Moving averages act as a fundamental building block in many technical indicators, and they are conceptually critical to a host of trading concepts. However, no tool is without shortcomings, and potential investing assets can turn into liabilities if they are used incorrectly because traders fail to appreciate their limitations. The disadvantages of moving average analysis center around its simplicity and subjective flexibility.
Although other types of moving averages, such as exponential moving averages (EMAs), exist to help reduce lags in data, moving averages necessarily place significance on past values that may or may not be relevant in the present or into the future. A simple moving average places the exact same weight on activity 10 trading periods into the past as trading activity that took place yesterday; this cannot possibly capture changes in company fundamentals or the economy as a whole. Traders need to be informed and aware of all of the major variables at play when investing, not just the produced values from simple technical formulas.
Statisticians created moving averages to qualify time series data and highlight trends. The length of those time series and the interpretation of those trends are highly subjective. Some tools apply 14-day moving averages, while others might use 50-minute or six-month moving averages. Even after understanding shorter moving averages tend to be more volatile, it's very challenging to decide on the correct timeframe to use.
Similarly, the interaction between price action and a moving average line must be correctly interpreted because a moving average on its own does not tell traders what is considered a significant deviation or correlation. Prices are generated through the supply and demand pressures applied by buyers and sellers.
Due to their simplicity and subjective flexibility, moving averages are informative, but never declarative.