Nature Always Prevails…
The Curious Case of Long-Term Capital Management (LTCM)
Perry C. Douglas
March 19, 2022
Long-Term Capital Management is the ideal failure to illustrate the reasons why you cannot change the ‘nature-of-things,’ and how the wrong, self-serving, ego-driven application of data can lead to major blow-ups. LTCM illustrates how normally smart people can engage in constructive delusion and draw in the herd to their elegant but delusional construct of reality.
LTCM was a hedge fund founded in 1994 and led by two Noble Prize Laureates and other leading economists, who were titled “geniuses.” LTCM used complex mathematical models to drive huge returns, where investors had to qualify as wealthy and sophisticated to get into the fund, which of course was part of the allure. Make things exclusive, the more common sense is voided, and the more people want in. LTCM operated at a high leveraged position of 25:1; $25 of debt for every $1 of capital. Without any formal financial training, common sense alone should tell you that things didn’t add up, that those ratios were not tenable. So, as ‘nature’ goes, in August of 1998 the fund lost 44% of its value overnight. It was so much money lost, and so quickly that the impact led to the Federal Reserve intervening and gathering 11 other banks to bail out LTCM at the sum of US$3.65 billion.
The fall of LTCM was precipitated and set off by a major and unpredictable event — the Russian-led liquidity crisis in 1998, an immediate flight to liquidity in global markets began. The liquidity crisis pushed LTCM’s leveraged positions to reach astonishing levels: 250:1. The fund’s investment strategy was inherently fragile, vulnerable to unpredictable shocks, because of its extremely leveraged positions. It was a powder keg situation where any small spark could set the whole thing off, and that’s exactly what happened, the Russian liquidity crisis lit the fuse and LTCM blew up.
For all the ‘genius’ accolades and Noble Prizes stacked up at LTCM, these ‘geniuses’ made elementary math mistakes, and basic errors in thinking and judgment, which were inherently driven by ego and the belief that self-created artificial methods could circumvent or get around the laws of nature. LTCM strategy was designed around a predictive mathematical, computer-driven, investment model which ran by imputing infinitesimal amounts of variables/data and receiving outputs to execute the trades. Essentially, these guys thought they were smarter than everybody else, smarter than the market, and most fatally, smarter than the universe. So, arrogance led to non-adherence to the intrinsic math that is embedded in the universe. They failed to understand that the very nature of the universe is math. Artificial math is a subconscious construct that is essentially delusion, fooling of oneself, trying to bypass basic first principles in nature.
Consequently, attempting to bypass nature was the common denominator responsible for bringing down LTCM, and not respecting nature and the mighty unpredictable, and always looming independent variable factor. For example, not paying attention to the mathematical fact that it doesn’t matter how many dependent variables you throw at the model, the mighty independent variable can always crash the party and change the outcome in an instant. The independent variable superseded all the infinitesimal variables that concocted the reasoning of LTCM. The independent variable rendered the model useless to the ‘elements’ of nature and built-in extraordinary risk for investors. The model was fragile to single shock events, like the Russian liquidity crisis.
Essentially, when you come right down to it, LTCM’s investment strategy was bogus, created monumental risk by the artificiality of investment methods away from reality, and not grounded, so there was no place for the shocks to be absorbed or neutralized by the model’s math. The model couldn’t solve for uncertainty and unpredictability, randomness, so in the end, these guys engaged in constructive delusion. Fooling themselves first and others by waving their PhDs and Nobel Prizes in front of peoples’ faces, like Jedi mind control tricks. Never mind the chorus of journalists and commentators, who effectively knew nothing but turned into media cheering investment advisors for LTCM. The herd gathered momentum, but the alienation of peoples’ wealth was the outcome. By focusing on the egos of men instead of logic and common sense, people essentially bought into philosophy…elegant theories. They forgot that there are no accidents in the universe, just real math! They voided themselves of exercising their intellectualism, rational, and basic common sense thinking that my grandmother thought my country ass — that there is nowhere in the universe where 1 + 1 still doesn’t make 2.
LTCM, made up of Noble Prize Laureates and other leading economists, was all hype, in the end, all sounded so smart and so good, and of course, it worked for a while but was certainly not “Long-Term.” LTCM got away with defying nature for a bit because humans are susceptible to great storytelling in making decisions. Rather than doing the hard work and applying logic, and facts, to seek objective truths, they become lazy, wishful thinkers, relying on the egos of men engaged in delusional storytelling, rather than on their own intellectualism and doing their homework. Therefore, events like LTCM happen over, and over again…beautiful suckers are born every day as the herd mentality remains alive and well in our universe!
LTCM cleverly turned data into a working theory to sell investments, and everyone loves a new and good theory, especially when the writers and storytellers have PhD’s behind their names. LTCM in their delusional trance, somewhere between reality and non-reality made the data match their preconceived investment conclusions to prove their theories. And of course, to make a lot of money for themselves! Hence, LTCM was anything but scientific, it was pseudo-scientific, it was philosophy, and a bad one too. Data, as it stands alone, is ‘ignorant’ and can be easily manipulated by those in delusional and augmented states of reality. Human intelligence is always applicable, but arrogance, combined with ignorance is dangerous, and PhDs are not immune. Not being skeptical and always accepting of what others in “authority” have to say is a mistake. Question everything! If the dots don’t add up, then go back to the original question, the main problem looking to be solved, which usually provides focused logic to the problem and our understanding of reality.
Don’t be fooled by specialists, often their thinking is limited by their training, they operate in mental silos, classroom economics, with a delusional philosophical understanding of reality. The universe doesn’t care about your philosophy, because the universe can’t be anything other than what it is. Your range or scope, your domain of influence, competence, vision, understanding, and cognizance, is always ‘limited’ by reality itself. However, you can certainly work within the laws of nature, through imagination and entrepreneurship to solve problems. But once you begin to believe that you can defy those laws of nature, through artificial circumvention processes, then failure is inevitable. Don’t believe the nonsense that ‘anything is possible,’ all is possible of course, where actions are taken to it within the reality of the universe.
The lesson about LTCM is that despite its star traders and mathematicians, Nobel Laureates, the ship still went down. They tried to augment nature, artificialized things and created spurious math, and disobeyed first principles, cardinal rules of investing. Remember that all data is from the past, and past events or occurrences can not necessarily be indicative of future events or outcomes. In other words, economists can’t predict a damn thing! As mathematician Sofia Kovalevskaya tells us, “Nonlinearity places limits on human hubris.” The natural world is impossible to predict, there isn’t any math for that, models do not imply predictability, they are just working theories in the end.
“Risk is based on the assumptions of the existence of a well-defined and constant objective probability distribution which is known and quite possible. Uncertainty has no scientific basis on which to form any calculable probability.”
John M. Keynes, 1937
So, what you don’t know can be more important to your outcome than what you do already know; so, be humble to that reality, it could often be helpful in most things. Never buy into the hype, be wary of nonsensical juxtapositions, and of anyone who claims to have or is utilizing predictive models; be skeptical! Try to focus instead, as much as you can, on figuring out what you don’t know, and what is true.
