In the realm of algorithmic trading, a resounding surge is underway, with frequent discussions of automated trading systems both online and in financial media. It almost seems as if, sooner or later, every US family will be engaged in trading during their dinner gatherings, using their automated order placement systems on a screen that once displayed the evening’s TV entertainment. Reflecting on my own beginnings with the Omega TradeStation 2000i platform many years ago, where I developed trading systems, I recall that systematic traders like us were often viewed as outsiders in the field of technical analysis, if we were fortunate. In less favorable circumstances, we were regarded as failed scientists in search of new employment opportunities. Today, trading systems appear to be following the same path that technical analysis traversed years ago when online trading made an assertive entrance into the financial services market. Whenever commercial interests excessively promote a product or service, the result can be overwhelmingly misleading for the public. The advertising promoting trading systems seems to follow a familiar script: “Have you failed as a discretionary trader? If so, consider purchasing our trading systems, and you’ll start making money immediately, effortlessly. This is because automated trading is scientifically proven, it’s automatic, requires no discretion, and, most importantly, knowledge is 100% transferable without any deception, as it’s simply a computer code that works on my computer as well as yours.” Selling a trading system to a discretionary trader who has suffered losses and feels they’ve wasted time and effort is akin to selling fresh water to someone who has just crossed a desert. The purpose of this post is to demystify trading systems, despite being a firm believer in them myself. There’s no doubt about that. However, I must embark on this somewhat distasteful endeavor of critiquing trading systems for one reason alone: I don’t want the image of quantitative trading to be obscured, just as what happened with technical analysis in its early days when online trading emerged. So, what happened to technical analysis? In the last decades of the previous century, it seemed that the financial industry had co-opted technical analysis for marketing purposes, convincing traders that through technical analysis, they could gain 100% control over the markets. That, however, is entirely false. When it comes to financial markets, no one has absolute control over anything. If you’re fortunate, work diligently, and genuinely commit to mastering the best trading techniques, you can tilt the odds in your favor. That’s what you can reasonably achieve, but nothing more. A false sense of control led to the disrepute that the institutional and academic world openly displayed toward technical analysis. Fortunately, this has largely dissipated as technical analysis has become more integrated with quantitative analysis. In life, when you attempt to attribute meaning to something that doesn’t correspond to reality, the reaction is invariably harsh. The same phenomenon is occurring with trading systems: their promises and potential are often exaggerated in advertising and promotional communication. It’s untrue that trading systems don’t entail stress for traders. A trading system isn’t an immutable and unalterable law of the universe; it always has an expiration date. Trading systems are, in fact, built on certain market characteristics, but markets change day by day, and these characteristics appear and vanish without warning. Therefore, there’s no certainty in a trading system, only probability. Another point: it’s untrue that a trading system will magically work while you sleep, and you’ll wake up to spend all the money it’s earned for you. A trading system must be carefully monitored (often called “babysitting” in the jargon). The time you save when a trading system is running is the time you invested earlier in developing the system. Quantitative trading research demands a substantial amount of time. Proficiency in programming is required, along with emotional perseverance. It’s not a job for everyone. And in the end, it’s not true that all systematic traders make money. I can personally attest to knowing hundreds of failed systematic traders. The reasons for potential failure in trading systems vary. Sometimes, programming skills are lacking, and the trader must rely on others. Other times, the trader hasn’t done their homework and hasn’t properly tested their systems. Still, in other cases, their capital is inadequate (too low) to achieve meaningful performance. Perhaps the platform for quantitative trading isn’t up to par. Finally, maybe the trader miscalculated the drawdown and faced it after just two trades. Or, ultimately, the trader may have found this approach too stressful and opted to invest in government bonds. When you approach systematic trading, you’re essentially swapping some risks for other risks. You’re exchanging the risks of discretionary trading for the risks you’ll encounter in systematic trading. We can debate whether the risks in systematic trading are more or less numerous than those in discretionary trading. But we can’t paint the picture that systematic trading is risk-free, easy, and 100% successful. If that were true, everyone would be doing it, and it might be much harder to find a plumber because every plumber would be sitting in front of a computer running a trading system, without the need to go out and fix sinks. The reason I’m so concerned about clarifying the situation regarding trading systems, even though I’m a systematic trader myself and a strong advocate, is that if we don’t set the record straight, sooner or later, we’ll be treated as charlatans peddling a fairy tale. I don’t want that to happen. Systematic trading has much to offer the right individual committed to serious trading. And if you want proof that systematic trading isn’t for everyone, just call your plumber: if they answer and come to repair your faucet, it means that trading systems aren’t for everyone, and in that case, I’m right.