Improving Your Trading In A Challenging Environment

In case you might have missed them, here are several articles relevant to making money in the current market environment:

Three Keys to Winning in the Market

Four Lessons Learned From Training Successful Traders

How to Thrive in a Low Volatility Environment

Three Best Practices of Currently Successful Traders

Have a great holiday!

Brett
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The Market Is Not Broken

This post is my attempt to make sense of the interesting observation that many smart and experienced traders lapse into periods of trading like idiot rookies.  I don't think it's simply that their emotions get away from them or that they stop following sound processes.  In fact, I think it's just the opposite:  they keep doing what has worked in the past, but now--in changed market conditions--their strategies no longer produce an edge.  In other words, as market regimes change, consistency shifts from being a trading virtue to becoming a significant vulnerability.

Let's take a simple example.  I have created a daily measure of buying pressure and selling pressure from intraday uptick and downtick data.  I treat the upticks and downticks as separate variables reflecting buying and selling activity throughout each day.  My data set goes back to 2014 and we can examine how buying and selling pressure are related to price change X days forward.  Indeed, we can place buying and selling pressure readings into a multiple regression formula and identify an equation that significantly predicts forward price movement.

When we examine scatter plots of buying and selling pressure versus forward price change, however, we see significant departures from the linear regression line toward the extremes of the distributions.  In other words, when buying and selling pressure are unusually high or low, the implications for forward price movement are different than when the values are more moderate.  Methods that extend linear regression to identify significant nonlinearities are able to more precisely model the relationships among buying/selling pressure and future price change.  As it turns out, an important mediating (interacting) variable is the volatility of the market.  The relationship between past buying and selling pressure and forward price change is not the same in one volatility regime as in another.

So, for example, low volatility regimes see considerable momentum effects:  high buying pressure and low selling pressure tend to be associated with further price strength.  In higher volatility regimes, short term buying pressure or low selling pressure tend to be associated with short-term mean reversion.  In low volatility regimes, the most powerful predictive time horizon is between 10 and 20 trading sessions out--significantly longer than in higher vol regimes.

The point here is that the patterns we observe in markets do not have universal validity.  Whether we follow chart patterns and "setups" or statistical relationships, the predictive power of these varies as a function of market conditions.  When we move from a higher volatility regime to a lower one, for example, what used to work no longer has a universal edge.  The entire idea of finding your edge and trading it with flawless discipline and consistency is itself flawed.  We need to adapt to market conditions and find relationships specific to the conditions in which we find ourselves.

Lately I've heard many traders lament that the market is broken, that volatility is gone for good, that algorithms are manipulating prices, etc.  Meanwhile, they continue to apply their linear methods to a nonlinear world.  The stock market is not broken.  It is simply behaving like low volatility markets behave.  Edges are present.  They may not be the edges that were present several years ago, and they may not be edges on the time frame that you happen to prefer.  They also may not be edges that you can uncover with lines and patterns on charts or simple correlations and linear regressions. Our challenge is to adapt to what is, not stay mired in what used to be.

Further Reading:  Stable Market Distributions and Why They Matter

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Taking the Drama Out of Your Trading

There's a line in one of my favorite J-Pop songs that, roughly translated, says that the ill-naturedness of a love based on appearances is second only to getting a cold in summer.  We fall in love with appearances and quickly find there is no substance.  We should be enjoying the warmth of summer and instead we're miserable with a cold.

When I first started working with traders as a psychologist, I found a common assumption was that great traders were highly competitive.  Many were specifically selected because they had a history of athletic competition.  A surprising number of those traders turned out to be idiots.  They approached each trade as a win/lose situation of cardinal importance, falling in love with the appearances of great "setups".  The drama created by getting hopes up and getting hopes dashed took its toll.  When good opportunities finally did arise, they often could not fully participate.  They were miserable with summer colds...nursing wounds from the bad trading that came from sizing things up when they had confidence and sizing way down when they lost that confidence.

Here's an analogy that I recently provided to a trader:

When I was single, I finally figured out that the best way to meet the right person was to go on many first dates and relatively few second ones.  I couldn't perfectly predict who my soulmate would be without actually meeting the person, so the key was to meet lots of people.  If and when my soulmate showed up, I'd know for sure.  I didn't have to predict what would work and what wouldn't, and I didn't need to approach first dates with high expectations.  I just needed to let odds work in my favor, have lots of first dates, few second ones, and put my energy on the relatively few situations that were promising.  

It was that reasoning that led me to go out with a woman who was 10 years older than me, not yet through her divorce, and who had three children by that marriage.  I would not have considered that a promising situation but that first date led to a second and third and we remain together after 33 years.

A trade is like a first date.  It might work; it might not.  You look for certain patterns and you see what happens subsequently.  When it doesn't go so well, you don't let the first date spill into a second and third.  You exit when you're least invested.  If it goes well, you invest a little more and stick with it.  It's all about probabilities and learning that first dates that don't become second dates are not failures.  They are simply experiences that are necessary to find those opportunities of a lifetime.

Once you fully accept those probabilities, in dating and in trading, there's little drama.  You don't go in with huge expectations and, indeed, you embrace the possibility that this will be nothing more than a one-time situation that doesn't work.  It's not about winning/losing, and it certainly isn't about you being a success or failure.  If you draw poor cards in poker, you don't become depressed and frustrated.  You muck the hand and wait for the next round.  

First trades are small and they are exploratory.  If the idea behind them is sound and flows support that idea, you'll have plenty of opportunity to size up by buying the dips or selling the bounces.  If the flows don't support the idea, or if the idea is incorrect, you'll scratch the trade or stop out when you're least invested.  

Trading with drama is like carrying on relationships with drama.  It becomes exhausting.  Once it becomes about probabilities, our ego is no longer part of the equation.  That allows us to see beyond mere appearances and enjoy the summer warmth of truly promising situations without the hangover of ill-natured colds.

Further Reading:  How Drama Can Create Trauma

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How Expectations Poison Our Trading

A while back I worked with a trader who was the most calm, balanced trader I had ever met.  He went through losses and drawdowns and I never saw his demeanor change.  During one particular drawdown that would have frustrated most traders--he went from up on the year to slightly down--I asked him why he didn't seem particularly upset.  He then quoted to me his lifetime Sharpe ratio (his profitability as a function of the variability of his returns) and explained the amount of risk that he was taking to make his desired return and explained that these statistics guaranteed that he would have such drawdowns at least once every year or two.  Tolerating the drawdowns was part of sticking with a process that had proven itself over many years.

This trader also explained why he did not size up particular trades relative to others.  He believed that having an edge in the market was a matter of probabilities.  He felt that he did not have a crystal ball that reliably predicted which trades would work.  If he were to size up particular trades based upon a false confidence, this would change his P/L dynamics, potentially creating drawdowns larger than those expectable based upon his historical Sharpe.  His goal was to trade consistently and let odds work in his favor over time.  Psychologically, he placed little expectation on each individual trade; probabilistically it might work out, it might not.  By reducing his expectations for each trade, he avoided frustration and trading reactively out of emotional reaction.

When we become frustrated and then either miss trades or overtrade out of that frustration, the problem quite often is with our expectations.  When we turn a trade into an issue of "conviction"--when we *need* for a trade to work out--we set ourselves up for disappointment.  Our job is to trade with the odds and accept the probabilities that the odds may not play out on any particular occasion.  Confidence in trading comes from the cultivation of a set of robust processes for identifying opportunity, expressing that opportunity as trades, and managing the risks associated with those trades.  

Can you imagine having a great romantic relationship if you kept score each day on the "performance" of your partner and became happy or disappointed based on that day's score?  How would you feel if your partner kept scores on your daily behaviors?  It does make sense to assess a relationship, but you do so over time by stepping back and making sure things are good in the big picture.  That is exactly how we should assess our trading.

Further Reading:  Overcoming Frustration in Trading

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(Re)Making It As A Trader

If there's any more challenging than making yourself a successful trader and starting from scratch, it's remaking yourself into a successful trader once you've been on top and your edge has eroded.  Not many people can learn markets; even fewer can relearn them.

Per the above quote, the reason remaking ourselves is so difficult is that it brings suffering.  We have to kill off old impulses and ideas to open ourselves to new ones.  We have to pass up the old trades to open ourselves to new ones.  Remaking ourselves is all about letting go, and that feels like loss.

Most of all, when we go back to square one and relearn trading, we let go of ego.  We go from being successful to being a beginner.  We go from trading size to trading one lots.  Not everyone can move from a level of success to a level of humility.

I recently spoke with a very successful trader whose edge in the market went away.  After taking time away from trading, he is now returning, learning entirely new strategies.  As I was speaking with him, I began to feel optimistic about his comeback.  There were several reasons why:

1)  He is keeping detailed statistics on his trading:  what's working, what's not, how he traded, what he could improve, etc.  He truly accepts that he's a beginner and is willing to work the learning curve just like the newbies.

2)  He is looking at markets in new ways:  exploring different markets and different ways of trading those markets.  He's networked with some smart people and is finding edges very different from what he used to do.  He's willing to try new things.

3)  He's looking to leverage his strengths:  knowing the skills that made him successful in the past, he's looking for ways of employing those skills in his new trading.  He's not trying to be a different person.  He's trying to find niches for the person he knows himself to be.

The traders remaking themselves aren't merely looking for markets to "turn around" and give them their old edges back.  They take responsibility for adapting to the markets as they are.  They aren't sitting around blaming algos or choppiness or bad luck for their challenges.  They embrace new learning curves.  They observe what others are doing successfully and find a way to incorporate those things into what they know and do.  A great example is a trader I know who used to trade the ES futures directionally, but now--in a lower volatility environment where there is considerable sector rotation--he is trading the relative strength of one sector versus another and finding solid short term moves and trends.  

Still another trader looks for stocks showing strength or weakness near a pronounced support or resistance area.  When the move goes into that area and volume comes into the stock (playing for the breakout), he is harvesting profits.  He is making money from the failure of breakouts to sustain themselves in low volatility conditions.  That is very different from his past "momo" trading!

All the elements that help make new traders successful--mentoring, coaching, observing skilled traders--equally apply to traders remaking themselves.  If you can embrace the challenges and successes of the new learning curve, the remaking process may bring more than suffering!

Further Reading:  

*  Seven Training Resources for Traders

*  Three Best Practices of Successful Traders

*  Four Lessons Learned From Successful Traders

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Will Quant Blow Up?

A recent Wall St. Journal article made the point that quantitative approaches to markets are sowing the seeds of their own demise, as the rush into these approaches means that they will blow up when markets change their character.

The MAFFIA group (Mathematicians Against Fraudulent Financial and Investment Advice) offers a convincing alternative view in an insightful blog post, pointing out the difference between pseudo-quants and actual quants.  Specifically, there is an important distinction between academic finance--and theories popular within academic finance--and actual mathematical finance.  The gap between the returns of such math-based firms as Renaissance Technologies and Two Sigma and strategies based on academic finance theories reflects the differences in approaches to investing.

Because I am intimately involved in the recruitment processes of trading firms, I see first hand the rise in pseudo-quant practitioners:  those using math in casual ways and marketing their approaches as quantitative.  An extreme example occurred in a job interview with a junior candidate who asserted his quant background and skill.  I mentioned to him my development of an ensemble model for the ES futures and asked him how he deals with large data sets to avoid overfitting.  The candidate looked distinctly uncomfortable and said that he had not developed any models.  Instead, he said, he plots market price changes on a graph and looks for patterns.  Needless to say, our conversation about quant came to a crashing halt!

Less egregious but still highly problematic was the trader who came to the interview with a regression model developed over the past few years of market data.  The model had a very high fit with the data, relying on a variety of rate of change measures.  He confidently asserted that his model was valid because he had tested it "out of sample".  Unfortunately, research suggests, if the search space is sufficiently large, it is not difficult to find a strategy that "works" in and out of sample merely by chance.  What looks like "smart beta" is all too easily mined with large data sets, resulting in inferior forward performance.  Such "quant" approaches can easily crash if they are implemented by the trading and investing herd.

True quant is the application of mathematics to the world of finance.  For those interested in mathematical finance, a wide-ranging collection of papers can be found on the MAFFIA site.  You'll see there insights into everything from the Sharpe Ratio to fresh strategies for hedging risks and what to look for in legitimate backtests.  The answer to the limitations of pseudo-quant strategies is not to abandon mathematics altogether, but rather to employ rigor in the application of mathematics.  Just as medicine has evolved from a discipline dominated by village doctors to more of an evidence-based science, finance is doing the same.

Resources:  

Quant Research Site

 Quantocracy

Quantitative Resources for Discretionary Traders

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The Art of Getting Better

A savvy trader sent me his trading review for the week.  It wasn't a journal entry or collection of journal entries.  It also wasn't a mere recitation of his trades and what he made or didn't make.  Rather, what he sent me was truly a business plan for the week.  He distilled what he needed to improve into two basic areas, figured out what he was doing wrong, and outlined the specific things he would be doing next week to make an improvement.  

What was interesting was that the things he was looking to improve were not grand overhauls.  They were tweaks in things he was already dong well.  But he saw that he could improve and take more out of the trades he was taking.  In a worthwhile post, James Clear points out that, if you can get one percent better each day over the course of a year, you'll wind up 37 times better than when you started.  Small changes, consistently implemented, add up to big results.

The best goal for most traders is to get better at getting better.  Turning a weekly journal into an actual business plan is one example of getting better at getting better.  Doing more of what works is a way of getting better.  Doing less of the things that don't work is yet another way of getting better.  But the greatest yield comes from turning self improvement into a habit pattern, a continuous process.  Per Deming, it's not just about doing your best.  It's about taking a step back and figuring out what to do before doing your best.

You would never take a cross country trip without a road map or GPS.  Self-improvement is no less a journey.  Your plan is your map, your assurance that your travels are taking you in the right direction.  Study your losing trades: what is one thing you could do better to stem those losses?  Study your winning trades:  what is one thing you did well that can be replicated next week?  Forget big goals.  What is the one thing you can change tomorrow?

How can you get better at getting better?

Further Reading:  Five Keys to Making Big Life Changes
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Is the Market Getting Stronger or Weaker?

Here's a useful measure of strength and weakness of the US stock market for the intraday trader (raw data from e-Signal).  Imagine that you are tracking every stock traded on every exchange every minute and computing how many stocks are making fresh new highs for that trading day minus the number making fresh new lows that day.  That tells you how strength and weakness are emerging, across stocks, through the trading day.  

Most of the time, the new highs/lows measure will track price well.  When we have a trending market, we'll see an expansion of new highs over new lows and the measure staying consistently positive or negative (depending on trend direction).  Oscillating above and below a neutral zero point is more common in range bound, rotational environments.

Note how, on Friday, we tested the day session lows in ES (blue line) and yet the new highs/lows measure (red line) held well above their morning lows.  This was an important sign that selling was not gaining breadth.  We then saw the new highs/lows climb steadily higher with price through the afternoon.  The positive and expanding breadth was an important tell that you wanted to be on the long side of the market.  There was no emerging weakness to fade, intraday.

An interesting facet of this time series is that you can track the new highs/lows during premarket hours to see if breadth is strengthening or weakening among stocks trading before the NY open.  This sets up valuable comparisons when the market opens, as on Friday, and breadth immediately deteriorates from premarket levels.  This is a useful indication that early morning participants who rely on liquidity in the opening minutes are distributing shares.  That information helpfully flipped me from long to short in my early morning trades.

At a broader level, this is an example of how traders can benefit from looking at new and different information.  There are many stagnating traders who look at the same information in the same old ways.  Collecting new data sets allows for exploration of patterns, some of which can be useful in innovating and finding fresh sources of edge.

Further Reading:  Finding Your Trading Strike Zone

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