t's common for some traders to see things in black and white, worrying too much about the outcome of each individual trade and giving excessive importance to winning or losing on every try. This perspective is pernicious because it overlooks the inherent uncertainty in the process, which often leads to unnecessary emotional burden and is almost always detrimental to decision-making.
Unlike gambling, trading is more akin to a marathon than a hundred-meter sprint. Both for the trader and the marathon runner, the key factor isn't the outcome of a single operation or the speed in covering a short distance, but rather maintaining a consistent pace that allows them to reach their goals.
Just like a professional marathon runner doesn't run the entire race at the same pace, a trader will experience losses and gains at different times. However, the key is to maintain a steady and consistent progress, evaluated in blocks of operations rather than each individual transaction.
In the case of the runner, it's the stopwatch that shows the pace and acceleration, while in trading, the appropriate tool for this purpose is basic statistics. Both serve the same function: to numerically describe the activity being carried out. However, while analyzing the past is important for evaluation purposes, one of the most crucial aspects is the ability to make future estimates based on partial and past readings. While these readings may not provide much context on their own, when aggregated, they become powerful.
In trading, two of the most basic statistics are also among the most important: expected value (average) and standard deviation, as they are fundamental to adequately describe a large sample of operations. Additionally, along with an appropriate estimation of probability, they allow for the calculation of future scenarios through statistical inference.
Precisely, the task of statistical inference involves aggregating individual data points to obtain a broader view, enabling us to look towards the future, always recognizing the uncertainty and the importance of probability.
Thus, mathematics allows us to understand the irrelevance of a single data point, such as the specific outcome of a trade. Statistical inference allows us to anticipate future outcomes by aggregating past data points, allowing us to understand how irrational it is to obsess over being right in each individual operation. Like the marathon runner, what matters is the final result, so the truly important thing is to focus on the process and the discipline in applying the set of predefined rules that form the backbone of our trading system.
Moreover, an approach that moves away from the need to be correct in each individual operation and focuses on maintaining process consistency has the ability to completely change the trader's relationship with their operations, avoiding unnecessary emotional burdens, which often are the starting point for disaster.
A brief look at the scope of backtesting can help us better understand the power of statistical inference. It's relevant to note that while backtesting is an important and very useful tool for evaluating past performance, it completely lacks the ability to extrapolate (anticipate the future) because it only looks backward. Although it can calculate averages, standard deviation, and some other more advanced metrics, it always operates in a world where there is no uncertainty because all the data is known in the past. It also doesn't incorporate a probability estimation, making it impossible to construct future scenarios. In short, the limitation of backtesting refers to replicating past operating conditions and staying there.
While statistical inference looks to the future, backtesting looks to the past. Stay tuned to read more about it!
In summary, trading involves maintaining a constant pace, evaluating performance in blocks, and recognizing the importance of the process over individual results. This discipline and strategic focus allow us to look confidently towards the future, as if we had a window showing us the path ahead.
Comments
Post a Comment