Ma analysis is not easy to master, despite its numerous benefits. Many mistakes occur in the process, resulting in incorrect results that could have grave consequences. Recognizing these errors and avoiding them is essential to unlock the full potential of data-driven decision-making. The majority of these errors result from omissions, or misinterpretations that can be easily corrected by establishing clearly defined objectives and promoting accuracy over speed.
Another common mistake is to think that a variable has a normal distribution when it doesn’t. This can lead to over-/under-fitting their models, which could result in the loss of the confidence levels and intervals of prediction. It could also result in leakage between the training and test set.
It is crucial to choose the MA method that is compatible with your trading style. For example, a SMA is the best choice for markets that are trending, while an EMA is more receptive (it removes the lag that exists in the SMA by putting priority on the most recent data). In addition, the parameters of the MA must be selected with care, depending on whether you are seeking either a long-term or short-term trend (the 200 EMA would suit a longer-term timeframe).
It is essential to double-check your work prior to submitting it for review. This is particularly true when dealing with large amounts of data, since errors could be more likely to occur. A colleague or supervisor examine your work can also help you identify any errors that you might have overlooked.
