A helpful guide to accumulate references to understand the real nature of markets and how we can use them.

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This PKM page is part of the open-asset-allocator project! If you want an application to help you manage an investment portfolio using asset allocation techniques and this knowledge, check it out!

https://github.com/benizzio/open-asset-allocator

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First, to start diving into Antifragility

• https://en.wikipedia.org/wiki/Antifragile_(book)
• https://youtu.be/6kVgIfMMeWM?si=h2SyoF3RsOoODMRQ
• https://youtu.be/cP5tQGWagKc?si=S7dP0w6fOjT1bcMk

Non-predictive decision-making

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If you keep sampling humanity for height, you can safely bet on an average between 170 cm and 180 cm at any point in time after a sufficient base sample. If you try to do that with individual wealth, you will be mistaken by multiple orders of magnitude. Just try inserting Bill Gates in the sample after the first 10K people or the first 10M people.

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What are the premises that I need to accept to continue?

• Traditional finance is mostly based on probability models that follow normal (Gaussian) distributions or assumptions. This is worsened by human biases and the tendency for these models to “make sense,” since the systems we evolved to spend most time dealing with live in the domain of the Gaussian.

• Markets, economies, societies, biological ecosystems, and multiple other examples are Complex Systems (https://en.wikipedia.org/wiki/Complex_system) that belong to domains that follow fat-tailed distributions.

• A fat-tailed domain is an environment that looks like a Gaussian domain for a longer period of time but causes enormous ruptures when an extreme sample is added.

• The change of domain implies the need to select different models and tools. In fat-tailed domains, models are not so easily accessible, so applying rigor in non-predictive, forecast-averse strategies is highly beneficial;

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  Think weather. You can mostly trust the forecast a week forward to decide suitcase content and ignore the forecast for next year and just pay for an extra suitcase with extra equipment “just in case.” (Just remember: weather and climate are very different things).

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What is the concept and its practical applications?

• Replace common forecasts, “target prices” and predictions for situational awareness and protection against bad outcomes;
• Protect decisions from your Gaussian, emotional brain by not trying to get in or out in the right time/price, but by staying in and benefitting from things going good or bad (suffering a lot less than everyone at the worst times is also beneficial to enjoy the opportunities after the chaos);
• Buying cheap and selling expensive is predictive reasoning. Spending energy and time on the correct assets to have in the portfolio to survive the good and the bad, then leaving the buy/sell decision to the system via balancing, is non-predictive. Correct assets to have may become wrong assets to have in time, but the period of such changes tends to be a lot bigger than extreme price fluctuations. Good investments needs to be boring;

Where does Asset Allocation fit?

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Asset allocation allows the non-predictive management of a portfolio. Instead of focusing on target prices in a time frame, you can have target proportions during a cycle phase (observing signals of it starting or ending) and balance those proportions when they change. This strategy also pushes focus to the long term.

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• If you have 2 good, negatively, or neutrally correlated assets, AAA and BBB. You evaluate the market situation and buy 60% of AAA and 40% of BBB, allocating all your money;
  • You plan to re-evaluate and re-balance every year;
  • After 9 months, something wonderful happens to AAA, and it grows in value hugely; the news can’t stop talking about it. It’s now 75% of your entire portfolio. BBB did lose a bit of value in the scenario, and it now occupies 25% only.
  • There is no reason to re-evaluate the market situation; expectations are the same. Since the changes were huge, you already rebalanced to 60-40, selling AAA and using the money to buy BBB.
  • You sold “expensive” and bought “cheap”, without having to create a target price. This and the correlation strategy are non-predictive, as they need no forecasts to function.
  • Rinse and repeat.