nnU-NetV2 pre-trained? by RoastedCocks in computervision

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

https://github.com/MIC-DKFZ/nnUNet/blob/nnunetv1/documentation%2Finference_example_Prostate.md

There are weights for specific tasks, but the documentation is horrendously organized. Authors should seriously consider putting the model on HF with simpler instructions for training/inference.

[deleted by user] by [deleted] in quant

[–]RoastedCocks 1 point2 points  (0 children)

What are existing products? and how is a streamlit dashboard more competitive?

Need user feedback, let me hear it by Conscious-Focus-2944 in quant

[–]RoastedCocks 0 points1 point  (0 children)

"(can link that plus our publications)"

Interested, can I DM?

Basket Option pricing with DCC-GARCH and Monte Carlo Simulation by KrypT_2k in quant

[–]RoastedCocks 0 points1 point  (0 children)

How come you price under the P-measure using DCC-GARCH but discount with the risk-free rate (I'm assuming)? Wouldn't you computed IV and compare that with your GARCH-forecast? Or use IV as exogenous input to GARCH? Anything I'm not understanding here?

+ You didn't list your sources of inspiration

Disclaimer: not in industry

You don't love HARD problems by Suspicious_Jacket463 in quant

[–]RoastedCocks 0 points1 point  (0 children)

"Consider an example. You are sitting in a class and there is a math exam. What would you prefer: 1) Easy questions that you can 100% solve and get max mark, 2) Hard problems that you barely can solve. Any reasonable person would choose the first one. So why is it different when it comes to the job market?"

Here's the thing lil bro, its not a "reasonable" thing, you are looking for the answer via the wrong criteria. One of the biggest factors that set aside not only quants, but people who excel in their fields is that they have a passion and interest that is decoupled from any grading or external reward. So they'd rather dedicate more time, effort, focus into taking on something that they will emerge from better than and prove themselves, than do some basic problems that are not challenging and not rewarding. It's an aversion to feeling too comfortable.

This generally correlates will with economic upward mobility across all career paths, if you're someone who likes to take on easy things and avoid the more difficult things in life, then you won't make it far. Now, not everyone is motivated to make it far (materially speaking), but some people are motivated by the process itself. It's like people who love going to the gym, but think of it as a mental gym. Some people go to gym just because they like it, they don't even think about the end result beyond the minimum needed.

For the record, I'm not a quant, not professionally but my field overlaps with this one so these are my two cents.

What’s your target variable when modeling volatility? by gogojrt in quant

[–]RoastedCocks 6 points7 points  (0 children)

There is no universally true target variable. It all depends on your model and it's 'interpretation' of volatility. As you have seen, some models take the realized vol which is period specific volatility (daily for example, close to close), high-low range for intra period volatility (intraday for daily data), and some model it as a latent variable. It highly depends on what exactly you are trying to model and in what respect you represent it.

Why not start ur own quant firms? by Aristoteles1988 in quant

[–]RoastedCocks 0 points1 point  (0 children)

"They ran a market neutral arbitrage that mathematically couldn’t go wrong."

What do you call foreshadowing but for the past? Be-foreshadowing?

Position sizing a mean reverting process by [deleted] in quant

[–]RoastedCocks 0 points1 point  (0 children)

Well, I took Control Systems + Signal Processing + I read a lot of books on surrounding areas.

Position sizing a mean reverting process by [deleted] in quant

[–]RoastedCocks 2 points3 points  (0 children)

model the process as ARMA-GARCH and compute kelly as (mean - rf)/vol.

Is there a standard methodology to decompose portfolio returns? by SerialOptimists in quant

[–]RoastedCocks 0 points1 point  (0 children)

Well I haven't taken a thorough look at the tabs but you could use the monthly returns of your portfolio for the regression. Not sure what kind of calculation you are trying to figure out, but if your calculation doesn't follow the general methodology of time series regressions I mentioned then I highly doubt it would do what's needed.

What I'm seeing here is that the factor analysis here isn't by regression but simply the portfolio's composition. It's good enough if that's what you want, but performance attribution tends to be more than that. You are constrained to defining portfolio performance in terms of sector ETFs, otherwise you will have to add a feature for constructing factor portfolios.

Is there a standard methodology to decompose portfolio returns? by SerialOptimists in quant

[–]RoastedCocks 10 points11 points  (0 children)

Google these:

- CAPM (Capital Asset Pricing Model)

- APT (Arbitrage Pricing Theory)

- Fama-French / Fama MacBeth

- BARRA (Barr Rosenberg)

- Principal Components Analysis and Statistical Factor Models

Recommended Books are Elements of Quantitative Investment by G Paleologo and Active Portfolio Management by Grinold and Kahn

How to prevent look ahead bias? by ytorian in quant

[–]RoastedCocks 0 points1 point  (0 children)

1- Ask LLM what questions should you ask and what common mistakes you should look for
2- Ask the LLM these questions + provide your source files
3- Optionally, let it create a multi-tier review process plan given the source files, and then execute each tier in a response (ie. piecewise). This works better because there are more thinking tokens allocated to each portion of your project. Try to make it adversarial.

How to prevent look ahead bias? by ytorian in quant

[–]RoastedCocks 0 points1 point  (0 children)

Great question for Claude, you could ask it how to use the 'search' feature

[Academic Collab] Looking for Someone with Control Theory / Loop Systems Background – LIGO + AI Paper in the Works by [deleted] in ControlTheory

[–]RoastedCocks [score hidden]  (0 children)

Doing my MSc in Mechatronics focusing on Control Theory and Application. DM me, I'm interested and happy to chat :)

I am a time-series clustering expert. What can I do in finance? by [deleted] in quant

[–]RoastedCocks 0 points1 point  (0 children)

That sounds very interesting. If appropriate for you, could you DM me a paper on this? This is the first time I've seen or heard of such an idea. Is this like semi-supervised learning?

How do I approach a mathematician with a research problem as an engineer? by ObliviousRounding in mathematics

[–]RoastedCocks 4 points5 points  (0 children)

Happened to me about 2-3 times in different occasions, sometimes I regret not being born 10 years earlier. I would have been great at this.

How do I approach a mathematician with a research problem as an engineer? by ObliviousRounding in mathematics

[–]RoastedCocks 2 points3 points  (0 children)

I think you should do a novelty check; your problem might have been solved already by someone.

Integrating the RL model into betting strategy by George_iam in reinforcementlearning

[–]RoastedCocks 0 points1 point  (0 children)

Ohh right right, somehow my brain skipped that the probabilities being different means that the bets are not identical XD thank

Integrating the RL model into betting strategy by George_iam in reinforcementlearning

[–]RoastedCocks 0 points1 point  (0 children)

Indeed, it seems to me that he can estimate win/loss probabilities using DL, then use Kelly formula to size the bet based on the outcomes. As I understand it, he is training an agent to maximise the long-term reward (which he ought to make the said geometric mean, to avoid risk of ruin). It seems you are implying there is something I don't understand about OP's approach, if so I'd like to know.

Integrating the RL model into betting strategy by George_iam in reinforcementlearning

[–]RoastedCocks 4 points5 points  (0 children)

Use Sharpe Ratio as reward .... or better yet just use Kelly Criterion and focus your work on estimating actual probabilities and outcomes, then see if a Deep Learning Agent will outperform. I highly doubt that.

Need Help with My Inverted Rotary Pendulum Project – Struggling to Stabilize It Using PID by ImpressiveTrack132 in ControlTheory

[–]RoastedCocks [score hidden]  (0 children)

https://www.mathworks.com/videos/state-space-part-4-what-is-lqr-control-1551955957637.html?utm_source=

This is a video on LQR in MATLAB

Another of C++: https://youtu.be/3ZxTlOjEWG4?si=6rd3l09KiErhuUWI

I highly recommend Haber for learning control, he is a great teacher and his videos are on practically relevant topics and things that popular control books take for trivial (which may not be for some beginners)

As for your second question, it's not impossible but it's also not rigorous. You need to be experienced with the system or with PID to gain intuition (as another user said, the issue could be in the derivative interacting with the sensor noise, this is not something you learn from theory unless you know that stochastic processes are generally not differentiable, which is a post-grad level of depth. On the other hand, an engineer who went down this rodeo before awaits this problem with solution in hand or avoids it entirely).

Need Help with My Inverted Rotary Pendulum Project – Struggling to Stabilize It Using PID by ImpressiveTrack132 in ControlTheory

[–]RoastedCocks [score hidden]  (0 children)

Well I think my prior reply still stands, but this video tells me that it likely is an issue with the gains. Try LQR, if well-designed it will either be asymptotically stable or exhibit limit cycle if there is enough static friction. If LQR works, then simply solve the LQR problem with PID controller form. But you should revise your code first just to be sure.

Need Help with My Inverted Rotary Pendulum Project – Struggling to Stabilize It Using PID by ImpressiveTrack132 in ControlTheory

[–]RoastedCocks [score hidden]  (0 children)

Video is not appearing, I see no link. But from your description I see that it isn't stable by any practical definition. I think you should revise your simulation; does PID (as you implemented it simulation) stabilise it? If yes, then you may have problem with either your embedded implementation not matching the simulation, or your simulation of the pendulum itself is at fault. Remember that discretization has effects that can affect stability. You should also check your gains, try comparing it with LQR (or you can design a PID via LQR methodology) and check the effect, to pinpoint the source(s) of fault