With Claude Code I created an agent that spawns 5 copies of itself branching git worktrees from main branch using subagents so no context leaks into their instructions. The agent will every 60 seconds analyze the performance of each of the copies which run for about 40 minutes answering the question "what would you do different?". After they finish the task, the parent will update the .claude/ files enhancing itself reverting if the copies performed worse or enhancing if they performed better. Then it creates 5 copies of itself branching git worktrees from main branch ..........
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.
> 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.
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.
Let us perform a thought experiment. You do this. Many others, enthusiastic about both LLMs, and stocks/options, have similar ideas. Do these trading strategies interfere with each other? Does this group of people leveraging Claude for trading end up doing better in the market than those not? What are your benchmarks for success, say, a year into it? Do you have a specific edge in mind which you can leverage, that others cannot?
People used to laugh about quant strategies the same day, I wouldn't count it out so quickly. One of my friends is already turning meaningful profits with agent driven trading (though he has some experience in trading to begin with.)
Classic AI psychosis, you can do it with a single prompt, etc. etc.
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.
> Next I'm going to set it loose on 263 GB database of every stock quote and options trade in the past 4 years.
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 see, I said "stock quote" instead of "minute aggregates". You are correct that data set is much larger and at ~1.5TB a year [0] I did not download 6TB of data onto my laptop. Every settled trade options or stocks isn't that big.
I have Claude Code Max $200 a month plan. I ran aggressively for 4 days and ran through 80% of Opus 4.6 for the week. I was also running it 16 hours a day. Today and tomorrow I will wait until 5pm PST because they have a 50% special to run with the remaining tokens.
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 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
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?
I think the name "massive" combined with the direct link to the docs is a bit misleading; it's not at all obvious from where you land w/ that link that they are selling the actual data. (It kind of sounds like they're selling software that helps you deal with massive data in general, which, no.)
I might be regressing communicating with other humans after using natural language in prompts 10 hours a day 10 days straight. My spelling is improving however I need to focus more on the context with humans.
you can have it build an execution engine that interfaces with any broker with minimal effort.
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.
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.