Trading > Analysis > Becoming an Analyst
Becoming an Analyst
Filtering information
Whenever you are analyzing a stock, there are hundreds of factors you need to look at. A beginner might wonder how it is possible to look at so many factors for each stock when you are expected to analyze so many companies in order to find a good one. The way you do it is to build up your analytical skills so that you can ignore many of the factors that you already know. I'll use McDonald's in the following example:Part of any analysis you do on a stock will encompass an analysis of the industry that the company operates in. Some of the various analytical questions that need to be asked are: What is the industry? How big is the industry? What is the growth rate of the industry? Who are the major players? What differentiates this company from the rest?
When it comes to McDonald's we already know the answers. The industry? Fast food. Industry growth rate? Slow growth (we don't actually have to calculate the growth rate in this case because we know fast food is a large, mature industry. We can just assume that growth is probably about 5%.). Major players? McDonald's, Burger King, and Wendy's. Differentiation? A strong brand, high-quality (for fast food, that is), good management, and a global presence.
The difference between "information" and "data"
One of the most often espoused principles of investing is that having information is the key to success. Although this maxim is actually not true (because having investing skills is the key to success), information is still important. The problem I have with this principle is that "information" is a term that is misused because a distinction isn't made between "data" and "information.""Data" consists of raw facts which are used as the basis for analysis. Examples of data are stock quotes and business news that comes off the wire. "Information," on the other hand, is an analysis of data which will then be used as the basis for making a decision. An example would be an article offering an analysis or an analysis that you do yourself.
There are ways to use both data and information. Data tends to be commoditized information which you can get from many sources for free. Therefore data is not something you should be paying for. An example would be: you shouldn't be paying The Wall Street Journal $99 a year to tell you the daily price of your stocks. Also, data is published in high volumes so you want to be careful not to spend too much of your time on it. There are tons of business news items coming out every day so you don't want to spend many hours a day reading them. With the exception of skimming the news at the beginning of the day to see the major business stories, data sources are used primarily when you need to look something up. Therefore, data is demand-driven research, not supply-driven. In other words, I look at data only when I need it. I don't browse it just because it is there.
As far as information goes, there is relatively little valuable information available. Some magazines have good information and Motley Fool does too. Other than that, there is very little information available. Why is this? Because information is based on analysis and analysis takes both time and skill so most publishers - be they newspapers or web sites - either don't have the skills to offer it or don't want to pay someone to create it. Another reason is that good analysis is very valuable so oftentimes it won't be free.
So you might be asking "If there is so little investment 'information' available then what do I do?" The answer, of course, is that you will create it yourself by doing your own analysis. As a matter of fact, this will the whole basis of your competitive advantage as a trader since the only way you will succeed is by being able to competently analyze information yourself. And the lack of good analysis that is widely available creates an opportunity for good analysis to be rewarded.
Note: The lesson above (the difference between information and data) is one of the most important lessons in investing. But to keep the confusion at a minimum, going forward I will be using the term "information" the same way everyone uses it - to refer to data or analysis.
