Evolution is an interesting process. The theory goes that over time the optimal outcome will emerge.
Billions of years after Georges Lemaître’s “big bang” kick-started evolution, the species occupying the Earth today represent the current pinnacle of that evolutionary process.
The axolotl. Platypus. Zombie cicada.
Donald Trump. Q-Anon conspiracy theories. Reddit trolls.
Actions without consequence. Internet memes that move markets. Truth as a subjective choice.
Survivorship tells us what worked. Who was sufficiently fast? Lucky? Smart? Or ruthless?
The Natural History Museum, law courts, and unemployment office keeps score of what did not.
Machine Learning is an interesting process. The theory goes that if we feed a computer enough answers to a problem, eventually artificial intelligence will be able to tell us the best way to solve it.
First, ingesting vast quantities of training data. Then, iteratively evolving a solution to a problem. Sometimes the same problem that the data “scientist” was attempting to solve!
Microsoft once force-fed an AI chatbot millions of social media messages so it could become more adept at speaking like a millennial. It quickly evolved into a sarcastic feminist hating nazi.
Amazon built an AI to shortlist job applicants, using a blended picture of the perfect hire created by ingesting the CVs of thousands of successful tech bros. The algorithm determined that few engineers had captained a women’s sporting team nor attended an all-female school, so it proceeded to screen out those candidates who had.
A cancer detection algorithm decided the most efficient way to identify cancerous spots from photos was to look for the presence of a ruler, after all the training images supplied by oncologists contained one.
Faith, hope, trust, and blind repetition underpin many of our beliefs and actions. Yet if we fail to critically access their effectiveness, we simply emulate those errant evolutionary algorithms that resulted in the camel, Brexit, and generations of amateur investors who believe those expensive actively managed investments their broker recommends will outperform the market.
Everything we do involves choices. Choices made. Choices avoided.
Taking action requires choice. Doing nothing is also a choice, though not always a conscious one.
Every significant financial event in your life can be traced back to just a small handful of choices. Their effect and impact compounding over time. All leading to the point at which you find yourself today.
The blogger Finumus recently made £1,000,000 in just four short months, by taking a punt on bitcoin. Many would write off the windfall as a fluke. Stars aligning. The investing gods smiling upon him.
However, I challenge that conclusion.
True, Finumus got lucky when the herd briefly attached their desires to the latest shiny object, a token of digital imaginings without any intrinsic value of its own, shortly after he had bought his stake.
True, Finumus lucked in again when he cashed out of his position, shortly before the herd became bored with bitcoin and rushed off to join the WallStreetBets driven Gamestop pump and dump scam.
Yet let’s take a moment to reflect on how Finumus was able to make that million.
His bitcoin investment generated a 10x return, not a million-to-one lottery win.
That means he consciously decided to invest £100,000 of his hard-earned money into bitcoin.
Which means he had a spare £100,000 available to invest, nearly 4x average annual earnings.
Which (hopefully) means he had a £100,000 that he could afford to lose.
Which (probably) means that £100,000 was not a material portion of his net worth.
Which (likely) means that he breathes the rarified air of the top 1%. Able to take bigger financial risks. Survive greater financial losses. Enjoy larger financial rewards.
Which suggests that before the point he decided to invest, Finumus had already done pretty well for himself. Perhaps he was an entrepreneur, high-income earner, inheritance beneficiary, married into money, successful investor, or a trust fund baby.
Whatever the source of his wealth, Finumus had made a series of choices throughout his life. Choices that compounded until they made it possible for him to place that fortuitous bitcoin buy order.
His punt was not for the faint of heart. It wasn’t one that I would have made. Each of our choices had consequences. In this case, Finumus made a million quid and I did not. Credit where credit is due.
It would be easy to read about his success and think “he’s so lucky” or “why does nothing like that ever happen to me” or “it’s not fair!”.
What those who do so forget is that Finumus had put in the work. Identified the opportunity. Done the thinking. Borne the risk. Taken action. Put himself in the position to then experience that good fortune.
Made a series of choices that evolved and compounded.
Once we start to look for them, we see examples of these compounding decisions everywhere we look.
Fire and Wide retired early to a life of globetrotting.
Cashflow Cop wants to buy a forever home by the sea.
Banker on FIRE ponders the tax implications of a six-figure bonus.
“They’re so lucky!”. Except these would all have been impossible dreams, had those individuals not consciously chosen long ago to prioritise wealth generation. A side hustle as an amateur property developer. A buy-to-let property empire. A career as a high-flying master of the universe.
Some folks chose to sit on the couch, and enjoy a “Netflix and chill” moment each evening. Others put in the work to create value, negotiate property deals, unblock toilets, and slay corporate dragons.
Each of those choices had consequences. The bloggers will enjoy a sustainable financially independent existence, while the couch potatoes will not. Credit where credit is due.
We have seen some examples of the evolutionary compounding of choices. In some cases for the good, successfully executing a plan to create a leisurely life of slow travel or climb the greasy pole. In others, the not so good, like the innocent AIs that learned to replicate humanity’s own worst instincts.
Now let’s consider another example of evolutionary compounding, specifically when applied to the common lament: “London property prices are overvalued”.
If you ask London millionaires how they made their money, the majority of them would tell you that a decade or two ago they had purchased a crappy overpriced house in an up-and-coming neighbourhood. Then they simply kept up with the mortgage, and rising property prices did the rest.
The perception back then was that prices were overvalued.
The perception today is prices are overvalued still.
Those millionaires chose to buy a property anyway. Many others did not, deciding to wait for a market correction. Each of those choices had consequences. Today the home buyers are millionaires, while those who waited on the sidelines are probably not.
Which isn’t to say that owning property in London led to automatic riches. Nor that prices always went up. Nor that what has occurred in the past will occur again in the future.
No, my point here is that our perceptions of what represents fair value are often faulty, remaining tethered to the past.
We fail to update those perceptions for simple things like inflation, which erodes our purchasing power over time.
For example, in my current neighbourhood, houses today sell for the same amounts they did nearly a decade ago. Identically expensive in nominal terms, but representing a 15% fall in value over that period when inflation is taken into account.
The properties still feel ridiculously overpriced it is true, but they are now comparatively less overpriced in purchasing power or earning multiple terms. The widely quoted headline national and regional figures tell a different story, of record-high prices and a stamp duty holiday induced property boom, demonstrating once again that high-level averages mask a multitude of different stories within.
However, perceptions of aspiring buyers in my neighbourhood failed to correctly evolve. They were anchored to the wrong piece of information: nominal prices. Every year would-be buyers waited impatiently for nominal house prices to fall. Every year they compounded the error of their faulty thinking.
The absence of klaxons sounding, flashing warning lights, and media doomsayers shouting that the sky is falling meant the pullback in real prices that they should have been waiting for had happened while they weren’t paying attention.
Instead of recognising their mistake, re-evaluating their perceptions, and evolving they instead look enviously at their neighbours, “you’re so lucky!”. “Buying the dip” can be a wonderful strategy when it pays off, but the opportunity cost of waiting too long can be vast and in some cases irrecoverable.
We often fail to evolve our perceptions for externalities that alter the balance between supply and demand in a given locale. Examples might include net migration rates, fertility rates, zoning changes impacting population density, development approvals, infrastructure improvements, and the ever-changing employment prospects of local residents.
Do these changes make a location more or less desirable to live in?
Will they harm or help the prospects for future capital growth?
Such changes should cause us to reassess our perceptions of what would constitute fair value. Yet how many of us consciously adjust our expectations accordingly?
Media reports recently announced that London’s population had fallen by 8% during 2020. An estimated 700,000 overseas-born former residents had packed their bags and headed home. The pandemic cruelling their jobs in tourism and hospitality, driving them away. High barriers to entry for migrants wishing to move to post-Brexit Britain prevents their return.
What does such an exodus mean for property prices? A material demand shock in the short term.
Asking prices start to look very aspirational, as fewer prospective buyers compete to bid them up.
Property listings have surged, as a generation of existing homeowners sense a market peak, and hope to cash out before the music stops. Meanwhile, lenders share these concerns, as evidenced by the high numbers of prospective buyers who are failing to secure financing for properties at their current asking prices with high loan-to-value multiples.
Long term, there is the possibility of some more permanent structural changes at work.
If Britain’s recent penchant for nationalism results in the migration drawbridge remaining raised, then that “new normal” level of demand will become a permanent feature rather than a temporary bug.
Widespread adoption of remote working has shown it is technically possible to work from anywhere that offers a reliable broadband connection. Should remote working practices persist beyond the days of social distancing, then prospects for London’s expensive real estate would appear less than rosy.
Will buyers paying today’s “overvalued” prices face a similar negative equity trap to that endured by folks who paid too much for properties back in the late 80s/early 90s? Or will the populist government make good on their promises of that “sunlit uplands” for post-Brexit Britain?
I have no idea how things will play out in practice. Nobody does.
I do know that those who critically assess the effectiveness of their thinking, then evolve their perceptions to make decisions based upon evidence rather than faith and opinion, will produce more successful outcomes than those who blindly cling to belief and hope alone.
The impact of this evolution in thinking compounds over time.
Getting it right leads to successful careers, sustainable passive income streams, and maybe even million pound investment wins.
Without this discipline, errors creep in. Compounding over time. Resulting in the nazi chatbot, the sexist AI, and the envious couch potatoes who complain about how lucky others were to have achieved their goals.
- Banker on FIRE (2021), ‘Show Me The Money (Lessons From Bonus Time)‘
- Cashflow Cop (2020), ‘Forever Home Series (Part 1) – Our Search Begins‘
- Champion, K. (2020), ‘Recognizing a ruler instead of a cancer’, Menlo Machine Learning
- Dastin, J. (2018), ‘Amazon scraps secret AI recruiting tool that showed bias against women’, Reuters
- Elassar, A. (2020), ‘“Zombie cicadas” under the influence of a mind controlling fungus have returned to West Virginia‘, CNN
- Finumus (2021), ‘Thanks a Million! Bank Compliance Department Causes £1m Crypto Profit‘
- Fire and Wide (2018), ‘Our Journey To Financial Freedom‘
- Giles, C. (2021), ‘Coronavirus sparks exodus of foreign-born people from UK’, Financial Times
- Leadem, R. (2017), ‘Microsoft’s Twitter chatbot turns anti-feminist and pro-Hitler‘, Entrepreneur
- NASA (2021), ‘What Is the Big Bang?‘
- Office of National Statistics (2021), ‘Average weekly earnings in Great Britain: January 2021‘