One fish two fish red fish I follow you fish

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Hey I have a data science background. This is good and entertaining fluff, but if you know what you're looking at, there are important things missing and some things that look good but don't make sense. I give him 4.8/5 for making it look important. For example: He has two time series (S&P500 and the bonds) and he compares them to many possible offsets. This is called cross-correlation analysis. It's a real thing, but it's also notorious for overfitting the data and showing spurious relationships if you misuse it like OP dies here. When you test many different offsets, you increase the probability of finding a high correlation *somewhere*, purely out of random chance. This is kind of like flipping a coin and getting heads 10 times in a row; it's impressive if you only flipped the coin 10 times, but much less exciting if you flipped it 10 million times. You were bound to get a 10-head steak at some point. An overfit predictor is one that performs very well on the historical data used to find it, but poorly on new, unseen data. If you select the single best lag based purely on the highest R-value from your historical test (precisely what OP did here), you risk overfitting to random noise that exists in the sample, but isn't truly predictive. And that's almost surely been done here and the validation should have been on showing that the model isn't overfit. To validate a model like that you wouldn't back-test (what OP does). Some things you could do are split the data into in and out of sample (e.g. make the model based on only the first X days in the series, and then judge it based on its ability to predict the data after day X). You should/could take steps to remove seasonality or trends within the time series first (which we already damn well know the stock market is seasonal, so him using untransformed values is most definitely increasing his calculated correlation). It would also be good to do bootstrapping to check statistical significance, instead of just p value. But it is very entertaining. OP probably also has a data background, to be knowing what to do to specifically torture the data this way.

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This snapshot just captures my largest positions in the port + the options I’m holding (I only grabbed $30k in KRKNF as a smaller bet). But I did TLH BULL a week or two ago, I’ve got a bunch of realized gains this year so took the opportunity to offset some with that -20% hit. They had a great earnings but got punished for it which was odd. I’d say my conviction is also just higher in my other stocks but I’d still look to rebuy in at a later date if they continue to execute

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You need all that to notice that the graphs don't really seem to affect each other? Two generally upward trends are not predictive of anything. By that logic my age is predictive of market sentiment. Besides, wtf do a bunch of children know about market sentiment? It ain't stock brokers and investors playing RuneScape. It's like seeing patterns in clouds and concluding they were formed with intent. A bunch of nonsense.

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I need whatever you smoked that compelled you to try and correlate these two metrics holy fuck

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No, but you could get her an E-Golf. Also ace

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Yesterday $SPY +0.91% while $VIX −11%. A similar event occurred only once in the past two decades,Dec 15, 2017, and SPY gained +0.65% the following session.

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Guess OF is cooked. Looks like e-thots will have to go work the corners again.

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Older coworker was explaining to me how I should be maxing my 401(k) so I “get the full company match” and that I should start investing. But lil bro doesnt realize I already have 2x his net worth and am actually IRS maxing the 401(k). I just let him think he taught me a thing or two

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Two scenarios I’m facing Monday at open Scenario 1: market inflows but not enough to send it to the moon chop suey all day I lose my money on my far OTM puts Scenario 2: market outflows but not enough to send it to my break even or the flat earths core chop suey all day I lose my money

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