By Daniel Archibald | CFA
In the early '90s, successful traders and finance academics, tired of making billions in profits for their employer, decided to set-up their own hedge fund and company, LTCM. And from 1994 to 1997 they made billions more, some for themselves and some for other investors. They had grown their fund from $1 billion to $7.4bn and all was looking great. They thought it was so great that they handed back over $2bn to investors in a forced sale so that they could effectively gear-up the fund and increase returns further. By the end of 1998, LTCM were virtually bankrupt and needed to take a $3bn bailout from concerned parties (US Government, banks).
So what went wrong? History will show that factors such as over-gearing and underrating of LTCM risks by counterparties were the driving forces. Greed was also a major factor of course. But another important piece to the bankruptcy puzzle was an incorrect assumption or two in their proprietary models. Yes, they got some of the numbers wrong; and when the world economy got hit by a series of unfortunate crises (Russian debt crisis, Asian financial crisis) the whole ship went down.
LTCM weren't the first or last to have suffered from financial modelling errors, but the amount of money that was subsequently lost, has made their downfall a well-examined example. Not learning from history, JP Morgan also suffered a multi-billion dollar loss at the hands of the "London Whale" and friends. And their error of underplaying losses at the extreme ends of the spectrum, was not dissimilar to what brought LTCM undone.
Perhaps more costly from an indirect point of view was the error that underpinned findings from a paper written in 2010, "Growth in a Time of Debt". In it, the authors Rienhart and Rogoff argued that the fiscal stimulus from running budget deficits would start to reverse at a relatively low level of accumulated debt. These findings, music to the ear of economic conservatives, led many western countries (particularly in Europe) to run hugely unpopular austerity programs.
Of course, tightening one's belt to live within one's means, is not a bad thing. However, the academically-backed austerity measures may have been implemented with a little more thought had they not been pushed along by the paper's findings. By the time the paper was discredited in 2013, Europe was suffering from its worst depression since WWII and the US was headed for a budget crisis and federal Government shutdown. Of course, with all the data and numbers to be crunched, mistakes are always going to creep into the system. One other criticism of Reinhart and Rogoff was the potentially misleading way in which they got to their final figures. Leaving out countries that might work against their desired result or including assumptions that were on the periphery of reality also highlights the need for independent number checking.
And where greed is involved, trying to skew the numbers in your favour will often lead to incorrect calculations and misleading figures. "LIBORgate" and other rate fixing scandals went unchecked for years, helping big banks to overcharge billions on contract settlements. And in Australia, the banks have been indicted over a number of issues involving the incorrect calculation of fees.
In a world full of information and useful data, it can be easy for errors to creep into the vast amount of number crunching that help turns some of the most important cogs of society. It can also be easy for figures to be presented more for propaganda than for education purposes. No matter the source or seeming insignificance, it is crucial to validate data, scrutinise the analysis and check the numbers.