Despite its many advantages, analysis can be difficult to master. Making mistakes can result in inaccurate results with serious consequences. Recognizing these mistakes and avoiding them is crucial to fully harness the power of data-driven decision making. The majority of these errors result from omissions or misinterpretations, which can be easily rectified by setting clearly defined objectives and promoting accuracy over speed.
Another common mistake is assuming that a variable is usually distributed, when it isn’t. This can result in models being over- or under-fitted, compromising confidence levels and prediction intervals. It can also lead to leakage between the training and test set.
It is crucial to pick the MA method that fits your trading style. A SMA is best for markets that are in a trend, whereas an EMA is more reactive. (It eliminates the lag of the SMA since it gives priority to the most recent data.) The MA is also http://sharadhiinfotech.com/ carefully selected based on whether you are seeking the long-term or short-term trend. (The 200 EMA is a good choice for a long-term timeframe).
It’s important to double-check your work before submitting it for review. This is particularly important when dealing with large quantities of data as errors can be more likely to occur. A colleague or supervisor examine your work can also help you spot any errors that you could have missed.