Z47
August 12, 2021

Calculating Liquidation Preference

As a venture investor / founder / banker / lawyer, you’ve likely heard the term Liquidation Preference (LP) - and that LP determines how the proceeds will be shared at the time of a liquidity event (M&A, change of control, etc). You’re likely also aware that LP is either non-participating (straight) or participating (commonly referred to as double-dip). Lastly, LP is usually stated as a multiple e.g. ‘1x straight LP’ means the holder of preference shares has the option to receive either a) 1x of capital invested OR b) participate pro-rata in the proceeds with common stock holders.

What’s less known is howexactlythe LP math works. Recently, this topic came up in a portfolio company documentation discussion and I was surprised to learn that very few VCs (myself included) / founders / bankers / lawyers know exactlyhowto calculate LP. While the concept and theory is known to all, there are various nuances of calculating LP and practical application that are unclear to most. Some examples of these nuances are below.

  1. If the company is sold for less than capital invested, are the proceeds distributed pro-rata to capital invested or pro-rata to ownership?
  2. Is LP calculated for the total shareholding of an investor or applied per series of shares issued? Does it matter?
  3. If one investor elects to exercise LP (i.e. take the capital invested or a multiple thereof), how do other investors distribute the proceeds? Is it inter-se pro-rata with the founders? Or is it based on each investors absolute ownership %? Is this pro-rata share applied to theremainingproceeds (after paying of investors who elected LP) or is it applied tototalproceeds? If one does the latter is there enough to distribute?
  4. Does one investors LP decision change the payoff for other investors? How?
  5. Does LP mean investors shares are ‘senior’ to founders shares?

...and many more.

I did some reading to get answers to these. While there are reams of articles dedicated to explaining the concept of LP, there aren’t actual LP calculation examples that clearly answer the above questions. So I thought I’d take a stab at this.

After several discussions with colleagues, other investors, lawyers and bankers, I think I’ve finally understood how this practically works. And I thought I’d share my learning with others by using an example of a company that has gone through 3 rounds of financing after which it is acquired. I’ve used different scenarios of the sale value ranging from the company being sold for less than capital invested, to the sale value being more than capital invested but less than the last private round valuation, to finally a scenario where the company is sold for greater than the last round valuation.

Please see theattached spreadsheet.The calculations are a bit involved so you’ll have to patiently walk yourself through the formulae to understand this completely. And if you think LP calculation is hard, wait till you see an Anti-Dilution spreadsheet:) that’s an article for another day!

Would be great to hear your feedback / questions on this. Thanks to Archana fromRajaram Legalfor patiently reviewing versions of this till her eyes glazed over. Also, thanks to my friend and VC from Saif,Mayankwho helped with this and also pointed me to a fantastic article by Charles Yu that cleared many of my doubts.Here’s the articlefor those of you interested.

For more information, write to us: namaste@Z47.com.
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August 12, 2021

Calculating Liquidation Preference

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As a venture investor / founder / banker / lawyer, you’ve likely heard the term Liquidation Preference (LP) - and that LP determines how the proceeds will be shared at the time of a liquidity event (M&A, change of control, etc). You’re likely also aware that LP is either non-participating (straight) or participating (commonly referred to as double-dip). Lastly, LP is usually stated as a multiple e.g. ‘1x straight LP’ means the holder of preference shares has the option to receive either a) 1x of capital invested OR b) participate pro-rata in the proceeds with common stock holders.

What’s less known is howexactlythe LP math works. Recently, this topic came up in a portfolio company documentation discussion and I was surprised to learn that very few VCs (myself included) / founders / bankers / lawyers know exactlyhowto calculate LP. While the concept and theory is known to all, there are various nuances of calculating LP and practical application that are unclear to most. Some examples of these nuances are below.

  1. If the company is sold for less than capital invested, are the proceeds distributed pro-rata to capital invested or pro-rata to ownership?
  2. Is LP calculated for the total shareholding of an investor or applied per series of shares issued? Does it matter?
  3. If one investor elects to exercise LP (i.e. take the capital invested or a multiple thereof), how do other investors distribute the proceeds? Is it inter-se pro-rata with the founders? Or is it based on each investors absolute ownership %? Is this pro-rata share applied to theremainingproceeds (after paying of investors who elected LP) or is it applied tototalproceeds? If one does the latter is there enough to distribute?
  4. Does one investors LP decision change the payoff for other investors? How?
  5. Does LP mean investors shares are ‘senior’ to founders shares?

...and many more.

I did some reading to get answers to these. While there are reams of articles dedicated to explaining the concept of LP, there aren’t actual LP calculation examples that clearly answer the above questions. So I thought I’d take a stab at this.

After several discussions with colleagues, other investors, lawyers and bankers, I think I’ve finally understood how this practically works. And I thought I’d share my learning with others by using an example of a company that has gone through 3 rounds of financing after which it is acquired. I’ve used different scenarios of the sale value ranging from the company being sold for less than capital invested, to the sale value being more than capital invested but less than the last private round valuation, to finally a scenario where the company is sold for greater than the last round valuation.

Please see theattached spreadsheet.The calculations are a bit involved so you’ll have to patiently walk yourself through the formulae to understand this completely. And if you think LP calculation is hard, wait till you see an Anti-Dilution spreadsheet:) that’s an article for another day!

Would be great to hear your feedback / questions on this. Thanks to Archana fromRajaram Legalfor patiently reviewing versions of this till her eyes glazed over. Also, thanks to my friend and VC from Saif,Mayankwho helped with this and also pointed me to a fantastic article by Charles Yu that cleared many of my doubts.Here’s the articlefor those of you interested.

We are excited about the innovation and growth opportunities in this sector.

If you are considering building in the footwear space, we’d love to chat.
Drop us a line at consumer@matrixpartners.in

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Index Performance

+28.1%
Since Jan 2024
NIFTY 500
+19.0%
Since Jan 2024

Z47^fortyseven is up +23.9% since its January 2024 base date, versus Nifty 500's +18.4%, ahead by 550 bps.

The cohort moved +4.7% over the month versus Nifty 500's +2.5%, leading by 220 bps.

Anchored in domestic demand and rising digital adoption, the cohort remained resilient amid global headwinds.

Consumer Tech was the best-performing sector at +9.2% last month, driven by sustained growth in consumer demand and strength in consumer-internet platforms.

Largest Constituents  ·  The Names That Anchor The Index

1.
Eternal
Quick-commerce leadership and continued investment
▲ +12.8%
2.
Groww
Broking market-share gains and margin-funding growth.
▲ +10.4%
3.
Lenskart
Store densification and margin expansion.
▲ +2.4%

Top Gainers  ·  Key Drivers

1 MONTH RETURN
1.
CarTrade
Auto-marketplace dominance and a cash-rich balance sheet.
▲ +59.4%
2.
 Amagi Media Labs
Profitability turnaround and AI-led cloud media adoption.
▲ +31.4%

Top Laggards  ·  Key Drivers

1 MONTH RETURN
1.
Fractal Analytics
Enterprise AI spending trends and post-listing share supply.
▼ -10.8%
2.
MedPlus Health
Pharmacy-margin pressure and competitive intensity.
▼ -6.6%

Key Themes  ·  Latest Results

In Q4FY26, Z47^fortyseven's cohort grew top line ~39% YoY, more than 3x the broad market's ~12% growth.

Operating leverage lifted net margins around 500 bps into positive territory, even as broad-market net margins remained roughly flat.

With 40 of 47 companies now profitable, the cohort reflects a broader shift toward profitable growth over growth at any cost.

AI adoption runs deeper across this cohort than in the broader market, with companies using it to drive growth and reshape demand, not just improve efficiency.

Cash generation is increasingly defining the winners, enabling market leaders like Eternal, CarTrade, and PB Fintech to fund acquisitions and expansion from their own balance sheets.

Market & Macro Context

The cohort saw several block deals this month, including sizeable stake sales in Lenskart, Delhivery, Honasa, and Shadowfax.

Ownership continues to shift from foreign investors to domestic institutions, creating a more durable shareholder base.

AI remained the defining technology investment theme, driving capital deployment across both private and public markets.

IPO Takeaway · Kissht

Listed May 2026

A modest listing pop followed by strong post-listing gains reinforced the market's preference for asset quality and disciplined underwriting over pure loan-book growth.

The listing helped reset perceptions around unsecured lending, creating a constructive valuation anchor for the issuers that follow.

The buyer mix was a notable positive — strong participation from long-only domestic institutions supporting a durable post-listing ownership base.

Net Read

Fundamentals continued to strengthen across the cohort, with growth, margins, and cash generation improving in tandem.

Performance dispersion widened, with profitability and earnings quality increasingly distinguishing the strongest performers from the rest.

Disclaimer

Z47^fortyseven is published for informational purposes only and does not constitute investment advice, or any offer, solicitation, or recommendation to buy or sell securities. Index performance is historical and should not be construed as indicative of future results.

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