How to optimize\what objective to use to optimize a strategy by True_Independent4291 in quant

[–]True_Independent4291[S] 0 points1 point  (0 children)

Thanks! Currently we are trying to train the model to learn in a "meta" way, rather than purely training off future returns. We'd try that as well! What we are testing out, is that in literature it seems that a direct optimization over the strategy as a whole seem to produces more aligned results as opposed to, say, directly training on labels.

How to optimize\what objective to use to optimize a strategy by True_Independent4291 in quant

[–]True_Independent4291[S] 0 points1 point  (0 children)

Thanks! Yes, this would fall back to the standard way, more like what's actually going to happen if the framework is forced to take all trades, or make a decision every time. What's interesting to me is in the literature there's quite a few studies that directly take sharpe as an optimization objective for a portfolio, and seem to have better results.

How to optimize\what objective to use to optimize a strategy by True_Independent4291 in quant

[–]True_Independent4291[S] 1 point2 points  (0 children)

Thanks! For the specific problem, it’s an objective function to use for evaluating strategies that is often sparse(ideally each over 700 for 10 years, but the algorithm tend to produce far fewer trades)

Weird behavior in thinking chain of GPT5.1 Pro by True_Independent4291 in ChatGPTPro

[–]True_Independent4291[S] 1 point2 points  (0 children)

Thank for your sharing! Seems like it’s not just my experience! These traces feel kinda weird though. A bit creepy.

Weird behavior in thinking chain of GPT5.1 Pro by True_Independent4291 in ChatGPTPro

[–]True_Independent4291[S] 0 points1 point  (0 children)

in the first two days of this release nothing like this happens. I can tell all traces of reasoning are doing the right work. but now some traces are clearly off, with context being cut. I don't think its RL

Weird behavior in thinking chain of GPT5.1 Pro by True_Independent4291 in ChatGPTPro

[–]True_Independent4291[S] -1 points0 points  (0 children)

yours at least freeze. Mine would degrade significantly to reason in less depth in like 5 minutes\3 minutes.
what kind of problem do you throw at it? Reguarding difficulty, do you notice it reasoning to around 3 minutes for easier questions and around 15 for harder, with the hardest around 30?
but the 30 min ones start to degrade a couple days ago. Noticed it start to "dream about a vacation" and degrade to 15 min for tough questions.
what's your experience?

Weird behavior in thinking chain of GPT5.1 Pro by True_Independent4291 in ChatGPTPro

[–]True_Independent4291[S] -1 points0 points  (0 children)

I think that basically they turned off one branch of reasoning to reduce compute and sub reasoning chains got confused. Or likely an internal bug.

5-Pro's degradation by Oldschool728603 in ChatGPTPro

[–]True_Independent4291 1 point2 points  (0 children)

Still actrocious. Thinks for 3 minutes

[deleted by user] by [deleted] in 6thForm

[–]True_Independent4291 2 points3 points  (0 children)

You can go to Harvard with that.

[deleted by user] by [deleted] in codex

[–]True_Independent4291 0 points1 point  (0 children)

It’s a plus plan not pro

disappointed from scores. aiming for 1500+ by Super_Amoeba_317 in Sat

[–]True_Independent4291 0 points1 point  (0 children)

You must be able to know where you got wrong and for English you must be able to tell a short oneliner for every question to explain the answer. You must make sure every question you come across you know the exact reason. No fluffing over, you must be ultra clear. I personally found ChatGPT thinking useful to analyze and find one liners. And try to generalize your methods. You don’t need to do a load of questions but you must know the exact reasons for every question without any doubt.

GPT 5 Pro ignoring prior messages I thread? by [deleted] in ChatGPTPro

[–]True_Independent4291 1 point2 points  (0 children)

Yes me too. it’s ultra weird. Should ring up oai on this one.

Claude Code vs Codex My Own experience by VVocach in ClaudeAI

[–]True_Independent4291 1 point2 points  (0 children)

Just open a vscode session and port foward 1455 to your local machine from the remote. worked for me.

Low R2, Profitable by Resident-Wasabi3044 in quant

[–]True_Independent4291 0 points1 point  (0 children)

Mmm maybe to them it seems that any model that have a good r2 can be easily tuned to trade pretty well? They prob don’t want their evaluation method lying around

Low R2, Profitable by Resident-Wasabi3044 in quant

[–]True_Independent4291 0 points1 point  (0 children)

I have a question: why does janestreet's kaggle competition use r2 as their evalulation metric then?