Ma analysis is not easy to master, despite its numerous advantages. When it comes to the process, mistakes can result in inaccurate results with severe consequences. It is important to avoid these mistakes and identify them to maximize the potential of data-driven decisions. The majority of these errors result from omissions, or misinterpretations, which can easily be rectified if you set clear goals and encourage accuracy over speed.
Another common error is to believe that a variable is generally distributed when it isn’t. This can lead to over-/under-fitting their models, which could result in the loss of the confidence levels and intervals of prediction. Furthermore, it could cause leakage between the test and the training set.
It is important to select an MA method that fits your trading style. For example, a SMA will be best for markets that are trending while an EMA is more reactive (it removes the lag that is present in the SMA by putting a priority on the most recent data). Additionally, the parameter of the MA should be carefully selected, depending on whether you are seeking an immediate or long-term trend (the 200 EMA is a good choice for the longer timeframe).
It is essential to double-check your work prior to submitting it for review. This is particularly true when dealing with large quantities of data, as errors are more likely to occur. You could also ask your supervisor or a colleague review your work to help you identify any errors you might have missed.