Wednesday, May 27, 2015

Buy and Hold Traders

Buy and hold traders, also called long-term traders, are stock market investors who are buying stocks and holding them for a long period of time. This category most likely constitutes the largest group of people who are buying stocks, as it requires the least amount of time spent focused on the stock market.
Many buy and hold traders believe the best way to have exposure to the stock market is to buy great companies and hold them through any market condition. When they buy stocks with the intention of holding them for years, they are more likely to steer clear of trendy companies or up-and-coming, high risk businesses.
Benefits of buy and hold trading
On the whole, for long-term investments, time spent in buy and hold trading is much less compared to time spent on medium- and short-term investments. Very long-term investment is not time-sensitive, while in shorter-term investment, you have to take timely action.

Being a passive, long-term investor has many advantages over other types of trading:
  1. Fewer fees and commissions - Fees are often overlooked by traders. But when trading with small amounts of money, fees and commissions become even more important. Learning to control impulse trading and doing far less portfolio management may be the most profitable move a trader can make. Many believe that the big money in investing is made by diligent, long-term traders - buy and hold traders.
  2. Low maintenance - Buy and hold traders are not required to spend a lot of time keeping track of the stock market daily movements. The practice of watching daily price movements is highly counterproductive to the temperament a long-term investor must maintain.
  3. Less nerve-wracking - Companies that are typically chosen for buy and hold portfolios are less volatile than the average stock. Due to the lower volatility, there is less chance that a stock in a buy and hold trader’s portfolio will suddenly gap-up or gap-down overnight. The stock price fluctuations are more evident for the short-term trader - as buy and hold investors, time is on their side, and so if their stock goes down from where they bought it, they don’t have to worry as long as they still think the company is great.

  1. Bonus for dividend growth investors - If they are dividend growth investors, there is an additional bonus to being a buy and hold investor. As the dividend rate continues to rise, their yield on cost will increase as well!
  2. As the company grows, the dividends and bonuses are added to the net investment.

Disadvantages of buy and hold trading
  1. The buy and hold strategy may give the appearance of a safer investment model, but no strategy is above risk. For example, traders who bought Microsoft in 2005 would have made less than 2% as of July 2013 on that investment (see the chart above).
  2. The other buy and hold problem is the onset of bear markets. If a buy and hold trader purchases a stock prior to a swift market decline similar to the ones in 1987 and 2002 and again in 2008, the traders may have to wait five to 10 years to break even on their initial investment. A buy and hold trader may be required to undertake more fundamental analysis before making an investment decision - which involves a great deal of parameters. Then, over time, these fundamentals can change - the political scenario, war and famine, supply and demand of the products, etc., can all affect the outcome of the profit.
Many of the shares that were good a decade ago may not be so good in today’s scenario.

When to sell
A buy and hold trader should know when the strategy isn’t going to work or when it makes more sense to sell the stock they intended to hold until retirement or later. There are exceptions to every rule, including the buy and hold strategy. Here are a few situations when they may decide to sell their stocks rather than hold them:
  • Company files bankruptcy.
  • CFO indicted for accounting problems or theft.
  • Company does something that goes against personal values or beliefs.

Friday, May 8, 2015

Why We Trade

Why do we trade? To be sure, trading allows us independence, the opportunity to
work for ourselves. Trading also offers the prospects of a lifestyle in which evenings and
weekends need not be consumed by work. Some of us crave the competitive aspect of
trading, doing fresh battle each day. Others approach trading as a puzzle to be solved,
deriving a sense of intellectual achievement. Finally, there is income. A successful
trader can make seven figures in a year—and many of the traders I work with are living
proof of that.
So why do they trade? Once you have the money, all of trading’s lifestyle
advantages could easily be yours. Needs for competition and intellectual stimulation
could be met in so many other ways. Why do traders remain traders long after they’ve
won the game?
Perhaps we can illuminate this question by asking it of practitioners in other
fields. Why do artists continue their craft long after they receive recognition for their
paintings, novels, or films? Why do elite Special Forces troops stay in units that test their
mettle even after they’ve earned their coveted badges? A gifted athlete such as Michael
Jordan earned plenty of money and honors and, in fact, did retire on a couple of
occasions—only to return to his game. Why?
There is something deep here that speaks to the nature of productive work.
People retire from jobs and even careers, but they never abandon their callings. For
some, work means something more than earning a living or achieving a lifestyle. Work
is their path in life. It is the way they have chosen—or perhaps that has chosen them—
for self-expression and self-development.
Suppose the pastor of a large, successful church wrote a book, made significant
money, and promptly retired from the clergy and all religious life. What would that say?
Surely, we would think, this person’s faith could not have been too heartfelt. But why
should our productive work mean less to us than the clergy means to a devout pastor?
Presumably, the religious life meets deep, important needs for the pastor. Is it really so
different for the artist? The athlete? The trader?
The great professions are those that serve as personal playing fields. They are the
arenas we choose to express and develop ourselves. In mastering a discipline, we
cultivate self-mastery. In writing a poem or placing a large trade, we capture—in a single
act—our vision of how we see the world at that moment. The great occupations are great
precisely because they are such meaningful playing fields. Long after we’ve earned fame
and fortune, the calling remains to be more than we are, to return to the arena and do
battle with our limitations. The profound urge to extend the human grasp is common to
all the great callings. To run faster, to capture more beauty, to predict ever better: in no
small measure, our work is our pursuit of the godlike, however fleeting.
Maybe it is our different images of the godlike that animate our career choices. If
my deepest view of godhood is that of a meek and all-forgiving Christ, perhaps I will be
drawn to an occupation of service. If my deepest view is more akin to the ancient
Greeks, whose gods sent heroes on quests, then my calling may be on a battlefield or a
playing field. Either way, in work we find something divine within ourselves. Whether
as scientists, monks, or traders, we strive for those moments when we are just a little
closer to perfection, a little nearer to immortality. That is why we trade.

Tuesday, May 5, 2015

The Three Vices of Trading

Perfectionism is often the chief culprit when the pain of losing exceeds the
pleasure of winning. Desperately trying to feel good about themselves, perfectionists set
unrealistically high ideals. They think they will finally be OK if they just accomplish X.
(For X, you could substitute many things, including looks, wealth, popularity, or
achievement). Because X is an unattainable goal, perfectionists ironically use their ideals
as a basis for self-criticism when their performance doesn’t match up. After all, is
achieving X will make me OK, then I must not be OK if I fail to achieve X. The
emotional theme of the perfectionist is “not good enough”. Perfectionists are driven to
do more and more because they never feel competent, worthy, and loved as they are.
Thus, even when there’s a profit on a trade, perfectionists will look for the portion of the
move that they did not participate in. If they caught most the move, they will reprove
themselves for not trading a larger position. And when trades don’t go well,
perfectionists review all the reasons that shouldn’t have made the trade, should have
known better, etc. By focusing on the portion of their performance that doesn’t match
their ideals, perfectionists transform successes into defeats, losses into failures. They
rationalize their perfectionism as a drive for achievement, but all they are accomplishing
is an undercutting of their confidence.
Perfectionism shows up as negative self-talk and self-blaming. Emotionally, we
recognize perfectionism from frustrated, angry feelings when trades don’t work out as
planned. “Beating myself up” is how many perfectionists describe their self-talk. The
way to beat perfectionism is to make a concerted effort to talk to yourself the way you
would talk to a good friend in a situation where things went wrong. Most people know
how to treat others with respect, love, and dignity. They just haven’t learned to do the
same for themselves. If you would be more nurturing, understanding, and supportive of a
friend than you are of yourself in the identical situation, then you know that you’re not
being your own best friend. If a trade doesn’t work out, the constructive trader focuses
on, “What can I learn from this?”—not “What’s wrong with me?”. In Woodie’s
language, the best antidote to perfectionism is the ability to reassure yourself, “There will
be better trades down the road.” The key is to not miss those better trades while you’re
beating yourself up!
Vice Number Two: EGO
Everyone likes to win in the markets. It’s only natural to feel good when you’ve
done your homework and end the day with a profit to reward your efforts. Ego
involvement in trading, however, goes further than this. When the ego is involved, we
write the market a blank check for our self-esteem. If trading is green, we feel good
about ourselves; if we go into the red, we feel diminished. That places tremendous
pressure on our trading over time. Not only do we have the burden and challenge of
reading complex market patterns; now we also have a psychological gun pointed to our
head ready to go off any time our pattern recognition fails us.
Most traders are aware of the dangers of trading with too much leverage. A trader
accustomed to trading 2 lots, where each tick in the ES is worth $25, would feel
overwhelmed jumping to 100 lots, where each tick now moves the account $1250. With
the stakes raised to such a degree, the same trade would now no longer feel the same. It
would be hard to let a position go against you by a point ($5000, instead of $100), and it
would be difficult to let a profit run. When traders invest their feelings about themselves
in their trading, they are operating with maximum emotional leverage. In the currency of
self-esteem, they trade 100 lots. So much of their emotional account rides on each trade,
that it inevitably affects decisions about cutting losses, letting profits run, and entering
and exiting in a timely fashion. The successful trader wants their trades to work out; the
ego-involved trader needs them to be profitable.
We know that ego threatens our trading when we find ourselves needing to trade
just to win back some recently lost dollars; when we feel a desire to advertise our
positions; and when we find ourselves riding an emotional roller coaster as profits wax
and wane. Just as we can recognize traders’ perfectionism from anger/frustration, we
recognize ego-involved traders from euphoria/depression. If trading has us truly
depressed, we know that it’s not just our trading account that’s hurting. The antidote to
ego-involved trading is to place our self-esteem eggs in many baskets: recreational
interests; other work involvements; relationships; and our spiritual lives. Many times we
pour our self-esteem into trading because those other facets of our lives are not properly
developed. A balanced life makes for balanced trading. In the spirit of Woodie’s CCI
Club, we can take some of the ego out of trading by learning from others, by becoming a
candle that lights other candles, and by using a portion of market profits to help others
make a wish that will come true. If your good feelings in life come from good
relationships and worthy achievements, you won’t need the markets for your happiness.
Market success can be the frosting on the cake of your successful life, rarely can it
substitute to the cake itself.
It is common for traders to complain of a lack of confidence in their trading, but
very often it is overconfidence that does them in. Overconfidence results from a lack of
appreciation of the complexity of markets and an underestimation of the challenges of
trading them successfully. In a sense, overconfident traders lack respect for the markets.
They think that reading about a few setups or buying the newest software will prepare
them to make money. Overconfident traders don’t want to work their way up the trading
ladder: they resist the idea that screen time is the best teacher. They also chafe at the
idea of growing their account. Rather than start with one contract and wait until they’re
profitable before trading larger size, they want big positions—and profits—right away.
Because they’re so eager to make money—and so sure they can make it—overconfident
traders generally trade impulsively. They won’t wait for the setup to form; they’ll jump
the gun—and get whipsawed in the process. Instead of being patient and waiting for
short-term patterns to align with longer-term patterns, they will take every trade,
enriching their brokers in the process.
The hallmark of overconfident traders is that they think they are going to make
something happen in the market, instead of patiently waiting to take what the market
gives them. Spelling out profit goals for each day or week of trading is one manifestation
of overconfidence. Humble traders know that markets expand and contract their
volatility—sometimes the trade just isn’t there. The overconfident trader, however, feels
that he/she is bigger than the market. Indeed, overconfident traders will often take great
pains to try to catch the tops of bull swings or the bottoms of corrections. As a result,
they often fight the market trend—and can get run over in the process. If the emotional
signs of perfectionism are anger/frustration and the emotional signs of ego involvement
are elation/depression, then the emotional signs of overconfidence are
impatience/impulsivity. Overconfident traders overtrade. They fear missing
opportunities more than they fear losing money. The antidote to overconfidence is rulebased
trading and the intensive rehearsal of trading rules. By making entries, exits, stops
and position sizing rule-governed and vigorously rehearsing trading rules during
simulated trading (as well as in real time with small positions), traders can greatly reduce
their impulsive trading. Very often this means training oneself to focus on (and rehearse)
what-if scenarios of being wrong in the market, as well as forcing oneself to spell out the
rationale, targets, and stops for all trades. By making trading a more self-conscious
process, traders interpose thought between impulse and action, gaining greater control of
their trading. When the trading room admonishes, “No boasting, just posting”, it is
encouraging restraint on overconfidence.

The Challenge of Changing Yourself

The intensity and the repetition of change efforts are directly responsible for their
ultimate success. The new, constructive patterns that are likely to stick are the ones that
have become associated with highly distinctive states of mind and that have been
overlearned. Conditioning new patterns to a distinctive state of mind makes it easier to
summon those patterns any time you reenter that state. This connection becomes
internalized most readily when it has been rehearsed intensively. It is rare that insight
alone will create change; more often, doing things differently allows you to make the
change part of your ongoing repertoire. The greatest challenge to changing yourself as a
trader is also the greatest challenge to change in therapy. It is relatively easy to initiate
change, but it is far more difficult to sustain it. Without consolidation, people are likely
to relapse into their habit patterns. An essential ingredient in change is to repeat a desired
pattern again and again in the same way, at the same time, in the same situations on every
occasion that presents itself. At first, enacting the new behaviors will require conscious
effort. With repetition, however, the behavior becomes automatic, an internalized part of
the self.

The Best-Kept Secret in Trading Success

Every trader is familiar with what Victor Niederhoffer calls the “ever-changing cycles”
within the market. Just as a pattern makes itself evident in the market, the pattern shifts
to a new configuration. For example, the market may trade for a while within a range,
offering nice buy and sell signals with a 14 period RSI. Then, abruptly, the market will
break out and an overbought RSI will stay overbought or oversold for a prolonged period
as the market makes a trending move.
It is because of these ever-changing cycles that traditional tools of technical
analysis cannot be successfully applied in a purely mechanical fashion. The website has a nice feature where they track trading signals from such standard tools
as moving averages. Over time, it is clear from their tracking that the signals do not
perform better than random chance. For a while the signals will prove profitable, only to
degrade once the cycles change.
It is ironic that traders spend considerable time researching better indicators and
models while giving little thought to the time frame over which these trading tools might
be valid. If, indeed, the market consists of ever-changing cycles, then any system or
indicator is apt to degrade in its performance over time. In fact, if one waits for an
indicator or system to develop a fine historical track record, the odds are good that their
useful life are limited.
What can a trader do in the face of such uncertainty?
The statistician’s term for ever-changing cycles is stationarity. A number series is
stationary if the process that generated the series has been constant. Clifford Sherry, in
his excellent text The Mathematics of Technical Analysis explains, “A stationary time
series is one in which the underlying rules that generate the time series do not change
over time.” (p. 9).
My favorite example is the Las Vegas casino. Let’s say that you are playing
blackjack and think that you have a superior card-counting strategy that will help you
make money. By counting the number of picture cards vs. other cards that have been
dealt, you can assess the probability of drawing a picture card on subsequent hands,
tilting odds in your favor.
Such a strategy will work as long as the number of decks employed by the dealer
is constant. If, however, the dealer intermittently and secretly changes the number of
decks in the shoe, the card counting strategy would be imperiled. If the gambler assumed
that twelve cards worth 10 or higher were left in the deck because eight had been dealt,
the assumption would be faulty if two decks instead of one were being used. By
changing the rules for dealing cards, the dealer creates a distribution that is nonstationary.
Clifford Sherry notes the importance of nonstationarity for traders: “If you use
these methods and techniques and find that your time series is nonstationary, it is
probably best to stop and think carefully about your investment strategy. Nonstationarity
implies that the underlying rules that ‘generated’ your time series change from time to
time without warning. Therefore, you are dealing with maximum uncertainty about the
potential outcome of your investment.” (p. 6). Sherry’s phrase “from time to time” is
important. If, say, the card dealer changed the number of decks in the shoe after each and
every hand, no card counting strategy would be possible. What makes counting viable is
that the cycles are changing, but not constantly changing. A regime—a period in which
the market follows a stable set of rules—can last for a while, allowing an alert trader to
profit while it is in force.
What should be clear is that a skill essential to trading success is early
identification of regime change: those occasions when the cycles are shifting and the
distributions of price changes are significantly varying from their recent norms. If a card
counter can quickly identify when the number of decks in the shoe have changed, he can
avoid betting his old system and take the time to develop a new one. Similarly, once a
trader notes that market behavior has shifted, he or she can stand back and identify the
new rules that the market is following and position themselves for the new regime.
Amazingly, very few traders bother to look for stationarity and even fewer shift
their trading strategies according to the characteristics of recent price change series. This
includes technical analysts who employ the same indicators and indicator values across
all markets and quantitative traders who fail to properly adjust their lookback periods
when testing a relationship between predictors and price change. Would we expect the
time series from 2000 to 2002 to provide an accurate database for gauging relationships
in the 2003 market? Did the market from 1998 to 2000 provide useful guides over the
subsequent two years?
Assuming stationarity when it is not there is one of the cardinal errors of trading.
If you are trading a pattern that has been valid in the past and you don’t know if the
current distribution of price changes match those from the past, you are flying blind.
Successful trading requires that you identify the rules the market is following and base
your strategy on those.
Fundamental Uncertainty in Trading
Let’s go back to that last sentence. The trader knows that there are ever-changing
cycles, but makes a fundamental assumption. That assumption is that the regime that is
in place will not change over the next trading interval. The trader assumes that the
market’s rules will continue to be in force at least one more time. Without that
assumption, the trader is either assuming randomness or is assuming regime change in the
absence of concrete evidence of such. The only way we know if a regime has changed is
by seeing an actual shift in the distribution of price changes. That means that there is a
fundamental uncertainty in trading. The next trade may be the one in which the cycles
shift. We cannot know for sure. Any trading strategy needs sound money management
for this reason. Betting the house on a single trade—or during a single time frame—is
courting ruin.
This has some interesting implications. For example, a well-researched trade that
loses money may be an important source of trading information. If I have tested a
historical period and found stationarity and then test a relationship between predictors
and prospective price change over that period, my trade should have a high probability of
success—if the market is remaining stationary. A losing streak with well-researched
trades is often a sign that the markets are changing. Standing aside, waiting for evidence
of the new regime, and remodeling the market over the more recent time frame
corresponding to the new regime may allow the trader to learn from losses—and recoup
them as well!
The fundamental uncertainty of trading is highest in daytrading the stock
market—particularly index futures such as the SP/ES and ND/NQ. This is because
markets are nonstationary on an intraday basis—almost without fail. Markets are most
volatile early in the day’s trading, retreat to lowest volatility in early afternoon, and then
pick up volatility toward the close (only to plunge in volatility during Globex trading). It
is rare indeed that the distribution of price changes from 09:30 – 11:30 AM ET will
match those of 11:30 AM – 13:30 PM ET. Using the same indicators and indicator
values in morning trading as in early afternoon and Globex sessions is a sure road to the
poorhouse. Conversely, identifying regime change and valid relationships with each
intraday regime shift requires a nimbleness—and an ability to control losses—that most
traders lack.
Interestingly, markets exhibit greater stationarity from day to day and week to
week than from hour to hour. That is one of the factors that has sped my transition from
intraday trading to swing trading. But if stationarity is as important to trading as Sherry
and I believe it to be, then it makes little sense to pigeonhole oneself as a short-term
trader, a long-term trader, a daytrader, etc. One should trade the time frames that offer
the greatest stationarity. If the market is stationary over a period of weeks and if you can
clearly identify the rules the market is following over that period, it makes sense to trade
those rules. Later, the market may exhibit stationarity over a shorter time frame,
covering a series of days. The rules that capture that regime will provide the basis for
Many times, we hear of the distinction between mechanical and discretionary
trading. This is a false dichotomy, because both mechanical and discretionary trading
often fail to take ever-changing cycles into account. The real alternative to mechanical
trading is flexible trading that searches for regimes and the rules guiding regimes,
exploiting these in a rule-governed manner.
From Theory to Practice
Analyzing the market for trades should begin with tests for stationarity. In my
new swing trading system, I begin my analysis by identifying the longest swing period in
which the markets are exhibiting a stationary series of price changes. (There may be
more than one such stationary swing period, permitting diversification of trading by time
frame, and—of course—there may be stationarity for certain instruments and not others,
permitting diversification by trading vehicles.) My procedure for assessing stationarity is
to divide the time series into halves and statistically test to see if the means and standard
deviations for the halves are equivalent. For readers interested in the math involved,
Sherry’s book outlines a practical procedure for testing stationarity. The math is simple;
I employ a quick-and-dirty t-test to the data and conduct the test entirely within Excel.
What takes time is the repetitive testing of various lookback periods to find the proper
window of stationarity.
Once I have that window, I then analyze the market qualitatively. I look at my
indicators and observe how they have behaved during the stationary lookback period.
The indicators that have consistently traced swing highs and lows over that period are the
ones I will use to plan my next trade. I test signals yielded by the indicators (individually
and in concert) over the lookback period to examine their entries, exits, and drawdowns.
When I have a cadre of indicators that have performed well over the lookback period, I
rely on them for my next trade.
But that’s curve-fitting, you might protest. Isn’t it dangerous to overfit the data
with an optimized model?
My response is that optimization is only a problem when you fail to take
stationarity into account. If you know you are trading within a stable regime, it makes
sense to do your best to capture the rules the market is following over that period. My
swing trading methodology might best be described as serial optimization: continually
hunting for periods of stationary market behavior and trading optimized models derived
from those periods.
Now here’s the rub. When markets shift regimes, the window for the new regime
is small. In testing the indicators that best follow the new, emerging rules, there aren’t
enough instances to properly conduct statistical tests. That is where historical tests
become important. By identifying past periods of market history where the markets were
following the same rules as today, we can see if the indicators and signals that work in
the recent lookback period also worked back then. The crucial assumption is that
markets that exhibit stationarity and equivalent means and standard deviations in price
changes are following the same rules—regardless of whether those markets were taking
place in 2003, 1993, or 1983. If the strategy that we’ve optimized in the recent,
stationary market window also produces profitable trading signals during past, similar
regimes, we increase our confidence in the strategy and, indeed, can even test its signals
statistically to ensure their departure from randomness.
Perhaps this is why we see so few traders incorporating stationarity into their
analyses: It is time-consuming to assess market windows, operative trading rules, and
test strategies for exploiting those rules. It is easier—and far more beguiling—to assume
that a single system or indicator will produce consistent profits. More than one person
has encouraged me to make my writing, research, and trading strategies less complex so
that they can be more readily understood and accepted by the bulk of traders who attend
seminars, buy trading books, and hire gurus for advice. One seminar organizer even
fretted that I might be a threat to the self-esteem of traders, because the majority of
traders lack the data and/or statistical background to conduct my kind of trading. I took
that, of course, as quite a compliment.
If you read the Trading Psychology Weblog with any frequency, you’ll notice that
many of the charts that I post have a common—and seemingly random—starting date.
For instance, as I write this (12/28/03), many of my charts begin with 8/1/03. This is not
an accident. The period from August through December represents one of those
stationary windows from which we can extract useful swing trading strategies. By
posting charts over stationary time frames in the market, the Weblog can assist you in
identifying tradable market patterns.
Incorporating stationarity into your market thinking and trading opens the door to
innovative trading approaches. For instance, within a longer stationary window (several
months), you might identify a smaller window (the past several days) for a short-term
trade. By nesting and aligning the short-term trade within a longer-term pattern, you can
formulate some high probability trades. Beginning January, 2004, I will be posting real
time swing trades to the Weblog that take advantage of rules derived over one or more
stationary windows.
Yet another avenue for research is the use of very short-term nonstationarities to
identify points of larger regime change. A while ago, when I was exclusively trading the
SP on an intraday basis, I noticed how short-term shifts in the NYSE Composite TICK
tended to occur at points of trend change in the market. The short-term nonstationarity
was a marker for longer-term trend change. I believe the same occurs at all time frames.
By monitoring shifts in short-term patterns and indicators, we may be able to hop aboard
early phases of regime change.

Fundamentals of Short-Term Trading: Part Two

How one employs this information will depend upon his or her time frame of trading,
which in turn reflects one’s risk tolerance, which is closely related to personality traits.
Longer holding periods yield more variable results—including drawdowns. Adjusting
the mix of holding period and position size is essential in ensuring that one is taking a
level of risk that will produce adequate rewards, but that will not court ruin during a
losing streak. The management of risk is an oft-neglected facet of trading psychology.
Risk, Size, and Holding Period
Let us say, for instance, that we are going to risk 2% of our trading capital on a trade. If
we are trading tick-by-tick, we could trade dozens of contracts and still remain riskprudent.
If, however, we are holding positions overnight, where the odds of a multipoint
move are now greatly increased, the same 2% parameter would yield a position size of
only a few contracts. Even on an intraday basis, a scalping trade placed early in morning
has a greater risk of a multi-tick adverse move than the same trade placed nearer to
midday. Keeping size constant during periods of nonstationarity—or worse yet,
increasing size when you see volatility ramping up—courts the scenario in which a single
losing trade undoes several previous winners.
A fixed-fractional trading strategy defines the number of contracts you can trade for a
defined level of risk. Michael Bryant, in his article “Position Sizing With Monte Carlo
Simulation” (Technical Analysis of Stocks and Commodities; Feb. 2001), shows how
simulations of trading outcomes with particular strategies can help one define the fraction
of trade capital to place in a trade while keeping the risk of severe drawdown under 5%.
Simulations using his MiniMax swing trading system, for example, show that trading 2%
of capital produces a maximum peak to valley drawdown of 24% on the ES futures with
95% confidence. If one wanted to reduce that drawdown to 12% of capital with the same
level of confidence, one would risk only 1% of capital.
The fixed-fractional strategy described by Bryant is drawn from the following equation,
where N = the number of contracts traded; ff = the percentage of trading capital allocated
to the trade; E = total trading equity prior to placing the trade; and R = the risk of the next
trade in dollars (which is your stop).
N = ff * E/R
Thus, if I am willing to risk 2% of my $100,000 trading account on a trade where my stop
is set at 4 points ($200 per contract), I could trade 10 contracts and still remain riskprudent.
If I am a scalper and my stop is much smaller, I can trade a larger number of
contracts with equivalent risk. If I am a swing trader willing to set a double-digit point
stop, I will trade smaller size.
Adjusting Risk and Reward
This brings us back to the topic of stationarity. In the above example, I have set my stop
at 4 points. The odds of a four-point setback, however, are not the same early in morning
trading as in midday or late in the day. If I am an intraday trader and rely on a fixedpoint
stop, I no longer am managing risk consistently. I may be taking too much risk at
one time of day and too little at others. I need Monte Carlo simulations on a horizontal
basis to tell me the 95% probability of a defined market drawdown for morning trades,
afternoon trades, etc. Just as I would not trade similar size on an intraday vs. swing basis,
I would not trade identical size at various times of day.
It is difficult to square this position with the reality that very successful traders tend to
increase their size in direct proportion to their confidence in a trade. A consistent theme
among “Wizard” traders is that, once they identify a move, they exploit it for all its
worth. The less-successful trader is apt to become risk-averse in the face of a profitable
position and exit early. Since volatility is commonly increasing as a trade is working out,
adding to positions is significantly adding to risk. A reversal at the end of a move, when
size is greatest, could eliminate all profits, even if one has been correct in anticipating the
direction of the move.
Scaling into positions over time can address this challenge. In a forthcoming book on
Trend Following by Michael Covel, he quotes Ed Seyoka’s approach to pyramiding. The
instructions for pyramiding, Seykota explains, are depicted on every dollar bill: add
smaller and smaller units, while keeping your eye open at the top. The advantage of
scaling into one’s maximum position is that it keeps risk lowest early in the trade, when
its outcome is most in question. As the trade works out, adding to the position allows the
trader to maximize profits. The successful trader is thus thinking like a Bayesian,
watching the unfolding of a trade to see if the market is gaining or losing strength, and
adjusting the position accordingly.

Monday, May 4, 2015

Fundamentals of Short-Term Trading: Part One

The Challenge of Stationarity
I’d like to begin this article with a set of descriptive data on the ES market, the main
market that I trade. For purposes of convenience, I looked at the market between October
9th, 2003 and January 16th, 2004, which gave me 68 full days of data. I broke down each
trading morning (9:30 ET – 12:00 ET) into half-hour segments to see how each segment
compares to the ones around it.
Below is a table of the average range and standard deviation (in ES points) for each 30
minute period in the morning.
TIME                              RANGE                      ST. DEVIATION
9:30 – 10:00 ET            4.06                            1.451
10:00 – 10:30 ET          3.765                          1.452
10:30 – 11:00 ET          2.9                               0.991
11:00 – 11:30 ET          2.458                           0.806
11:30 – 12:00 ET          2.597                           1.333
Now let’s look at the average number of trades placed per minute during each half-hour
period from 10/9/03 to 1/16/04:
TIME T                     RADES                ST. DEVIATION
9:30 – 10:00 ET        187.88               98.91
10:00 – 10:30 ET      183.78              121.26
10:30 – 11:00 ET       133.20              91.97
11:00 – 11:30 ET       101.04              77.90
11:30 – 12:00 ET       84.60                84.24
Here’s the average volume of trading in contracts per minute during each 30 minute
morning period:  
TIME                             VOLUME                ST. DEVIATION
9:30 – 10:00 ET             2331                        1470
10:00 – 10:30 ET           2133                        1679
10:30 – 11:00 ET            1533                        1310
11:00 – 11:30 ET            1121                         1046
11:30 – 12:00 ET             932                           1091
Finally, let’s look at the average one minute level of the NYSE Composite TICK over
each half-hour period in the morning from 10/9/03 through 1/16/04:
TIME                                NYSE TICK                ST. DEVIATION
9:30 – 10:00 ET                    300                                378
10:00 – 10:30 ET                  240                                390
10:30 – 11:00 ET                 212                                   311
11:00 – 11:30 ET                 243                                   289
11:30 – 12:00 ET                 295                                   272

What do these numbers tell us? Most traders are aware that there is more volatility and
volume in morning trading versus the early afternoon, and more volume and volatility
late in the day than in the middle. These half-hour figures, however, drawn solely from
early day trading, suggest that even the morning hours are not uniform. Volume and
volatility is highest in the first half hour and tends to wane through the morning, with
particularly notable drops from 10:30 ET on.
This suggests that even the very short-term trader is going to run into problems of
stationarity. When analyzing a market from hour to hour, we are—to a large extent—
comparing apples and oranges. The time series of price changes from one period may not
be drawn from the same distribution as the time series of price changes from the next or
the one before it. This seriously compromises any technical analysis strategy (moving
averages, oscillators, chart pattern analysis) that involves blending one period’s trading
with adjacent ones.
The lack of intraday stationarity also compromises quantitative efforts to model the
markets, because we cannot use period one’s data to predict period two if we have reason
to believe that the two periods were not drawn from the same distribution of price
changes. To use the analogy from my previous article on stationarity, if we count cards
in blackjack while the dealer is drawing from a two deck shoe, our count will be invalid
once the dealer switches to a four deck shoe.
The market, as dealer, is changing shoes every hour of the trading day. And this is a
very big challenge to short-term trading.
Re-Visioning Market Analysis
Most traders, myself included, tend to view the market vertically. That is, if we build a
spreadsheet, we array the recent data on top of the prior data and create all sorts of
statistical manipulations that aggregate the data from bottom up. Vertical market analysis
is problematic, however, in that it runs into the aforementioned challenge of stationarity.
When I created the tables above, I was looking at the market horizontally. Instead of
putting each day’s data on top of the previous values, I placed it to the right. That means
that the rows of the spreadsheets represent common time periods—in the case of the data
above where we looked at ranges, these were thirty-minute periods. Viewing data
horizontally tells us some interesting things, in part because there is greater likelihood of
stationarity across sixty common time periods than across sixty adjacent, different
Let me give a concrete example. Suppose during a given five minute period of the day
we see 800 ES trades being placed. Is that a meaningful volume or not? If the 800 trades
occur during the opening half hour of trading, the volume is not significant. On the other
hand, 800 trades in a five minute period that occurs between 11:30 – 12:00 ET would be
close to the top 5% of all values for that period. The average volume in early morning is
actually a mini buying or selling climax around noon. And, as we shall see later, this is
an important piece of information.
Here’s another example: Suppose we break out of a hour-long range and make a new
high or new low on the ES. What are the odds of the move continuing in its breakout
direction? If you aggregate all similar breakout moves through the day, you’ll get a very
fuzzy reading. About half the breakout moves will continue; half will reverse. But if you
analyze the market horizontally, you’ll find that breakouts behave differently early in the
trading day than later on. There are many more false breakouts as you move on through
the day. Why? On average, the reduced volume/volatility of those later hours makes it
more difficult to power new market trends.
But wait! If the odds and extent of breakout moves is different from one hour to the next
then that means that chart patterns will vary from one period to the next. That also means
that oscillator readings—what constitutes overbought and oversold—will similarly vary.
Here’s something to try: If you want to analyze the market by chart patterns or indicator
readings, switch your analysis from vertical to horizontal. Look only at similar time
segments from a stationary lookback period in the market and see what the market has
done when the patterns or readings have been similar to those observed currently. If you
see a breakout from a two-hour range that occurs at 9:45 ET, look at all similar breakouts
that have occurred in the first half-hour of trading. The chances are good that your
findings will be less fuzzy—and may even reveal a tradable edge.
Equivalent Bars: Another Approach to Slaying the Stationarity Beast
Richard Arms once came up with an intriguing idea: He drew charts where the bars were
defined by volume rather than time. Tick charts accomplish something similar. Each bar
represents X number of trades, not X units of time. The reason this is a promising
concept is that volume and volatility are very highly correlated. If we draw our bars on a
chart in such a way where they have equal volume, the odds are improved that we will
have a stationary intraday distribution as we move from one bar to the next. This would
improve our vertical analyses of the markets. For instance, if we wanted to use a 14
period RSI to define overbought and oversold levels, we would be on firmer ground if
each of the fourteen periods were relatively uniform and drawn from the same
distribution of values.
If we take the data from the tables above, we might think about making each bar equal
approximately 2000 contracts of volume. That would, on average, give us one bar for
each of the first two half-hours for the day; then one bar for each 45-minute period later
in the morning; and one bar for each hour around midday. Making this segmentation of
the day standard (where we always equate, say, the first half-hour of trading with the full
noon hour) is a quicker and dirtier solution than Arms’, but it does have advantages as
well. When you draw bars that are supposed to be equivalent in volume and volatility
and then you see an unusually large or small bar, it is much easier to visually identify the
significance of the breakout or consolidation.
Making the bars equivalent also affects the holding period of a trade. Instead of holding
a trade for X hours—where morning hours will expose you to much more volatility than
midday hours—you would hold the trade for X bars. Each trade would be more similar
to others, which is helpful for risk control.
Most important of all, however, is that you could have greater confidence that the chart
patterns and indicator readings that emerge on a uniform bar chart will be more reliable
than those that show up on a standard chart. A breakout of certain size from bar 1 to bar
2 will be more likely to have the same meaning early in the day as later, since you are
adjusting the time value of the bars.
My basic trading is intraday, but when I hold a position for swing periods, I use the
equivalent bars to help me time the trade. A future article will detail this swing trading
and how it addresses stationarity concerns.
Scalping: Still Another Response to Nonstationarity
In many ways, scalping is the opposite of creating equivalent bars. The scalper holds a
trade for a very short period of time—so short that the next bars are likely to be drawn
from the same distribution as the previous ones. Scalping reduces the average size of
gains and losses per trade and runs the very significant risk of overtrading and allowing
commissions and slippage to eat away at equity. If, however, the scalper can find reliable
patterns for trading, this can be the tortoise’s response to the swing-trader’s hare.
Scalping can be anything as short as trading the next tick if you’re on the floor to holding
a trade for multiple minutes. I define scalping pragmatically as exiting a position within
a time frame after which you normally expect the distribution of price changes to shift.
Thus, a scalp might be held for under 30 minutes early in the day, but could be held for
over an hour around midday. To use the above idea of equivalent bars, a scalp is a
position held within one of those bars.
Given this definition, most of my trading is scalping. Here’s an example: A market
drops on high volume at 11:00 ET, with the NYSE Composite TICK hitting –750.
Despite this drop, the market makes only a marginal new low for the day before
rebounding smartly as the TICK moves to zero. As the market pulls back lazily on only
modestly negative TICK, I might enter that trade on the long side to take advantage of the
failed downside breakout. The recent low—and the –750 TICK level—serve as logical
stops. On the first surge in upside volume and NYSE TICK, suggesting that the shorts
are panicking to cover their positions, I might exit the position and take a few quick
points of profit—particularly if it appears the larger time frame trend is down.
Note that a key to this trading is the horizontal analysis of the market. I know that the
volume is high on the downside breakout attempt, because I know the exact distribution
of volume for the 11:00 hour. I also know that the TICK reading is extreme for that hour
based on an analysis of distribution. The horizontal analyses allow me to objectively
define a buying or selling panic. I am buying a panic where the market shows underlying
strength; selling a panic where there is weakness. Because the trade takes place within a
half hour period, I need not be overly concerned about shifting distributions of price
changes. I can use standard one-minute charts and indicators without the need for
equivalence adjustment.

Risk and Success

Sometimes you hear people debate whether trading success is attributable more to trading
techniques vs. psychology. The answer, of course, is both—but the point where the two
intersect is risk management. A huge percentage of trading success or failure can be laid
at the doorstep of risk management. A recent book on risk management (that I’ll be
reviewing next week) observed that, across different traders and trading firms, 90% of all
profits were attributable to 10% of all trades. While traders would like to think of
themselves as making money on a majority of their trades, the reality for frequent traders
is that a minority of trades are winners—and it is the few large winners that produce a
favorable profit/loss statement (P/L).
The book goes on to observe that, if 10% of trades account for a majority of profits, it
follows that a large percentage of trades have to be “scratched”. A cardinal skill in
trading is recognizing that a trade is wrong before it hurts the P/L. Time and again, I
have seen good traders exit trades when the trades fail to move in their direction; bad
traders exit only after the trade has moved against them.
And yet it is equally true that, if 10% of trades are going to account for the lion’s share of
profits, traders must be willing to milk very good trades. This not only means finding the
sweet spot where you can “cut your losses and let your profits run”; it also means being
willing to trade sufficient size to maximize returns from a good trade. The worst traders I
know put on their maximum size when they’re trading at their worst. Typically, they
have just lost on one or more trades and now are trying to get the money back. The best
traders are able to identify superior trading opportunities—and are patient in waiting for
those—and will put size on to take advantage of these. This is how 10 good trades more
than make up for 90 scratches and losers.
A favorite trading story that I tell concerns a very successful trader. He promised to tell
me the secret of trading success. Of course, my curiosity was piqued and I asked, “What
is that?” He responded with a question: “What the ratio of your largest position size to
your normal size?” “Three-to-one”, I told him. He smiled. “Consider 20-to-1,” was his
advice and his success formula.
I completely believed him. The reason he was successful had nothing to do with finding
a better oscillator, regression analysis, or chart formation. He was successful because he
had the ability to identify—and wait for—particularly profitable opportunities and then
take maximum advantage of those. While 20:1 position sizing is—and will always be—
rich for my blood, I think the principle is valid: success is partly a function of putting
size on for the logical, not psychological, reasons.
This is one reason trading is so difficult. It is an unusual blending of traits that allows
someone to be prudent with risk, scratching trades that don’t move promptly as expected,
while at the same time milking opportunity. It is easy to find traders who are risk-averse
and stick with their one and five lot positions; it is also easy to find traders who will
swing size freely, including times when they are frustrated with the trade. What is rare is
to find the mix: the ability to accept and limit the 90% of occasions that don’t work, and
yet act aggressively on those 10% of times when there is a move to be exploited.
What is true for size is also true for time. Much can be learned simply by identifying
how long a trader has held onto winning vs. losing trades. If a trader is quickly exiting
trades that aren’t going in the desired direction, the average holding times for such trades
should be quite low. Conversely, with the good traders, it’s not unusual to see a trading
log that registers 10% of trades that are held for a lengthy period of time. Invariably,
these are the winners that contribute significantly to the overall P/L. The truly
unsuccessful traders will also display a minority of trades with long holding times—and
these will be the losers. I recently asked a trader why he hung onto a long position for an
unusually long period of time. He looked at me somewhat quizzically and replied,
“Because I had the bottom!” He was willing to sit through a choppy trade as long as it
went in his direction and as long as nothing happened to convince him that he didn’t
identify the bottom. That one trade made his entire day.
Perhaps this is a truism in all of life. The people who I have seen who have been very
successful in dating and relationships have been willing to go on very many first dates,
but not so many second and third ones. They “scratch” the unpromising dates and then
focus their energies on the 10% that look worthwhile. The same is often true with respect
to career and company success. A successful individual may take on ten projects over the
course of a year, but focus efforts on a single initiative when it yields promise. A
company may roll out ten products and quickly pull nine, making significant money on
the one that finds ready acceptance in the marketplace. Even successful artists and
inventors, researcher Dean Keith Simonton found, tend to churn out creative efforts,
deriving their fame from the small minority of works that attract the attention of an
appreciative world.
Successful traders risk manage their market exposure. Successful individuals risk
manage their life exposures. It is not just how much we undertake, but how much we
scratch in life that determines our ability to benefit from the episodes of promise that
come our way.

Sunday, May 3, 2015

Reversals in Minds and Markets

Consider the following scenarios:
• A highway patrol officer aims his radar gun at passing cars to determine who is
speeding. He notices a vehicle traveling 45 miles per hour in a zone that only
permits 30 mph. As it passes the patrolman, however, the car accelerates to 50,
then 60, then 70 miles per hour. The officer lets out a sigh of relief, noting to his
partner, “Well, we don’t have to worry. He’s going down the road so fast, he’ll
have to slow down eventually!”
• A psychologist meets with a client who has been complaining of feelings of
depression. For the past several weeks, she has not been eating well and her sleep
has been disrupted. At this meeting, however, the client divulges that she now
can barely get out of bed and is entertaining regular thoughts of suicide. “That’s
good news,” the psychologist responds. “You’re feeling so bad, you’ve got to be
improving shortly!”
• For the second time in a row, the stock market declines over 3% in a single
session, with the number of issues making new 52 week lows swamping the
number making annual highs. Volume and volatility have picked up on the
decline and a well-known market analyst concludes, “We’re seeing a capitulation.
This is a great time to buy.”
In all three examples, people are making inferences about a reversal of trend based upon
its increasing trajectory. Interestingly, where the first two situations seem absurd, the
third has been a staple of recent market commentary. It has also been a major reason why
investors have held onto positions through the recent decline, reluctant to sell when a
bottom might be at hand.
In this article, we would like to explore the psychology of reversals and shed some light
on how change occurs in minds and markets. We believe that such an analysis will help
investors frame their market strategies in the light of Wednesday’s dramatic reversal and
the raised hopes it has fostered.
Reversals and Emotional Change
The idea of the positive feedback loop is common to many approaches to psychotherapy.
Problems occur when people become locked into coping patterns that create negative
consequences. As the consequences mount, so do their faulty efforts at coping, creating a
downward spiral.
A classic example is insomnia. Once a person finds that she cannot sleep, she begins to
worry about sleeping and engage in a variety of actions to make herself sleep. Of course,
it is difficult to feel naturally drowsy when one is trying with all one’s might to induce
rest, so the very efforts at coping help to maintain wakefulness.
Ironically, the best treatment for such insomnia is to convince the person to cease all
efforts at making sleep happen. Simply having the individual perform a boring task is
sufficient to get their minds off their insomnia and naturally lapse into drowsiness and
sleep. The key to “cure” is reversing the faulty coping strategy with sufficient emotional
impact and/or repetition to ensure that the new pattern becomes self-sustaining.
Research conducted by cognitive psychologist Daniel Wegner of the University of
Virginia suggests that much personal change has this ironic quality. When we try to
control an action, as in attempting to not think about an unpleasant person or event, the
results typically backfire: an ironic process leads us to focus even more upon them.
People change, he observes, by reversing their coping efforts and thwarting this ironic
British psychologist Michael Apter, has proposed a Reversal Theory of motivation that
helps make sense of this irony. His research suggests that emotional states are organized
in polar extremes. During a given day or week, people shift from one pole to another, as
in the case of a person moving from excitement to boredom. Much of what
psychotherapists accomplish is a shifting of individuals from one pole to another,
enabling them to access new thoughts and behaviors.
A dramatic example of Apter’s reversals can be found in the research of University of
Texas psychologist James Pennebaker. He found that people who make efforts to avoid
expressing painful emotions wind up experiencing more of those emotions, taking a toll
on their mental and physical health. Interestingly, however, individuals who write about
their suppressed emotional pain in journals find relief from their experiences and
subsequently enjoy greater health. Once again, cure is found by radically reversing
people’s coping efforts.
Reversals in the Markets
Markets, we propose, operate on the same principle of psychological reversal as people.
In a sense, this is Newton’s First Law of kinetics applied to minds and markets: an object
in motion tends to stay in motion with the same speed and in the same direction unless
acted upon by an unbalanced force. It is the unbalanced force of the therapist, nudging
the person toward their opposite pole, that creates reversals of mood and behavior.
So what provides the unbalanced force among markets?
Here we turn to Edgar Peters, author of Fractal Market Analysis and Senior Manager of
Systematic Asset Allocation for PanAgora Asset Management, Inc., for an answer. He
explains that market participants are arrayed at a variety of time frames. Some trade on a
minute-to-minute basis. Others hold positions for days, still others for weeks or longer.
While the magnitude of average price changes vary as a function of holding period, the
distribution of those changes is shaped similarly across time frames.
What holds the market together, Peters explains, is that low probability events at a short
time frame—extreme rises or declines—are normal events at higher time frames. When a
steep short-term rise or decline occurs, relative values for selling or buying are created
for participants at longer time frames, who then enter the marketplace. They provide the
unbalanced force that reverses the short-term trend. In a very real sense, traders and
investors at longer time frames are therapists for the market. By entering the markets in
force when prices become attractively high or low, they become agents of reversal.
One important, Newtonian implication of this line of reasoning is that trends will stay in
place until price extremes are reached that convince the longer time frame participants to
enter the fray. Markets, it would appear, are prey to the same ironic process as people.
While traders and investors are actively seeking tops and bottoms, markets inexorably
continue their rises or declines. Only the reversing effects of the longer time frame
participants can nudge a market trend to its opposite pole.
Reversals in Market History
A study by Paul F. Desmond in the February 26, 2002 issue of Lowry’s Reports supports
this notion of market reversals. Going back to 1938, Desmond investigated all instances
of significant market declines. He specifically looked at the distribution of volume
among rising and declining stocks each day and the distribution of total point changes
among rising and declining stocks.
Desmond found that major market declines were typically accompanied by a series of
days in which 90% of volume was concentrated in falling stocks and 90% of price
changes were concentrated in declining issues. This suggested to him that panic and
indiscriminate selling was a hallmark of the latter stages of market declines.
He also found, however, that declines did not terminate until there were one or more days
in which 90% of volume was concentrated in rising stocks and 90% of price changes
were concentrated in rising issues. This, to use our phrase, was the unbalanced force that
created the reversal. Vicious downtrends tended to remain in place until such bargain
conditions were created that buyers (presumably from longer time frames) piled into
Could the market lows have been predicted in advance? No, although they can be
identified quickly once the strong upthrust days have occurred. Market bottoms do not
exist independent of subsequent market action. It is the mass buying noted by Desmond
that creates bottom points in the markets. “Days of panic selling cannot, by themselves,
produce a market reversal,” Desmond notes, “any more than simply lowering the sale
price on a house will suddenly produce an enthusiastic buyer…It takes strong Demand,
not just a reduction in Supply, to cause prices to rise substantially.”
What Does This Mean For Investors in Today’s Market?
Desmond notes that the September, 2001 decline did not produce a single day in which
90% of volume and price changes were concentrated in falling stocks. Similarly, during
the rise that followed the September lows, there were no strong demand days in which
90% of volume and price change were concentrated in rising issues. This led Lowry’s
Reports to conclude that we had not seen the ultimate market bottom, despite the severity
of the September drop. In retrospect, their call was correct.
In the recent market, the closest we came to a day with 90% of volume concentrated in
declining stocks was July 2nd, when the figure was in the high 80s. The sharp rise on July
5th saw 90% of volume concentrated in rising issues, but then the meltdown accelerated
without a single 90% day in either direction. Most notably, the rise this past Wednesday
did not meet the criteria of vigorous buying despite the magnitude of the price changes
achieved. This raises the very uncomfortable proposition noted by Desmond that the
market’s eventual fall may not be broken until we have seen a series of down days with
90% negative volume and price—enough of a decline to bring the longer term bargain
hunters out in force.
“Look at the extent of the decline we have had,” Desmond exclaims in wonder, “and we
havent even had the panic stage yet! … We had the long bull market where investors
were trained like Pavlov’s dogs to buy every dip and it takes a long time for people to
unlearn those lessons.” Indeed, Desmond notes, this may explain why major bear
markets tend to occur once in each generation.
If Wegner, Apter, Pennebaker, Newton, and Desmond are correct, only significant
reversals create change. Prices have retreated significantly from their highs, but not yet
so significantly that buyers are stampeding to pick up the bargains. Wednesday’s rally
may have been therapeutic for traders and investors, but it was not the therapy Paul
Desmond—and market bulls—need to see.

Reasoning and Trading

In many situations we face in daily life, we recognize that action must be guided
by reason. Thinking is a powerful antidote to impulsive behavior. A perfect example is
the breaking of habits. We learn to overcome compulsive eating or drinking by making
ourselves first think about the consequences, then consciously choose an alternate course
of action. Without clear thinking about priorities, it is far too easy to fall into patterns of
behavior that offer short-term rewards but longer-term consequences.
So it is for traders. Having worked with dozens of traders over the past year, I
can vouch for the fact that, among active market participants, overtrading is the single
most common problem they face. Overtrading in this context means putting trades on
where there is no explicit edge—and even no valid rationale—for the trade. Generally,
the reasoning behind the excessive trade is nothing more than, “I felt like it was going
up.” What the impulsive trader fails to realize is that this is no different from the dieter’s
excuse, “I felt like eating the chocolate cake.”
A common occurrence for me is that I will go into a trader’s room and observe
him/her trade. Although the trader may be struggling and losing money every day,
generally they make money while I am watching them. This is not because I am offering
such grand market insights; usually I do not impose my market views on a trader. Rather,
I require the trader to verbalize the reasons behind his or her trade. This has the natural
effect of slowing down their trading and making them distinguish between genuine trade
ideas and mere trading impulses.
From my vantage point, all trading ideas boil down to variations on two themes:
1. The market is trending, and we want to buy pullbacks in an upward trend; sell
bounces in a downward trend;
2. The market is range bound, and we want to sell moves toward the top of the
range once buying dies out; buy moves to the lower end of the range once selling
dries up.
If I am employing solid reasoning in my trading, I want to assess the status of those
themes in both the time frame that I am trading and in the larger time frame. A trend in a
shorter-time frame may be part of a range in a longer frame; a range in the short time
frame may be a consolidation within a larger trend. Not infrequently, your ideas
regarding targets for a trade will come from the assessment of the larger time frame.
A sure-fire way to identify impulsive trades is by their absence of a well-conceived
exit. Ninety percent of the effort is going into getting into the trade—the entry—because
the purpose of the trade is to be in the market, not to make a profit. The impulsive trader
seeks action, not results. Because exits are associated with the cessation of action, they
get short shrift.
Conversely, the reasoned trade contains several components:
1. An assessment of current price behavior: Is buying pressure expanding or
contracting; is selling pressure expanding or contracting; is price volatility
expanding or contracting?
2. An assessment of market conditions at shorter and longer time frames: trending or
3. A target for the trade: A move to new highs/lows for a trend trade; a move toward
a price mean for a bracketing trade.
4. Criteria for stopping the trade: Conditions that will convince you that your trade
idea is no longer valid
5. A decision of resource allocation to the trade: How much of your capital you are
willing to put at risk on the trade idea.
If talking these five components out loud before each trade would lead you to trade
less often and would lead you to trade far differently from how you’re currently trading,
there is a likelihood that you are overtrading. There is definitely something to be said for
having a feel for trading. That doesn’t mean, however, that feelings substitute for market
knowledge and awareness.

Personality and Trend-Following

I would describe my approach to trading as research-based trend following. By that I
mean that I attempt to ride strength or weakness in the market after it has been
manifested. I do not, however, automatically assume that any trend is my friend.
Instead, I use historical research to distinguish between trending movements that are
likely to continue and those with a high probability of reversal. This is a highly
disciplined approach to trading in that it requires significant research and preparation
time, as well as an ability to stick with market movements and one’s game plan.
In my book The Psychology of Trading, I referred to personality traits that tend to
distinguish successful traders from less successful ones. Several of these traits are also
likely to influence the degree of success traders are likely to have in adopting a trendfollowing
approach to trading. Below are several self-assessment questions that might be
useful in determining whether you’ll face particularly great challenges in riding market
trends. Please write down “yes” or “no” answers to each of the twelve questions before
reading further:
1. When something goes against you in the market, do you often find yourself
venting your frustration?
2. Do you enjoy (or as a child did you enjoy) roller coasters or other thrill rides?
3. Do you often find yourself procrastinating over work?
4. Do you consider yourself moody—sometimes rather up, sometimes rather down?
5. Would you generally prefer going out and partying with friends rather than
staying at home with a good book or movie?
6. Do you often find yourself apologizing to others because you forgot to do
something you were supposed to do?
7. Are you generally high-strung, tense, or stressed?
8. If given the choice at a buffet, would you prefer to try exotic foods you’ve never
heard of rather than familiar dishes?
9. When you have a task that needs to be done around the house, do you tend to take
a quick and dirty approach, rather than a meticulous, painstaking approach?
10. After a losing trade, do you often feel guilty or get down on yourself?
11. Have you experimented with or regularly used two or more recreational drugs
(other than alcohol) in your life?
12. Are you often late for appointments or for social plans you’ve made?
If you indicated “yes” to most or all of questions 1, 4, 7, and 10, you most likely score
high on a trait called “neuroticism”. Neuroticism is the tendency toward negative
emotional experience, and it shows up as anger, anxiety, or depression.
If you responded “yes” to most or all of questions 2, 5, 8 and 11, you probably score high
on a trait called “openness to experience”. Openness reflects a tendency toward sensation
seeking and risk-taking.
If you answered “yes” to most or all of questions 3, 6, 9, and 12, you potentially score
low on a trait called “conscientiousness”. Conscientiousness measures the degree to
which an individual is oriented toward duty, responsibility, and dependability.
Other things being equal, the ideal personality pattern for trend following is one of high
conscientiousness, low neuroticism, and low openness. A good trend-follower will stick
with rules and systems (conscientious), won’t impulsively enter or exit trades on the
whim of emotion (neuroticism), and will trade for profits, not stimulation (low openness).
In my experience, some of the best systems traders are among the least flashy people.
They are meticulous and conscientious about their research and execution, and they don’t
let their emotions or needs pull them from their discipline.
Conversely, individuals who are high risk-takers and who crave novelty, stimulation, and
action often take impulsive and imprudent risks. Very frequently, the neurotic emotions
kick in after a series of losing high-risk trades. Such individuals are trading for
excitement and self-validation, not just profits. Even if they are given a tested, profitable
trading system, they will not be able to follow it faithfully.
System traders often focus their research and energy on defining the optimal parameters
for a system’s profitability. Equally important is finding a trading strategy that meshes
with one’s personality. Traders who are relatively risk-averse may trade shorter time
frames and/or smaller positions than those who are risk-tolerant. Traders with a higher
need for novelty and stimulation may benefit from trading a greater number of stocks
and/or markets rather than focusing on a relative few. Are some personalities simply
unsuited for trading? I would say yes, just as some personalities are not cut out to be
fighter pilots or surgeons. It is difficult to imagine a trader enjoying ongoing success
without the capacity for disciplined risk-taking.
It is not at all unusual to find that a trader is losing with a trend following approach
because he or she is acting out unmet personality needs in the market. One of the best
trading strategies one can employ is to find adequate outlets for attention/affection,
achievement, self-esteem, emotional well being, and excitement outside of trading.
Sometimes traders I talk with try to impress me by explaining that trading is their entire
life. They do not realize that their very “passion” and “obsession” with the markets are
likely to sabotage them, imposing undue pressures and interference. If you have a trading
system and you faithfully execute that system, trading should be reasonably boring and
routine. Better to enjoy roller coasters outside of market hours than ride them with your
equity curve!

Saturday, May 2, 2015

The Neuropsychology of Trading

Abstract: This is a lengthy posting on brain activity as it relates to trading. While recent
advances in functional magnetic resonance imaging are revealing important brainbehavior
relationships, such research is difficult to conduct with traders. Use of thermal
biofeedback holds particular promise in objectively quantifying the degree to which
individuals are engaging in executive cognitive functions. Preliminary data suggest that
such biofeedback accurately discriminates between haphazard/discretionary and rulegoverned/
mechanical trading methods.
One of the traditional challenges research psychologists have faced is the reliance upon
the self-report of experimental subjects for data on such variables as moods, intentions,
etc. With the advent of functional magnetic resonance imaging (fMRI), it has become
possible to track cerebral blood flow patterns among subjects as they perform various
tasks. This allows researchers to see which areas of the brain are activated during
standardized tasks that draw upon particular cognitive functions.
Such standardization is necessary when assessing the functioning of particular patients.
For instance, a task called the PASAT (Paced Auditory Serial Addition Test) presents
subjects with a series of numbers. Each number in the series is followed by n seconds of
silence before the next number is presented. The task is for subjects to add the series of
numbers mentally. This tests auditory processing speed, attention, and calculating
ability. By obtaining fMRI pictures of normal subjects engaging in the PASAT, we have
a sense for the brain regions that are activated when engaged in these functions. When a
brain damaged patient is asked to perform the PASAT, the fMRI reveals those relevant
brain regions that are not receiving adequate blood flow. Interestingly, when efforts at
cognitive rehabilitation are undertaken, the brain damaged patients can regain some of
their skill at tasks such as the PASAT. This is corroborated by fMRI pictures that show
new regions of blood flow to those brain areas associated with auditory processing and
The implications of this work are profound, suggesting that the brain is much more
plastic than has been assumed in the past. With imaging, we can now see the brain
develop new blood flow patterns. Obsessive-compulsive patients, for example, who
undergone successful behavioral psychotherapy reveal structural brain changes before
and after their treatment. In the future, such changes might even constitute an objective
measure of whether a pharmacotherapy or psychotherapy has been successful.
One of my longstanding passions has been to identify the brain regions that are activated
during trading, and particularly the patterns of brain activation that distinguish successful
traders from their less successful counterparts. It is reasonable to believe that traders who
experience emotional interference with their trading, for example, would display different
blood flow patterns under fMRI than traders who maintain a reasoned discipline in their
work. It is also reasonable to believe that neophyte traders might show different blood
flow patterns than their more experienced peers. (Research, for example, finds that novel
tasks tend to be processed in the right cerebral hemisphere, while routine tasks are
processed dominantly in the left. Intriguingly, negative emotional experience also tends
to be lateralized to the right).
There are significant logistical difficulties in studying trading with fMRI. Imaging is
very expensive, and getting on the magnet at busy medical centers is not easy. Perhaps
even more daunting is the challenge of placing an entire trading station inside an MRI
tube and creating realistic trading conditions. Finally, there is the challenge of creating
standardized trading tasks, so that different individuals can be assessed on the same
I've mentioned on the List (and in my book) that one way I've tried to begin exploring the
brain/trading relationship is through a novel form of biofeedback. Most biofeedback
measures physiological arousal, and is used to track patterns of anxiety for the purpose of
relaxation. Forehead skin temperature biofeedback, however, evaluates minute shifts in
skin temperature on a real time basis. This reflects increases or decreases of cerebral
blood flow to the frontal regions of the brain, which are the mind's "executive center".
The logic behind the biofeedback unit is that skin temperatures should increase when
subjects are engaged in such processes as concentration, judgment, planning, and verbal
reasoning. Conversely, forehead skin temperatures should decrease when subjects are
frustrated or otherwise emotionally aroused and when they are physically active.
I commissioned an engineer to build such a machine (since none are commercially
available) and have been engaged in using it for research purposes. Most recently, I have
created standardized tasks for the unit that involve varying degrees of emotionality,
activity, attention/concentration, etc. By taking forehead skin temperatures every 10
seconds during task performance and calculating the standard deviation of the readings, I
can compare the distribution of temperature scores under one set of task conditions with
those derived from other tasks. The readings strongly support the underlying rationale of
the device: tasks requiring the greatest mental effort consistently generate the highest
temperature readings. The biofeedback unit appears to be an accurate means for
quantifying the degree to which subjects are exercising their executive brain functions.
An interesting side note: Very high skin forehead temperature readings that are sustained
over a period of minutes are invariably accompanied by major mood shifts, in which
subjects report feelings consistent with being "in the zone". They report an unusual
degree of clarity, focus, present-centeredness, and ease of thought. I should emphasize
that this is not a placebo effect: the digital readings of the machine are hidden from the
subjects so that they have no idea of whether their readings are high or low.
In my most recent experimentation, I attach myself to the biofeedback unit while placing
a variety of trades in the market. Unlike fMRI, there is no logistical problem with being
hooked up to the machine while trading. Specifically, I tried to create two very different
trading conditions: 1) uncertain, frustrating trading where I made decisions intuitively on
the basis of common technical oscillators and chart patterns, and 2) structured trading
where I traded a tested, mechanical system. To keep conditions constant, I traded over
identical time frames in similar midafternoon markets. During the seat-of-the-pants
trading, I started with relatively high forehead skin temperature readings, which
deteriorated over the course of the trade. In the structured trading, however, my readings
continued significantly higher throughout the trade. In fact, the average readings were
much higher than the highest levels recorded during my standardized concentration tasks.
Objectively (and subjectively) I was in the zone--but only when trading was structured.
The reason for this is a bit subtle. In the seat-of-the-pants trading, I didn't really know
what to look for to base my decisions and had to flit from screen to screen to pick up
(probably random) cues of strength and weakness. My attention was highly divided, and-
-because the trade duration was short (less than a half hour)--I felt rushed in my decisionmaking.
During the mechanical trading, however, I knew exactly what to follow on a
minute to minute basis and stayed glued to a customized screen that contained all the
relevant data for decision making. My attention was not divided, and I experienced no
sense of time pressure or frustration. (Yes, the mechanical trading has also been more
Much more experimentation remains to be performed. How are the biofeedback readings
(reflecting sustained concentration and mental effort) affected by large increases in
market volatility or position size? By holding period? By the nature of the trading
system? Do successful traders sustain significantly different readings from unsuccessful
ones? How much individual variability in readings occurs during hot and cold trading
Perhaps the most intriguing questions involve training. Can we train people to sustain
mental effort and access "the zone"? Would such training improve trading performance
by enhancing trader discipline, pattern recognition, and problem-solving? Can
dysfunctional trading patterns (blaming self for bad trades, failing to take valid trading
signals, impulsively trading when valid signals are absent) be eliminated by reprocessing
anxiety during states of high frontal activation? This, I believe, represents an important
frontier for trading psychology.