Despite its many benefits, analysis can be difficult to master. There are many mistakes that occur during the process, resulting in incorrect results that could have devastating consequences. It is important to avoid making these mistakes and recognize them to maximize the benefits of data-driven decisions. The majority of these mistakes result from omissions, or misinterpretations that can be easily rectified by setting clearly defined goals and promoting accuracy over speed.
Another common mistake is assuming that a variable is typically distributed, when it isn’t. This can result in models being either overor under-fitted, and thereby compromising confidence levels and prediction intervals. 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. A SMA is best for markets that are in a trend, whereas an EMA will be more reactive. (It eliminates the lag of the SMA because it gives priority to the most recent data.) In addition, the parameters of the MA should be carefully selected based on whether you are looking for either a long-term or short-term trend (the 200 EMA would suit the longer timeframe).
In the end, it is essential to always double check your work prior to you submit it for review. This is especially true when dealing with large amounts of data as errors are more likely to occur. You can also request that your supervisor or a colleague review your work to help identify any errors you might have missed.
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