Ma Analysis Mistakes

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Despite its many advantages, analysis isn’t easy to master. There are many mistakes that occur during the process, leading to incorrect results that could have serious consequences. It is important to avoid these errors and recognize them to maximize the value of data-driven decisions. Most of these errors result from omissions, or misinterpretations that can be easily corrected by setting clear goals and promoting accuracy over speed.

Another common mistake is to assume that a variable has normal distribution even though it doesn’t. This could lead to under- or over-fitting their models, which can result in a decrease in prediction intervals and confidence levels. This can also lead to leakage between the test and training set.

It is crucial to choose an MA method that is compatible with your trading style. A SMA is ideal for markets that are trending, while an EMA will be more reactive. (It eliminates the lag in the SMA since it gives priority to the most recent data.) The MA parameter must also be carefully selected based on whether you are seeking a long-term or short-term trend. (The 200 EMA would be suitable for a long-term timeframe).

Finally, it’s vital to make sure you check your work before submitting it for review. This is particularly true when dealing with large quantities of data, since mistakes are more likely to occur. You can also have your supervisor or a colleague review your work to help find any mistakes you may have missed.