Lessons from 2008: Can Blockchain Pioneers Avoid Repeating the Mistakes of the Past?

Chancellor on brink of second bailout for banks.”

These were the first words inscribed onto the first block, of the very first blockchain. Satoshi Nakamoto, the creator of Bitcoin, did not choose these words lightly. Even then, I think they knew of the historical significance of that “genesis block”. Even then, they knew that their technology could fundamentally change the way we approach transactions.

In the aftermath of the 2008 financial crash, public confidence in the capital markets plummeted even further as the government poured billions into the “bailout”. By then, it was already clear to investors that the credit-ratings couldn’t be trusted, the SEC regulations were full of holes, ad the big banks were running wild. The bailout cemented their fears, showing that even the value of the US dollar was not a guarantee.

The blockchain was created to deal with the supposed root cause of these issues, allowing us to bypass the need for trusted third parties like banks and exchanges. But as it stands, the cryptomarket may fall to the same mistakes that failed traditional capital market.

For things to be different, there are some critical questions that need to be addressed. But first, we must understand the concept of “neoliberalism”, and the role in played in the 2008 financial crisis.

The Ghost of Neoliberalism

Neoliberalism is a highly-charged term, a term which has been so twisted and manipulated for so many political purposes that it’s hard to determine what it even means anymore.

But at its core, neoliberal philosophy is simple: people should be as free as possible to make their own choices, so long as they do not make others worse off. The ideal system is therefore one which gives them the freedom to maximize their individual welfare.

This philosophy inexorably tied in to the concept of “homo economicus”, often associated with the works of economists John Stuart Mill and Adam Smith. Homo economicus is an agent that is rational, self-interested, and single-minded in the pursuit of maximizing utility. Those familiar with economics will recognize this agent as the foundation for almost every economic model. But the application of neoliberal philosophy has seeped far beyond economics. For instance, CapM (capital assets pricing model), one of the most commonly valuation methods for assets, is built off the assumption that the average investor is a rational agent who hold a well-diversified portfolio, containing both the market portfolios and other risk-free investments.

While neoliberal philosophy was instrumental to the development of modern economics, the 2008 crash showed the dangers of over-reliance on these assumptions. Indeed, the years leading up to the crash were marked by a period of rapid deregulation in the capital markets. This deregulation granted financial institutions the freedom to channel enormous sums of money into highly volatile investments with little transparency, including subprime mortgages. After all it was said, as “rational agents”, investors could be trusted to know what was best for themselves. If they wanted to dabble in risky bets, then why shouldn’t they be allowed to? Whatever problems arise, the market would eventually correct itself.

And so it was that driven by the unchecked greed of speculators, the prices of these assets exploded to monstrous proportions beyond anything a group of “rational agents” might have produced. And so it was that the 2008 financial crisis came to be.

The Rise of Behavioural Economics

Behavioral economics is a field positioned at the intersection between psychology and economics. At it’s core, it’s economics that deals with humans as they are, and not as always-rational agents.

Within behavioral economic models, humans act within the confines of “bounded rationality”. This rather abstract idea can be envisioned as a limitation on decision-making power. While homo economicus have unlimited decision-making power, and are assumed to have all the relevant information they need so that they may consider it all to make the optimal choice every time, real humans do not have that luxury, given the sheer amount of information they have to deal with, and various time constraints. Thus they will often act without knowing all the relevant facts, with imperfect or incomplete information. In some dire cases, they may even deliberately choose to ignore relevant information.

We know from our everyday experiences that this is a much more accurate descriptor for human behavior. Unlike the traditional economic approach, which uses a set of unproven assumptions on what humans should be, behavioral economics takes humans as they are, with their rationality bounded by other factors such as emotion, instinct, and information asymmetry.

While this contemplation of these adds a higher level of complexity, it also allows behavioral economic models to better capture the reality of human behavior, recorded in empirical data. And as exponentially more data on human behavior is gathered through an ever growing world of sensors, the relevance behavioral economic will only grow with it.

The extrapolation of behavioral economics into the financial sector has yielded enormously valuable data on investor behavior, data that shakes old financial models to their core. In a 2011 paper, the researchers found that contrary to the rational agent used in tools like CapM, who maximizes individual profit whilst minimizing risk, the vast majority of investors tend to hold under diversified portfolios, and trade actively without careful selection. Furthermore, real investors were found to be particularly susceptible to the “disposition effect”, whereby they sell their winning investments while holding on to the losing ones.

Through these studies, we are increasingly closer to understanding why the efficient market hypothesis so often appears to fail, why bubbles form, and how psychological factors like loss aversion and overconfidence can skew the market. By acknowledging that humans do not behave in accordance with our old models, we can then challenge these old assumption. This will in turn allow us to create better systems that improve market efficiency, while keeping in check mankind’s most irrational, self-destructive behaviors.

Applying These Lessons To Blockchain

As the blockchain takes on an ever growing role in society, the pioneers of this technology must learn from the hard-won lessons of 2008. Yes the technology is powerful, but at the end of the day, while blockchain may reduce our reliance on trusted third parties, it cannot take humans out of the equation. Therefore, it is subject to many of the same issues of human irrationality that have plagued traditional finance.

Looking at the current state of things, those same past mistakes could be repeated. The cryptocurrency market has been dominated by rampant speculation. White papers are drafted in intentionally obscure forms. Overly simplistic incentive structures are being set up, ones designed for “rational agents”, and not for humans. The transparency of the blockchain is more of an ideal, rather than a reality for most people.

Too often, I hear people talking as if the blockchain will allow for some kind of unregulated, anarcho-capitalist free market. I think that’s an naive view. For an efficient transactions system to exist, regulations need to be put in place, not just to protect against malicious actors, but keep irrational ones in check.

With the blockchain, we have a rare opportunity to build up a new system from the ground up. And with this opportunity, comes the chance that we can do things better. The technology will certainly help to facilitate it, but the economic models we use will play an equally important role. By acknowledging actual behavior of human, instead of relying on outdated assumptions, we can create more user-friendly systems of transaction, which are safer for investors, increases the efficiency of transactions, and promotes confidence in the capital markets.

Concluding Thoughts

At this point, I’ll leave it to the real experts to figure out how to go about doing this. But here are a couple questions to get the conversation started.

  1. What are the touch points at which humans interact with the blockchain system? What assumptions about their behavior are we making when designing these points?
  2. How do factors like emotion and instinct negatively impact transactions? Is there a way for to create rules on the blockchain to address these failings?
  3. How can information on the blockchain be conveyed in such a way that reduces the “cost” imposed on the user by having the learn it?
  4. How can we build to blockchain to not only identify bad actors, but good actors behaving irrationally? What sort of mechanisms can we put in place to restrain these individuals from hurting others / themselves?
  5. If we have an incentive structure, how do we structure it so as to best encourage good behavior?

For Your Consideration

I’m currently working on a software that would allow human like ourselves to handle their investments like a “rational agent”. Holdbot is a program that that automatically diversifies & rebalances one’s cryptocurrency holdings, so one doesn’t have to go through the hassle of doing it themselves. If you’re interested in learning more about the initiative, more information can be found here.

This article was first published in Hackernoon in July 2018.

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