How Professional Traders Differ From Amateurs

One thing I am coming to believe more and more is that passion is a distinct edge in itself.

When you are truly passionate about something, the concept of ‘work hours’ becomes irrelevant. The best traders are fascinated by the markets; they absolutely love what they do. When you are fully immersed in your craft, you are working even when you’re not working. Great ideas can pop up when you’re brushing your teeth or walking in the park or hitting golf balls on the driving range. Setbacks are opportunities to learn more, not reason to quit. The thought of quitting is like the thought of cutting off your right arm. All your subconscious ducks are lined up and pointed towards the goal. Because you love it, you live it.

It’s the same with average guys and sports scores. How many guys say they hate math and see any type of figuring as a chore, yet they can memorize Kobe’s free throw percentage or Barry Bonds’ on base percentage with zero effort. Love makes the work easy–not like work at all. Which of course lets you work three times as hard as the guy who is force feeding himself… and finish the day with more energy to boot.

Point being, anyone seeking to play a competitive game without passion is at a clear and compelling disadvantage vis a vis those who have it in spades. Everything else can be learned except that.

Just my .02

With the rise of the Wall St. quant, I’m surprised to see that institutions and professionals still use technical analysis when all sorts of more formally developed and tested methods exist (statistical arbitrage and market microstructure analysis).

Is this a situation where politics wins out over performance? That is, fund managers and traders with no hope of ever understanding this stuff will ignore it in favor of Elliott Wave and the like.

I’m not knocking technical analysis — I actually believe most securities markets are nowhere near efficient. It’s just that recent developments in applied math and computing make it look like gambling.

Everyone talks their book Trader75, the quants certainly included; it could not be otherwise. The problem with quants or other widely accepted truthiness is that, like LTCM, they tend to cluster in the ‘proven’ zones – the ones where the models say most profit is to be made – the problem there being that that reduces variance and variability is the stuff evolution works on; when there is too little of it the most likely result when the system changes (as it always does eventually) is extinction. Today’s predator is tomorrow’s prey; always. Humility is a good survival trait.

Check out this fascinating piece from Seed Magazine: http://tinyurl.com/m4xwc

Another interesting factor in terms of trading and investing success: Stress, or the lack thereof. Those who enjoy their work, and naturally traverse a rich array of topics in the course of their work, are more likely to encourage neurogenesis. Those who handle stress badly, or don’t like their work, or have a very narrow focus, or all three, are falling behind on the cognitive front. Them that has gets, and doing what you love can actually make you smarter (as long as it doesn’t stress you out too much). Zazen anyone?

mentalmodel,

I agree with you that many of the popular uses of charts are a bit goofy. There is a whole lot of ‘mumbo jumbo’ in technical analysis, as Bruce Kovner has put it.

With that said, I think charts still hold their own in certain unconventional ways–for example, as a compacted source of information and a sorting tool. It is possible to look at a significant number of charts in a compressed period of time and very quickly discern what is worth further examination. If one has an idea stable of, say, twenty stocks long and short in seven different industries, selected by various data-driven metrics and contemplations etc, then one can still use charts to ‘check in’ on the ideas in the stable relatively quickly each day / week etc.

It is also possible to get a mental visual of market activity via chart… if you see a downside blowout followed by an immediate reversal on strong volume, that is a clue that a significant number of weak hands have been washed out and the composition of the longs has changed. The more layers of context you add, the more nuances you get… and the ability to distinguish subtleties and nuances in various situations, with an ability to ‘chunk’ the result into a single higher level action pattern, is a key differential between experts and novices. The skilled practitioner doesn’t calculate more quickly, he cuts off alternatives and comes to a recognized meta-level conclusion more quickly. Charts help with that.

Last but not least, discretionary traders and investors are still playing a game that computers can’t beat in my opinion. Big Blue has taken on Garry Kasparov and supercomputers have beat out prop traders, but making money in longer timeframes is closer to the game of Go than the game of Chess in that raw computational ability still falls far short of the human mind’s creativity / combination capacities. Because this is true, a longer term trader / investor (i.e. someone who isn’t competing for ticks) has the task of keeping his mental landscape up to date with a consistent flow of useful information, as much of the valuable work is done in the ‘back room’ of the subconscious, and a very useful / practical element of that flow includes charts. Put fundamental information together with skilled intermarket analysis, add charts to assess multiple elements very quickly, and hey presto, you can have an actionable thesis develop that a computer could never replicate.

Point being that a skilled practitioner can ignore the ‘mumbo jumbo’ and use charts to both assess a large volume of information quickly and visualize rapid shifts in investor composition / sentiment. This process has very little to do with the voodoo of elaborately named patterns or mystical Gann wheel type stuff; it is closer in spirit and application to the fundamental investor’s perusal of a balance sheet. The ‘expected value’ of a trade or an investment is cobbled together from a whole host of interoperating variables, and those variables can include the information presented by a chart.

Thanks for the interest.

“It is also possible to get a mental visual of market activity via chart… if you see a downside blowout followed by an immediate reversal on strong volume, that is a clue that a significant number of weak hands have been washed out and the composition of the longs has changed”

Two points seem worth making. First, there is a sub-discipline in the field of statistics called Exploratory Data Analysis. Computer Science types have reinvented this for themselves as “data visualization”, and technical analysis has been slow to embrace it. Modelers tend to start there, and construct methods for data reduction or signal identification using pictures as a guide. In many areas, such as political science where statistics gets used extensively, these models usually don’t have very strong “physical” underpinnings. I think the case with financial markets and economics is more encouraging (hence the comfort physicists can find within it). Expected utility plays a role, but so does prospect theory, or something equivalent (call it behavioral bias, bounded rationality, herding, whatever you like). This leads to my second point. Terms like support, resistance, and weak hands appear almost everywhere you look, but almost never get mentioned together with fund flows, open interest in options, curvature in implied volatility surfaces, or sentiment measured by polls of retail and professional investors (answer yes or no, the market is overpriced but I continue to participate as it will go higher), even though they all seem to be measures of more or less the same thing — all things a good model should incorporate.

My training in the dogma of science leads me to think that if I was handed other peoples’ money to invest, I’d probably choose to hire some experts in market microstructure analysis and behavioral finance to help identify trends as they develop, and make calculated gambles on the basis of this (all investing is gambling as I see it). The last thing I’d want to do is base my decisions entirely from a list of stock price charts coupled with a list of news articles (which seems like a pretty widespread practice on Wall St).