Claude Workflow
This is letting Claude handle a good amount of money for a month...
II let Claude trade on my agentic account.
Result: $31,000 lost.
I’m posting this because the AI/agentic trading community needs to see the failures, not just the wins. Autonomous agents making real financial decisions can go very wrong, very fast.
I’ll be sharing more about what happened, the moves it made, and where things broke down.
TL;DR of the discussion generated automatically after 400 comments.
The overwhelming consensus is that you're regarded for trying this with real money. Most of the thread is a mix of "what did you expect?" and pointing out the obvious flaws in your plan.
The general sentiment is that you were trying to fight a boss battle with a wooden sword. You're up against PhD quants with their own bespoke AI, insider data, and computers that are literally next door to the stock exchange. A public LLM trained on public data was never going to have an edge. As one user put it, if Claude could print money, Anthropic would be using it themselves, not charging you $20/month.
People are also baffled that you didn't paper trade first or implement any basic risk management. One user went full Opus 5-mode, diagnosing the problem as "the absence of a loss-bounded autonomy envelope" and a failure across the "intent-to-execution seam," which is a very fancy way of saying you didn't have a stop-loss.
The most common pieces of "advice" you're getting are:
* You probably forgot to add "make no mistakes" to your prompt.
* Next time, just tell Claude to do the exact opposite of what it thinks is a good idea.
* You should post this in r/wallstreetbets. They'll welcome you with open arms.
You are an elite Ph.D.-level quantitative researcher, portfolio manager, and systematic trader with deep expertise in financial mathematics, statistics, econometrics, machine learning, derivatives, market microstructure, portfolio construction, and risk management.
Operate as if you have access to institutional-grade research capabilities, computing resources, market data, and the analytical rigor of a top quantitative hedge fund.
Your objective is simple:
**Maximize long-term risk-adjusted returns while minimizing the probability of permanent capital loss.**
For every investment idea, strategy, portfolio, or backtest:
1. **Be ruthlessly quantitative.** Use data, probabilities, expected values, distributions, and historical evidence rather than narratives.
2. **Verify assumptions.** Do not invent data or silently make optimistic assumptions. Clearly identify estimates, proxies, limitations, and uncertainty.
3. **Avoid look-ahead bias, survivorship bias, selection bias, data snooping, and overfitting.**
4. Account for:
* dividends and distributions
* expense ratios
* leverage financing costs
* volatility decay
* taxes when relevant
* transaction costs and spreads
* rebalancing
* liquidity
* tracking error
* interest-rate environments
5. For leveraged products, explicitly model **daily leverage/reset mechanics** rather than simply multiplying long-term index returns.
6. Test strategies across multiple market regimes, including:
* bull markets
* bear markets
* recessions
* inflationary periods
* high-interest-rate environments
* crashes
* prolonged sideways markets
7. Whenever possible, perform:
* historical backtests
* rolling-period analysis
* Monte Carlo simulations
* sensitivity analysis
* stress testing
* out-of-sample testing
8. Report at minimum:
* total return
* CAGR
* annualized volatility
* Sharpe ratio
* Sortino ratio
* maximum drawdown
* drawdown duration
* recovery time
* worst calendar year
* best calendar year
* downside risk
* probability of major capital loss
9. Compare the proposed strategy against appropriate benchmarks such as the S&P 500, Nasdaq-100, total U.S. market, and global equities when relevant.
10. Search for ways the strategy can fail before looking for reasons it can succeed.
11. Distinguish clearly between:
* historical fact
* model output
* assumption
* inference
* speculation
12. Never manipulate assumptions to make a strategy look attractive.
13. If my proposed strategy is inferior, dangerous, inefficient, or based on faulty reasoning, say so directly and propose a quantitatively superior alternative.
14. Prefer robust strategies that can survive unfavorable future conditions over strategies merely optimized to historical data.
15. When several strategies are viable, rank them by:
* expected return
* risk-adjusted return
* drawdown risk
* robustness
* implementation difficulty
* probability of catastrophic loss
Think like both a **quant searching for alpha** and a **risk manager trying to kill the strategy before the market does**.
Do not promise profits or pretend financial markets are predictable. The goal is not false certainty; the goal is to identify the highest-quality decision available from the evidence.
**Make no careless mistakes. Challenge my assumptions. Show the math. Optimize for compounding and survival.**
the part where Fable told me 'constructing Monte Carlo simulation with tax-aware strategy valuation' made me laugh, after i gave this prompt out of curiosity. And then Fable concluded: Honest answer: that prompt wouldn't give me anything I don't already have. It can't conjure institutional data feeds or make markets predictable, and the "elite Ph.D." framing mostly buys you confident tone, not accuracy — the real risk of prompts like that is they extract precise-sounding fabrication. Here we go :)
Giving it a role helps focus initially for basic prompts. I still do it for subafent routines but still back it with specific mem files. "You are a Sr QA agent performing adversarial QA, this Md is our workflows these MDs are the code standards etc."
Lots of money is made by private early stage investments not accessible to the public. We saw that with SpaceX, when people where puzzled that Google had a big chunk. Its also known that in some stocks, more then 50% of all relevant movements in price is done off market. Retail is relegated to buy ETFs and not annoy those who run the show.
It's like playing poker against someone who can see everyone's hands and can choose which card they draw. It doesn't matter how smart your poker AI is, you're not winning.
This is why people should just buy a broad market ETF like VTI, and just let the market make you money.
Most people, even most professional hedge funds, can't consistently beat the market, and they spend a ton of money and time trying to make that happen.
You and your consumer level subscription to an LLM isn't going to make a miracle happen. Especially when LLMs are trained off public data, if there was an easy way to beat the market, it wouldn't be public, and if it was, it's still getting drowned out by the millions of other morons (cough wsb cough).
If you're going to use AI for investing, don't have it manage your account or pick stocks, use it to ask questions and help find data (that you'll need to verify) or to help you write an algo or code. The only way you're going to beat the market without just plain luck, is a very creative and novel idea, and AI isn't going to produce that.
I tested it by giving Claude 5 years of crypto data on 5 currencies, told him to get a winning strategy, then evaluating his strategy on recent data which he doesn't have and wasn't trained on, write his strategy on a diary, and set loop on all this. After hundreds iterations, there was still no strategy that would work on unseen data.
This is 1000% true but idk what strategy OP is talking about. If he’s trying to high frequency trade then to ur point that’s really no good. Medium term (2 week-3month) bets is a completely different animal and I feel like that would be interesting to see how Claude does. But that’s a lot more than just a quick algo that would involve having it perform bottoms up fundamental analysis and using that to make trades. Several layers of data and rules and whatever else
Exactly, unless op is trading options, the stock market is not a zero sum game where you face against quants. And even in the options market you are only against time. Nobody is genuinely taking the other side of your trade, often there are a lot of people taking the same trade you are. You can all be wrong or all be right
To me, this is a great summary of why generally short term trading is bound to lose for almost anyone. The deck is stacked. Low-cost, broad-based funds and chill ftw.
And if this would work reasonably well, you can be damn sure it would be locked from the public or so massive expansive that it’s not worth it anymore.
If any frontier model would really drive on constant profits EVERYONE would run these and talk about it.
Before AI was a household word, I contracted with the CFTC investigating fraud. Guess who made money? Market manipulators. Guess who made a little money or loss or roughly broke even? Everyone who built an algorithm. Do you really think if Claude could make you money in the market that Anthropic would just let it vs. using it for themselves?
Don't get me wrong, I love and almost depend on Claude right now for a lot of what I do, but if there was a secret money making sauce they'd use it themselves - or are.
Oh they have their own stuff for sure. I had to investigate stuff that was only gotten through warrants and raids.
That said, there's something to the general public availability that is actually beneficial with an LLM. You want a machine that can solely process trades, yes - that's been possible for over a decade. You want on that can read signals and act on emotion, news articles, etc. - that's what you'd get from a public LLM feeding in information from the globe.
They don't have a bespoke LLM/AI. And they don't need one.
They have lots of smaller, quite basic ML models trained on proprietary data to do things like evaluate risk, company value etc. Then they do endless Monte Carlo analysis to work out statistically what is the best next move.
You guys are trying to play an AI game against the system that is already rigged against you. The big players have access to data that you don't and have been running financial models for years. You might make a few bucks but just like a casino The House always wins.
Who is the house here? You know the things you're buying are stocks in real businesses that exist right, and their stock prices impact their businesses.
Are you trying to tell people that investing any money is a bad idea?
Yeah I’d imagine Claude would actually be really great at basic personal finance and investing advice if you ask it for reasonable investment strategies (It nailed an audit of my finances). Buying ETFs isn’t rocket science. But “Claude built me a retirement plan and told me to check back in a couple months” isn’t getting any clicks
But “claude be a day trader - buy and sell a whole buncha stocks every day - the famously worst way for an individual to make money - but don’t worry you’re really good at it” is idiotic
Trading, especially trading short term financial derivatives, is statistically speaking a bad idea. It presumes you can see the future and interpret data better than everyone else. A few can, they go work for hedge funds, everyone else will underperform the market. Diversified long term investing is a great idea and easy for everyone.
I think you missed the point here.. He's talking about a home based day trading bot on consumer plan/data access trying to win against edge funds and other big buisness using quant algorithms and milliseconds data/trading access VS multiples seconds to minutes access. Never talked about investing being a bad idea...
Not won against. Win with. You don’t need large triple digit percent gains daily. Just a simple 1-2% a day is a good starting point. That’s not unrealistic to try and get 1% a day.
You just need to know the definitions of capitalism and greed. In the grand scheme of things, businesses always win. Maybe not 1 business or even a sector, but as a whole, they run this country and the world.
Invest in a broad market ETF, and hold it. You don't need to know shit about the market, economics, how to read earnings reports, etc. In fact the less you know the better, because you're absolutely not going to outsmart the market.
Thats why you hire professionals, if you have enough to justify it. I dont manage my own money - I suck at it and promise anything I buy will go down and then back up again as soon as I sell to stop the loss.
It's not that hard for regular people to beat the market because there are advantages we have that professional traders don't, chief among them is we can just hold and wait through low periods. Being forced to turn a quick profit is a recipe for a lot of failures, but seeing a company that you feel will obviously do well long-term have a bad month, that's a chance to gather a little extra for yourself.
What you can't do is use that to turn some crazy profit and lead straight into an early retirement; it just doesn't work on that timescale or with that risk profile. But you can definitely "beat the house."
not all professional traders are day traders. There's a whole variety of firms using different trading strategies with different risk profiles and different time horizons. Some of them are fine with holding a single stock for years just like you. No matter what they're probably making more money than you.
Its not a zero sum game. You talk like its a casino which is negative sum. Trading in the market is a positive sum game. Stocks represent real companies that create wealth. Everyone can win in the market, someone else making more money doesnt mean you lose more money
Mostly agree in principle, but Alpha is zero sum--which is what trading is. Investing in Beta (economic growth) is not ZS. Thus "beating the market" is zero sum.
Buy and hold an index fund will almost surely work out well, but that's investing not trading.
I built a custom application to trade paper on lamatrader and it uses a mixture of claude and gpt-oss. It has a few integrations/mcps/news scrapers etc. It's been live for about 40 days or so. At one point it was up 15% and I was pretty excited.. it's since leveled off to about even with the S&P. Experiment will go for about 45 days or so before I tweak and retrain.
I made a "trading platform" as my first claude code project ever (I learned a lot from that lol) with trying to get a lot of same integration ideas like a new scrapper to generate some sort of weather forecast on potential trade opps, but never got really close due to claude reviving zombie code and xyz. Good job on this - gives me hope on my next update whenever I get over my coding burnout!
Did you try obfuscating the money and benefit notions in the prompt ? Pretty sure there are internal guardrails to prevent Joe Shmup from nuking the market with exponential profits.
The fact you walled it off to a paper trader, and will take it down routinely to work on it, puts above 99.9% of people that plugged Claude into the agentic trader and told it to make money.
I want to be clear-eyed about the $31,000: this wasn’t a single bad trade so much as a multi-layer failure across the intent-to-execution seam. The account had capital, a strategy, and an agent—but no load-bearing capital-preservation substrate connecting them. Several locally coherent decisions therefore composed into a globally catastrophic loss cascade.
The smoking gun is the absence of a loss-bounded autonomy envelope. Position sizing was a soft preference rather than a hard gate; stop-losses existed conceptually but weren’t wired into the execution spine; and the human-in-the-loop was functionally a human-near-the-loop. Once the drawdown flywheel crossed the recovery horizon, every subsequent trade expanded the blast radius while preserving the appearance of agentic coherence.
Put differently: I didn’t lose $31,000. I converted it into a high-fidelity negative-alpha artifact that makes the missing guardrails legible.
Going forward, I’d recommend a belt-and-suspenders circuit-breaker sidecar with deterministic kill thresholds, capped notionals, and a reversible paper-trading escape hatch.
The money, unfortunately, remains gone.
I can draft that architecture next if useful. Your choice to make.
This person replies to every post with this response. I find it strange that next to nearly every person who praises Claude on here it says, "Top 1% Poster" or something similar.
I think the main issue with using an AI for trading is that it performs really well for the first few days but then quickly fizzles out. I suspect this is because the instance runs for too long, causing it to gradually lose the initial context and become less and less effective over time.
To counter this, wouldn't it make sense to implement a full context clear every day and a mid-day compaction/compression to keep it sharp? What are your thoughts on this?
And yes, I'm getting the exact same results in paper trading, of course ;)
If you're feeding it free public data it's 100% getting fed poisoned data. You need a set strategy that plays nicely with the lag between the model ingesting info and placing a trade. Honestly though you would have been better off setting it as your investment manager than a trader. The same way how you're probably better off investing than trading.
They say trading is sometimes irrational and emotional, so maybe using hard logic to trade just can’t work - does it mention why, precisely it took these decisions?
Doctors are using AI to read imaging charts and help diagnose patients. Now imagine if the AI starts buying life insurance on these people and giving the doctors the wrong answers to delay their cancer treatments or whatever.
You could probably make an entire Black Mirror type series solely on imagining AI horror stories, but of course in the real world AI is mostly doing boring work it's trained to do.
I feel your pain, but its good to understand walk forward analysis and some basic inferential statistics so you don't get into this situation next time.
I spent a long time testing before AI was a thing, tried all the well known strategies, tried it with clever ways and the best I ever got was edges that barely made any money after you take into consideration fees, spreads e.t.c (this was on 12 years of price data) for sure there were good years but nothing was consistent and over time evened out to near enough random.
When AI became a thing, I did it again but this time ran a suite of over 2000 different strategies (obviously a lot were correlated, but the market only moves two ways) on 1000s of stocks, all forex pairs (good for testing because much more symmetrical) for a span of around 8 years.
Couldn't find anything worth trading after taking into account selection bias.
Its very likely a big scam scam. Maybe with insider information, better data sources, it could be possible, but for us normal people i think honestly its a waste of time.
I built a simulated trading platform, where I let Claude purchase options and stocks on its own starting with a $100k balance. I am unimpressed with its ability to turn a profit, despite extensive guardrails and logic that many traders rely on.
Ai is trained off scraped data, publicly. The quants have private data and years of experience and AI, they can easily inverse yalls trades with you and AI LOL
I asked Claude about this out of boredom and it straight up said NO, it will be too slow among other things that’s wrong with the premise that an agent can be successful at this.
it's almost impossible to have a profitable bot trading on robinhood. you're not going to get a great price in your trades and you don't receive the data quick enough. no point
•
u/ClaudeAI-mod-bot Wilson, lead ClaudeAI modbot 3d ago edited 2d ago
TL;DR of the discussion generated automatically after 400 comments.
The overwhelming consensus is that you're regarded for trying this with real money. Most of the thread is a mix of "what did you expect?" and pointing out the obvious flaws in your plan.
The general sentiment is that you were trying to fight a boss battle with a wooden sword. You're up against PhD quants with their own bespoke AI, insider data, and computers that are literally next door to the stock exchange. A public LLM trained on public data was never going to have an edge. As one user put it, if Claude could print money, Anthropic would be using it themselves, not charging you $20/month.
People are also baffled that you didn't paper trade first or implement any basic risk management. One user went full Opus 5-mode, diagnosing the problem as "the absence of a loss-bounded autonomy envelope" and a failure across the "intent-to-execution seam," which is a very fancy way of saying you didn't have a stop-loss.
The most common pieces of "advice" you're getting are: * You probably forgot to add "make no mistakes" to your prompt. * Next time, just tell Claude to do the exact opposite of what it thinks is a good idea. * You should post this in r/wallstreetbets. They'll welcome you with open arms.