Wolfram Computation Meets Knowledge

Losing a Country’s GDP in the Financial Markets

Yesterday it became known that a 31-year-old trader at Société Générale had been performing fraudulent transactions in the futures markets that ended up costing the French bank more than 7 billion USD. Some news sources have even speculated that the large market losses on Monday were caused by SocGen unwinding the bad trades. These market losses, on their turn, were the main cause behind the US Federal Reserve’s decision to cut interest rates by 75 basis points on Tuesday.

I was chatting about the topic with a coworker today when he mentioned—as people often do when these things happen—that this value was larger than the economy of many countries. Sure, but how many? As we do all the time, we fired up Mathematica to put things into perspective. And indeed, it’s trivial to get Mathematica to answer that question: you just use the built-in function CountryData to generate a list of all countries in the world, and select those whose gross domestic product (at market rates) is smaller than 7 billion.

In[1]:= Select[CountryData[], CountryData[#,

In[2]:= Length@%

The SocGen rogue trader managed to annihilate an amount of money that surpasses the yearly output of the economy of 112 countries, among them Madagascar, Mozambique and war-torn Afghanistan, all of which have population sizes larger than 15 million. A more visual way to present this fact is to use the "FullPolygon" property in CountryData to generate countries’ shapes, and then color those countries with a GDP below 7 billion USD:

In[3]:= Graphics[{{EdgeForm[Black],White,CountryData[#,

It took me less than a minute to visualize my office mate’s comparison, and indeed this is a type of visualization that a lot of Mathematica users can just pull out of their hats—thanks to the effort that was put into designing Mathematica to make sure that all of its functionality fits together.

For more examples of CountryData, visit The Wolfram Demonstrations Project.