Why are the long-term charts favourite among investors?
It is arguably true that most traders and chartists use the daily timeframe when it comes to drawing analysis of an underlying asset. The daily chart is also one of the most popular charts in technical analysis. So, let's know why bigger timeframes are needed for the analysis.
The average traders' dependency on the daily charts along with their preoccupation with the short-term market behaviour causes them to overlook a very useful as well as a rewarding area of price charting i.e. the use of weekly and monthly charts for longer trend analysis & forecasting.
The purpose of the weekly and monthly charts is to compress the price action in such a way that the time horizon can be greatly expanded and much longer time periods can be studied.
The randomness or the ‘noise’ which occur can be completely eliminated with the use of the weekly as well as the monthly charts. Anyone, who is not consulting these longer-timeframe charts, is missing an enormous amount of valuable price information.
How a chart should be studied?
The best way to study a chart is by first analysing what the longer-term picture of the stock depicts. An investor chartist can consider analysing the monthly and weekly charts to get a clear idea about the trend of the underlying asset.
One point to note here is that the long-term charts are not intended for trading purposes. Long-term charts are useful in the analytical process to help determine the major trend and price objectives. It also helps in avoiding false breakout signals. Thus, it is important to completely watch the market through the lens of the monthly and weekly charts.
The long-term charts are quite useful for an investor rather than a trader. Investors are more concerned about the long-term performance of the stock and hence, would tend to use the long-term charts for a better understanding of the stock behaviour and the trend. However, a trader would be more concerned about the short-term trend and thus, would rely on the daily as well as the smaller timeframe for more collection of data points.