We’re having a heat wave here in the UK so as I lay out under my lawn sprinkler (suitably primed with a mixture of spring water and a rather nice chardonnay – me that is, not the lawn sprinkler) I began leafing through one of my favorite journals  - Biological Cybernetics. Yes, I know you all have a prized copy hidden away somewhere – under the bed or in the garden shed – but there, back in the 1981 volume, I came across Associative Search Network: A Reinforcement Learning Associative Memory introduced by the authors as:

In this paper we describe an associative memory structure which is not told by some outside process (e.g., a “teacher”) what pattern it is to associate with each key. Instead, for each key, the network must search for that pattern which maximizes an external payoff or reinforcement signal. As this kind of learning proceeds, each key causes the retrieval of better choices for the pattern to be associated with that key.

and I wondered what relevance this might have to XBRL. Read the rest of this entry »

We know that it’s pretty easy to analyze XBRL data when companies are using the same base taxonomy element.

• What about when companies have used different base elements?
• What about companies that did not tag the totals but instead tagged all of the details?
• What about companies that tagged using an extended element?

It’s still a simple process to compare multiple companies even if some use base elements and others use extended elements. Read the rest of this entry »

Thanks to companies leveraging XBRL to report their financials, I can now compare companies side-by-side – and I can do it more quickly than ever before.

I created a report to compare 24 different companies.  In a single report, I gathered data for the 3 previous months and created 16 different ratios for these companies.  This report was created in just a few hours.  Now, when any of these companies file, this report is updated automatically with no additional work involved.  I am even alerted when these ratios fall outside the norms that I defined.

Because these financials were tagged using XBRL, I know the answers to questions within minutes that in the not too distant past would have taken me weeks to figure out. Read the rest of this entry »

Imagine a world where a company files today with the SEC and you are automatically alerted if their Return on Sales has dropped below 20% and their Quick Ratio has dropped below 2.0.  Well that world is today, thanks to XBRL.

Prior to XBRL, this was not possible, unless you paid to have this information delivered to you.  Companies would produce their SEC filings in HTML.  To get at this data, you would go the SEC site, copy and paste the data into Excel, and begin the process of “fixing” the data (modifying all of the negative numbers, etc) because the HTML tables did not come over seamlessly. Now imagine doing this for 20 of your peers. Read the rest of this entry »

For the past year, I have seen multiple blogs where people have questioned the benefits of XBRL. I believe the time has come to start recognizing the benefits of XBRL. Whether you want to analyze how your company is performing as compared to your 5 closest competitors, analyzing the financials of companies who you want to invest in as well as their peers, or just wanting to look at the contingencies and commitments for selected companies, XBRL is a tool that will allow you do all of these plus more.

Over the following week, I will have a series of blogs that will showcase the benefits of XBRL. Read the rest of this entry »

I enjoyed skimming Tim O’Reilly’s presentation from TED 2011 Towards a Global Brain. It has some good dare to share quotes in it like this one from Peter Norvig, Chief Scientist at Google:

We don’t have better algorithms. We just have more data.

As XBRL is just one of many bricks in the wall of data sharing, this is encouraging.

One of the concepts O’Reilly also refers to is ‘selection by association’, which is something that has an XBRL connection in relation to the kind of compliance analytics Rivet supports e.g. the decision to extend or not extend a tag or to select or not select the same tag for a fact as your peer group. Associating your tag selection choices with those of your peer group could help to avoid ‘red flags’ when your S.E.C. filings are reviewed by regulator or investor analysis tools.