Pranay Bhansali

CA | Research Analyst | Seek knowledge and share!!!!

[Pranay Bhansali @Iampranayb]

CASE STUDY: How a $4.5M SMB acquisition fell apart pre-LOI

Broker pitch: $1.0M “Adjusted EBITDA” (4.5× multiple)
Forensic reality: $110k true EBITDA
The deal was overvalued by $3.9M.

Here’s the EBITDA bridge 👇

[Pranay Bhansali @Iampranayb]

Was $MSFT building ahead of demand or was demand simply waiting for capacity to come online?

One quarter doesn't settle that debate

The complete research memorandum is in the Featured section of my LinkedIn profile.
https://t.co/olLLW83tRd

[Pranay Bhansali @Iampranayb]

The most interesting part of $MSFT earnings was not revenue or EPS.
It was this.
Azure grew 43% while Microsoft continued investing at an extraordinary pace in AI infrastructure.

For months, the dominant debate has been that Microsoft is spending too much.

[Pranay Bhansali @Iampranayb]

These results suggest we may have been asking the wrong question.
What if the real constraint was never demand but capacity?

In June, I published a research memorandum arguing that this earnings release would be the first meaningful test of that hypothesis.

[Pranay Bhansali @Iampranayb]

I think every industry has one sentence that completely changes how you see it

Mine:
AI Infrastructure: Every solved bottleneck creates the next trillion dollar bottleneck.
CPUs → GPUs → Networking → Power.

What's the sentence that took you years to believe in your industry?

[Pranay Bhansali @Iampranayb]

If you’re reviewing SMB acquisitions right now:

I help search fund principals and SMB acquirers run pre-LOI red-flag screens before committing time or capital.

DMs are open if you’d like to see a redacted memo or discuss a live deal confidentially.

#SMBTwit #SearchFund #ETA

[Pranay Bhansali @Iampranayb]

CASE STUDY: How a $4.5M SMB acquisition fell apart pre-LOI

Broker pitch: $1.0M “Adjusted EBITDA” (4.5× multiple)
Forensic reality: $110k true EBITDA
The deal was overvalued by $3.9M.

Here’s the EBITDA bridge 👇

[Pranay Bhansali @Iampranayb]

Outcome:

The buyer walked away.
$3.9M of overpayment avoided.
Months of wasted diligence avoided.

Sometimes the highest-ROI decision is saying no early.

[Pranay Bhansali @Iampranayb]

Most analysts I meet think financial modeling starts in Excel.
That’s the first sign they’re not ready for the buy-side.

When I was working in a family office, the first investment meeting never involved a spreadsheet. In fact, my CIO once told me:

“If your thesis can’t survive a whiteboard, don’t bring me a financial model.”

That hit hard.

Because I realised
Retail traders and even many junior analysts believe conviction comes from complex Excel sheets.
But in reality, institutional conviction is built before the first cell is typed.

Here’s what actually happens on the buy-side:

We stress-test the core business logic before forecasting revenues.

We ask “What would need to be TRUE?” before touching a multiple.

And more importantly, we first decide whether this business even deserves the effort of modeling.

Most models fail not because of wrong formulas, but because they’re built on businesses that should have been rejected in the first 15 minutes.

I’ve packaged the exact 3 filters we used before touching Excel at the family office.

If you want it, comment “THESIS” below.
I’ll send it personally.

#equityresearch #buyside #financialmodeling

[Pranay Bhansali @Iampranayb]

Seems a reasonable reply with lots of room for improvement. Do comment and tell if you want me to try more such prompts.

[Pranay Bhansali @Iampranayb]

Recently I asked @Google Bard to create a long term portfolio and this is the reply I got

Portfolio for a 27-year-old with 10000000 rupees

Investment Criteria

Age: 27
Amount in rupees: 10000000
Risk Appetite: 30% (Medium Risk)
Investment Goals: Long Term (Retirement)

[Pranay Bhansali @Iampranayb]

Conclusion

This portfolio is a good starting point for a 27-year-old with 10000000 rupees who is looking to invest for the long term. However, it is important to consult with a financial advisor to create a portfolio that is tailored to your specific needs and risk tolerance.