Shocking how far ahead Claude Code is from Codex on the CLI front.
After 43 iterations, it can turn any website using any transport (WebSocket, GraphQL, gRPC-Web, SSE, JSON API (XHR), Encoded API (base64, protobuf, msgpack, binary), Embedded JSON, SSR, HLS/Media, Hybrid) into a typed JSON API in about 10 - 30 minutes.
Next I'm going to set it loose on 263 GB database of every stock quote and options trade in the past 4 years. I bet it achieves successful trading strategies.
Claude Code will be the first to AGI.
I use TimescaleDB which is fast with the compression. People say there are better but I don’t think I can fit another year of data on my disk drive either or
Where'd you get the data itself? You sense I suppose everyone's skepticism here.
I don't understand your question? Are you saying the source of the data I linked to is corrupt or lies? Should I be concerned they are selling me false data?
But they are in fact selling the actual data! https://massive.com/pricing
Options quotes alone for US equities (or things that trades as such, like ADS/ADR) represent 40 Gbit per second during options trading hours. There are more than 60 million trades (not quotes, only trades) per day. As the stock market is opened approx 250 days per year (a bit more), that's more than 60 billion actual options trades in 4 years. If we're talking about quotation for options, you can add several orders of magnitude to these numbers.
And I only mentioned options. How do you store "every stock quote and options trade in the past 4 years" in 263 GB!?
I think this would be pretty straightforward for Parquet with ZSTD compression and some smart ordering/partitioning strategies.
how do you have it build a "trading strategy"? it's like asking it to draw you the "best picture".
it will ask you so many questions you end up building the thing yourself.
if you do get something, given that you didn't write it and might not understand how to interpret the data its using - how will you know whether it's trading alpha or trading risk?
I can care less about scraping and web automation and I will likely never use that application.
I am interested in solving a certain class of problems and getting Claude to build a proxy API for any website is very similar to getting Claude to find alpha. That loop starts with Claude finding academic research, recreating it, doing statistical analysis, refining, the agent updating itself, and iterate.
Claude building proxy JSON api for any website and building trading strategies is the same problem with the same class of bugs.
Maybe I’m misreading what you’re trying to say.
Now what is important is developing techniques for detecting patterns as this can applied to research, science, and medicine.
If you find such a db with options, it will find "successful trading strategies". It will employ overnight gapping, momentum fades, it will try various option deltas likely to work. Maybe it will find something that reduces overall volatility compared to beta, and you can leverage it to your heart's content.
Unfortunately, it won't find anything new. More unfortunately, you probably need 6-10 years and do a walk forward to see if the overall method is trustworthy.
I bet it doesn't achieve a single successful (long term) trading strategy for FUTURE trades. Easy to derive a successful trading strategy on historical data, but so naive to think that such a strategy will continue to be successful in the long term into the future.
If you do, come back to me and I’ll will give you one million USD to use it - I kid you not. Only condition is your successful future trading strategy must solely be based on historical data.
The problem was testing it against 5 websites at a time after every change to instructions to ensure there wasn't any regressions. The orchestrator agent tracks all token expenditure and would update its own instructions to optimize.
I've used/use both, and find them pretty comparable, as far as the actual model backing the tool. That wasn't the case 9 months ago, but the world changes quickly.
I did notice that codex - like Claude - is now better about auto delegating to agents for keeping the context focused and agents in parallel.
None of them are particularly sticky - you can move between them with relative ease in vscode for instance.
I think the only moat is going to be based on capacity, but even that isnt going to last long as the products are moved away from the cloud and closer your end devices.
Even the AI itself is goofy. So many false positives during reviews immediately backtracked with "You're right, I'm sorry" in the next response.
It seems like there's either a paid pro-Anthropic PR campaign on HN because the comments fawning about it don't match my experience with Claude at all, or I keep getting the worse end of the A/B testing stick..