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Brainstorms: Systematizing, Oppurtunity and Macro Logic
How To Think About This Process
I hope the week has gone well for you. As we move into the weekend, I wanted to touch on several ideas:
The process of systematizing or automating
Opportunity and difficulty are two sides to the same coin
The process of systematizing or automating
While there are some amazing books on systematic trading (link and link), the principles for systematizing and automating work processes are functionally the same across any domain. The markets just happen to be a domain where there is a large amount of data due to the number of transactions.
When you begin to dig into strategies and models across the entire world you will realize the data in a lot of other countries is horrible compared to the US (transaction and liquidity differential). You wonder why there are more systematic strategies in the US compared to Europe? One of the reasons is that data in the Eurozone is an absolute mess.
Big picture though, the entire goal of systematizing analysis or actions is so that you can reduce the cognitive load you have and either free you to make higher-level decisions or have more time to allocate to other things.
Systematizing forces you to clearly identify the variables and signals that do change and don’t change. Similar to how teaching a subject forces you to really know it, systematizing actions forces you to explicitly test your knowledge.
There are three major principles I think about when systematizing processes:
Systematizing always has limitations: Typically, when you are systematizing a specific process, you are identifying all the variables of continuity an action or signal has with the past. However, a good systematized model will typically only show you a specific part of the dataset and its specific continuity with the past.
Systematizing isn’t a substitute for creativity and discretion: Finding things that have statistical significance doesn’t negate thinking about possible outcomes outside of the historical distribution. Furthermore, many times discretion is required to update a systematic model. There is a reason why someone who has a backtest of their returns rarely has traded the entire backtest. For example, if someone shows a backtest for the past 20 years on a strategy, they are likely to make updates as they trade it for the next 5-6.
Stay in your lane: I spend a lot of time thinking about what a machine is best at and what human discretion is best at. Many times I see people trying to do what a model is better at or see models trying to do what human discretion would be better at. For example, there is a divide between people either bashing or praising ChatGPT. In reality, you should be identifying what it is really good at and what it is really bad at and then figure out how you can merge your human abilities with ChatGPTs quantitive abilities. (The book Godel, Escher, Bach has been very helpful for me on this topic).
Opportunity and Difficulty:
Within this context of creating or automating the work process, I wanted to share how I think about identifying opportunities.
One of the most influential resources I have read on thinking about wealth, business, and opportunity is The Almanak of Naval Ravikant. You can read it free here: https://www.navalmanack.com/
One of the quotes from this book contextualizes how I think about opportunity:
In my mind, opportunity and difficulty are two sides of the same coin. If there is an opportunity without any difficulty then it’s technically a risk free trade and likely to get arbitaged away by society since human nature always pushes the evelope.
When I think about opportunity, I think about solving problems that are incredibly difficult and being able to scale the solution so the payout is unlimited. I am always looking for incredibly difficult things to do because I know most people stray away from difficult things. If my baseline is accomplishing difficult things then I am already ahead of most people.
This is part of the reason I do difficult things in every part of my life like working out. I will do intense workouts almost every day along with cold plunges and fasts. Why? Because the way you do little things is the way you do everything. I don’t say this as a prescription for you. All I am saying is I can’t do difficult things in one domain of my life and then just be lazy in another part of my life. When there is a fire in part of your house, you can’t stop it from spreading. You simply get to choose, is that spreading fire laziness or doing difficult things?
The final thing I will say on this is I now think about collocations of difficult things people don’t usually do. If creativity is bringing together 2 or more variables in perfect tension to address a specific temporal problem, then how can I do multiple difficult things that I know other people aren’t doing? Maybe someone is learning something difficult but is that person learning multiple difficult things at the same time?
And again, the point is not just doing difficult things, it is that difficulty and opportunity are two sides to the same coin. Find a really difficult problem to solve and then provide the solution at scale.
In the information age, you simply need to be at the right place, at the right time, with the right information to succeed
The last idea I am going to touch on is macro logic. There continues to be this idea out there that we will “return to normal.”
There is an implicit bias that we will always revert to a previous situation. If you want to fail in financial markets and life, always think in this mindset.
I never think about “returning to normal” for making decisions or trades. I always think in terms of “what will change?”
In financial markets and the world, you are always betting on change, not a return to some obscure definition of normalcy. When have you ever heard the media say, “OK guys we are back to normal and we can relax now.” NEVER!
Path dependency and change are the concepts you think most about when actively taking bets in any domain of risk-taking.
Things are always changing. The game: adapt or die!
Thanks for reading!
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