Find Your Niche by Developing Balanced and Individualized Trading Systems
My professional background is in systems development and software engineering. Over the years, I’ve gained experience writing computer simulation models, developing large-scale systems, and analyzing large data sets.
When I first started trading several years ago, this engineering background gave me transferable skills to backtest and validate trading strategies. For example, it was a shallow learning curve to program and backtest strategies using tools like NinjaTrader and Amibroker.
However, it has also taken years to learn about and find a balance with important higher-level concerns, such as market dynamics, supply and demand, and trading psychology. Dedication to ongoing research has been needed to discover new trading ideas or refine existing strategies.
In general and for purposes of discussion, I also very much consider a trader to be an integral part of an overall system. Even if a trader adopts an existing system, there will at least be development of a custom workflow and process around the system. In this regard, there is always some further development or adaptation of a system to suit an individual trader. Moreover, an otherwise profitable system can fail if a trader doesn’t have the right skill, discipline or psychology to effectively trade a system; in other words, a trader can be the weakest link in the system.
Don’t Overly Focus on Algorithm Design and Technical Analysis
Coming from my own experience and background, there was a tendency to initially focus too much on the lower-level engineering of a system, but not have a more holistic, top-down approach. There are several pitfalls to overly-technical trading systems development:
- Hammer looking for nails (aka “Law of the instrument”): Especially for engineers and programmers, there is a strong tendency to view trading primarily as an engineering, programming or math problem. This was definitely the case when I first started trading, and I see it all the time when programmers, engineers or data scientists focus almost exclusively on backtesting, machine learning, artificial intelligence, trading bots and the like.
- Overuse or Misuse of Computerized Backtesting: Backtesting is a very powerful tool, but has its limitations. For example, backtesting tools orient around information which can be easily represented…