Give ’em a number or give ’em a date, but don’t ever give ’em both.
The above quote is from Howard Simons, a fellow Real Money contributor who is known for his “Iron Law” of forecasting (for economists). Putting together a market forecast is fun, but it is incredibly easy to make errors in the process. You can easily go back and forth, from hero to goat, several times. Keep laying out a forecast and eventually you’ll be right. The key is to nail your time frames.
Knowing your time frame allows you to drill down and find the characteristics that may define the market’s next move(s). You can determine market direction for just about any time frame, but your experiences with trends and patterns helps with accuracy. Analyze trends and patterns to form an opinion about future prices, and you have your market forecast.
Suffice it to say, creating a market forecast is difficult. To make sure your time frame leads the way (rather than leads you astray), you must understand the expectations for a potential move within your time frame. Hence, your analysis is critical.
For example, you can look at a 15 minute chart of a stock or index and get a completely different read than a daily chart. Similarly, we can also look at longer time frames, such as the weekly or monthly, and receive the same contradictory data. Unfortunately, this is a common occurrence in equity stock charts when the market is choppy or in a bear phase.
However, sometimes charts across different time frames are in agreement. Take a look at the charts for crude oil. The monthly chart shows the formation of a bullish “morningstar” pattern, which is confirmed in the month of April. April is roughly six weeks away, so we really cannot put this chart in the bullish camp yet. The weekly chart is the most bullish of all and is forecasting higher prices ahead, extending out toward the $43-$45 level. This may take several weeks to play out, and at that point, the monthly chart may be confirmed. This is valuable information and can be played with a high degree of reliability based on previous data points and probabilities.
Again, the key is knowing your time frames, digging into trends and patterns, and using your experience to create an accurate market forecast.
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