When I first started out, I had quite a losing streak as an independent trader.  Nearly every day, I would consider throwing in the towel. I asked myself continually why this wasn’t working out.  I couldn’t get it.  I’m smart enough (I studied applied math in college and finance in business school.)  I worked extensively with statistics and advanced probability theory in my past jobs.  I understood risk management, IN THEORY.  So what was going wrong?


Finally, in my darkest hour, a friend took me aside and directed me to read the books that would change the way I viewed trading forever.  I put my head down and started to study.  And I asked myself, what was the missing piece in my trading?  It turns out, the answer was productive psychology.  Being a trader takes serious guts, or as I like to call it -- strength of conviction under pressure.  That seemed simple enough to understand.  But the fix to my trading shortcomings ended up being much more complicated than ever I expected.


You see, we all know we’re supposed to buy low and sell high.  We also know we’re supposed to cut our losses short and let our profits run.  But I found that in the moment, I was doing anything but that!  How was this possible?  Was I so completely lacking in discipline?!  I’d run half- and full marathons before, hiked through Antarctica, for goodness sakes.


Turns out, the reason I floundered wasn’t just psychology.  It was biology too.  See, we’re all designed to prefer avoiding losses to acquiring gains.  In economic terms, this is called LOSS AVERSION.  Some prize winning economists even suggest the feelings of loss might be twice as powerful as the feeling of gain.  So how did this play out for me?  It meant that when I was trading, I was letting my losses run and cutting my profits short.  In other words, a surefire ticket to failure.


I’m sure I wasn't alone in making these mistakes.  And you might even be thinking to yourself, HA, rookie errors!  But this is just where things got interesting.


I believe in efficiency.  I want to do things in the most elegant, labor saving manner.  So I began to think to myself.  How difficult would it be to change my psychology, to unlearn what had been hard-wired into me through millennia of biological impulses?  Hmmm.. Pretty hard, I figured.  And so it was back to the drawing board.


If trading psychology was my problem, why not get someone else to trade my strategies.  Someone that wouldn’t be susceptible to these weaknesses.  Someone, or in this case, something!


And so was born my interest in automated strategies.  It turns out that a computer is brutally efficient when it comes to following rules.  If you have an algorithm (i.e. strategy) that works and you can tell the computer exactly what to do, then you never have to worry about getting your trades all twisted.  You just let the program do what you told it to and relax safe in the knowledge that you and your psychology are not going to get in the way of your growing account.


Now some people out there may be dubious.  They’re thinking to themselves, no computer can do better at analyzing markets than the human eye.  And I agree with that to a point.  See, the human part is in recognizing the trends that are going to make money.  Then you translate them into language the computer understands and let it take over.  It’s the best of both worlds.  You provide the market expertise and the computer handles the execution.  Now that sounds like a partnership made in heaven.


So all you need to do is download your ideas into a little black box.  As easy as it sounds, it’s actually quite time consuming to translate those human ideas into computer language.  Here’s what it takes.  You start with a general concept and then whittle it down into bite-size steps that the computer can handle.  Once you have a system that runs, then you start the process of refining and testing.


This is where a lot of would-be algo-developers go astray.  See, there are lots of great software platforms out there that make developing and testing algorithms really easy.  NinjaTrader has a wonderful system for backtesting and optimizing strategies.  But what happens is that many first-time (and even some more experienced) developers fall into the over-fitting trap.  They massage their strategy so much, adding indicators, tweaking the parameters to an extent that the results provide 99% profitability and returns off the map.  Hello, ONE BILLION DOLLARS!!


Not so fast though.  You see, with all this tweaking, you make the system behave perfectly on one dataset and one dataset alone..  the one you're using for testing.  And then when you start running your moneymaker on live data, you’re in for a big surprise!


That’s how we’re different.  I put all my statistical and quantitative finance study to good work in helping to develop strategies.  I use the finest methodology in practice today for testing and optimization.  The final piece of the puzzle is running the strategies through simulators and on live data to triple check that the parameters are set for winning results and not susceptible to those pesky feelings like fear, doubt, and greed.  


I got into this business because I love markets, I love analysis, and earning money to do what you love is one of the greatest gifts anyone can have in life.  I’ve learned a lot through this journey to build this business.  And I want others to benefit too.  As Thomas Edison put it, “the value of an idea lies in the using of it.”  And so let's get to work transforming your ideas into action.


Go Get 'EM, Traders!!


Note: Although automated trading can reduce the risk of psychological factors impacting results, there are risks inherent with this mode of trading including but not limited to system outages, market disruptions, market illiquidity, and unanticipated bugs in the software.



Founder of LakeshoreATS - Kara Boniecka has years of finance experience from the floor of the CBOT to developing automated strategies for experienced traders at a prop shop in Chicago and then most recently and since 2010, developing her own systems.  Her expertise is in applying advanced statistical and data science practices to the analysis of futures markets.  She's a decent programmer, but for the really tough stuff, she enlists the aid of her rockstar software engineer husband.

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