addition, there was no news to explain the action. By February 10, the S&P 500 was making new highs, and oil was close to a new high, yet the relative strength of XLE versus the S&P 500 was nowhere close to a new high. By February 15, marked by the white crosshair, the new relative strength low triggered a market tell sell signal (if you hadn’t sold well before that moment). Eventually, on March 8, oil prices cracked, putting further pressure on energy stocks.

Figure 1: Poor market tone associated with energy stocks versus the S&P 500 in early 2017.

Michael Marcus, interviewed in Jack Schwager’s Market Wizards book, talks about using market tone in his trading.3 On page 31, he talks about noticing in late 1978 the dollar acting mysteriously strong, and the strength couldn’t be explained by any known information. They eventually jettisoned their short-dollar positions right before Jimmy Carter announced a dollar support program over the weekend.

Security Acting Strong or Weak in the Face of Persistent or Compelling Fundamental News

As discussed above, deriving a market tell from a news event is generally difficult, especially if the timing of the news release is known ahead of time. Common news events include earnings announcements, economic data releases, central bank policy announcements, election results and new legislation.

Markets are generally excellent at properly discounting the odds associated with these announcements such that better-than-expected news will cause prices to pop, and worse-than-expected news will trigger falling prices. After the pop or drop, it’s not obvious whether the market’s reaction was an underreaction to be jumped on or an overreaction to be faded. I’m sure there are talented traders who can parse through these sorts of events as part of their trading discipline and identify market tells. I’m not one of those traders.

Yet we can still employ such an approach when the market reaction seems so out of character that it’s compelling to act upon. In this case, the magnitude of the news event is so large that an unusual reaction is something to take notice of.

Another version of this market tell is an asset class that’s acting unusually strong in the face of persistent day-after-day and week-after-week bad news. In this case, even if each of these news events is not large enough to define a market tell, the positive action in the face of the multitude of these news events suggests underlying strength that can be bet on.

This latter version is like the tells associated with good market tone, where a bunch of little and short-timescale tells can be aggregated to constitute a market tell over a longer time frame. Alternatively, an asset class that can’t seem to outperform in the face of repeated good news suggests a market tell of future weakness.

This was gold in 2013 and 2015. Figure 2 shows the SPDR Gold ETF (Symbol: GLD) as the gold bars on the chart, and the U.S. dollar index (Symbol: DXY) as the purple line. Gold’s secular peak occurred in 2011, yet many traders and investors were extremely interested in gold as a hedge in the post-banking crisis world, expecting the 2011 high to eventually give way. Gold put in a lower high in September 2012 right around a very bullish announcement by the U.S. central bank introducing QE3. Then, during the first quarter of 2013, gold struggled to move higher even as the Japanese indicated their intention to dramatically weaken the yen at all costs. It appeared that the world was entering a period of competitive devaluation, which should be very bullish for gold. However, gold could not make any headway in the face of all this good news and a relatively benign environment for the U.S. dollar. Gold eventually collapsed below 2012 lows.

In 2015, gold struggled even though more and more countries were issuing bonds at negative interest rates for the first time in human history. If this couldn’t get gold going, then nothing else could. The German two-year yield dipped below 0 in August 2014 for the first time. The Swiss unpegged their currency from the euro in late 2014 and let their rates go severely negative. Europe also greatly expanded their QE program in January 2015. Many other countries followed suit throughout 2015 as more and more bonds drifted into negative territory. Once the dollar peaked in March 2015, gold should have been strong throughout 2015, yet lost value versus all major currencies, including the euro and yen.

At some point in 2015, a market tell was triggered, indicating further weakness on a half-year time scale.

Figure 2: Gold and U.S. dollar index from 2011 to 2016.


Market Reaction to Truly Unexpected News

Watching how the market reacts to truly unexpected news may provide a tell about what asset classes are strong and weak. Crisis events such as an assassination, natural disaster, terrorist event or a flash crash can provide useful market tells in a manner discussed in Market Tells – Part 1. These events are completely unexpected and generally have no lasting effect on the world economy. In Jack Schwager’s book Hedge Fund Market Wizards, he interviews Scott Ramsey on using the market’s response to unexpected events as a signal of future strength and weakness (see p. 116).4

Other shocks may have positive ramifications for one group of asset classes, and negative ramifications for others, which can complicate such an analysis. Care must be used to sort through the market action from what should be happening with respect to the unexpected news. The Trump election in November 2016 was a shock to the markets, even though the election date was known ahead of time. Perhaps “the shock” was that the market rocketed higher when all the pundits expected a huge plunge. This was a very difficult time to search for tells since some risk-on assets did very well (Russell 2000 and financial stocks), while other risk-on asset classes were hurt by the news (such as emerging market stocks and currencies). This was a time when interpreting market action to find market tells was very tricky.

The Brexit vote in June 2016 was a similar unexpected event, again in part because the pundits expected a sharp drop in risky assets if the U.K. voted itself out of the European Union. An unexpected central bank policy change can also provide a shock to the markets. For example, in January 2001, the Fed suddenly reversed monetary policy from tightening to easing with a surprise mid-meeting rate cut. Not every shock will produce tells, but it’s worth using the next month’s market action to provide clues as to what asset classes are currently favored.

At the individual stock level, unexpected news can also be used as a potential market tell, especially for those who know the ins and outs of a stock or industry. If a stock performs very poorly after a bullish Barron’s article, that is a potential short term tell. For instance, Suncor (Symbol: SU) did not respond well to a bullish March 2013 Barron’s article, which suggested future weakness. The market’s reaction to the unexpected Intel chip defect in 1994, and its resolution, fix and resulting earnings charge from November through January 1995, was a sign of strength. Intel doubled the next year.

Market Tells and Crowded Trades

I discussed crowded trades in a previous blog. We want to avoid crowded trades and crowded asset classes because by the time too many traders have joined the party, the investment theme is very likely completely baked into prices. Once a trade is crowded, it becomes more volatile and correlated with equities, especially on the downside due to enhanced contagion risk. The odds associated with trade success, or the expectation of future risk-adjusted outperformance, is 50:50 when a trade becomes crowded.

The crowded-trade behavior occurs because too many traders are leaning on one side of the trade, counteracting the forces in favor of the trade. We have a similar explanation for why market tells work – a brief moment in time when market participants are leaning the wrong way in aggregate. The primary difference between the crowded trade effect and the market tell effect is that the market tell is underfollowed by asset class traders, as discussed in the previous Market Tells – Part 1.

We must account for the “crowded trade” playbook when searching for unusual behavior to be used for a market tell. The playbook for crowded trades is different. An asset class that fails to go higher on good news could be a market tell for an asset class that’s currently underowned by traders and hedge fund managers. Yet in a crowded trade environment, this sort of behavior happens all the time, so it’s not unusual enough to be the basis for a market tell.

After a long run of outperformance, we should expect to see an asset class held by many traders. It’s likely crowded, and the playbook for how it will react to better than expected news is different than an asset class that’s completely off the hedge fund radar.

Implementation Hints

Using market tells to find trading edges is an art that takes practice to master. I’ve learned so much from writing this blog in clarifying my views on what works and what doesn’t. Market tells should work with all trading and investment disciplines, although we should expect that each discipline and portfolio manager will be sensitive to different market tells.

As a trader becomes very experienced, any highly unusual behavior that makes no sense with respect to all information (news and price action) is worth heeding. Almost by definition, if a market veteran hasn’t seen a certain behavior ever, or in a long time, then the behavior probably satisfies the 80% rule.

Here are some hints to get better at implementing this trading edge.

Follow the market daily

Read the market news and try to explain the day’s moves. Sometimes there’s no explanation, and that’s okay. The point is to gain a feel for what the market cares about. Journalists are always trying to tie market movements to some sort of fundamental news. Yet there are many reasons for market movements that are not news-driven: technical breakouts, a mismatch in selling/buying pressure, a trade is crowded, a research note is released or a collapse is occurring in another major market.

Also note that just because you can explain movements after the fact, doesn’t mean you have a trading edge. Follow a couple of trading websites to get their views on why the market is doing what it’s doing. Sometimes the newspaper will quote a money manager or trader. Pay attention to why he or she thinks the market is reacting the way it did. Note correlations between the various asset classes. Short-term correlations change over time, and these changes reflect what the market currently cares about.

Do your best to learn the market playbook

Read all sorts of books on how to trade the markets – technical analysis, managing portfolios, stock picking, asset allocation, etc. Study financial market history. Be able to explain the relative performance of various asset classes over the intermediate term. The more you know about the various ways to trade the markets and find alpha sources, the better. Be aware of regime shifts in the market, and the possibility of a playbook change. After the hedge fund proliferation period from 2002 to 2007, the crowded trade playbook became very important. After the 2008 financial crisis, the playbook incorporated a variety of new themes such as quantitative easing, negative interest rates, financial repression, retail investors exiting the market, the rise of financial advisors and ETFs, Reinhart and Rogoff’s book This Time Is Different, and many more.5

Keep track of results

Much like the motivated selling trading edge, the market tells trading edge is very difficult to back test. Thus, keeping track of results is required to receive the crucial feedback on using this trading edge.

When you observe a market tell, write down the following information when you put on the trade:

  • Date
  • Description of market tell
    • What’s acting strong or weak?
    • 80% rule assessment (show backtested results, or provide an explanation of why this is a rare event)
  • What is expected to happen (X should outperform Y)
  • Time scale (X should outperform Y over Z months)
  • Is it widely followed?

Then, periodically evaluate the results and search for improvements. The goal is to improve your skills at identifying market tells and jumping on these reliable signals as early as possible.




  1. Pring, M.J., Technical Analysis Explained, Third Edition, 1991.
  2. Murphy, J.J., Technical Analysis of the Financial Markets, 1999.
  3. Schwager, J.D., Market Wizards: Interviews with Top Traders, 1989.
  4. Schwager, J.D., Hedge Fund Market Wizards: How Winning Traders Win, 2012.
  5. Reinhart, C.M. and Rogoff, K.S., This Time is Different: Eight Centuries of Financial Folly, 2011.  



The content contained within this blog reflects the personal views and opinions of Dennis Tilley, and not necessarily those of Merriman Wealth Management, LLC. This website is for educational and/or entertainment purposes only. Use this information at your own risk, and the content should not be considered legal, tax or investment advice. The views contained in this blog may change at any time without notice, and may be inappropriate for an individual’s investment portfolio. There is no guarantee that securities and/or the techniques mentioned in this blog will make money or enhance risk-adjusted returns. The information contained in this blog may use views, estimates, assumptions, facts and information from other sources that are believed to be accurate and reliable as of the date of each blog entry. The content provided within this blog is the property of Dennis Tilley & Merriman Wealth Management, LLC (“Merriman”). For more details, see the Important Disclosure.

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