Ma analysis isn’t simple to master, despite its numerous benefits. It is common for mistakes to occur in the process, leading to incorrect results that could have serious consequences. Recognizing these mistakes and avoiding them is crucial for harnessing the full potential of data-driven decision making. Most of these errors result from mistakes or misinterpretations. These errors can be easily corrected If you set clear goals and encourage accuracy over speed.
Another mistake that is common is to assume that a variable is typically distributed, even though it isn’t. This can result in over- or under-fitting their models, compromising the confidence levels and intervals of prediction. In addition, it could cause leakage between the test and training set.
It is crucial to choose the MA method that is compatible with your trading style. An SMA is best for markets that are trending, whereas an EMA is more reactive. (It eliminates the lag in the SMA since it gives priority to the most recent data.) Furthermore, the parameter of the MA should be chosen carefully based on whether you are seeking either a long-term or short-term trend (the 200 EMA is suitable for the longer timeframe).
It is essential to double-check your work before you submit it for review. This is especially important when dealing with large amounts of data, since errors are more likely occur. You can also have your supervisor or a colleague review your work to help you identify any mistakes you might have missed.