Wherever I look, I see the same two traits in consistent winners. Their methods look different on the surface, but something common runs underneath. 1) They accept the game’s probabilistic nature and willingly submit to it. Randomness sways individual outcomes, but over a large enough sample its noise recedes and a well-built edge prevails. So they optimize for positive expected value, size positions to survive variance, and let the long run surface their skill. 2) They love the game enough that the pitfalls randomness creates don’t feel like pushing through; they feel like puzzles worth solving. That passion makes reviewing losses, iterating, and returning the next day feel natural, not forced. From the outside it looks like grit; from the inside it’s immersion that lasts long enough for the edge to compound. Taken together: cold probabilistic discipline paired with genuine love for the game. The first keeps you making +EV choices and surviving the swings; the second keeps you engaged long enough for the edge to emerge.

"The market offers a premium to anyone who can tolerate being wrong frequently. It's a psychological tax that most people can't afford to pay. Money is transferred from those who need to be right to those who need to be profitable."

yes sir, you posted copper/gold ratio a gazillion times already without naming it, we understand

What frustrates me about most debates on Twitter is that they’re framed around the wrong question: Was this person right or wrong? It’s the wrong framework entirely. A trade shouldn’t be judged by whether it happened to work out, but by the quality of the decision at the moment it was made. A “right” result can come from a bad process (luck), and a “wrong” result can come from a good process (variance). Optimizing for hit rate is a trap. It’s outcome bias. But Twitter is obsessed with hit rate. Being right as often as possible, ideally on tiny timeframes so it’s easy to keep score. This is what makes us come across like gamblers, because that’s exactly the framework gamblers operate on. Short horizons amplify noise, great processes will look “wrong” often. The result is a lot of noise and certainly not the kind of discussion that actually makes you a better trader. If anything, it rewards the exact habits that cause traders to blow up: chasing quick wins instead of building sound, repeatable decision-making. Stop grading trades by outcome. Grade them by process.

The real hot take is probably this: Scalping > Swinging doesn’t mean price is fractal. It isn’t. Different timeframes = different participants with different goals. Different markets = different players entirely. Scalping works as a learning tool not because lower timeframes reflect the higher ones but because they compress feedback. You still need to know what you’re extracting. This isn’t just “head and shoulders but faster.”

Hot take Contrary to popular belief, you shouldn’t start with swing trading but scalping. Everyone starts swing trading because it feels more ‘strategic.’ But early on, you don’t need strategy; you need feedback. Scalping accelerates iterations. You don’t learn markets by holding a thesis on where Bitcoin will be in 3 months. You learn by making 50 decisions in a week and seeing what works. Scalpers can always scale up to longer timeframes. Swing traders rarely adapt down.

A system should be as simple as possible to use, but as complex as necessary to retain value. If a unit of complexity doesn’t drive a disproportionately valuable insight, output, or decision, cut it. Every added layer, rule, or feature must pay rent in the form of marginal utility. You optimize for net information efficiency.

If there are two meta-skills that unlock the door to learning just about anything, they’re these: • first principles thinking break down and reconstruct complex ideas • cognitive bias literacy ensures that this reconstruction isn’t distorted by faulty reasoning First principles thinking allows you to break down complex topics to their most fundamental elements. It helps strip away the bias that comes from personal experience. Most of us operate on assumptions built over time, and while experience is useful, it can also create mental inertia. First principles thinking forces you to pause and observe what something actually is, not just what you assume it to be. But there’s a catch: this process only works if your reasoning stays clean. Even if you’re skilled at breaking things down logically, biases can quietly sneak in and distort your understanding. So if you want your first-principles approach to actually work, you need to actively train yourself to spot and correct these distortions. When you put these two abilities together you can pick up a new domain, dissect it properly, and avoid most of the traps that lead others astray. Especially when you layer in feedback-integrated iteration, which lets you pressure-test your models. Once you’ve mapped it out you can reintroduce your experience, but this time with intention.

daily reminder BTC pumped 7x since the ECB called the “artificially induced last gasp before the crypto-asset embarks on a road to irrelevance” at the pico-shmico bottom gm

Copying strategies without knowing how they’re built is renting. You might see results, but you're leaning on borrowed logic. The moment the strategy stops working, you’re cooked. Understanding their first principles is owning. Self-reliance starts by reversing what works and tracing it back to first principles. When you own the engine, you can modify, rebuild, or invent new strategies on demand. Understanding the generative logic behind success gives you something that survives context collapse. That’s the difference between renting a strategy and owning the engine. Strategies expire. Principles don’t.