Monday, 15 June 2026

Ferns, Coastlines and the Nifty 50: Why Choppy Markets Keep Repeating 15Jun2026

Ferns, Coastlines and the Nifty 50: Why Choppy Markets Keep Repeating 15Jun2026

 

 


(This is my 518th blog since 2010. Over the years, I have covered global financial markets, with a focus on India, and continue to share insights to help readers understand complex topics in simple language.

The views expressed here are for information purposes only and should not be construed as a recommendation or investment advice. While the author is a CFA Charterholder with nearly 25 years of experience in financial markets, this content is intended to share general insights and does not constitute financial guidance. 

Please consult your financial adviser before taking any investment decision. Safe to assume the author has a vested interest in stocks / investments discussed if any.) 

 

 

Nifty 50 Chart showing similar patterns in Oct2021-Mar2023 and Sep2024-Mar2026 period

 

1 Introduction


Ferns, coastlines and the Nifty: Look closely at a fern. Each little frond has the same shape as the whole leaf. Photograph a coastline from a plane, then from the sand and the jagged outline looks much the same at both heights. 

A mathematician named Benoit Mandelbrot gave these repeating self-similar shapes a name: fractals. The whole looks like its parts and the parts look like the whole. You see it in ferns, snowflakes, rivers and clouds.

Mandelbrot argued that financial markets behave in a similar way. Look at the two red boxes on the above chart (Nifty 50 index). The first runs from Oct2021 to Mar2023. The second runs from Sep2024 to Mar2026. 

They are not identical, but they are strikingly alike. 

Each is a stretch of choppy, big swings: a jagged climb, a sharp fall, a fresh push to new highs, then another drop. The same shape, drawn twice.

Now think of the Nifty 50 as a coastline on a map you can zoom. Zoom into the first box and you find rough bays and inlets, the big moves up and down. Slide across and zoom into the second box, and the same bays and inlets appear. 

The prices differ. The character is the same. Even the sizes rhyme. In both spells the index fell by about 15 per cent, bounced back by close to 20 per cent, then fell again (for data, see tables given under 'Additional data' at the end of the blog).

 

2 Backdrop
 

This is an update of an article titled: "The Pitfalls of Market Timing – And Why FOMO is Your Worst Financial Adviser 12Jul2025." 

The earlier article comprehensively analysed the market behaviour of Oct2021-Mar2023 period and the current piece builds on that, focusing on the latest Sep2024-Mar2026 period. 

Ups and downs are part of markets. 

 

(article continues below)

---------------

Related blogs:

The Pitfalls of Market Timing – And Why FOMO is Your Worst Financial Adviser 12Jul2025 

Tweet thread 15Sep2020 Portfolio Rebalancing and Market Timing 

--------------- 

 

You are better off focusing on the business nature of a company, rather than a price chart. 

There is a strange irony in how investors behave. During the Oct2021-Mar2023 choppy period, many investors assumed the choppiness would continue and resorted to heavy trading.

But they were completely caught off guard when Indian markets (represented by Nifty 50 index) experienced a spectacular one-way upmove from 17,000 levels in Mar2023 to 26,000 levels in Sep2024. 

In Sep2020, I argued that rebalancing and market timing are different animals. Rebalancing is a calm rule you follow. Timing is a guess about the future that rarely pays.  

The Jul2025 piece delved deeper into  the choppy stretch of 18 months from Oct2021 to Mar2023, and the price investors paid for assuming the volatility would continue for long.

The pattern has returned during the Sep2024-Mar2026 period and the same two lessons hold. Do not try to time the volatile markets. Meet it with your own rules and with patience.

 

3 The Latest 18 months: Sep2024-Mar2026

The numbers tell a plain story of motion without progress. In Sep2024, the Nifty 50 stood near 26,200. By Mar2025, it reached a level of 22,100, losing almost 16 per cent in nearly six months. 

From Mar2025 lows, it bounced back to 26,300, in a matter of 10 months, by the first week of Jan2026, But it lost over 15 per cent in under three months to reach a 2026-low of 22,300 by end-Mar2026. So, between Mar2025 and Mar2026, the index went nowhere. 

Overall, during our observation period of Sep2024 to Mar2026, Nifty 50 returned nearly minus 15 per cent. 

One detail is worth a pause. The falls were quick; the recovery was slow. The climb from Mar2025 to Jan2026 took about ten months. The two drops took roughly five months and three months. 

Fear, it seems, moves faster than patience and the sharpest fall was the most recent one. An investor who glanced only at the start and the end would shrug at the overall decline (see Additional data at the end of the blog for the data).

These kind of repeated, zigzag patterns keep coming back in leaves, snowflakes and price charts. The secret to survival is learning to spot this repeating behavior early. 

When the eventual market fall arrives, disciplined and calm investors have better chance of earning superior returns. 

 

4 What the behavioural scientists tell us

Why are these violent movements so hard to sit through? The behavioural scientists have an answer, and it is not flattering to us.

Daniel Kahneman and Amos Tversky showed that losses hurt far more than equal gains please us. 

Losing a thousand dollars, say, on a gold trade hurts twice as much as the pleasure of gaining a thousand dollars in a chip stock—even though the net financial result is zero.

After a long rise we expect more rises. Our feelings run ahead of the facts.

That is why a long, jagged stretch is so dangerous, not to your wealth, but to your judgement. The market does not need to ruin you. 

It only needs to frighten you into ruining yourself. Benjamin Graham warned, long ago, that an investor's worst enemy is usually himself.

The way-out of such a ruinous path is not cleverness but discipline. Make fewer decisions, and make them in calm moments, not panicked ones. 

Follow a rule, such as rebalancing, so you act by plan rather than by mood. And judge yourself over years, not days.

We do not yet know how this second box ends. The leg after Mar2026 is still being written, and I will leave it for another day. From the lows of 22,300 in Mar2026, Nifty 50 has recovered, though in a choppy way, to nearly 24,000 levels now. 

Nobody knows whether the market breaks higher or lower from here; but your own behaviour should serve you well. Keep your nerve, keep your rules and avoid keeping constant watch on the screen.

 

5 Why Markets Keep Repeating

Human nature tends not to change. People get greedy when things go well and panic when things go bad. New investors enter the market every day, but they still feel the exact same emotions. 

Because human memory is short, every big rise and fall feels completely new to the crowd.

Fear travels much faster than patience. When prices drop, people rush to sell, which forces prices to drop even lower. On the flip side, long periods of calm make people overconfident, which quietly sets up the next big crash. 

Markets are constantly hit by unexpected events like wars, oil crises, tariff wars, promise of new technology, changes in interest rates and political shockwaves. 

The specific trigger changes every time, but the surprises never stop, forcing you to constantly guess a changing future.

Prices move faster than human judgment. News travels in a matter of seconds, but figuring out the true value of a company takes a long time. 

If you look at a market chart for a single day, a full year, or an entire decade, you will see the same zigzag outline. This is the main point about fractals: the time frame changes, but the chaotic character of the market stays exactly the same.

Check below for references and additional data. 

 

- - -


---------------

References:

Tweet thread 15Jun2026 Ferns, Coastlines and Nifty 50: Why Choppy Markets Keep Repeating

NSE Historical index data

Tweet 03Sep2025 Nifty 50 fractal pattern

Tweet thread 12Jul2025 - The Pitfalls of Market Timing – And Why FOMO is Your Worst Financial Adviser

Trendlyne Nifty 50 chart 

---------------

Additional data:

Table 1 showing high volatility period of 18 months between Sep2024 and Mar2026 >

 


 


Table 2 showing high volatility period of 18 months between Oct2021 and Mar2023 >

 


Tuesday, 9 June 2026

Collected Notes 2026

Collected Notes 08Jun2026

 

 

This is a running collection of news items, articles, images, ideas, observations, statistics, predictions, and other things I found interesting during 2026. Entries are brief and primarily intended as a personal reference archive.

Newest entries will be at the top.

 

Jun2026

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15Jun2026 HCL Tech is investing USD 150 million or Rs 1,400 crore for a 10.5% stake, in Sarvam AI (Axonwise Pvt Ltd), as the lead strategic investor  

Sarvam AI is an LLM startup based out of Bangalore. With this investment round, Sarvam AI is valued at USD 1.5 billion. It's India's first unicorn in AI space. 

This is the kind of OPTIONALITY, fundametally strong companies like HCL Tech possess. Most investors ignore this optionality at their own cost.

This investment positions HCL Tech as a frontrunner in cutting-edge fields like "Agentic AI." 

Sarvam AI is India's full-stack sovereign AI company.

Sovereign AI is just AI built and controlled within a country's own borders. The core technology is the same. 

The difference is about ownership, control and location.

Though Sarvam AI is mostly private-funded, Govt of India is providing some kind of support to it.

Sarvam AI was co-founded in Aug2023 by Dr Vivek Raghavan and Dr Pratyush Kumar.

(Good to know Chandra R Srikanth and Tushar Goenka of Moneycontrol.com got the story right; they reported on 14May2026, HCL Tech was likely to invest USD 150 million in Sarvam AI.)  

 

15Jun2026 Tweet How exciting is this! Now, foreigners like, Elon Musk and Richard Branson can now open trading accounts in India and start buying Indian stocks directly.

15Jun2026 Tweet CEA Dr V Anant Nageswaran is parroting what economist Dr Ajay Shah has been advocating for long for allowing rupee as a shock absorber for Indian economy during hard times

15Jun2026 Tweet Checks and balances in the US  > Trump tariff refunds > Wheels turn for over  USD 10-billion US tariff repatriation to India

14Jun2026 Condensed PDF of Adam Smith's "The Wealth of Nations" -- the condensed version was written by Eamonn Butler

13Jun2026 Under orders from Trump administration (export control order based on national security bogey), Anthropic suspended access to its Fable 5 and Mythos 5 AI models - so, foreign countries will not be able to access them - 

earlier Tweet thread  09May2025 - AI diffusion rules - trade protectionism - Sovereign cloud - Digital sovereignty >   tech sovereignty - sovereign AI

Tweet thread 28Jul2025 Microsoft suspends services to Rosneft-Backed India Refiner Nayara Energy - weaponisation of digital services? - EU sanctions

13Jun2026 Tweet - Elon Musk is both a builder and seller. Other comparisons include Apple, Microsoft and Google >


 

 

13Jun2026 Corporate demerger thread 🧵> (with image containing recently demerger schemes or schemes of arrangement) > Vedanta Ltd, Maharashtra Seamless and others

13Jun2026 India crude basket (USD / barrel) is 93.2 as on 11Jun2026.Monthly average prices > PPAC data

13Jun2026 Tweet Crude oil prices USD / barrel >   Prices (Brent, WTI and Murban) are down sharply in anticipation of US Iran war settlement

13Jun2026 Tweet Heavy colour & graphics in annual reports often serve as "impression management". They distract readers from weak financial results. 

13Jun2026 On its IPO debut (public listing) on Nasdaq on 12Jun2026, SpaceX has become world's seventh largest listed company by market cap, ahead of Broadcom, Saudi Aramco, Tesla, Meta and Samsung. SpaceX stock is part of Nasdaq Composite index, but it is not yet a part of Dow Jones Industrial Average (DJIA) and S&P 500. 

World's top 10 companies by market cap as of 12Jun2026 (as per companiesmarketcap.com, the world's total stock market cap for 10,632 listed companies tracked by companiesmarketcap.com is USD 150 trillion as of 12Ju2026) > 


 

13Jun2026 On its historic debut on the Nasdaq on Friday, 12Jun2026 (under the ticker symbol SPCX), SpaceX’s stock performance registered the following key figures (at the IPO price of USD 135 a share, SpaceX's market cap was USD 1.77 trillion; but at the close price of USD 160.95, its market cap is USD 2.1 trillion:

IPO Price: USD 135.00 (The fixed price set the night before trading)  

Open Price: USD 150.00  

High Price: USD 176.52  

Low Price: USD 149.34

Close Price: USD 160.95 (nearly 19% gain from its initial IPO price)


 

13Jun2026 According to Forbes, Elon Musk, CEO of Tesla, became world's first trillionaire with a net worth of USD 1.1 trillion on 12Jun2026, when SpaceX (Space Exploration Technologies Corp) went public (IPO listing on Nasdaq)


 

12Jun2026 CFA Institute Research Foundation:

Jun2026: A Comprehensive Guide to ETFs (2nd edition) Module 2: Evaluating ETFs

Three-leg approach for evaluating ETFs:

1) Efficiency -- expense ratios, tracking difference (it differs from tracking error), tax consequences, transparency (disclosures)

Efficiency metrics:
AUM
expense ratio
median tracking difference
portfolio disclosure, monthly or daily

2) Tradability - order types, volumes, spreads, premium and discounts (difference between NAV and ETF market price)

In case of volumes, median volumes can be tracked. 

3) Fit - whether ETF's investment strategy aligns with investors' objectives; in some cases, the return difference between the best and worst ETF can be quite large

ETF count (number of ETFs)

Concentration (Herfindahl Ratio)

Six prototype investor personas (like mid career retirement savers, Next Gen retail investors, foundations, family offices, etc.)

Apr2025: A COMPREHENSIVE GUIDE TO ETFs (2ND EDITION) MODULE 1: ETF FEATURES AND EVOLVING LANDSCAPE
 

12Jun2026 ETV video SP Balasubrahmanyam Emotional Speech About Director Bharathiraja In Swarabhishekam programme on 26Jan2014 - ETV - Ramoji Rao 

11Jun2026 Bharathiraja's film, Mudhal Mariyathai (Telugu version à°†à°¤్à°® à°¬ంà°§ుà°µు, 1986) is based on the love story of Russian writer Fyodor Dostoevsky and Anna Snitkina, who was 25 years younger to him.


11Jun2026 Tweet  CMS Info Systems buyback proceeds credited today. entitlement vs acceptance 

In one individual ("small shareholder") case, the company accepted 9.5 times the original entitlement!

This high acceptance ratio happened because many eligible investors either skipped it or simply forgot to participate.

11Jun2026 MSCI EM Index 31May2026 - for the first time in 26 years, no Indian stock is in top 10 of the index - Taiwan, South Korea, China, India and Brazil are top five countries in the index, with China and India dropping their top ranks. TSMC weight at 14.5% is much higher than that of entire India weight of 10.9%. 

EMs have, both in 2025 and 2026 (so far), outpeformed the World index.

 



 

11Jun2026 Javier Blas - The drop in nitrogen fertilirer (urea) prices has now extended into Asia. India has received offers for its latest urea tender at an average price of USD 530 per tonne, down ~44% from $947 per tonne in April. (The massive drop in Asian urea prices is primarily driven by China. After implementing stringent export bans on urea in March to protect its domestic supply, Beijing recently decided to open up its export quotas again.)

11Jun2026 Ten Reasons Oil Is Still Below USD 100 a Barrel - by Javier Blas - weblink for free read

After more than 100 days of Iran war, crude oil prices are still below USD 100

Before the war, an average of 20 million barrels a day of crude and refined products transited the Strait of Hormuz — about a fifth of global demand

1 China has reduced its imports (they imported much more oil in 2025)
  China may have tapped its SPR
  China essentially bailed out the global economy
2 demand destruction
  China oved to EVs, may have further reduced oil demand
  India consumption of LPG and natural gas has come down after Iran war
  Asia switched to coal and firewood
3 Crude oil is still leaving Strait of Hormuz
  Saudi Arabia and UAE are using oil pipelines
  Some tankers too are moving out of SoH
4 there was oversupply of oil at the start of war (around 27-28Feb2026)
5 The US and other IEA members released their SPR
6 Refineries are now more flexible in terms of what they produce--diesel, petrol, jet fuel, fuel oil, petrochemicals
7 the art of jawboning the oil market
8 oil price insurance (call options) is more available
9 satellite tracking of oil tankers has improved allowing trades to take a better view
10 higher prices, higher production (the US, Canada, Brazil, China and Guyana are producing more)

But the future is uncertain 

 

11Jun2026 Tweet thread - India market cap >

India market cap to GDP ratio based on nominal GDP (new series with base year 2022-23) >

BSE market cap of all listed companies is Rs 461.60 lakh crore (or USD 4.84 trillion), as of 07Jun2026.

India nominal GDP Rs 346.36 lakh crore (or USD 3.64 trillion) for FY 2025-26 (New Series), so market cap to GDP ratio is 133 per cent.  

 

11Jun2026 KKR bullish on India’s long-term investment prospects - higher-quality services - India growth story -

11Jun2026 India has potential for over 102 GW of floating solar capacity: Govt of India - reservoirs - water bodies - Omkareshwar Floating Solar Park, Madhya Pradesh - solar power - renewable energy

11Jun2026 Tweet thread Evidence-based investing requires us to test market narratives against actual data.

One narrative making the rounds today is that a weakening rupee is driving foreign investors (FPIs) out of Indian equities.

But does the evidence support that claim?

 

10Jun2026 Vivek Mashrani - Claude AI tips - Claude tips for investing prompts -   

20May2026 X Article by Shruti Codes - how to use Claude -  Claude tips to unlock its full potential

10Jun2026 Tweet thread gold and silver prices - world prices - India gold / silver prices

09Jun2026 Ground report from Akash Prakash - huge AI capex - zero interest about India

09Jun2026 (via msn / Bloomberg) Pentagon accuses Alibaba, Baidu of aiding China’s military

09Jun2026 (via msn / Bloomberg) China's pharma compnay, WuXi AppTec Co, is named by Pentagon to have links with the Chinese military - Biosecure Act - India CDMO sector 

09Jun2026 Tweet thread FCNR (B) and NRI deposits create a FUTURE LIABILITY for India - FPI flows - FDI flows - 

09Jun2026 China’s exports surged 19.4% year-on-year to a record high of USD 376.78 billion in May2026

08Jun2026 A US Federal Judge blocks Trump’s USD 100,000 H-1B visa fee - checks and balances in the US

Checks and balances in the US - Tweet thread 08May2026: Some decisions of Trump administration reversed by courts in the US and the Congress:

US federal judge blocks Trump's USD 100,000 H-1B visa fee

US Supreme Court reverses Trump's universal reciprocal tariffs 

Trump's executive ban on new offshore wind power projects struck down by a federal court

Trump admin's restrictions on tax credits to clean energy projects vacated by a federal judge

The US Senate bipartisan passage of a War Powers Resolution to halt unauthorized military hostilities in Venezuela

A sweeping hold on immigration applications from dozens of nations struck down by a federal judge

The addition of a citizenship question to the 2020 census blocked by the Supreme Court

The executive-backed push to completely "repeal and replace" Obamacare defeated by the US Senate

 

04Jun2026 Aswath Damodaran SpaceX valuation is USD 97.83 per share - his video

 

 

 

20May2026 Tweet thread - resource nationalism -Resource sovereignty - Indonesia - inward looking world - deglobalisation? - weaponising global trade - supply chain security - Strategic resource stockpiling - Resource weaponisation - resource rich countries - resource poor countries - China curbs

 

 

 

12Apr2026 Tweet  - Sovereign cloud - Digital sovereignty >  EU tech sovereignty - data security concerns

 

14Oct2025 Tweet Most Investments are Actually Bad. Here’s Why. By Lyn Alden.

Leverage

Moats (network effects, brands, patents, intangible assets, economies of scale and others)


 

 

Tweet 25Mar2021 Imagine yourself running into Vincent vag Gogh and walking into his paintings! 

Tweet 08Apr2018 'Other painters paint a bridge, a house, a boat,' Claude Monet explained. 'I want to paint the air that surrounds the bridge, the house, the boat.'  #Painting 

 

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Read more:
 
Blog of Blogs Theme-wise 
 
Weblinks and Investing
 
India Fixed Income Data Bank - Tweet thread 08May2026
 
Indian Economy Data Bank - Tweet thread 07Jun2026

India Forex Data Bank - Tweet thread 26Apr2026
 
Who is Eating my Gold ETF Return? (gold data / gold ETF data) 
 
JP Morgan Guide to Markets  28Feb2025
 
Corporate Groups and Listed Companies 29Dec2024
 
Corporate Governance Concerns - Indian Companies 13Dec2024 (including family feuds / family disputes) 
 
Stocks and Peer Comparison by Industry 16Feb2024
 
various uploads on Scribd by VRK100  
 
 
 

 

 

 

 

Monday, 8 June 2026

Fire money, Regret minimisation and SpaceX 08Jun2026

Fire money, Regret minimisation and SpaceX 08Jun2026

 

 

I grew up on a story about Motilal Nehru: He was so wealthy, legend says he brewed tea, when friends visit him at home, by burning currency notes.

I call that "fire money"—the money you're rich enough to set on fire.

So how much fire money can one afford to lose on SpaceX?

Before you decide on that, let me tell you another story. A real one. 

In 1994, Jeff Bezos had a great job on Wall Street. Good salary, strong career, comfortable future.

Then he discovered that the Internet was growing explosively and started thinking about building an online business. But leaving his job felt risky.

Instead of asking, "Will this succeed?", he imagined himself at age 80 looking back on his life and asked:

"Which choice am I more likely to regret?"

He realised he could live with failing. What he couldn't live with was never trying.

So he quit his job and started Amazon.

That's regret minimisation: making decisions based not on what looks best today, but on what your future self is least likely to regret.

In investing, the question becomes:

"When I look back 10 or 20 years from now, which decision would I regret less?"

I missed Bitcoin in 2012, 2015 and even in 2020! I missed so many experiences too, by not doing trial and error. 😅

So, the two first principles before you invest in SpaceX IPO or Anthropic IPO or OpenAI IPO are: fire money and regret minimisation. 

Coming to the present...

SpaceX is going to be a one-man company.

Big ego means Elon Musk may bet big on xAI and burn cash.

xAI is the biggest risk for SpaceX.

In my opinion, a price of one hundred and thirty-five dollars per share and a total market valuation of USD 1.8 trillion is high for Space Exploration Technologies Corp (SpaceX) IPO. 

After public listing, the share price might rise to 200  dollars a share or fall to 50 dollars. Who knows! As they say, nobody knows anything beyond a point.

Happy investing! 

 

- - -



Sunday, 31 May 2026

Nifty Valuation Tracker Series: May 2026 Update – Broad Market and Smart Beta Indices 31May2026

Nifty Valuation Tracker Series: May 2026 Update – Broad Market and Smart Beta Indices 31May2026

 

 


(This is my 515th blog since 2010. Over the years, I have covered global financial markets, with a focus on India, and continue to share insights to help readers understand complex topics in simple language.

The views expressed here are for information purposes only and should not be construed as a recommendation or investment advice. While the author is a CFA Charterholder with nearly 25 years of experience in financial markets, this content is intended to share general insights and does not constitute financial guidance. 

Please consult your financial adviser before taking any investment decision. Safe to assume the author has a vested interest in stocks / investments discussed if any.) 

 

Introduction

This note is the second part of the updated valuation framework for select NSE indices, building on earlier studies published:

1) On 21Apr2026 namely “How Valuations Shape Returns and Risk in Select NSE Indices” and 

2) On 03May2026 namely “Valuation Changes in Broad Market and Smart Beta Nifty Indices”. 

While those studies focused on valuation, returns, risk and short-term re-rating, this section focuses on current valuation positioning within a historical range.

The analysis compares current levels (as of 31May2026) against a 21-quarter baseline from Mar2021 to Mar2026 across six Nifty indices. It uses percentile-based positioning of PE, PB and dividend yield to assess whether valuations are relatively rich or attractive across segments.

Note: The idea is to update this 21-quarter framework each quarter as new data become available. For example, inclusion of the Apr–Jun2026 quarter will extend the dataset to 22 quarters in the next update, maintaining a rolling historical reference.


Section 1:  

Valuation Re-rating across Largecap, Midcap, Smallcap, Low Volatility, Momentum and Quality Indices (31Mar2026 – 31May2026):

This note updates the earlier valuation framework by examining how select NSE / Nifty indices have moved from end-Mar2026 to end-May2026, focusing on Midcap 150, Smallcap 250 and Nifty 200 Quality 30. 

The objective is to decompose recent price gains into PE re-rating and PB movement, and assess whether valuation changes are being driven by earnings support or multiple expansion.
 
While there are six Nifty indices included in the two charts below, let us focus on three indices, namely, Nifty Midcap 150, Nifty Smallcap 250 and Nifty 200 Quality 30, for our short analysis.

Across Nifty Midcap 150, Nifty Smallcap 250 and Nifty 200 Quality 30, price gains over the period have been accompanied by varying degrees of PE expansion / contraction and PB expansion.
 
Data are fascinating. Sometimes.

In the past two months 
(31Mar2026 – 31May2026), Nifty Midcap 150 PE ratio has fallen, while the price index itself has risen.

In contrast, Nifty Smallcap 250 index's PE expansion is much faster than the rise in underlying index. 
 

A. Midcap index
 
The Nifty Midcap 150 index gained 16.2 per cent over the period under review (end-Mar2026 to end-May2026). Despite the rise in prices, its PE ratio declined by 5.5 per cent. This suggests that earnings grew faster than stock prices

The implied earnings contribution is approximately 21.7 per cent, offset by valuation compression. The rally appears to have been driven primarily by fundamentals rather than multiple expansion. 

Midcap returns appear earnings-driven, but the precise contribution cannot be directly verified without the exact EPS aggregation methodology and update timing used by NSE India.  
 
One big assumption here is: NSE India and Nifty Indices are in the habit of updating all the earnings without any time lag. 
 
B. Smallcap index

The Nifty Smallcap 250 index advanced 18.9 per cent during the same period. Its PE ratio, however, expanded by a much larger 30.2 per cent. This indicates that valuation rerating contributed more to returns than earnings growth. 

The implied earnings contribution is nearly minus 11.3 per cent, meaning earnings lagged the increase in prices. Future performance may depend on earnings catching up with elevated valuations.
 
Why the big contrast? Midcap and Smallcap indices delivered similar returns.

Yet the source of those returns is completely different.

Midcaps:

Return driven by earnings.
Valuation becoming more reasonable.
Risk profile improving.

Smallcaps:

Return driven by multiple expansion.
Valuation becoming richer.
Risk profile increasing.

That distinction matters because earnings-driven rallies tend to be more durable than valuation-driven rallies. 
 
C. Quality index:  
  
The Nifty 200 Quality 30 index delivered a return of 10.5 per cent. Its PE ratio increased by 5.5 per cent, indicating moderate valuation expansion. The implied earnings contribution is therefore  nearly 5 per cent. 

Both earnings growth and valuation rerating appear to have contributed to performance. Compared with small caps, the return profile for Quality index looks more balanced and fundamentally supported.
 
Overall interpretation:
 
Broad Market Indices:

The broad market presents a mixed picture beneath the surface. Midcaps are being supported primarily by earnings growth, while smallcaps are benefiting mainly from valuation expansion / re-rating. 

Similar price returns are therefore being driven by very different underlying factors. Overall, fundamentals appear stronger in midcaps, whereas smallcaps are becoming increasingly dependent on sentiment and liquidity. 


Smart Beta Indices:

The smart beta segment appears to have better earnings support than the broader smallcap space. The Quality index has delivered returns through a combination of earnings growth and moderate PE expansion, while Momentum has relied more heavily on rerating. 

This suggests that quality stocks still retain relatively balanced valuation support. Overall, Quality appears better positioned than Momentum if market conditions remain stable.
 
Note on implied earnings contribution
 
In the investment industry, it is a standard practice to use phrases, like, earnings growth, earnings contribution, or fundamental contribution.

To be on the safer side, the author has used the term 'implied earnings contribution,' since it is inferred from index return and valuation changes rather than measured directly from reported earnings. 

In practice, these terms generally convey the same underlying idea: the portion of return attributable to growth in earnings rather than changes in valuation multiples.

To put simply, at the market index level:

Price Return ≈ Earnings Growth + Multiple Expansion

At the stock level:

Price Return ≈ EPS Growth + Multiple Expansion
 
One could also say: 
 
Earnings Component ≈ Price Return − Multiple Expansion.
 
 
Two charts below: 
 
1)  Chart showing valuation change in Broad Market and "Smart Beta" Nifty Indices 
(31Mar2026 – 31May2026) >
 
 2) Chart showing PE and PB Expansion versus Index Returns
(31Mar2026 – 31May2026) > 

 



Section 2:  

Current Valuation Positioning vs 21-Quarter Historical Range:
 

Section 1 showed how valuations evolved over the period from 31Mar2026 to 31May2026, decomposing index-level returns into earnings contribution and valuation re-rating across broad market and smart beta segments. 

That analysis helped explain the drivers behind the recent move in different parts of the market.

Building on that, Section 2 shifts the focus from movement to positioning. 

Instead of looking at how valuations changed over time, it examines where current valuations (as of 31May2026) stand within their own 21-quarter historical range, using percentile-based comparisons across the same six Nifty indices.

 

Across the six Nifty indices, the current valuation versus the 21-quarter historical range shows a clear divergence between large caps, cyclicals and factor strategies (see two charts below for data).

Broad Indices:

Large-caps (Nifty 50) stand out as the most comfortable segment, with both PE and PB below their lower quartile and dividend yield above the upper quartile. Large caps appear to be cheaper compared to their recent history versus other segments.

Mid-cap stocks (Nifty Midcap 150) appear more neutral on earnings valuation, but expensive on book value and weak on yield. This suggests that while earnings-based valuation is not stretched, market seems to be pricing in strong growth expectations.

Small-cap stocks (Nifty Smallcap 250) are the most stretched among broad indices, with PE above the 75th percentile and yield near historical lows. This indicates that recent performance has pushed valuations into richer territory relative to their own history.

 

Smart beta Indices:

Among the so-called smart beta indices, the picture is more mixed. Low Volatility sits close to its historical median, reflecting relatively balanced valuation conditions, while Momentum is also near median but with subdued yield, indicating continued preference for growth-oriented exposure without extreme valuation stress.

As is well known, Quality index stands at premium valuation, with PE around median levels but PB above the 75th percentile, highlighting persistent willingness to pay for balance sheet strength and earnings stability.

Overall, the six-index framework shows a clear valuation divergence: large caps appear most attractive on a historical basis, mid-caps and quality sit in a fair-to-rich zone depending on the metric, while small-caps and parts of the growth/cyclical space reflect elevated valuation pressure after recent re-rating. 

 

Two charts showing:

Nifty 50, Nifty Midcap 150 and Nifty Smallcap 250 Indices Current Valuation vs Historical Range, and

Nifty 100 Low Volatility 30, Nifty 200 Momentum 30 and Nifty 200 Quality 30 Indices Current Valuation vs Historical Range >

(please click on the charts to view better) 




Shortcomings of the analysis

First, the framework is based on a relatively short history of 21 quarters, which is not enough to fully capture multiple full market cycles such as deep bear markets or extended bull phases. 

Second, the analysis is purely valuation-based and does not explicitly incorporate macro variables such as interest rates, inflation, liquidity conditions, growth prospects or risk premia. These factors can significantly influence both valuation levels and their interpretation across cycles.

Third, the study relies on index-level aggregates, which can hide significant internal dispersion. Within each index, sector and stock-level behaviour can vary widely.

Fourth, the framework is descriptive rather than predictive. It shows where valuations stand relative to history, but it does not establish causal relationships or provide forward return forecasts with certainty.

 

Conclusion

Taken together, the 21-quarter percentile framework provides a structured way to understand where current Nifty index valuations stand relative to recent history. 

The current snapshot highlights a clear divergence across segments, with large-caps appearing relatively attractive, mid-caps and quality positioned closer to fair value, and small-caps reflecting elevated valuation pressure after recent re-rating.

Valuations alone do not determine near-term outcomes, especially in environments where earnings cycles, liquidity and sentiment shifts play a dominant role.

Overall, the framework is best used as a positioning guide within a broader investment process, helping to assess relative valuation comfort across market segments rather than as a standalone buy or sell signal.

The analysis and views expressed are purely for educational and informational purposes and do not constitute investment advice or recommendations. 

Investors are advised to consult a qualified financial advisor before making any investment decisions. The author is not responsible for any losses arising from use of this information.

Check below for references. 

 

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References:

Nifty Return Profile

Nifty Indices factsheets

NSE Index Dashboard monthly - PDF for May2026

NSE Live Analysis - showing index values and valuation ratios of all Nifty Indices on a daily basis  

NSE Market Watch - all indices 

 

 

 

Sunday, 24 May 2026

Why Nifty 100 Is Mostly a Nifty 50 Portfolio: Lessons from a Simple Thought Experiment 24May2026

Why Nifty 100 Is Mostly a Nifty 50 Portfolio: Lessons from a Simple Thought Experiment 24May2026

 

 


(This is my 514th blog since 2010. Over the years, I have covered global financial markets, with a focus on India, and continue to share insights to help readers understand complex topics in simple language.

The views expressed here are for information purposes only and should not be construed as a recommendation or investment advice. While the author is a CFA Charterholder with nearly 25 years of experience in financial markets, this content is intended to share general insights and does not constitute financial guidance. 

Please consult your financial adviser before taking any investment decision. Safe to assume the author has a vested interest in stocks / investments discussed if any.) 

 



Today, I have done a thought experiment. I'm pleasantly surprised by the results. Let me explain. 

At first glance, index investing looks straightforward. A broad index like Nifty 100 is often treated as a simple, diversified basket of the largest companies in the market. But when you break it down at the level of underlying weights, the picture becomes less intuitive.

In this piece, I explore a simple thought experiment comparing Nifty 100 with a 50:50 combination of Nifty 50 and Nifty Next 50. 

On paper, both approaches invest in the same underlying set of large companies, yet they can generate different returns over long periods. 

The objective here is not to argue for one over the other, but to understand why such differences can arise in the first place and what they reveal about how indices actually allocate capital.

It may also be noted that both Nifty 50 and Nifty Next 50 are constructed from the same underlying universe of Nifty 100 stocks. 

In fact, NSE India / Nifty Indices first defines the Nifty 100 universe and then selects the top 50 stocks by free-float market capitalisation to form Nifty 50, with the remaining constituents forming Nifty Next 50. 

Because of this specific design, the mathematical relationship always holds true:

Nifty 50 + Nifty Next 50 = Nifty 100 

 

1 When Equal Weight Outperforms Nifty 100

As of 30Apr2026, the one-year total return of Nifty 50 index was minus 0.3 per cent, while Nifty Next 50 delivered a strong return of 9.1 per cent. Nifty 100, which combines both these segments through market-cap weighting, ended the same period at minus 1.3 per cent.

If we instead construct a simple 50:50 blend of Nifty 50 and Nifty Next 50, the return for the same period comes to approximately 4.4 per cent. This is a straightforward average of the two index returns, given equal allocation.

What is interesting is that this 50:50 combination significantly outperformed Nifty 100 over the same period. A portfolio built from the same underlying universe of stock, but with a different capital allocation rule, delivered a materially different outcome in just one year.

Note: Nifty 50 contains 50 stocks, Nifty Next 50 has 54 stocks, and Nifty 100 consists of 104 stocks due to ongoing index adjustments related to the Vedanta Ltd demerger process starting in Apr2026.

 

2 What 20 Years of Returns Reveal

To understand whether the one-year observation is an anomaly, it is useful to look at a longer history of calendar year returns across Nifty 50, Nifty Next 50 and Nifty 100 from 2006 to 2025 (see additional data at the end of the blog for the 20 year data table).

The data show a consistent pattern. Nifty Next 50 exhibits significantly higher cyclicality compared to Nifty 50. In strong market phases, it tends to outperform sharply, while in weak market phases it tends to underperform with similar intensity. 

Nifty Next 50 reflects a much wider dispersion of returns across market cycles.

Nifty 50, in contrast, shows relatively stable compounding across periods. Nifty 100 remains closer to Nifty 50 due to its higher aggregate exposure to large-cap stocks, a natural outcome of its free-float market-cap weighting methodology.

This difference in cyclicality is visible even in individual years. For example, in 2024, Nifty Next 50 delivered a return of 28.4 per cent compared to 10.1 per cent for Nifty 50, reflecting strong upside participation in a risk-on market phase. 

In such a year, a 50:50 combination of Nifty 50 and Nifty Next 50 would have delivered 19.2 per cent, compared to about 13 per cent for Nifty 100, highlighting the impact of higher allocation to the more cyclical segment.

In contrast, during 2011, Nifty Next 50 fell by 31.3 per cent while Nifty 50 declined by 23.8 per cent, reflecting sharper downside in a risk-off environment. 

In such a period, the 50:50 combination would have declined by about 27.7 per cent, compared to roughly 24.9 per cent for Nifty 100, showing how higher exposure to the more volatile segment amplifies losses in adverse cycles.

What emerges is that the underlying universe does not behave as a single uniform return stream, but as two distinct return regimes: relatively stable large-cap compounding represented by Nifty 50 and higher-volatility, cyclical growth exposure represented by Nifty Next 50.

Because Nifty 100 assigns weights based on free-float market capitalisation, its composition results in a higher aggregate exposure to Nifty 50 stocks compared to Nifty Next 50. 

As a result, the return behaviour of Nifty 100 tends to be more closely aligned with the performance of Nifty 50 stocks.

Even though Nifty 100 and the 50:50 mix invest in the same stocks, their returns can still differ a lot because:

> sometimes Nifty Next 50 does much better than Nifty 50
> sometimes Nifty Next 50 does much worse

And since Nifty 100 gives Nifty Next 50 a smaller weight (because of market-cap weighting), 50:50 combination (of Nifty 50 and Nifty Next 50) gives Nifty Next 50 a much bigger weight.

To clarify: Nifty 100 assigns weights based on free-float market capitalisation, its composition results in a higher exposure to Nifty 50 stocks (about 81.7 per cent) and a lower exposure to Nifty Next 50 (about 18.3 per cent). 

As a result, Nifty 100 index's return behaviour tends to be more closely aligned with large-cap performance (data as of 30Apr2026).

The stocks are not the real reason for performance difference.

The real reason is:

How much money you put into each part of the market.

 

3 What the Long-Term Pattern Actually Implies

There is no persistent leadership between Nifty 50 and Nifty Next 50. Instead, performance leadership rotates across market regimes depending on whether large-cap stability or broader risk participation dominates.

This directly affects the earlier comparison. A fixed 50:50 allocation between Nifty 50 and Nifty Next 50 does not replicate Nifty 100, even though both draw from the same universe. 

It shifts capital toward the more cyclical segment, making returns dependent on which segment leads across cycles.

This pattern should not be viewed as a structural guarantee of outperformance. It reflects historical cyclicality between two segments under specific market conditions, and can change if leadership dynamics shift.

The key takeaway is that long-term returns depend not only on index constituents, but on how capital is allocated across segments that behave very differently across cycles.

 

4 What the Indices Actually Contain

The earlier discussion focused on how Nifty 50, Nifty Next 50 and Nifty 100 behave across market cycles. But the underlying reason becomes much clearer once we examine how weights of individual components are distributed within these indices.

Although all three indices are built from the same broad universe, the return influence of individual stocks inside them is very different. Nifty 100, despite formally containing both segments, remains heavily influenced by the largest Nifty 50 constituents because of market-cap weighting.

Chart showing top holdings comparison of Nifty 50 versus Nifty Next 50 and their effective weight inside Nifty 100 (all data as of 30Apr2026) >

 


The contrast is immediately visible. As shown in the above table, the top five Nifty 50 constituents account for 37.3 per cent of Nifty 50 and still retain a combined weight of 30.5 per cent inside Nifty 100. 

In contrast, the top five Nifty Next 50 constituents account for 17.2 per cent of Nifty Next 50, but collectively shrink to just 3.1 per cent inside Nifty 100.

This asymmetry is important. The dominant Nifty 50 companies continue to exert significant influence even after being absorbed into Nifty 100, while the strongest Nifty Next 50 constituents become heavily diluted within the broader index structure.

As stated above, the top five Nifty Next 50 constituents carry a combined weight of 17.2 per cent inside Nifty Next 50, but only about 3.1 per cent inside Nifty 100. Which means, a weight difference of roughly 14 percentage points. 

During periods when these more cyclical stocks in Nifty Next 50 outperform strongly, a fixed 50:50 allocation between Nifty 50 and Nifty Next 50 captures much more of that upside compared to Nifty 100, where the influence of Nifty Next 50 is substantially diluted.

The same pattern is visible at the aggregate index level as well. Based on the constituent weights as of 30Apr2026, stocks belonging to Nifty 50 collectively account for 81.7 per cent of Nifty 100, while stocks from Nifty Next 50 account for only 18.3 per cent. 

In effect, Nifty 100 remains heavily driven by Nifty 50 stocks despite formally containing both segments.

This helps explain why Nifty 100 returns tend to behave much closer to those of Nifty 50 despite containing the same broader universe of stocks.

The divergence between Nifty 100 and a fixed 50:50 allocation therefore arises not from the stocks themselves, but from the different weights assigned to those stocks within the Nifty 100 index structure.

 

5 What Could Make This Relationship Reverse? 


The historical data discussed earlier show that a fixed 50:50 allocation between Nifty 50 and Nifty Next 50 often produced different outcomes compared to Nifty 100. But this should not be interpreted as evidence that the 50:50 approach will always outperform in the future.

In reality, the relationship can reverse for long periods depending on market leadership.

If large-cap stocks dominate market returns over an extended cycle, Nifty 100 may outperform a 50:50 allocation because of its much higher exposure to Nifty 50 constituents. 

This is especially likely during periods characterised by risk aversion, global uncertainty or weak liquidity conditions, when investors tend to prefer larger and more established companies.

The earlier historical examples themselves illustrate this cyclicality. During 2011, Nifty Next 50 fell much more sharply than Nifty 50, causing the 50:50 combination to underperform Nifty 100. Similar periods can occur again in future market cycles.

It is also important to recognise that market-cap weighting is not inherently flawed. One of its strengths is that it automatically allocates more capital toward companies that have already become economically dominant within the market. 

This can reduce volatility and improve resilience during difficult market environments.

By contrast, a fixed 50:50 allocation structurally assigns a much larger role to the more cyclical Nifty Next 50 segment. That can improve upside participation during strong phases, but it can also amplify downside volatility during weaker periods.

In other words, the earlier outperformance of the 50:50 structure reflects a particular historical interaction between stability and cyclicality. It is not a permanent structural advantage.

The broader lesson is that even small changes in allocation methodology can materially alter return behaviour over long periods, despite starting from almost the same underlying stock universe.

 

6 Passive Investing Is Not Truly Neutral in Allocation 

One of the most interesting insights from this thought experiment is that passive investing is not truly neutral in  allocation as it first appears.

[Note: This thought experiment was inspired by a Business Line article on Nifty 500 equal-weight combinations, which prompted a deeper look into index construction and capital allocation.] 

At a surface level, Nifty 100 and a 50:50 combination of Nifty 50 and Nifty Next 50 appear very similar because both invest in almost the same underlying companies. 

But the return behaviour can still differ meaningfully because the weighting structure itself changes how capital is distributed across segments.

In other words, index construction is not merely a technical detail. It directly shapes portfolio behaviour.

Market-cap weighted indices such as Nifty 100 naturally allocate more capital toward already dominant companies, which tends to anchor performance closer to large-cap behaviour. 

A fixed 50:50 allocation approach, by contrast, intentionally increases participation from segments that may behave more cyclically.

Neither structure is inherently superior. They simply represent different ways of distributing capital across the same market universe.

This is perhaps the broader lesson from the entire exercise. Even within passive investing, allocation methodology matters. 

Two portfolios can own almost identical stocks and still generate very different outcomes over time because weights, concentration and segment exposure all influence return behaviour across market cycles.

7 Summary 

This thought experiment began with a simple question: how can two portfolios built from the same underlying universe of stocks produce meaningfully different returns over time?

The comparison between Nifty 100 and a 50:50 allocation of Nifty 50 and Nifty Next 50 shows that the answer lies not in the stocks themselves, but in how they are weighted. 

Even when the underlying constituents are broadly similar, differences in allocation rules can lead to different exposure to market cycles, concentration, and segment behaviour.

Over shorter periods, this effect can appear quite pronounced, especially when one segment significantly outperforms the other. Over longer periods, the same mechanism continues to operate, but with outcomes that depend heavily on which segment leads during different phases of the market cycle.

The key insight is not that one approach is universally better than the other. Rather, it is that index construction itself embeds an allocation choice. 

Market-cap weighted indices like Nifty 100 naturally lean towards large-cap stability, while an equal allocation approach increases participation from more cyclical segments.

For investors, this shifts the way indices should be viewed. They are not just passive representations of the market, but structured ways of distributing capital across different parts of the market.

In that sense, the difference between Nifty 100 and a 50:50 allocation is less about what is being owned, and more about how much is being owned in each part of the market.

Check below for references and additional data. 

 

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References:

Nifty Return Profile

Nifty Indices factsheets

NSE Index Dashboard monthly - PDF for Apr2026

NSE Index Tracker (tracker for all NSE indices), for example, Nifty 50 

Nifty Indices Methodology document May2026 

Tweet 24May2025 Nity50-NiftyNext50-Midcap150-Smallcap250 mix outperforms single Nifty 500  

Business Line article 23May2026 Why This Nifty 50-Midcap-Smallcap Mix Crushes the Nifty 500 -- it shows equal allocation to Nifty 50, Nifty Next 50, Nifty Midcap 150 and Nifty Smallcap 250 outperforms Nifty 500 in majority periods, based on 10 year rolling returns over a 20 year period

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Additional data:

Chart showing TRI returns of Nifty 50, Nifty Next 50 and Nifty 100 from 2006 to 2026 (2026 YTD returns are as of 22May2026) >