4 ms·

Here is an example rollout trace with gpt 5.6 luna. Checkout if you are interested what kind alphas the agent found XD https://hub.harborframework.com/jobs/af02

by Mzzzzz 2mo ago

Here is an example rollout trace with gpt 5.6 luna. Checkout if you are interested what kind alphas the agent found XD https://hub.harborframework.com/jobs/af0299f9-a3bb-44ea-8ced-7b56682bf739 https://hub.harborframework.com/jobs/af0299f9-a3bb-44ea-8ced...

jjallen 2mo ago
I looked through the transcript/output of the model/run linked but didn't find anything that showed much, if any, alpha. Maybe I missed it?
- RuiWang0811 2mo ago
  not sure about your background, the trace shows the feature engineering the LLMs did
  - jjallen 2mo ago
    The comment in the parent said "kind alphas the agent found". It linked to a job then a trial. All of the comments I read there except for one said things like "The final alpha check is still fitting; the prior lagged backtest’s exact zero metrics make clear that model was not acceptable economically". One said "successful backtest’s" but did not expound on what that means or anything. I was looking for the alpha it found and not the feature engineering. My backgroud is in finance but do not look at things so quantitatively. Here is another comment/output: "correlation −0.007 and directional accuracy 0.498". Wouldn't directional accuracy have to be greater than .50 to be profitable? Forgive my ignorance I am interested in this though. I have asked Claude/ChatGPT to show me where the alpha is that the model found as well so I can learn.
    - jjallen 2mo ago
      Spent more time looking at this because I was still interested in the alpha it found and found this: "cumulative_after_cost_return": -0.004003033519454746" https://hub.harborframework.com/jobs/af0299f9-a3bb-44ea-8ced-7b56682bf739/trials/5b38696a-7175-4c68-a673-24c6642c039a?tab=verifier https://hub.harborframework.com/jobs/af0299f9-a3bb-44ea-8ced... ¯\(ツ)/¯
- Mzzzzz 2mo ago
  It is the raw trace, so it is the most complete records but hard for human to read. We showcased some features they found in this research blog post: https://edotenv.com/blog/alpha-autoresearch https://edotenv.com/blog/alpha-autoresearch

by Mzzzzz 2mo ago

jjallen 2mo ago

I looked through the transcript/output of the model/run linked but didn't find anything that showed much, if any, alpha. Maybe I missed it?

RuiWang0811 2mo ago
not sure about your background, the trace shows the feature engineering the LLMs did
- jjallen 2mo ago
  The comment in the parent said "kind alphas the agent found". It linked to a job then a trial. All of the comments I read there except for one said things like "The final alpha check is still fitting; the prior lagged backtest’s exact zero metrics make clear that model was not acceptable economically". One said "successful backtest’s" but did not expound on what that means or anything. I was looking for the alpha it found and not the feature engineering. My backgroud is in finance but do not look at things so quantitatively. Here is another comment/output: "correlation −0.007 and directional accuracy 0.498". Wouldn't directional accuracy have to be greater than .50 to be profitable? Forgive my ignorance I am interested in this though. I have asked Claude/ChatGPT to show me where the alpha is that the model found as well so I can learn.
  - jjallen 2mo ago
    Spent more time looking at this because I was still interested in the alpha it found and found this: "cumulative_after_cost_return": -0.004003033519454746" https://hub.harborframework.com/jobs/af0299f9-a3bb-44ea-8ced-7b56682bf739/trials/5b38696a-7175-4c68-a673-24c6642c039a?tab=verifier https://hub.harborframework.com/jobs/af0299f9-a3bb-44ea-8ced... ¯\(ツ)/¯
Mzzzzz 2mo ago
It is the raw trace, so it is the most complete records but hard for human to read. We showcased some features they found in this research blog post: https://edotenv.com/blog/alpha-autoresearch https://edotenv.com/blog/alpha-autoresearch