Wall Street has analysts. Now you do too.
Moneda AI and investing are live. Ask about any stock, ETF, commodity or crypto. Get an answer built from filings and live prices, with the source for every number.
Then invest in the same app.
It does the homework. You make the call.
Deep financial research used to belong to analysts.
Now it starts with a question.
Screen the market in plain words. Get the case for and against any stock. See how it stacks up against its rivals.
It does the homework. You make the call.
What would you ask first?
One test checks how well an AI reads company filings. Another, live market data. Another, how easily it can be tricked into helping with financial crime.
Every score is sourced and dated. Moneda built the site, and our own AI is on it too.
https://t.co/NzaQQdMJg4
There’s no best AI for money.
It’s like asking which doctor is best. You wouldn’t book a heart surgeon for a sprained ankle.
We track 47 finance AI tests. No single model leads them all.
So don’t ask which AI. Ask: good at what?
What do you ask AI about money?
Today we’re launching benchmarks(dot)finance.
One site to track AI models, finance AI products and every finance benchmark we could find. Every score sourced and dated.
Most benchmark sites test coding or general intelligence. Finance needed its own.
Figures as of 30 Oct and 3 Nov 2026, sources in the guide. Not investment advice. Capital at risk. Past performance is not a reliable indicator of future results.
The S&P 500 holds 503 stocks. On 30 October, ten of them made up 37.3% of it.
That's by design. The index weights each company by market value, so the biggest companies get the biggest slices.
What's less obvious is how much of the top is tied to AI. Six companies in that top ten make AI chips, rent out AI computing or spend tens of billions a quarter building it. Together, about 26% of the index.
The companies buying AI computing and the companies selling it sit in the same top ten.
Going global changes less than you'd think. MSCI World holds 1,248 stocks from 23 developed countries, yet 72.8% of it is US companies, and all of its top ten are the same US names.
For scale: from 1990 to 2015, the S&P 500's top ten were about 18% to 23% of it. In 2000, at the height of the dot-com boom, about 27%.
The label counts the companies. The weights tell you what you own.
See what's inside your own fund, how weighting works, and how each of these companies describes its link to AI, in our new guide: https://t.co/aJ5fnaUjME
@vvarrdi@Mr_BONI_@fekunze Absolutely! Thanks for the feedback, this is helpful.
We’re actively improving the chat experience atm. Know we still have a long way to go to improve the UX
I asked @moneda_com AI what specific shares to take in order to get 15-25% net in the coming years.
He immediately said that no one can guarantee it, the market on average gives about 10%, and on the short horizon it's almost a coin. He looked at my profile (conservative, horizon up to 3 years, the goal is preservation) and honestly wrote: for such goals, the race for 15-25% means sitting in heavy shares and being ready for -20-30% on paper in a bad year.
Offered a balanced option (not as advice, but as a starting point):
35% VOO, 20% QQQ, 15% dividends (type JNJ/PG), 10% VXUS and 20% cash/short treas.
Then he asked how much such a briefcase could fall in a bad year. Chased the backtest in 15 years - the worst drawdown is about 25% (2020 + 2022), the average annual ~11.7%. And he immediately added that there was no 2008 in the window, so in a more serious crisis there may be 30-40%, and 25% is the floor, not the ceiling.
This is one of the options for requests that Moneda AI can respond to in detail.
Realistic assessment, binding to your profile, historical context and honest conversation about risks.
You can ask about portfolios, individual papers, drawdowns, comparisons - and get an answer with sources, not just confident text.
Every benchmark links to the paper or source behind it, and products are compared feature by feature. Moneda built the site, and our own AI is on it too.
https://t.co/NzaQQdMJg4
Today we’re launching benchmarks(dot)finance.
One site to track AI models, finance AI products and every finance benchmark we could find. Every score sourced and dated.
Most benchmark sites test coding or general intelligence. Finance needed its own.
We’re also introducing Moneda Bench: seven new benchmarks for the gaps we found.
Live market data. Not making up numbers. Company filings. Cited sources. Portfolio decisions. Explaining finance without giving advice. Questions models haven’t seen.
Curious how your own would have done in each one?
Build a test portfolio paper with Moneda AI and replay it through all three: https://t.co/lDWLjZdu1L
Not investment advice. Capital at risk. Past performance is not a reliable indicator of future results. Availability varies by country.
Three crashes. Three completely different ways to lose money.
2008: the S&P 500 fell 57% and took five and a half years to get back to its old high. Bonds rose about 5%.
2020: the fastest bear market on record. Down 34% in a month, back at a record by August. Bonds rose about 7.5%.
2022: inflation hit 9.1% and the Fed raised rates seven times. Stocks fell 19%. Bonds fell 13%, their worst year since the index started in 1976.
Why? When rates rise, new bonds pay more, so the ones you already own are worth less.
Bonds are usually the part of a portfolio that holds up when stocks fall. In 2008 and 2020, they did. In 2022, they didn’t.