Friday, August 22, 2014

A Look at New Highs and Lows During the Stock Market Rally

Above we see a different measure of stocks making new highs vs. new lows than the usual 52-week figures posted by the exchanges.  This measure takes all common stocks and looks at the number making fresh three-month highs minus those making fresh three-month lows.  (Data from the Barchart site).

In general, the new highs top out ahead of price during intermediate-term market moves and new lows either lead price lows (at important bottoms) or are coincident with those lows (at corrections).  Note how we recently peaked in new highs following the August lows; note also how the current levels are well below the levels recorded at the July peak, despite new highs in SPY.  This partly reflects continued relative weakness among small cap shares, with the Russell 2000 Index well below its March and July highs. 

Also lagging July highs are energy shares (XLE), consumer staples stocks (XLP), industrial issues (XLI), and utilities stocks (XLU), as well as homebuilders (XHB) and retail stocks (XRT).  Thus far the stock market rally has shown itself to be durable--and increasingly selective.

When is the Stock Market Overbought and Oversold?

Abnormal Returns posted a few particularly good links yesterday; check out the study of how returns early in the market day predict those later in the day.  I'll have more to say about that topic later this weekend, as it dovetails nicely with recent observations regarding who is participating in markets.  Also worth a read is Adam Grimes' post regarding the dark side of technical analysis.  A lot of market folk lore falls short of wisdom.  As we saw a while ago, cognitive biases have a way of entering many forms of market analysis--even those that appear to be rigorously quantitative.

The bottom line for the above posts is that there are worthwhile patterns out there in markets, but it is hazardous to outsource the identification of those.  Nothing substitutes for doing the work yourself and seeing, in your own experience, what works and doesn't work.  That not only yields knowledge, but also produces the genuine confidence required to trade noisy and risky financial markets.  It's tough to hold an position through normal adverse movement when the idea is not truly your own. 

Let's perform a data exercise that challenges what we know.  When is a market overbought or oversold?  Many market indicators included in data services will highlight those levels, perhaps above 70 and below 30 in an oscillator that moves between zero and 100.  But do we really know that those are meaningful levels?

I went back to 2006 and took a look at the percentage of SPX stocks trading above their 5-day moving averages.  (Data available via Index Indicators).  I broke the market down into quartiles based upon the day's closing level of VIX.  Here's what we get:

The lowest volatility market quartile averaged 59% of stocks above their five-day moving averages, with a standard deviation of 19.  The next lowest volatility market quartile averaged 54% of stocks above their moving averages, with a standard deviation of 24.  The third volatility quartile averaged 51% of stocks above their moving averages, with a standard deviation of 27.  The highest volatility market quartile averaged only 45% of stocks above their moving averages, with a standard deviation of 32.  

We know that volatility has a directional component in the stock market, so the averages are not so surprising.  Note, however, those standard deviations.  If we define overbought and oversold as fixed indicator levels--say, 30% is oversold--then we're accepting a reading of about half a standard deviation in high volatility regimes and a reading of almost 1.5 standard deviations in low volatility periods.  

At the recent lows, we got to a point where about 10% of SPX stocks were trading above their five-day moving averages when VIX was trading around 17.  That was a much rarer occurrence than if the same reading had occurred with a VIX north of 30.  Same indicator reading, two different meanings.

What is a warm day?  45 degrees on the Fahrenheit scale is a warm day in Connecticut winter and a cool day in the summer.  Context matters:  what is overbought and oversold highly depends upon the market season.  An important part of interpreting any piece of market data is knowing the season you're in.

Further Reading:  Honing Your Trading Process

Thursday, August 21, 2014

Handling the Adversities of Trading

How do you handle adversity in trading:  when trades move against you, when drawdowns accumulate?  One of the interesting observations from the Market Wizards interviews was that many of the great traders had undergone periods of great loss prior to their success.  Hardships prepared them for an extraordinary career by teaching them important lessons about risk management, diversification, and sustaining psychological self-control.

How do traders trading today's markets handle adversity?  An excellent set of interviews posted by Richard Chignell on the Embrace the Trend site captures, in the traders' own words, how they deal with the emotions and challenges of trading.  The interviews also illustrate the great diversity of trading styles out there.

Among the gems in the interviews is the running from fire analogy of Charles Kirk from The Kirk Report; the use of visualization exercises from Mike Bellafiore of SMB Capital; the process focus of David Blair from The Crosshairs Trader; and Derek Hernquist discussing the importance of trade blueprints.  An interesting common theme among the traders was the value of physical exercise in managing the pressures of trading.

Where my perspective would differ from that of many of the interviewees is that I would distinguish between negative emotions resulting from particular losing trades and those that are more ongoing, resulting from failure to adapt to changing markets.  When a trader has a demonstrable edge, following plans and sticking to a replicable process will make the most of the positive expected return.  When a trader's edge erodes, those same actions can lock in frustration and negative results.  Sometimes traders experience hardship because they need to change their destinies.

Further Reading:  Adapting to Change

Institutional Participation, Momentum, and the Thorny Question of When to Exit Winning Trades

One of the most difficult challenges in trading is knowing when to exit a position, particularly a profitable one.  Loss limits you can define firmly, risking no more than a given amount of your capital per idea.  Profit targets are a bit more elusive, however.  Will the move in your favor continue to make you money, or will it reverse and erase a potential profit?

My recent efforts to separately define buying and selling power in the stock market were a first effort to capture when markets, in the near term, were more likely to display momentum (continuation of price movement) versus value (reversal of price movement) effects.  In a nutshell, I found that momentum to the upside was positively correlated with buying activity (the upticking of a broad range of stocks).  Reversals typically followed from high levels of selling activity (the downticking of a broad range of stocks).  More recently I've been studying whether buying/selling across a broader range of shares is more predictive of momentum and value than across a smaller number of dominant large caps.  More on that topic to come...

What I find interesting about the upticks and downticks, when disaggregated, is that they are typically occurring at precisely the same time.  When I look at the upticking and downticking second by second, an unusual number of stocks will tick in the same direction at the same time.  This reflects the buying or selling of baskets of stocks, most often either as outright directional bets or to bring futures prices in line with the cash index.  Either way, small traders and market makers in individual shares are not typically buying and selling broad baskets of stocks.  Such basket execution is a footprint of larger, institutional involvement in the market.

Proceeding on that logic, I constructed a measure of total upticks and downticks on a moment to moment basis.  This measure simply looks at the total amount of uptick/downtick movement across stocks and doesn't care whether the ticks are more to the upside or downside.  The idea is that more total ticking is a reflection of greater institutional participation.  If large (and largely directional) participants are more present in a market, I would expect market moves to have a greater odds of extending.  Without such participation, I would expect directional movement to more often run out of gas.

From February, 2012 forward--the period of time in which I assembled moment-to-moment total ticking--I found 165 trading days in which SPY moved more than 50 bps (half a percent) or more to the upside in a trading day (prior day's close to current day's close).  Three days later, the average market gain was +.14%, with 107 occasions up and 58 down.

If we simply break down those occasions by median split based on total ticking, the next three days after a high institutional participation winning day averaged a solid gain of +.26% (55 occasions up, 28 down).  If the winning day occurred with low institutional participation, the next three days averaged a gain of only +.02% (53 occasions up, 29 down).  In other words, days following a solid gain were as likely to rise when institutional involvement was low vs. high, but the degree of follow through was so much greater when institutions were active that essentially all momentum effects (in terms of price movement) occurred at those times.

This is a nice example of the importance of, not only how markets move, but who is in the market.  Many valuable research questions follow from this kind of analysis.  For instance, does institutional participation early in the day session help predict movement for the remainder of the trading day?  Does institutional participation help to predict, not only general market movement, but the movement of individual stocks and sectors?  In trading, as in other high performance fields--from cycling to warfare--we increasingly find quantitative tools supporting and informing discretionary decisions.  The popular mantra to follow one's trading plans means little if those plans are uninformed.

Further Reading:  Factors That Affect Short-Term Stock Market Movement

Wednesday, August 20, 2014

Fresh Insights from the Blogosphere

One thing I find among successful money managers and traders is that their idea wheels more than keep pace with the changes in markets.  Here are a few sites you may not be familiar with that might contribute to your idea wheel velocity!

James Clear writes clearly and insightfully about elite performance.  Check out his post on the trajectory of success among creative geniuses; also his post on getting past procrastination; and what we can learn about success from Richard Branson. 

*  Check out the unique industry perspectives from Simple Alternatives, including a great deal of performance on hedge fund performance; the falling correlations among stocks; and the relative performance of various hedge fund strategies.

*  Lots of insights from James Altucher, including what you need to become a great leader; lessons learned from Shark Tank; and Warren Buffett's approach to stock picking

The more I scour the blogosphere, the more I'm impressed with the sheer scope of information and perspective out there.  It's difficult to become stale when you're regularly exposing yourself to fresh ideas!

Building Your Pyramid of Success

Here is a great article on the "pyramid of success" taught by legendary UCLA basketball coach John Wooden.  Coach Wooden spent years honing the pyramid, but the cornerstones of "industriousness" and "enthusiasm" always remained constant.  A key concept is that each level builds on the one below it:  building your foundation of industriousness, friendship, loyalty, cooperation, and enthusiasm is necessary toward maintaining self-control, alertness, initiative, and intentness.  Those, in turn, form the foundation for condition, skill, and team spirit, which anchor poise and confidence--and ultimately competitive greatness.

"A key ingredient in stardom," Coach Wooden emphasized, "is the rest of the team."  Notice how many of the success elements in the pyramid relate to interpersonal strengths.  At the center of the pyramid is "skill".  Skill is central to success, and yet does not find expression in competitive greatness unless it is supported by self-control, industriousness, initiative, alertness, and intent.

A great exercise is to take the 15 elements of success in the pyramid and use these for a report card.  How would you score yourself in each of these categories?  Which are your greatest strengths?  Which are your weakest areas?  How could you shore up those weaknesses in a way that will make you a greater trader?  Self-assessment is always the start of goal-setting, which then can guide deliberate practice, which really is the process uniting the pyramid categories.  The pyramid is not a static set of traits, but a dynamic group of activities that are evident in every practice session, every game.

How do you begin working on your pyramid of success?  Check out James Clear's excellent post on making marginal, 1% gains.  Becoming just slightly better at a number of things, over time, creates a compounding improvement that can produce world champions.  Clear emphasizes the idea of "never miss twice":  if you allow yourself to make mistakes but don't allow yourself to repeat them, compounding can never work against your development.  The complementary principle is "always hit twice":  when you do something well, make sure you repeat it.  Becoming better in the long run is a function of many days of becoming slightly better.

Further Reading:  Insights and Inspirations From Legendary Basketball Coaches

Tuesday, August 19, 2014

When Do Overbought Markets Reverse?

Recent posts have focused on the role of sentiment in short-term market returns.  Let's take a look at strong markets and what we can learn from stretched sentiment.

It's common for traders to assume that markets that have risen meaningfully in a short period of time, like the current stock market, will either continue in their recent direction (momentum) or reverse because they are "overbought".

As of yesterday, we had over 80% of SPX stocks close above their 3, 5, and 10-day moving averages (shoutout to Index Indicators for the data).  Since 2006, we have had 132 occasions of such strength.  Two days later, the average change in SPX has been -.37%.  That compares to an average two-day gain of +.08% over that same period.  On the surface, it appears that "overbought" markets lead to "mean reversion".

If, however, we break down those 132 occasions by median split based upon the equity put-call ratio, a different pattern emerges:  Overbought markets with low put-call ratios (bullish sentiment) have averaged a two-day loss of -.68%.  Overbought markets with high put-call ratios (bearish sentiment) have averaged a two-day loss of only -.06%.  In other words, almost all of the weakness seen immediately following strong markets has occurred when overbought has been accompanied by stretched bullish sentiment, which is what we're seeing as of yesterday's close.

It's a nice illustration of how context matters:  The same price movement in different environments of market psychology can lead to very different forward price paths.

Further Reading:  Finding Trades When Sentiment is Stretched

Paying the Tuition for Your Intuition

Here's a shoutout to worthwhile observations about intuition from Abnormal Returns.  A key concept from that post is that intuition is not a mystical given:  it has to be earned.  Per the Einstein quote, the rational mind is a faithful servant to the degree that it accesses and assembles the raw materials for creative processes.  Analysis precedes synthesis:  we break things down in order to reassemble them.  Before the pianist delivers an inspired performance on stage, there is much work done on finger technique, expression, and cadence.  The creative chess move follows from hours of board study and play.  Whenever we see gifted intuition, we can identify the tuition paid in terms of deliberate practice.

A good illustration of this is that I do not have any productive inspirations about domains with which I have no familiarity.  No light bulb goes off over my head regarding such fields as ice skating or theoretical physics.  On the other hand, I have spent countless hours studying the short-term action of the stock market.  It is rare that I don't have a week where I think of some new way to parse data and make sense of market behavior.  

The key concept here is that intuition is earned with disciplined effort.  And disciplined effort typically involves immersion in decidedly uncreative work.  Medical students first learn the mechanical processes of taking down a history and physical before they are able to assemble those pieces into an insightful diagnosis.  Indeed, what one finds in professional education is similar to what occurred during the apprenticeships of great artists:  first there is a mimicking of the master and only later are there elements of originality that appear in the reassembly of the units of learning.  There can be no creative reassembly without the detailed labor on the individual pieces.

So what bridges the transition from analysis to synthesis, from working on the pieces to assembling a new whole?  Very often, the mindset that is necessary for the servant work--intense focus and immersion in observation and doing--is not the one that is necessary to receive the sacred gift described by Einstein.  Check out Zabelina and Robinson's study of using a childlike priming to inspire creativity.  A short exercise of thinking like a child stimulated subsequent creative thought.  Often one will hear researchers talk about "playing with ideas".  It may well be that the hard work of analysis requires free play before it yields fresh syntheses.  If, as Josh Brown hypothesizes, it's getting what's in your head into your gut that differentiates exceptional returns from mediocre ones, the process of play may be every bit as important as our work processes.

When an experienced trader has trouble adapting to changing markets, doubling down on work effort may not be the solution.  Ironically, that trader may need more play time with ideas.  Conversely, the struggling market newbie needs less time winging trades from the gut and more time mimicking the experts.  In trading as in poker, those who fail to pay the tuition required for intuition are merely into wishin'.

Further Reading:  The Role of Intuition in Trading Decisions

Monday, August 18, 2014

What is the Best Style for Coaching Yourself?

Thanks to Bella of SMB for the heads up on a worthwhile article regarding the pros and cons of fierce vs. friendly coaching styles

When you consider that all of us, as participants in a performance activity, engage in self-coaching, this issue takes on distinct relevance.

When you make mistakes, lose money, or simply fail to perform well, how should you deal with yourself?  

Some performance professionals take a fierce style and are unusually hard on themselves.  Dan Gable is an excellent example of ferocity as athlete and coach. 

Other elite performers stress a more supportive, teaching approach to coaching, as the fierce style can come across as hostile.

Ryan and Deci suggest that three factors are crucial to motivation:  autonomy, competence, and relatedness.  Think of employees at a company:  those that experience a degree of independence in their decision-making; those who feel competent at what they do; and those who are closest with co-workers are most likely to be satisfied and motivated workers.  

At a self-coaching level, we can ask the question:  How well do we keep ourselves motivated?  How well do we manage ourselves?

An overly fierce style could easily interfere with the sense of competence, as in the case of unhealthy perfectionism.  Conversely, an overly friendly and supportive approach could fail to promote the challenges that would contribute to the sense of autonomy as well as competence.  

Think of a personal trainer working with you in the gym.  He or she can't be a total dictator or you'll never return for workouts.  Conversely, that trainer at times will have to push you when you don't feel like making the extra effort.  "I care so much about you that I'm going to push you beyond your comfort zone," is an important integration of directive and supportive coaching styles.

Self-coaching should provide daily experiences of success and gratification (supportive) as well as daily challenges and discomfort (directive).  In that sense, good self-coaching is not so different from good parenting, promoting regular experiences of autonomy, competence, and relatedness.  A great way to assess a trading journal is to review the entries from a self-coaching perspective and gauge the degree to which you are providing those experiences for yourself.  Each of us is our own employer.  How well do we keep ourselves motivated, satisfied, and productive?

Further Reading:  Coaching Ourselves for Trading Success

Sunday, August 17, 2014

What are the Factors That Drive Short Term Returns in the Stock Market?

What are the factors that drive short-term returns in the stock market?  

It's an important question for short-term traders obviously, but also for longer-term market participants, as the execution of one's positions ultimately has a significant role in determining profitability.  This is especially true in situations where longer-term participants face a mandate to keep losses at a minimum.  The demands of high Sharpe-ratio trading often necessitate shorter-term management of the price paths of one's trades, making entry and exit execution a meaningful part of trading returns.

I consistently find that traders do not think intelligently about short-term market returns.  They either make the blanket assertion that short-term returns are random, or they attribute short-term returns to single sources without having tested those sources.  So, for instance, short-term returns may be attributed to particular chart patterns or simply chalked up to loosely defined notions such as "trend".  When tested, those explanations can be shown to be weak:  very often, they apply to some market periods and not others.  

As for the notion that short-term returns are random, that falls by the wayside when one has directly observed and worked with successful short-term market participants.  They may be rare, but their superior returns can be documented across hundreds if not thousands of trades per year, year after year.  As one of the few trading coaches that has worked for trading firms on a full-time basis, with full access to traders' returns, I can personally verify the existence of persistent market talent/skill among an elite set of short-term traders.

Here is where short-term trading can learn from the research into longer-term investment.  That research suggests that longer-term market returns can be explained as the interplay of a number of factors.  Bender et al identify six factors that explain longer-term market returns based upon considerable academic research.  Capturing returns from these factors is an important principle behind asset management and can produce returns well in excess of active management.

The recent post on teasing apart buying and selling activity in markets suggests that buying and selling may separately account for two factors that account for short-term returns:  momentum (the tendency of price direction to persist) and value (the tendency of price direction to reverse).  I am currently operating with a third factor in mind that we can call "rotation".  This is a factor in which trader/investor funds are shifted from some market groups to others with relatively little impact upon broad market averages.  

The challenge of short-term trading is that all of these factors yield positive returns over time, but none of them produce positive returns across all market periods.  Traders who identify with a single factor inevitably perform poorly when other factors are dominant, resulting in frustration.  This is a great example of a situation in which a logical trading problem is mistaken for a psychological one.  A worthy challenge is understanding the range of factors that impact short-term returns, so that trading style can flexibly accommodate those regime shifts in which one group of factors takes over from another.

Further Reading:  The Momentum Curve

Saturday, August 16, 2014

Measuring Buying and Selling Power in the Stock Market

Recent posts have focused on improved versions of standard market indicators, including sentiment, Bollinger Bands, VWAP, and ticks.  One of my most challenging projects, however, has focused on the creation of measures of buying and selling pressure in the stock market.  My goal in creating this measure was to follow an intuition and treat supply and demand as separate, independent dimensions, rather than a single blended measure.  

My alpha version of this measure disaggregates moment to moment upticks and downticks across the broad list of NYSE stocks.  Unlike the standard NYSE TICK, which monitors upticks minus downticks across stocks, the new indicator measures upticking and downticking separately on a high-frequency basis and then assembles them into measures of buying and selling interest.  From 2012 to the present, the resulting measure of Buying Power correlates with Selling Power by -.22.  In other words, less than 5% of Buying Power can be explained by Selling Power and vice versa.

This is important because it suggests that buyers and sellers are different entities, behaving relatively independently.  We can have days in which buyers and sellers are both active; days in which buyers are active and sellers are not; days in which sellers are active and buyers are not; and days in which both buyers and sellers are inactive.  This differentiation opens the door to unique analyses, in which direction and volatility can be tracked as a function of the interplay between buyers and sellers.  

For example, the market might move to new highs because of a surplus of Buying Power or because of an unusually low level of Selling Power.  Those scenarios have led to different price paths over the near term.  When we made a price high in the latter part of July, Selling Power was very low, but Buying Power was also well off its peak.  The market held up, not because buyers were aggressive, but because sellers were on the sidelines. 

Here's another interesting observation:  Since 2012, when Selling Power has been in the top half of its distribution (high levels of selling pressure) over a four-day period, the next four days in SPY have averaged a gain of .45%.  When Selling Power has been in the bottom half of its distribution (low levels of sellers) over a four-day period, the next four days in SPY have averaged a gain of only .04%.

Also since 2012, when Buying Power has been in the top quartile of its distribution (high levels of buying pressure) over a four-day period, the next four days in SPY have averaged a gain of .43%.  All other occasions averaged a gain of only .18%.

Together, these findings invite the hypothesis that stock market strength can be attributed to two factors:  momentum effects from high levels of buying and value/mean reversion effects from high levels of selling (capitulation).  By independently parsing Buying and Selling Power, it may be possible to better anticipate momentum and reversal in the market.

Of course, much more investigation remains, especially over longer periods of market history.  There are also interesting questions that remain to be addressed, such as Buying and Selling Pressure measures for other indexes and for individual stocks and ETFs.  

My initial work in this area suggests that it is fertile ground for the development of new and valuable market measures.  For instance, during the recent market decline, Selling Pressure hit a peak several days before we hit the ultimate low price in SPY; that is also when Buying Pressure bottomed.  Price continued to make new lows, but the dynamics were already shifting away from Selling and toward Buying.  With the market bounce on August 8th, Buying Power absolutely swamped Selling Power and the conditions were set for momentum continuation.

I will be updating this research--and its application--in future posts.  It's a great example of how one of the best strategies for adapting to changing markets is to adapt quicker.

Further Reading:  When is There Significant Buying and Selling in Stocks?

Friday, August 15, 2014

Tomatoes and Fruit Salads: What Predicts Day Trading Success

Does day trading skill really exist?  The recent post took a research-based look and found evidence both for the existence of day trading skill and for its rarity. 

What might account for day trading success and failure?  Another valuable study was conducted in the Korean futures market, with the Kospi index.  Ryu studied the day trading results for the Kospi over a more than three year period.  He found that 91% of the day traders were domestic individuals and these traders accounted for over 85% of all transactions.  Foreign institutional day traders and domestic institutional day traders made up most of the remainder of the activity.  On average, these institutional day traders traded much more frequently--with much larger average volume--than the domestic individuals.

Ryu found that the domestic individual traders lost significant money on average.  He refers to them as "uninformed and noisy".  Conversely, the institutional day traders made money on average.  Perhaps most interestingly, domestic individual traders who traded more lost more money; they seemed to be overconfident.  Foreign institutional day traders who traded more made more money.  They seemed to be exploiting a genuine edge.  Ryu surmises that:

"This implies that foreign day traders and money managers are generally better equipped in terms of their wealth, sophistication, specialty, and trading experience than ordinary day traders." p. 9.

What does this mean?  Perhaps this:

Resources make a difference.

Knowledge matters.

Experience counts.

Most of all, wisdom is crucial:  the ability to act on the awareness that sometimes, the edge conferred by knowledge and experience simply isn't there.  There's no edge to putting a tomato in a fruit salad.

Consider this example of successful day trading from someone I knew years ago:  He cultivated relationships with the sell side and had access to the major forecasts for earnings releases for companies.  He also polled money managers and equity sales professionals quarterly.  This told him the "true consensus" for each release.  He tested which earnings releases were movers of stocks based upon several factors, including deviations from consensus.  Some deviations were worth trading on a same day basis; others provided a longer-term edge.  For the day trades, he and his team developed a rapid execution algorithm that entered orders into various stocks as soon as releases came out and deviations from consensus could be calculated.  Those trades were always closed out by end of day.

He was a successful day trader.  He had specialized knowledge and a clearly defined edge.  He also had the wisdom to make bets only when the consensus was off sides and all other factors lined up in his favor.  Many days he did not trade.  That alignment of knowledge and wisdom was the best predictor of his profitability.

Success is possible in trading, but not, as Ryu notes, to the uninformed and overconfident.

Further Reading:  Tackling the Challenge of Day Trading

Thursday, August 14, 2014

What Proportion of Daytraders Actually Makes Money?

I strongly recommend reading the research study of speculator skill from Barber, Lee, Liu, and Odean.  They studied the returns of daytraders over a 15-year period, the largest sample I am aware of in such a study.  Their study is also unique in that it looks at the ability of traders to make money in a second year after having made money in the first.  

The authors conclude that "there is clear performance persistence."  The very top traders who make money net of fees tend to continue to make money going forward.  The traders who lose money tend to continue losing money.

Here is the most important conclusion, however:

"In the average year, 360,000 individuals engage in day trading.  While about 13% earn profits net of fees in the typical year, the results of our analysis suggest that less than 1% of day traders (less than 1,000 out of 360,000) are able to outperform consistently." (p. 15).  

In other words, 87% of day traders in a given year lose money after fees are taken into account.  About .28%--one in 360--is able to make money after fees year over year.

To be sure, that small group of very successful day traders earns a significant return.  After expenses, they average +28 bps per day.  Compare that to the 350,000 out of 360,000 daytraders who average a daily loss of 5.7 bps per day after expenses. 

The authors conclude that day trading skill genuinely exists.  They also conclude that it is very, very rare.  

Further Reading:  Can Day Traders Be Successful?

Why Ugly Stock Markets Provide Pretty Returns

The recent post on the relative equity put/call ratio highlighted the importance of sentiment in near-term stock market returns.  In this post, let's take a look at the interaction between two factors:  overbought/oversold and sentiment.

First, definitions:  I am using as an overbought/oversold measure the percentage of SPX shares trading above their five-day moving averages.  (Data available from Index Indicators).  For sentiment, I am looking at the put/call ratio for all equities on all exchanges that have listed options.  (Data available from e-Signal).  For this exercise, we'll look at the period from 2010 to the present.

If we just break the market down by a median split on the overbought/oversold measure, what we find is that the next five days in SPX average a gain of .12% when we've been overbought and .38% when we've been oversold.  In general, chasing strength or weakness on the short-term has been a bad idea:  if we waited for several days of "price confirmation" before entering long or short, our near-term results suffered.

Now let's break down the overbought occasions by a median split of daily sentiment readings.  When we've been overbought and sentiment has been bullish, the next five days in SPX have averaged a gain of only .01%.  That is a paltry return, considering the bull market.  (For the sample overall, the average five-day gain was .25%.)  When we've been overbought, but sentiment has been bearish, the next five days in SPX have averaged a gain of .22%--nearer the sample average.  In other words, overbought readings have only led to diminished returns on average when they've been accompanied by bullish sentiment.

Next, we'll break down the oversold occasions by a median split of sentiment.  When we've been oversold but sentiment has been bullish, the next five days in SPX have averaged a gain of only .09%.  When we've been oversold and sentiment has been bearish, the next five days in SPX have averaged a whopping gain of .68%.  In short, the best time to buy stocks is when people have been dumping them and sentiment is bearish--precisely when stocks look their ugliest.  The trader who bought stocks when they were their prettiest earned almost no positive return over the past 4-1/2 years.

One takeaway:  The very same ideas in the stock market yield wildly different returns depending upon how they are executed.  You could have been a bull the last several years and still not made money in U.S. stocks if you needed the reassurance of price confirmation and could not take the heat of short-term price disconfirmation.  Buying when the market has been pretty and selling when it's been ugly has guaranteed losing returns.

Further Reading:  Volume and Volatility in the Stock Market

Wednesday, August 13, 2014

Supercharging Your Trading Journal

Trading journals are used for many purposes, from tracking markets and trade ideas to working on performance.  The recent post on the learning process of chess masters suggests a particularly powerful application of trading journals.

Suppose you were to treat each market day (or week, depending upon one's time frame and frequency of trading) as a separate chess game.  You would follow the market move by move and annotate your observations at each key juncture:  what was happening with important market indicators; what was occurring in related markets; how the market responded to news and economic reports; etc.  Of particular importance would be key turning points in markets and how those set up.  

Such a journal would consist of multiple charts, as well as commentary.  Actual trades logged during the market day would also be depicted, along with comments on the strengths and weaknesses of the trades.

Right away, there would be two distinct advantages of such a journal:

1)  It would be dynamic.  A journal that treats each day/week as a chess game would be the equivalent of the sports practice in which coach and player watch the video recordings of past games, review performance, and provide feedback.  The review could include replays of key market junctures and would provide a much more dynamic and engaging approach to learning than writing static prose entries. 

2)  It would be structured. As with chess education, the journal would help traders work on their openings (entry execution); their midgames (position management); and their endgames (exit execution), as well as their offensive (idea generation) and defensive (risk management) strategies.  Most written journals are mere summaries of a trading day or week.  A journal that captures each trading day/week as a chess game invites very concrete development for the skills central to each phase of the trading process.

Imagine further that such a journal was shared with valued colleagues via social media, so that each trader is learning many lessons every single day or week and working together on building strengths and correcting weaknesses.  By treating markets as chess games, we create new routines for viewing and re-viewing performance and adapting to changing markets.

Further Reading:  The Power of Trading Journals 

Replicating Talent: What Trading Can Learn From Chess Education

The recent post suggested that there is a meaningful overlap between the cognitive talents required by chess and trading.  Where traders can probably learn the most from chess is in the learning process.  While the cognitive strengths of the two domains overlap, the ways in which they are channeled and developed is typically quite different.

How does someone learn to play chess at a high level?  A look at a site devoted to the educational process provides some insight:

1)  Developing chess masters view and review games and key moves in a hands-on way- This is a staple of chess learning.  Illustrative games are archived for future players to review.  Many times, accomplished players annotate the games, providing insight for the learner.  Learners do not simply read the games from a text or watch a video.  Rather, they play the games move by move on a chess board, so that they actually see situations set up and actively think through each move.  This viewing and re-viewing provides the chess student with many, many games worth of relevant experience before he or she ever sets foot in a chess tournament.  This is not only deliberate practice, but deliberate practice guided by recognized experts. 

2)  Developing chess masters break the game down into key components and build their skills one component at a time - Once players master the basics, they hone their skills with different facets of performance.  They work on their openings, their midgames, and their endgames; they learn various defenses and how to play against them.  Computer applications offer targeted learning opportunities and provide relevant feedback, as can live lessons with a coach/mentor.  Just as an American football team would devote training time to specific plays, offensive sets, and defensive strategies, the budding chess master works in a focused way on specific parts of the game to master domain-specific skills.

3)  Developing chess masters learn from true masters - This is very important.  Accomplished chess players carry a ranking based on their performance in tournaments.  That ranking is publicly verifiable and based upon objective performance.  A developing student can learn from the world's top talent through live lessons, but also through training materials assembled by recognized experts.  Because each tournament game is publicly recorded move by move, every person has access to what the greats do--and have done.  

These three characteristics of chess education rarely occur in concert in the world of trading and investment.  Yes, there are valuable simulation platforms that allow practice trading, and there are review features for those platforms that enable the learner to learn from recent experience.  What is typically missing, however, is the expert input that breaks trading down into meaningful components, models successful skill deployment, and provides immediate and relevant feedback for learning.

This is why I find the best learning occurs within trading teams at established hedge funds, banks, and proprietary trading firms.  When an accomplished trader brings on junior talent--often junior talent with specific areas of expertise that contribute immediately to the business--the whole of the team becomes more than the sum of its parts.  The team becomes a dynamic start-up business within an established business. 

Imagine, for example, a senior portfolio manager hiring a junior team member with experience in options.  The junior hire helps with the structuring of positions in the portfolio, creates appropriate hedges, and provides insight to the team in terms of options-based sentiment measures.  The senior manager provides daily instruction to the junior member, helping build skills in such areas as idea generation and risk management.  This is a powerful model, because the learning occurs in real time, in real situations, from real experts, with real integration of coaching and mentorship.  It's also a sustainable model, because there are tangible benefits to mentors and students.

Suppose those teams archived and annotated their experience the way that chess masters do.  Over time, multiple teams could contribute to a central learning database that captures the wisdom of the experienced traders--and also their core skills.  The model of "siloed" traders operating in isolation is inefficient.  Can any one individual truly stay on top of a complex, global financial world?  In leveraging talent the right way, all parties benefit:  talent becomes replicable.

Further Reading:  A Different Kind of Proprietary Trading Group