In any competitive field, the awareness of tells can provide a significant and enduring edge. Most people think of poker when they hear about tells.1 Is a player acting strong to encourage other players to fold? Does a player seem nervous when they throw their chips in the pot? Can any useful information about an opponent’s poker hand be gleaned from these actions?
Tells occur in many aspects of life and competition. For most sporting events, searching for tendencies in an opponent’s play is an integral part of game preparation. In the home arena, parents look for facial clues when interrogating a fidgety teenager as the youngster explains what she’s doing on a Saturday night.
Tells are an important source of feedback when trading the financial markets. I call these “market tells” to distinguish between the variety of tells that occur in other forms of competitive environments (more on this distinction later). A market tell is a powerful approach to sensing moments in time when market participants are not positioned correctly.
A simple example of a market tell is a stock that’s acting strong when it should be weak. Perhaps the stock is in an uptrend when extremely bearish news is released about the prospects of the company (such as a product recall). Unexpectedly, after a momentary dip on the news, the stock price continues to go higher. That’s a positive tell for future outperformance.
Properly identified, tells can get you out of a trade much sooner than waiting for a technical trend-following sell signal. Tells can help you identify future outperforming asset classes. They can provide positive feedback that a current trade is working. No matter what your trading discipline or time scale, searching for market tells is a great trading edge.
The more you clarify and develop your thoughts around market tells, the more confidence you’ll have to quickly jump on trades and to trade with high conviction and size. I began noticing market tells soon after I started trading in the late 1990s. In 2005, I decided to be more disciplined about it by keeping track of results. When I observed a tell, I printed out a chart and documented what I expected to happen, and then slipped the paper into my “market tells” folder. I also traded on this information, and over the next four years, avoided looking at the results.
In mid-2009, I checked to see how these predictions worked. The success rates for these trades at both the short and intermediate time scales were excellent. These results piqued my interest to further investigate and refine the use of market tells in my trading. In 2014, I performed yet another trade analysis, and in 2017, I find myself slightly reshaping my views while writing this blog.
Classification of Tells
To provide a framework for thinking about market tells, I’ll review various forms of tells. (more…)
In this blog I’ll examine the old “sell in May and go away” seasonal pattern associated with risky assets. It’s timely to consider this pattern since the markets are now entering the seasonally weak period. Furthermore, stock market performance has been relatively weak in a number of recent “strong periods,” such as in January 2016, November 2015 through January 2016, and November 2015 through April 2016, which often provides a foreboding tell of additional weakness during the traditional seasonal weak period of May through October.
Seasonality as a trading edge is also worth considering because trend following has become very trendy these days, with billions of dollars flowing into this discipline every year via managed futures funds. The problem with these flows is that the effectiveness of trend following diminishes as more assets are devoted to the discipline, since trend following is naturally capacity constrained due to high turnover (>200%) and the liquid demanding nature of trading. It seems that trend following is crowded.
At this point in time, it may be interesting to examine other market timing signals as an alternative way to add and reduce risk exposure. One such approach is seasonality, which is probably underutilized by the asset class trading community and thus might be more effective than trend following over the near term.
The seasonal pattern has been well known for decades – the stock market’s best period is from November through April, and its poor-performing period is from May to October. This is not the case every year, but on average this seasonal pattern has held up really well with stock markets around the world for decades.
Academics call this pattern the Halloween effect since the buy signal is generated by buying at the close on October 31 every year and the sell signal is on every April 30. What’s amazing is that seasonality has not been arbitraged away, even though the cost of implementing a seasonal trading system has been low since the 1980s. The old adage of “sell in May and go away” still works! (more…)
The beginning of the year marks the time when chief investment officers, market strategists and other chief prognosticators publish their top investment themes. Barron’s also publishes their much anticipated “round table” issues in mid to late January, which pull together top investors to discuss the state of the markets and where they see investment opportunities.
There are hundreds of firms producing research all the time, most of it free. The big Wall Street firms produce enormous amounts of content, but so do practically all buy-side investment management firms these days. If you’re not careful, combing through research reports for trading and investment ideas can absorb all of the day. There are also the independent firms such as Ned Davis Research, BCA Research and the Leuthold Group, which are very expensive, but provide lots of interesting and useful information for asset class traders.
Common sense suggests that you can’t just read the research, implement the trades suggested and expect to outperform the market. That would be too easy. This is the case even for costly research from the independents, because after all, tens of thousands of professional portfolio managers can afford these services.
For an asset class trader, reading research and market commentary is important, primarily so you understand what everyone else is thinking, become aware of crowded trades and estimate what information is already priced into the markets. Every once in a while, a new piece of information is gleaned or a new way of thinking about an asset class is found. If discovered ahead of most other market participants, this information can be the seed of a new trade.
At any point in time, there are industry thought leaders who seem to have a special knack for investing and trading the markets. When they speak, I pay careful attention because the probability of discovering a new trade idea from them is much higher than reading the everyday, run-of-the-mill content.
Generally, these thought leaders are very experienced, talented and rich. They’re not inhibited by career risk. Their motivations are aligned with us, because being right about an investment theme is the most important goal associated with speaking publically since the prediction is on the record. Contrast this motivation with that of research content providers and newsletter writers, where maximizing readership is the primary goal. (more…)
In the last blog, I discussed the trading edge associated with predicting investment flows. In this blog, I’ll provide examples using this trading edge to pick outperforming asset classes. Of course, this is a hypothetical exercise with the full benefit of hindsight, and as is often the case, flows may not be the only cause of the observed performance.
1995 to 1999
This era is widely recognized as the culmination of the 1982 to 1999 secular bull market in U.S. equities. As shown in Figure 1, it was a time when retail investors were obsessed with stocks as illustrated by the meteoric rise in CNBC viewership.1 Index investing was also becoming very popular, but at that time indexing solely meant investing in the S&P 500. Mutual fund managers were the investment stars of the era.
Figure 1. CNBC viewership history.1
Figure 2 from Ned Davis Research shows equity mutual fund net flows as a percentage of U.S. market capitalization from 1960 to present.2 These flows can be attributed primarily to retail investors, who throughout the 1990s powered a strong equity bull market. (more…)
In a nutshell, I want to own securities held by asset classes receiving large inflows of cash over an intermediate 6 to 12 month time scale, and avoid asset classes facing large intermediate-to-long term outflows.
Large intermediate-term inflows create essentially continuous daily net-demand that tends to bid up the price of the associated securities over time. Outflows do the opposite. We want to jump ahead of the buying and selling as long as the flows are significant and expected to continue over time. Inflows leading to outperformance can also be self-reinforcing as many investors are susceptible to performance chasing (flows lead to more flows).
Who’s on the other side of this trade? Long-term flows tend to be strategic allocation decisions made by large institutional investors, foreign investors, investment advisors/brokers and retail investors, in a manner that is typically price-insensitive. Nowadays the vast majority of investors spend their time deciding what investment manager to hire rather than what securities to purchase. When fund managers receive new money, they tend to buy what they already own. Not all funds do this, but most do, and index funds in particular must buy securities in exact proportion to the current portfolio.
While there are many excellent and talented investors in all the above groups, allocation decisions tend to be herd-like and heavily correlated with each other. These allocation waves can last for years as hundreds of institutional investors, millions of advisors/brokers and tens of millions of retail investors implement the latest fashionable portfolio allocation approach. The faster an asset class trader can jump on these trends, the more profitable this edge may become. (more…)