I've utilized my limited time recently by going back and re-exploring mechanical trading programming from well over a decade ago. For the longest time, I have passed by this area of trading with the not-so-accurate attitude of "been there, done that, not interested."
Automated systematic trading is a broad, complicated and complex field
that I will never be able to fully grasp,
especially on the institutional side. Now days, this
field of trading has fancier names -- such as algorithmic, algo,
black-box, robot, HFT, and so on.
individual retail trader, I'm still confident that a very good discretionary
trader will be able to consistently outperform a solid mechanical
trading system. This is one of the primary reasons why I've always
wanted to become a good discretionary trader and moved away
from mechanical systems development.
Then why am I re-exploring developing mechanical systems?
have been recently inspired by Electronic Local's blog, which is
authored by a former pit trader on the LIFFE exchange who made the
transition to become an upstairs trader. I spent the past week going through his entire blog, and can report back that he has been very
generous explaining his trading system. I especially appreciate his
"how to learn to trade" process. Although he now sells training
courses, just the free content on his blog is a gold mine for those who want
to learn how to day trade the ES, forex, DAX, and other liquid trading
The initial purpose of EL's blog was to document his
journey of training his daughter how to become a consistently profitable
(CP) trader. It just happened to be that his daughter was from the IT
field, so it wasn't long before she started to utilize technology to
help her take what her father taught her and codify it as much as she could into a mechanical trading system.
Interesting use of trading systems
EL realized that by incorporating the basic overview of his trading
methodology into a mechanical trading system had some compelling advantages. He realized that there isn't a way to
distill and program all of his discretionary trading knowledge into a
mechanical system. However, he could setup a "hybrid" methodology where
the mechanical system can effortlessly monitor several markets, and alert him or
even automatically enter a trade.
Once a position
is established in the market, he can quickly scratch the trade if the
picture didn't feel right. He also discovered that he can
manage/scale out of the trade much more effectively vs. a static set of mechanical
rules. One reason is that there just hasn't been a way yet to code his
ability determine market "context" from his years of trading
experience. Therefore, the hybrid trading method will enable him to
cover and trade more markets, with less work.
EL has stressed many times in his
blog, your experience and ability to determine market context is
critical if you want to go beyond the performance of a typical mechanical
system and approach that of a good discretionary trader. For example, using
the most appropriate algo for the current market conditions is key. So
if you pick a trend following algo on a low volume chop day -- well, I
think we know what the outcome will be.
the hybrid approach, which seems to take the strengths from both technology and humans to leverage the best of both worlds. Another approach would be the totally
automated approach to utilize several different styles of
algos covering various markets, which would be similar to having having
your own group of prop traders (or multi-portfolio managers), each with
differing strengths and weaknesses. Ideally, this would smooth out the
profit equity curve over time.
Dusting off my programming hat to better understand probabilities
I've spent over the past week
dusting off my EasyLanguage programming hat, and have realized that my
learning curve has gotten quite steep again. I actually like this new
challenge. In a short period of time, I've been able to reproduce some
of his basic systems in TradeStation and have also been discovering some very
advantage of this return back to programming has been my ability to
test out various setups and patterns used in my discretionary trading.
There have been a few examples of setups based on indicators or price
patterns that I thought would be profitable over time, but my recent
tests have shown them to be lackluster.
By recently learning those trading setup probabilities, I'm sure I have saved myself
countless $'s in losses over the long term. It's an interesting
direction I'm headed -- coming up with various trading concepts, theories, and hunches, testing
them, and then determining whether it would work in a mechanical and/or
a discretionary trading system. Being able to code, test and understand my trading setup probabilities has given me a greater sense of confidence.
Where to from here?
interesting how EL's "inside out" setups (pullback in the direction of
the trend), as well as the "outside in" setups (catching tops/bottoms) leverage
and builds nicely upon what I have learned over the past year. I've
only scratched the surface so far with my exploration of systems development, but I believe this will be quite an
interesting path on my way to becoming a better and consistently
Although my summer non-trading schedule is getting even crazier, I hope to report some interesting updates soon...