Every quant model?

Day one of teaching you every quant model that actually gets used, starting with the most common one, mean reversion. The idea can be summed up in one sentence. Some prices when they move away from a certain level, will return back to that level. Not all prices and not always. And the idea of the models, knowing when. That's the whole game. So mechanically, you find two things that move together, two big banks, an ETF, um, and its basket, uh, when the gap between them moves or stretches wider than normal, a certain percentage, the expensive one, and then you buy the cheap one. Wait for the gap for that gap to close. So you're not directional, uh, model, you're betting on the relationship between those two correlated assets. The math is everything. The further the spread stretches from its mean, the harder it pulls back. You measure the stretch in standard deviation. So that's your Z score and the speed of the pull back. That's the half life. So stretch Z score, you enter back to out. And the half life tells you your holding period before you enter the trade. This edge exists. Force flow, funds rebalancing positions, blowing out people trading because they have to essentially. They need to get a certain, uh, liquidity balance, um, you get paid to trade essentially, um, and wait. The downside of this model, um, sometimes the, uh, sometimes the, uh, that move, uh, that or that relationship doesn't actually correlate and you can have some pretty expensive losses in some instances. One of the models in the world and I actually currently run one on the AUD USD using yield differentials as one of the drivers. So that's day one.