In 1992, I had developed just completed a spreadsheet that included the common PE ratios for companies in different sectors in America. There is little of the compound in it, but I made the decision that since it was had by me, I might as well share it. I posted that spreadsheet for students in my class to download and managed to get available to others who visited my website (more hopeful thinking than a genuine plan, since there were relatively few people looking for data online). Year since Each, I have added to the info collection, initially growing my list of data items for US companies, and within the last decade, adding to the collection by looking at non-US companies.
It is my first task each year and it requires up the first week of the year, today for the 2014 revise and I just published the info. While you can find them all by going to the info section on my website, I won’t bore you with the details in this article but focus instead on the what, why and what next of data.
The “what”: It begins with uncooked data! In the last three decades, we’ve witnessed a revolution in data-gain access to that we need to step back again to appreciate. In the 1980s, if you don’t prove helpful at a university or college or an investment bank or investment company, your access to data was not merely limited but often non-existent.
The first glimmers of the data revolution were in the 1990s and for me, it started with Value Line offering an electric version of the data, on a monthly basis by mail shipped on the CD. That was the foundation for my first data updates and Value Line data remains my base for US data, more because of my knowledge of it and its own history than any special characteristics. In fact, there are directories which have richer detail, not just in terms of having more data items for US companies, but in bringing in listings in other markets.
My decision to broaden my data improvements from US to global companies was prompted by my access to Bloomberg terminals which were installed at the Stern School of Business in regards to a decade ago. About five years ago, I started experiencing Capital IQ, an S&P product, today that is one of the more extensive directories for global companies.
In addition to accounting data, it offers market data and corporate and business governance data on specific companies and a simple interface for screening and downloading data. My focus in data analysis is to combine the info into a form where it not only less overwhelming but also more useful in valuation and commercial finance endeavors.
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To that impact, I compute averages on key statistics (profitability measures, risk procedures, and financial leverage steps) across sectors and geographical groupings. I also use the natural data to place my spin on corporate finance methods (cost of capital, excess returns) for individual companies. The why: It really is purely self-interest!
While I am gratified that there are some out there who use my data in their analyses, I want to be clear that there is hardly any that is altruistic about my attempts. So, if you’re curious, here are the reasons why I think that the week that I spend in the beginning of each 12 months is well spent.
Anchor Angst: Behavioral economists, you start with Kahnemann and Tversky, have noted that traders and analysts look for anchors, starting points for making judgments, when coming up with a decision. They also noted these anchors are often either skewed (by an investor’s own experiences and backgrounds) or predicated on fiction, resulting in bad decisions. So, exactly what is a low PE ratio in today’s market or a higher revenue multiple?
Rather than make those judgments predicated on bad information, Each year and let it inform my assessments I think it is useful to go through the data. It really is this theme that I used for my update last year, where I used one of the best books/movies, Moneyball, to illustrate the power of data. Go global: It is simple to speak “global” but it remains true that we are preferred with remaining “local”.