Despite its many benefits, analysis can be difficult to master. In the process, errors can lead to inaccurate results with serious consequences. It is important to avoid these mistakes and recognize them to maximize the effectiveness of data-driven decisions. The majority of these errors result from mistakes or misinterpretations. These errors can be easily rectified when you establish clear goals and encourage accuracy over speed.
Another common error is to think that a variable is normally distributed when it isn’t. This can result in over- or under-fitting their models, compromising the accuracy of their predictions and confidence levels. It could also result in leakage between the test and training set.
It is crucial to pick an MA method that fits your trading style. An SMA is the best choice for markets that are trending, whereas an EMA is more reactive. (It removes the lag of the SMA because it gives preference to the most recent data.) The MA parameter should be carefully chosen depending on if you are seeking a long-term or short-term trend. (The 200 EMA would be suitable for a longer-term timeframe).
It is essential to double-check your work before you submit it to be reviewed. This is particularly true when dealing with large amounts of data, as mistakes are more likely occur. It is also possible to have your supervisor or a colleague review your work to assist you discover any errors you may have missed.