Weekend Research

Lot's of Charts, Risk Taking and Intras

The weekend is for research……….

The nice thing about the weekend is that the markets are closed so there is a surplus of time to research and think without having to worry about markets moving. Crypto used to be a big deal over the weekend but ever since the BTC ETF and more institutional adoption, the majority of crypto moves are during regular market volume.

Research and Charts:

When you conduct research for any domain, you need to be intentional. However, your intentionality can’t squeeze out your curiosity and the ability for your mind to wander. I’ll take you through some of the research processes I run and then show you what I am looking at in markets.

One thing to remember is that it doesn't matter which domain you belong to if you are reading this. Your task is to figure out how to transfer the principles. I understand that a wide range of people might be reading this. Consider this perspective: among all the people in your field, no one is reading the exact set of publications you are reading. Therefore, use this as an advantage! Develop a unique knowledge and skill set that others cannot compete with you on.

Curiosity, Creativity, Research and Models:

When I approach market research, I always aim to solve a problem. The crucial aspect of being a practitioner is that you begin with the problem, while academics begin with theories. Each starting point has its advantages and limitations, but the critical thing to remember is to conduct thorough SOURCE RESEARCH!

Source research simply means going to the source data, books or papers on whatever topic you are trying to study. Anytime you go to secondary sources, you begin to create problems because it’s technically somebody’s interpretation of the original data/research. I cannot tell you how many mistakes I see from people not doing source research.

When I have a specific market I am trying to understand or a problem I am trying to solve, I aggregate all the data points, academic literature, and main books. From here I read everything and create lists of models I need to build, how to weigh various causal relationships, what data I need to look at, etc.

From here I systematize every variable that can be quantified. This is incredibly important because part of higher-level thinking to see 2nd and 3rd order effects is not needing to quantify things manually. For example, if you are doing higher-level math, you have a calculator or code to quantify specific parts of the problem so your mind can be free to think about the higher-level implications. This is the same thing in any domain.

In financial markets, I strive to build systematic models that quantify these “lower level” relationships so that I can use those as signals for making higher-level conclusions. Moving up this hierarchy of conclusions is the only way to scale and progress. I will give you a simple example, I have momentum models running on every asset in financial markets. These signals are synthesized into a dashboard so I can see the momentum of everything on multiple time horizons. This systematized dashboard begins to set a foundation for me to ask questions like: why is gold rallying with bonds? Why is copper chopping while oil is rallying? Why is the Russell down while the NASDAQ is up? Why is NASDAQ outperforming Dow when the dollar is down and oil is up?

These are some of the most fundamental questions you can ask in financial markets. The critical requirement is a model that integrates data or information as a basis for you to ask higher-level questions. This is where I believe most people fall short. They may possess a curious mind or be adept at questioning, but without a foundation that quantifies these "lower-level" variables, they will never be able to utilize their imaginative capacity for higher-level concepts.

AFTER I have quantified all the variables in a specific domain without being reductionistic, I then use this foundation of models to think creatively and ask questions. When I think about imagination, the primary goal is conceiving of scenarios that have not occurred in the past. Backtesting all previous scenarios or reading history is the baseline for imaginative a priori thinking.

There are two ways I think about imagination: first, I imagine different top-down scenarios that could take place where there is a specific collocation of variables sending specific signals. The second way is bottom-up by asking, what would the implications be if this single data point was doing x?

Let me provide tangible examples: for the top-down imagination, I might think about what type of growth, inflation and liquidity regime might happen in the future given the specific speed, levels, and direction of all my current signals. The second example would be asking, if the dollar moves up from here, what would that imply?

My goal is to consistently have systematic models running in a top-down and bottom-up fashion while also allowing my imagination to speculate along the same paths. Fundamentally, I want my imagination and intuition to explore what systematic models cannot quantify. Inversely, I want systematic processes/models to do what my mind is inefficient at doing.

I have spent a lot of time thinking about how these different ideas interact because the merging of man and machine is going to be incredibly important as we move into the next decade. In my mind, if you understand how these things function then you aren’t worried about AI or any technoloy destroying your job. You simply view it as a new piece of technology that can quantify things more effeciently which frees you to move to higher and higher levels of thinking in ways a machine can’t.

• If you want to look into this more there are several resources I would suggest:

  • Godel Escher Bach, a book that stretches me so much mentally and I still can’t say I understand it: https://www.amazon.com/G%C3%B6del-Escher-Bach-Eternal-Golden/dp/0465026567

  • The Beginning Of Infinity by David Deutsch. https://www.amazon.com/Beginning-Infinity-Explanations-Transform-World/dp/0143121359

  • These podcasts by Naval are still something I come back to again and again:

    • Link

    • Link

    • Link

The final thing I would say is that knowing basic human ontology and why we are the way we are is incredibly important for determining the limitations of machines and technology. This is a rabbit hole on its own so maybe we will do a future article on it.

Summary: when you are conducting research, you need to be intentional about it. There shouldn’t be this great divide between risk-taking and research. When you start with the problem in a bottom-up fashion, you realize how important your research is because it will tangibly determine how you take risks. Therefore, the way in which you research must be done with intentionality and rigor. This applies to all domains of life because risk-taking exists in all domains. This is why I continue to say that the principles we talk about here apply to any domain.

To Markets!

I want to connect a couple of the thoughts above to some tangible examples that myself and Noel Smith discussed on the Twitter spaces the other day. We had a great conversation and the recording can be found here: https://twitter.com/Globalflows/status/1646966297463500800

One thing we touched on was gamma hedging and intraday price action. I shared a paper that goes over this dynamic in this article:

Research Drop + Framework

Here are the specific papers:

https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3760365

https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4139328

https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3760365

https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3798844

https://www.researchgate.net/publication/326472346_Re-Appraising_Intraday_Trading_Patterns_What_You_Didn%27t_Know_You_Didn%27t_Know

This is a great example of when I did a lot of research on intraday price action. Last year, I read between 40-50 academic papers on intraday price action during different market sessions and market regimes. I spent a lot of time building models and backtesting things. From that, I spent time figuring out how I could synthesize these signals into a strategy that would trade intraday. I now use this strategy and models to identify execution points and short-term inflection points in assets.

An example of this is how the intraday volume profile overlaps with how price action takes place. For example, when the price has a significant deviation intraday as the volume decreases and begins to bottom, there is a reasonable probability that we rally into the close.

Obviously this isn’t always the case and there are some important clarifications you would actually need to know for trading situations like this. However, knowing how price action moves during different periods of volume is important for interpreting signal and noise.

I can’t really provide any more information on this type of dynamic but what I would say is there is a ton of edge in understanding how these relationships work, especially as they connect with macro flows and bigger-picture moves.

Ok to top things off, let’s go through a number of charts!

The yield curve did rally on the SVB crisis. However, I would be watching for it to revert back down temporarily as financials (XLF) rally.

We just had several big banks release earnings above expectations. This caused the big banks to rally but regional banks continue to show bearish price action due to deposits transferring to these bigger banks. I will be watching financials for additional signals in bonds.

I am expecting the dollar to bottom sometime around here but still need to do some more work on it. Funny story, the other day, someone who I never speak to texted me out of the blue asking if the dollar is collapsing. Mind you, this individual has no experience in financial markets. Just in terms of the whole narrative about the dollar collapsing, I don’t buy it. However, it is a bit more complicated than sentiment and the short-term narrative.

Michael Kao

has done some amazing work on this in his Substack. I would definitely check it out.

Doomberg

also has great takes on these types of situations.

The final question I will pose: will gold break out to all-time highs soon? It seems so close but I think we will need some type of catalysts to really push it through for a strong breakout. I see the possibility of another pullback if the yield curve flattens over the next couple of weeks but gold has diverged from real yields so we will see.

Alright! A lot of interesting thoughts in this piece but if there is one thing that purifies and tests any thesis, it’s skin in the game and risk-taking. Risk-taking is the one thing everyone avoids but only the brave face with courage.

Thanks for reading!