Speculating with Lindy

If you are not familiar with the Lindy effect here is a succinct summary from Wikipedia: The Lindy effect is a theorized phenomenon by which the future life expectancy of some non-perishable things, like a technology or an idea, is proportional to its current age.

This phenomena is not mere theory. There are numerous data sets to back it up. One real world example that I love is about the lifespan of plays on broadway. The longer a play has been around the longer it is likely to be around. The newer a play is the likelier it is to be a flash in the pan.

I’ll give two other examples from Taleb’s books before attempting to make an original contribution to the intellectual record:

In the Black Swan:

“With human projects and ventures we have another story. These are often scalable, as I said in Chapter 3. With scalable variables … you will witness the exact opposite effect. Let’s say a project is expected to terminate in 79 days, the same expectation in days as the newborn female has in years. On the 79th day, if the project is not finished, it will be expected to take another 25 days to complete. But on the 90th day, if the project is still not completed, it should have about 58 days to go. On the 100th, it should have 89 days to go. On the 119th, it should have an extra 149 days. On day 600, if the project is not done, you will be expected to need an extra 1,590 days. As you see, the longer you wait, the longer you will be expected to wait.”

You’ve likely experienced this with road construction on your commute. It’s why initial setbacks to a project can be so frustrating as that malaise of apathy and frustration sets in. There is some underlying problem whose magnitude is slowly uncovered as the project is continually delayed.

Conversely, it’s why initial successes can be so motivating. It’s why we all chase momentum. it is exhilarating and thrilling to have multiple things go right in a timely manner and we know inherently that it is setting us up for future success.

in Antifragile:

“If a book has been in print for forty years, I can expect it to be in print for another forty years. But, and that is the main difference, if it survives another decade, then it will be expected to be in print another fifty years. This, simply, as a rule, tells you why things that have been around for a long time are not “aging” like persons, but “aging” in reverse. Every year that passes without extinction doubles the additional life expectancy. This is an indicator of some robustness. The robustness of an item is proportional to its life!”

Classics are classics for a reason. They have withstood the test of time and the critics of many ages.

So how can we apply the Lindy effect to speculating in markets?

Using the above example we could simply buy the intellectual property rights to the oldest books on the market. Unfortunately IP law in the US state that you can only own the rights to a work for 95 or 70 years after the authors death depending on if it was published before or after 1978 respectively. Although the smart lawyer’s at Disney have managed to extend their rights to one pesky mouse for well over a century.

So if we cannot take the book example to its logical extreme how about buying the rights to plays on broadway. You should always want to pay more for an older play if all else is equal. you could do some interesting arbitrage here. Over the last 30 years the average broadway show had 588 performances. At an average of 8 performances a week that means the average show lasted for 73.5 weeks or 1.4 years. If we assume that there will always be 25 shows on broadway, the current number, that means that on average every 21 day a show dies and a new one is reborn to take its place.

If we assume the Lindy effect is linear you should want to pay twice as much for a show that is twice as old. This should be true for all instances. So you would be willing to pay twice as much for a two month old show as a one month old show. But at the extreme upper and lower bounds you are more likely to have higher variance in your dataset. I prefer not to bet on babies or geriatrics. So the safer strategy I would suggest is to buy shows that are over 1.4 years old and sell short plays that less than 1.4 years old. This way you have controlled for many extraneous factors and have nearly a normal sample size of plays to work with.

A far easier option, as I see no practical way to sell short the rights to a broadway play, would be to set up a betting market on the future lifespan of plays and place bets with Lindy in mind.

You can pragmatically make a market and give people even odds on their favorite new play making it another year while they assume the boring three year old play that has lost its luster is surely meant for the graveyard anytime now. You will laugh your way to the bank, while your trading counter-party experiences a great tragedy.

Some claim that Lindy itself may not be Lindy due to the rapid technological and social changes of modern society . What if we wanted to apply Lindy to a more ready market such as that of common stocks:

“A recent study by McKinsey found that the average life-span of companies listed in Standard & Poor’s 500 was 61 years in 1958. Today, it is less than 18 years. McKinsey believes that, in 2027, 75% of the companies currently quoted on the S&P 500 will have disappeared.”

The above brings to mind many interesting ideas for exploitation. You could buy new companies and short old companies. On average this should outperform the market if you knew the average of the S&P company was going to continue to shrink. Embrace accelerated creative destruction if you will.

You could overweight companies that are at the halfway point of the median life span. The logic here being that on average you should outperform by avoiding impudent upstarts who are sure to burn out quickly and also avoid lumbering elders surely on their last legs.

Or you could take the exact opposite approach and overweight both temporal extremes of the spectrum. You can catch the bright young stars before they have become household names and been bid up to unreasonable valuations while at the same time buying old stalwarts about to undergo lucrative turnarounds while the middle aged companies have nothing exciting to offer. All of these would be worth backtesting.

If you look at a global data set of all equities over the last 30 years:

“The best-performing 306 companies (just 0.5 per cent of the total) accounted for almost three-quarters of the wealth created by stock markets over the last 29 years. The best-performing 811 firms — 1.33 per cent of the total — accounted for the entire amount.”

When going overweight or underweight anything you really don’t want to miss the star performers whether they be young or old. The pain of underperformance is far greater than the joy of outperformance. So if you choose to go your own way its better to get lucky early than to get skilled later because when it comes to compounding returns it’s almost impossible to catch back up.