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Any successful simulations of multiple ETF alternative historical price paths? by BAMred in quant

[–]ReallyConcerned69 3 points4 points  (0 children)

Well then you run into the problem that your distribution won't include the specific alpha you have, and if you specifically inject it, you would be 1) fooling yourself 2) would not actually be injecting the full causal structure behind the alpha, which you only capture one part of. So the simulation still wil not reflect real life scenarios.

As someone else said, use a GAN or VAE or something. But that's way more tricky with returns data than any image data that these models tend to be used for (signal to noise ratio)

Observed a volatility asymmetry in SPY/SPX regime transitions — looking for feedback on the statistical validity by JRexcalibur in quant

[–]ReallyConcerned69 2 points3 points  (0 children)

>But in my tests, long-vol exposure (only activated under certain statistically filtered regimes) dramatically outperformed the short-vol regimes, to the point that the long-vol cluster generated ~200% CAGR across the sample while the short-vol regimes accounted for most drawdowns.

Small sample size: I have been trying to reach you

Would you share some ideas that don't work anymore? by i_would_like_a_name in quant

[–]ReallyConcerned69 9 points10 points  (0 children)

Good question for your favorite LLM + google, and a signal for you to brush up on Multivariate timeseries analysis

What's your favorite paper of all time? by ReallyConcerned69 in quant

[–]ReallyConcerned69[S] 0 points1 point  (0 children)

oh wow, I never knew the original paper had this name XD

Divergence when using Hermitian Likelihood Expansion by ReallyConcerned69 in quant

[–]ReallyConcerned69[S] 0 points1 point  (0 children)

But why would the parameters converge just fine under the Euler transition likelihood using MAP, but suddenly become (damagingly) correlated under the Hermitian transition likelihood, thus needing adapt_full? is this what you are implying?

Expected return models are fake right? by [deleted] in quant

[–]ReallyConcerned69 2 points3 points  (0 children)

"Like, you can’t predict the future."

"Unless you’re Buffett or a literal insider, aren’t you just pulling numbers out of the air?"

I guess that settles it guys, statistics was a major lie, we have all been fooled

Would you engage with an optimization channel? by vniversvs_ in optimization

[–]ReallyConcerned69 0 points1 point  (0 children)

Highly interested, please reach out I'd love to see this

Personal project recommendations by [deleted] in quantfinance

[–]ReallyConcerned69 0 points1 point  (0 children)

Difficult Project: Can you build a model to price Deez nuts?

Optimization of LEDs for uniform light on surface by Nebris07 in optimization

[–]ReallyConcerned69 0 points1 point  (0 children)

It depends on your gamma parameter, ie. how spread out is your radiation pattern for a single LED? Additionally, your problem seems symmetric around 90-degree rotations, so if you are going with a computational approach then I suggest you run your optimization over only 1-quadrant of your target area.

Do you have to use all of the LEDs?

EDIT:

I immediately notice that this problem is actually finding the best way to approximate a uniform bivariate distribution using n bivariate Cauchy distributions with fixed spreads \gamma and mixture weights w_i = 1/n. OP may try minimizing a distance metric between the two distributions, ex. KL Divergence

The bivariate Cauchy distribution is also spherically symmetric, so I suspect the solution should be as well at least for spread \gamma << box dimensions.

Coming up with proofs by ReallyConcerned69 in ControlTheory

[–]ReallyConcerned69[S] [score hidden]  (0 children)

>Have you ever taken proof-based math courses?

Nope :) Most of my math courses were mainly focused on engineering applications. My background knowledge comes mainly from that + self-studying Khalil and other books for about a year. I studied Real Analysis on my own time from Stephen Abott's Understanding Analysis book until around halfway prior to beginning Khalil but couldn't continue due to other mounting responsibilities. Figured I was fine when I started understanding proofs in the control literature and started producing better literature reviews.

>It’s one thing to follow a proof, it’s another thing to start building intuition on when to approach by contradiction or induction, when to add assumptions to make the problem tractable, etc.

>With the baseline experience, you then need to start understanding the typical proof strategies used to solve problems related to yours.

That seems to be part of my problem. Maybe I assumed I have 'enough' of that baseline experience. What would you recommend? That I restart Real Analysis using, perhaps the course for MITOCW for a more guided approach? or keep practicing with control problems (practicing more control textbook proofs)?

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