{"id":240088,"date":"2026-03-11T12:09:19","date_gmt":"2026-03-11T16:09:19","guid":{"rendered":"https:\/\/ibkrcampus.com\/campus\/?p=240088"},"modified":"2026-03-12T05:05:29","modified_gmt":"2026-03-12T09:05:29","slug":"everything-everywhere-all-at-once","status":"publish","type":"post","link":"https:\/\/www.interactivebrokers.com\/campus\/ibkr-quant-news\/everything-everywhere-all-at-once\/","title":{"rendered":"Everything Everywhere All at Once"},"content":{"rendered":"\n

The article “Everything Everywhere All at Once” was originally posted on Robot Wealth<\/a> blog.<\/em><\/p>\n\n\n\n

\"Solo<\/figure>\n\n\n\n

The four hats of the solo trader<\/h2>\n\n\n\n

At a trading firm or fund, the researcher doesn\u2019t run the execution desk. The portfolio manager doesn\u2019t build the tech and infrastructure. These are different jobs, done by different people, with different skill sets.<\/p>\n\n\n\n

When you\u2019re trading solo, you\u2019re all of those people (and more).<\/p>\n\n\n\n

And the thing that catches most of us is that even though you\u2019re one person doing everything, the jobs are still distinct. They require different mindsets and different tools. When you blur them, which happens constantly when you\u2019re doing everything yourself, you end up making a mess that\u2019s hard to even diagnose, let alone fix.<\/p>\n\n\n\n

I\u2019ve started thinking about it as four hats. You wear all of them. But ideally, you wear them one at a time.<\/p>\n\n\n\n

Hat 1: Edge Research (The Curious Scientist)<\/strong><\/p>\n\n\n\n

Something looks interesting in the data. You pull on the thread. You\u2019re trying to understand a phenomenon. Is this effect real? Why does it exist? Who\u2019s on the other side of this trade, and why are they willing to lose money?<\/p>\n\n\n\n

The mindset here is pure curiosity. You\u2019re just trying to understand<\/em>.<\/p>\n\n\n\n

Hat 2: Strategy Research (The Engineer)<\/strong><\/p>\n\n\n\n

OK, you\u2019ve satisfied yourself that something is real. Now, can you actually trade it? What do realistic costs look like? What constraints do you face?<\/p>\n\n\n\n

This is where backtesting and simulation live. And this is where most people start<\/em>, which is the problem. If you start here without having done the edge research properly, you\u2019re building on foundations you can\u2019t possibly understand.<\/p>\n\n\n\n

Hat 3: Portfolio Research (The Architect)<\/strong><\/p>\n\n\n\n

You\u2019ve got a few things that work individually. How do you put them together? How much capital goes to each one? What happens when two strategies want to do opposite things?<\/p>\n\n\n\n

This is where you zoom out and think about the whole portfolio. Sizing sensibly, spreading your bets, giving yourself the best chance of making money even when the future doesn\u2019t look like the past.<\/p>\n\n\n\n

Hat 4: Operations (The Process Person)<\/strong><\/p>\n\n\n\n

What do I actually trade today? How do I go from strategy signals to orders placed in the market? How do I track positions, reconcile, move money around, handle the daily grind?<\/p>\n\n\n\n

This is the least glamorous hat. I find it the least interesting too. But it\u2019s the one that determines whether everything else actually makes money in the real world. (Funny how that works.)<\/p>\n\n\n\n

The error I see most often is blurring hats 1 and 2.<\/p>\n\n\n\n

Someone spots an interesting pattern. Before they\u2019ve understood why it exists, whether it\u2019s stable, or what drives it, they\u2019re already simulating a strategy around it. Optimising entry and exit rules for something they\u2019ve noticed or theorised, but haven\u2019t yet understood.<\/p>\n\n\n\n

That\u2019s wearing the engineering hat when you should still be wearing the scientist hat.<\/p>\n\n\n\n

Think about it this way.<\/p>\n\n\n\n

An engineer designing a bridge can skip straight to the design phase because the underlying physics is well understood. Gravity, material strength, load distribution. Centuries of accumulated knowledge. The research is done.<\/p>\n\n\n\n

We don\u2019t have that luxury.<\/p>\n\n\n\n

When we find something interesting in the market, we understand almost nothing about it. A single chart tells us something, but the underlying dynamics, the stability, the regime dependency, all of that is still a mystery. The research phase is where you earn the right to build.<\/p>\n\n\n\n

Skip it and you\u2019re designing a bridge without knowing how gravity works.<\/p>\n\n\n\n

\u201cWill it survive transaction costs?\u201d is a fair (and important) question. But make sure you ask it at the right time. It can wait until the science is done.<\/p>\n\n\n\n

Next time you sit down to work on trading stuff, ask yourself: which hat am I wearing right now?<\/p>\n\n\n\n

Scientist hat: Am I trying to understand something? Then forget about costs, position sizes, implementation details, and anything goal-oriented. Just look at the data with genuine curiosity.<\/p>\n\n\n\n

Engineer hat: Am I trying to build something tradeable? Then I should already understand the effect well enough to explain it to someone in two minutes.<\/p>\n\n\n\n

Architect hat: Am I figuring out how to combine strategies? Then I need to think about the whole portfolio, every strategy in context, every allocation in proportion.<\/p>\n\n\n\n

Process hat: Am I figuring out what to trade today? Then I need simple, repeatable processes that I can stick with when I get bored or things get messy.<\/p>\n\n\n\n

Keep them separate. Know which one you\u2019re wearing.<\/p>\n\n\n\n

It sounds simple, but honestly, I reckon it\u2019s one of the most useful frameworks I\u2019ve found for organising the work of trading solo.<\/p>\n\n\n\n

I keep on coming back to it personally, and when I talk to other solo traders about problems they\u2019re facing, they can nearly always solve them by switching to the right hat.<\/p>\n\n\n\n

This framework is basically how we\u2019ve organised everything at Robot Wealth.<\/p>\n\n\n\n

For more information on this topic, visit Robot Wealth<\/a> blog.<\/em><\/em><\/p>\n","protected":false},"excerpt":{"rendered":"

The four hats of the solo trader.<\/p>\n","protected":false},"author":271,"featured_media":169823,"comment_status":"open","ping_status":"closed","sticky":true,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":"","jetpack_post_was_ever_published":false},"categories":[339,338,341],"tags":[4873,4697,21268],"contributors-categories":[13676],"class_list":["post-240088","post","type-post","status-publish","format-standard","has-post-thumbnail","category-data-science","category-ibkr-quant-news","category-quant-development","tag-backtesting","tag-portfolio-construction","tag-portfolio-research","contributors-categories-robot-wealth"],"pp_statuses_selecting_workflow":false,"pp_workflow_action":"current","pp_status_selection":"publish","acf":[],"yoast_head":"\nEverything Everywhere All at Once | IBKR Quant<\/title>\n<meta name=\"description\" content=\"The four hats of the solo trader.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, 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