Mzzzzz

5 ms·

1.
by Mzzzzz 1mo ago
Very interesting. I am curious: Is the "test" part actual live trading, or is it also a backtest? I am asking because I see the agents can do websearch, so how is Alphadidatic preventing the agents from just looking at the asset&#
2.
by Mzzzzz 1mo ago
We are selling to frontier labs, e.g. OAI and Ant, and fintech companies that are trying to build agentic trading system but do not have those internal quant setups, e.g. Coinbase, Kalshi etc.
3.
by Mzzzzz 1mo ago
It is not only quant research. We also have live trading: https://edotenv.com/blog/long-horizon-planning For now it is only facing LLM/Agent.
4.
by Mzzzzz 1mo ago
Quant trading is an extremely high margin business itself. Quant shops are printing billions and have on average much higher profits per employee than tech companies. So it is definitely a business worth doing. On the other hand, you could
5.
by Mzzzzz 1mo 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
6.
by Mzzzzz 1mo ago
It is both. We can use the same setup for both RL and Benchmarking.
7.
by Mzzzzz 1mo ago
We do a 2 step anonymisation: 1. Mask all symbols, timestamps etc. So the agents cannot infer the assets/time periods. 2. Mathematically transform numerical values and returns. E.g. the market return targets are not the raw market retu
8.
by Mzzzzz 1mo 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...
9.
Launch HN: EdotEnv (YC S26) – Quant Trading RL Envs to Teach LLMs Research(edotenv.com)
39 points by Mzzzzz 1mo ago|34 comments
10.
by Mzzzzz 2mo ago
test