Warnings of Hezbollah  striking against United States interests have appeared sporadically over the last several years, but recent events around the globe seem to warrant real attention in considering the Iranian-sponsored group’s efforts to hit US and Israeli partners abroad and at home.

Using Recorded Future to look at the last four months related to attacks associated with Hezbollah, we find:

Click for interactive view

The timeline gives us a quick idea of when reported attacks really bubbled up, but even more interesting is to line up connections to Hezbollah for this initial timeframe compared to those with months prior. First, we’ll view a network of entities (locations, organizations, and people) associated with Hezbollah from December 2011 through March 2012:

Hezbollah Network - December 2011-March 2012

We find some of the very much expected locations – Israel, Iran, Lebanon, Syria, – but we also see targets from India to Thailand to Azerbaijan to French interests that were either confirmed or alleged to be targets of Hezbollah attacks that are drawing attention to the group’s expanding scope of influence.

Next, we’ll shift the timeframe to describe connections from June 2011 to November 2011.

Click for live view with time slider

The reference to China in the network above comes from a write up by the Heritage Foundation blog the Foundry that suggests China is actually in the same market as Hezbollah for acquiring Club-K cruise missiles. And we’ve reported before on the now well known activity of Hezbollah in Latin America, primarily associations with drug cartels in Mexico.

So, the shift in recent months really does appear notable in the sense that these targets are quite different than previous targets more closely located to the group’s home base in Lebanon. It’s not the first time that connections have appeared in some of the locations, say for Thailand, which back in 2009 picked up weapons in Bangkok being transported to Hezbollah and Hamas from North Korea, but to actually carry out attacks there changes the game.

Keep an eye on where events related to Hezbollah are happening around the globe (view requires a Google Earth plug-in) using Recorded Future and set up an alert to make sure you’re monitoring activity as it happens.

Today we read in the Financial Times that “Analysts’ earnings forecasts have a negligible effect on a company’s share price, according to new research that will raise further doubts over stock-pickers’ ability to move markets”. While we have many friends who are analysts and certainly respect their work – it’s a pretty interesting point.

Now contrast that with the comment made by one of our blog readers recently

“It’s fun to contemplate the countless possibilities that come from aggregating data/events/etc … creating a “uniquely yours” data stream to shape your own indicators … and not having to wait-for and react-to the same data that everyone else is using (difficult to get ahead of the curve).”

Quite a contrast – would you rather track what everybody else reads or create your own unique insights?

As always, we welcome your comments below!

Christopher

When monitoring large amounts of media there’s an interesting opportunity to track potential economic indicators – direct and indirect – such as bankruptcies, corporate insiders buying/selling shares, credit ratings, analyst ratings, etc. at large scale. In this blog entry we’ll explore bankruptcies and ratings data from Recorded Future to make a high level judgement of whether the economy has turned around or not.

Bankruptcies

Bankruptcies are certainly an interesting part of the economy. Clearly when they start to happen at large scale things are about to go wrong (or perhaps already are). The ripple effects of single bankruptcies (General Motors, Lehman Brothers) can be massive across supply chains.

In this case we’ve reviewed the count of unique bankruptcies per month in aggregate as well as a simple rate of change metric for the same. The unique count is important as a bankruptcy event clearly can be covered repeatedly over and over – e.g. the General Motors event flooded the media stream in May/June. In the Spotfire visualization below we visualize the count of unique bankruptcies (red line) as well as the rate of change (blue line) over 2009 and can certainly see that bankruptcies picked up across the year, and peaked in July. The rate of change peaked earlier and has already turned negative. So, it seems that perhaps things are improving here!

Looking at a simple treemap of the bankruptcy events – organized by industry (just one level hierarchy) -  we can see on the left in the visualization below that the largest sector for bankruptcy events clearly is financial services, perhaps not a surprise. 

As a precursor to bankruptcies we may want to look at credit rating events – which we also pick up in Recorded Future. Reviewing those events below, across the year, in a somewhat simplified/filtered form, we can see how downgrades peaked earlier in the year, affirmations seems to be on the rise, but actual increases in credit ratings are still flat. The time lag between bankruptcies and credit ratings is quite logical – and would be interesting to model.

Finally in reviewing analyst ratings for 2009 we clearly see an increase across the year in upgrades – and actually perhaps now they (upgrades) are starting to flatten out (quite logical) – providing us with a sense of that analyst ratings first change, followed by credit ratings, before finally bankruptcies occur (yes, of course there is much more to story than that!). 

Applications

This type of data could potentially be used to create “macro indicators” – providing perhaps an early glimpse/prediction of what a later “official number” will be – which could be highly interesting in for example gaining an “up on the market” in terms of early indications of a impactful macro indicator. To improve it many things could be done – perhaps only looking at a particular industry or a specific data source (e.g. SEC filings).

However – the same sort of data could also be used to look at a particular company or portfolio of companies – what about if you could form an alert which allowed you to track the chain of a cut in analyst rating, a cut in credit rating, and first chatter of bankruptcy (and other events of course!) for a large set of of names/companies – and keep you notified along the way? Certainly something we want to do with Recorded Future.  

Conclusion

There are many ways this analysis may be argued as too simplistic – i.e. too short time period, should be compared against a baseline, seasonal adjustments, does it only look like an improvement – in reality the media flow just slowed down in August, or for that sake – media just getting bored with reporting bankruptcies. All these can be battled though – more/longer data frames, focusing on particular sources (SEC 8-K filings for bankruptcies), etc. etc.

The point of the exercise is less about trying to claim that this data is more accurate than for example an aggregation of bankruptcy court filings from primary sources or a number you may receive from an analyst – but more about how you can a) shape your own indicators from a novel data stream (media/internet) and b) be able to judge/read/react to those indicators faster than you can when waiting for a number that everybody else is waiting for (e.g. compare housing/jobless/etc. numbers).

Even more interesting is of course to combine this data with more indicators extracted from primary sources, internet, and media – insiders buying/selling shares, company restructurings, layoffs, buybacks, IPOs, company expansions,  etc. Recorded Future has all those event types and many more – and you can combine them – e.g. into a 4 step complex event that in total would indicate that a company is “turning around” or “flatlining”. Lots of opportunities for unique insights!

Finally: we’re obviously going to do some of the above improvements – and also look at incorporating forecasting/trending techniques here – as well as comparing results to 3rd party numbers/indicators.

As always, we welcome your comments below!

Christopher