What is the data collection bias in valuation?






What is the data collection bias in valuation?

Whenever we have to invest in a company or for that matter a debenture or a bond, our first step will always be to value the company's stock (if it is a listed company) or the business as a whole (unlisted company) or the bond's current and future value for making the right investment decision. If you see a company is undervalued, one will try to buy its stocks. On the other hand, if the value of the stock is overvalued, one will not see that as a good investment opportunity because of the chances of you losing your money due to consolidation of the stocks price is very high.

Now, the question is from where does this bias creep into the valuation process. Well, I have divided the answer into 4 parts for ease of understanding.

Outliers: When you are analyzing say for example a new e-commerce company, then you may want to refer to other companies for comparison of their PE Ratios. However, your comparison can be deeply affected if you don't be careful while considering which companies to use for valuation comparison. For example Company A, B, C, D, and E may all be in the e-commerce industry with PE Ratios of 24, 22, 21, 26, and 38. Now if you take out the Average PE for the industry it will be 26.2. However, if you exclude the outlier 38 (which is rare), the Average PE will be 23.25. The outlier company E skews the average upward by 2.95 which ultimately deteriorates the acceptability of the data.

Source of data: The second bias comes into the picture when the source of the data is not reliable. For example, the industry accepts the Bloomberg Data for analysis of companies to be reliable but the fact is that the data is mentioned from the report of the firms where there are high chances that there may be an error in copy-pasting an amount or inputting the amount manually by an analyst. The same is true when you get any information from any unreliable source. To be more accurate the sources must be official for example audited annual reports of the companies.


Thought Bias - When you want to know whether a particular bond is better for the investment then you might want to know whether the instrument beats inflation and gives a higher return than safe investments ( usually instruments with zero risk premium). But here comes the thought bias, two analysts analyzing the same instrument may have a different opinion. The reason being one might consider the safe investment to be a treasury bill and the other analyst might consider it to be a 10-year government bond. For example, let's say a treasury bill has a 4% return and a 10-year government bond might give a 5.5% return. Now if you are given a corporate bond which gives a return of 7%. In this scenario, the first analyst will inform that it is giving 3 percent more return and the 3% is completely fine because the risk premium is perfect for a large-cap firm. (Premium: 7-4=3%) The second analyst, however, will inform that the bond is giving 1.5% more return which is not appropriate as the risk premium of 1.5% is not enough for a company with such risk profile. (Premium: 7-5.5=1.5%) One has to be careful about the thought bias that may creep into a valuation.

Time period: One also needs to be careful about which historical data to be used for forecasting the returns. The economic environment is highly volatile and there are changes in the tax laws consistently. If you are using 10-year historical profit data to forecast a companies performance then you may get an inaccurate forecast of the profits. The reason may be that in the initial 6 years the company paid only 10% tax but after revision of tax laws, it paid 28% tax for the remaining 4 years. If the company is going to pay a 28% tax in the near future as well, it would be more appropriate if only the last 4 years' data is used for forecasting the profits of the firm.

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