What are you guys doing with VCX right now? Sell, hold, or ride it out? Do you think it could go way higher (like $800), or is it smarter to take profits? Are you going to keep investing on it?

Press release from last week showing Eledon has 10/10 people with Type 1 diabetes that have gone completely off insulin. Soon to be 12/12. Their therapy has been shown to be well tolerated without toxicity, this is remarkable news for 2 million Americans that suffer from type 1 diabetes.

These are myfxbook results.

Hey everyone,

I have been reading this sub for a while and have learned a lot from the discussions here.

Recently I started experimenting with a small side project to help me organize information when researching companies. I noticed that when I begin looking into a stock I usually end up jumping between financial statements, news, price charts, and sentiment indicators just to get a rough picture of what is happening.

So I tried putting some of those signals in one place. Things like fundamentals, price momentum, and some sentiment data. The prototype then generates a short plain language summary of what the signals might suggest (positive, neutral, or negative). The goal is not to replace real research. It is just meant to speed up the first pass when exploring a company.

Right now it is still very early and mostly an experiment. I am trying to figure out whether this kind of approach is actually useful or if it only makes sense from the perspective of the person building it.

I would be really interested in hearing how people here approach early research.

• When you start researching a stock, what information do you check first?
• Do summary tools help you get oriented, or do you prefer going straight into the raw data?
• Are there any signals or data points you think most screeners are missing?

(Not financial advice. Just a personal experiment.)

Salesforce just agreed to acquire Informatica for about $8B, and I’ve been trying to understand the strategic angle.

On the surface it looks like a pretty standard enterprise software acquisition.

But Informatica’s main product is data integration and data governance — basically the infrastructure companies use to clean and organize data before feeding it into analytics or AI systems.

Which makes the timing interesting.

Salesforce has been pushing Agentforce, their enterprise AI platform, and one of the biggest problems with enterprise AI is that most companies have messy, fragmented data.

If you control the customer data (Salesforce) and the data pipelines that clean and structure it (Informatica), you essentially control the full stack needed to run enterprise AI workflows.

That seems to be the thesis.

The deal is about $8B, which isn’t huge for a company generating $14B+ in annual free cash flow, but it’s still a meaningful strategic bet.

The obvious question though is whether this actually strengthens Salesforce’s position or just adds complexity to an already large software stack.

Curious what people who follow enterprise software think.

Is this a smart move to secure the data layer for AI, or just another expensive integration project?

Not financial advice. Just trying to stress test the thesis before forming a view.

I put together a full breakdown in a report of the filing DCF model, competitive analysis, 16-signal monitoring framework ........

Oracle posted results after the bell yesterday that exceeded analyst forecasts. Cloud revenue rose noticeably on continued AI-related demand, and the company lifted its full-year revenue outlook through 2027. The stock moved up roughly 9% in after-hours trading.

I’ve held a small position in ORCL on my Bitget portfolio for a while now as part of my broader tech allocation. After reviewing the numbers and the forward guidance, I plan to add a bit more in the next few trading sessions if the price settles. Nothing dramatic, just following my usual process of increasing exposure when the business shows steady progress.

The print lines up with what we’ve seen from a few other infrastructure names lately, though the wider market is still dealing with oil price swings and policy headlines. It feels like a quiet confirmation that enterprise AI spending hasn’t slowed.

Curious to hear how others are viewing this one.

Are you adding, trimming, or sitting tight?

Any specific parts of the report that stood out to you?

Source: https://www.cnbc.com/2026/03/11/stocks-making-the-biggest-moves-midday-orcl-nbis-cpb-serv-cdre.html

The market does a pretty decent job pricing things correctly most of the time. That's the uncomfortable part of value investing nobody really talks about. Finding genuine undervaluation requires working a consistent process, not waiting for obvious screaming deals to announce themselves.

Here's what actually makes it into my workflow:

Comparing P/E to the stock's own 5-year historical average, not just the sector median. A company trading at 14x that's averaged 22x for half a decade is telling you something sector comparisons won't catch. Earnings get temporarily compressed, fear gets priced in, and the business often hasn't changed.

EV/EBITDA below 8 in non-tech sectors. P/E is messier than people realize because capital structure differences, tax treatments, and one-time items all distort it. EV/EBITDA strips most of that out. Below 8 in industrials, consumer staples, or financials is a legitimate starting point.

FCF yield above 7%. Free cash flow divided by market cap. A stable business yielding 8% on FCF outperforms most fixed income alternatives over a full cycle and filters out a lot of the accounting noise that pure earnings metrics miss.

P/B below 1 in asset-heavy sectors. Graham built a career on this in banks, insurance, and industrials. Buying assets at less than recorded book value creates a real cushion even if growth never materializes.

Net insider buying over the trailing 90 days. Executives sell shares for dozens of reasons. Buying with personal capital after a drawdown is a different signal entirely. Not a standalone trigger, but when it stacks with two or three of the others it adds real conviction.

13F filings from concentrated value managers. When someone running a focused fund for 25 years takes a 5%+ position in something nobody's discussing, that's a free research lead. I track the super investor portfolios on valuesense rather than pulling edgar every quarter, which is a time sink I never want back.

The reverse DCF before you run a forward one. Instead of projecting growth to get a price target, start from the current price and back-solve for what growth rate the market is already assuming. If that implied rate is 18% annual FCF growth over 10 years, the margin of safety is thin. If it only needs 4%, you've found something worth modeling seriously.

The hard part isn't any individual method. It's applying all of them consistently when everything looks expensive and the temptation is either to overpay or stay out entirely.