The minds inside a derivatives account

SEBI’s Department of Economic and Policy Analysis has published a series of studies on individual traders in the equity derivatives segment since January 2023, the latest pair in August 2026. It is unusual for a regulator anywhere to publish this candidly on the losses of the investors it supervises. The August 2026 study of trading behaviour is the most valuable of the lot, because it does not stop at how much individuals lost and starts asking how they traded. In other words, it is less a statistics report than a behavioural report. Almost every headline number lines up with a bias that behavioural finance has documented for decades. The data does not merely tell us that individuals lose money in derivatives. It tells us how they talk themselves into it.

Overconfidence, and the illusion that experience teaches.

Time in the market does not help, at least not here. Among traders with one consecutive year of participation, 91 per cent made losses. The share rises with every additional year, reaching 96.5 per cent at four years. Among traders active through all five years from FY22 to FY26, only 0.5 per cent were profitable in every year. This learning curve slopes the wrong way, because what survives repetition is not skill but conviction. Traders do not learn that they cannot beat the market. They learn that they have not yet beaten it.

The lottery preference.

In the study’s sample, 93 per cent of traders were only options buyers. People overweight small probabilities, and a cheap option has the shape of a lottery ticket: a known small cost, an unknown vivid gain. Prospect theory says people will overpay for that shape, and they do. Options buyers had the highest incidence of loss, about 90 per cent. The sharpest number is their median return on capital employed, minus 114 per cent in FY26. Half of them lost more than the entire capital they had put to work.

Self-attribution.

No dataset observes this directly, but it holds the rest together. Gains are read as skill and losses as bad luck, and that asymmetry is what keeps overconfidence intact through a losing record.

The sunk cost fallacy, and the ego that feeds it.

Only 15.4 per cent of trader-quarters in the study were profitable. The median gain in a winning quarter was ₹4,366. The median loss in a losing quarter was ₹10,525, more than twice as large. Traders sat through losses far larger than the gains they banked, and at the level of the account that habit hardens into sunk cost. Traders with cumulative profits above ₹10 lakh during FY22 to FY24 continued trading at a rate of 88 per cent. Traders with cumulative losses above ₹10 lakh also continued at 88 per cent. Traders whose outcome, either way, was below ₹1 lakh continued at only 53 to 55 per cent. What predicts persistence is not whether you won. It is how much is at stake. Big winners stay because they believe they are good. Big losers stay because leaving now would make the loss permanent and admitted. They want to get back to even. Among the large past losers who continued, more than 95 per cent lost again.

What follows? Disclosure has done some work, but not enough, and the reason sits in the data. Every trader believes the aggregate describes someone else, so telling people that nine in ten lose money is a statistic about strangers. The design principle now should be to make each trader’s own record unavoidable, and to target named biases rather than risk in general.

Four measures are worth considering. Let the account’s own history be the credible witness: a personalised profit and loss statement at every login and each quarter end, showing the net outcome and all costs since account opening, in rupees and as a percentage of the trader’s own capital and portfolio. An appropriateness test at entry in place of a one-time consent screen, with graduated exposure limits for first-time traders. Self-set annual loss limits offered by every broker at onboarding, with a cooling-off period before a limit can be raised. And better framing at the order screen, with the premium shown as a share of capital at risk alongside the share of similar contracts that have expired worthless.

Mental accounting, used deliberately.

One more finding deserves to become the basis of investor education rather than another warning. Traders who lost more than ₹1 crore in derivatives held a median cash equity portfolio of about ₹138. For most of them the derivatives account was not a slice of a portfolio. It was the portfolio. Mental accounting, the habit of keeping money in separate mental jars, is usually filed as a bias. Made explicit, it is also the most workable remedy available. Individuals should be taught to allocate across three buckets: money that must stay safe, money that funds long-term goals through diversified market exposure, and a small aspirational bucket where the odds are poor and the loss is affordable. Futures and options belong in the third, sized in advance as a stated share of total wealth. That converts an open-ended activity into a budgeted one, and it gives a trader a number to check against. Brokers can carry this framing at onboarding, and investor education can make it the vocabulary: not do not trade, but decide first how much of your wealth this bucket is allowed to hold.

None of this should be mandated untested. SEBI now has the data and the broker relationships to run randomised trials of these nudges and see which change behaviour. Regulation has already done a great deal about the product, through expiry frequency, contract size and transaction costs. The frontier now is the account holder, and this study is the map.

Author – Rachana Baid, Dean – NISM

A Yen Rescue Dressed in Euros

Washington’s intervention was ingenious in its plumbing and silent on the flows that matter most

On Friday, July 31, 2026, the United States stepped in to prop up the Japanese yen for the first time since 1998. The mechanics were stranger than the intervention itself: rather than selling dollars to buy yen — the textbook move — the Treasury sold euros to fund the purchase. That single choice turned a routine-sounding rescue into one of the year’s most debated maneuvers.

What happened

The yen had been in freefall, touching 160-plus to the dollar, its weakest since 1986, stoking importdriven inflation. Japan moved first and big, selling an estimated $53–59 billion of reserves to buy yen. Then the New York Fed, acting for the Treasury, sold euros for yen. The US contribution was never disclosed, though a photographed notepad in front of Treasury Secretary Scott Bessent read “Buy

Japanese Yen — $5–10 bil.” By the New York close the yen had firmed to around 157.40, and both governments confirmed the coordinated operation on the subsequent Monday.

The euro trick, and why the yen rose against the dollar

Here is the puzzle. When the US sold euros to buy yen, it never touched a single dollar — so why did the yen also strengthen against the dollar? Because the dollar, euro, and yen are mathematically tied together, so shifting one pair forces the others to realign. It unfolds in five stages.

1. The starting balance. Normally the prices line up so no conversion route beats another. Using the July 31, 2026 rates — a dollar worth about 160 yen, a euro worth about 1.15 dollars — a euro was worth roughly 184 yen whether converted straight to yen or via dollars first.
2. The targeted push. The US floods the market with euros to buy yen. This does two things at once: it makes the yen harder to get with euros, dragging the euro-yen rate down (say from 184 to 176), and it pushes the euro down against the dollar.
3. The gap opens. Because the US never trades dollars, the dollar-yen rate stays put at 160 for the moment — creating a mismatch: it is now cheaper to get yen through euros than to buy them directly with dollars.
4. Traders close the gap — and drag the dollar. Traders rush in to pocket that difference, taking the cheaper euro route in volume. Their buying pulls the dollar’s price down against the yen too, from 160 toward about 155. The dollar is dragged along by the other two.
5. It all happens at once. In a live market these rates move together in the same instant, not one after another. The result: a stronger yen against the dollar, a slightly weaker dollar against the euro, and Washington’s dollar reserves left untouched. (This is just the US euro move; Japan was also selling dollars directly that day, so the real shift came from both.)

The starting rates above are the actual market rates on July 31, 2026; the post-intervention figures are illustrative, chosen to show the mechanism clearly.

Why bother? The Treasury-market motive

The reason has less to do with the yen than with the US bond market. Japan is the largest foreign holder of US Treasuries, and the fear was a doom loop: if Japan defended the yen alone by selling dollars, it might dump Treasurys to raise them, pushing US yields higher. Funding the operation with euros — and steering Japan toward the Fed’s FIMA (Foreign and International Monetary Authorities) repo facility, which lets foreign central banks borrow dollars against their Treasurys instead of selling them — let Washington lift the yen while shielding the Treasury market. Seen this way, it is genuinely clever: a currency operation reframed as a bond-market defense.

The blind spot: FIMA covers only the official channel

But the facility is open only to foreign central banks and official monetary authorities — and that is where the design springs a leak. It protects the Bank of Japan and the Ministry of Finance from dumping their own Treasurys, but does nothing for everyone else.

That “everyone else” is enormous. Japan’s $1.19 trillion in official Treasury holdings is only a slice of its foreign assets; Japan is the world’s largest net creditor, with net external assets near $3.7 trillion. On bonds alone, private Japanese institutions hold up to roughly $3 trillion in foreign bonds — dwarfing the official reserve stock FIMA protects by about three to one. Life insurers, banks, and pension funds piled in during years of near-zero yen yields; the Government Pension Investment Fund alone runs about $1.2 trillion. None of them qualify for FIMA. If they decide the yen has turned and repatriate — selling dollars and Treasurys to buy yen — they sell straight into the open market, exactly the pressure the facility was built to relieve for the BOJ(Bank of Japan). So the euro-and-repo architecture guards one channel of forced selling while leaving the far larger one wide open, and the Treasury-yield spike it was meant to prevent could arrive anyway.

The verdict

Both readings are partly true. As crisis management for the US bond market, the euro-funded maneuver is inventive and defensible. As a fix for the yen, it is almost certainly temporary and its safeguard only half-built: it left the fundamentals driving yen weakness intact and shielded only the official channel. Washington strengthened the right currency by selling the wrong one — and whether that reads as brilliance or improvisation depends on what the yen does next.

Disclaimer: 

• Intervention figures are estimates; the US contribution was not officially disclosed.
• Views are Personal.

 

Author – Kuldeep Thareja, DGM, NISM

The Closing Auction Needs Attendance, Not a Rethink

A well-attended closing auction benefits investors by lowering trading costs, providing a closing price closer to fair value, and making capital raising cheaper for traded companies. India has recently established this mechanism. However, it now requires participants, and the industry best equipped to supply them is now attempting to understand it at present.

Since August 3, all Indian stocks with listed derivatives now close an auction from 3:20 to 3:30 pm, collecting orders with a random stop. During this period, orders are pooled, and the price that clears the highest volume is set as the close, replacing the previous volume-weighted average of the last half hour. Until recently, India was the only major market that closed based on an average rather than an auction.

The evidence behind that switch is worth stating plainly, because research of this kind rarely reaches the people who trade. In 2003, Pagano and Schwartz studied Euronext Paris after its introduction of a closing call in 1996 and 1998. They found that execution costs decreased and price discovery improved, primarily due to mechanical reasons. In continuous trading, large orders cross the spread and walk the book, incurring higher costs with each share. Conversely, during an auction, all orders clear at a single price. Similarly, Kandel, Rindi, and Bosetti in 2012 examined Borsa Italiana following its 2001 closing call, discovering increased efficiency because orders can be revised during auctions without execution, allowing participants to reveal true intentions rather than quoting defensively. Additionally, Butler, Grullon, and Weston in 2005 analysed 2,387 U.S. share sales from 1993 to 2000, finding that banks charged firms with more liquid stocks approximately 101 basis points less in fees—about one-fifth of the average—since the risk to underwriters decreases when the market is capable of absorbing the shares.

A study warns that we should pay close attention. Ellul, Shin, and Tonks (2005) analysed the London Stock Exchange following the introduction of a closing call to its SETS order book in May 2000. While the auction improved price discovery compared to the dealer system, it consistently struggled to clear smaller, less-liquid stocks. They attributed this to the externality of a thick market: an auction works only if participants expect others to be present. In thin markets, traders avoid participating, fearing a lack of counterparties, which confirms their fears. The fault isn’t in the design but in the lack of attendance.

India’s situation is revealing: data indicates that during MSCI rebalancing days, 73 to 83 percent of trading in impacted stocks takes place in the last half hour. Volatility during these times is two to over three times higher than the rest of the day, and the difference between the reference price and the close ranges from 61 to 404 basis points. Foreign portfolio investors account for 56 to 60 percent of the traded value, proprietary desks about 17 percent, retail roughly 11 percent, and domestic mutual funds only 8 to 9 percent. Meanwhile, the industry most dependent on an accurate closing value appears to be a bystander.

So, what specific actions can each type of fund perform within their current legal framework? Let’s begin with the hedged categories, which had approximately ₹11.4 lakh crore as of June 2026. An arbitrage fund is required to keep its equity exposure fully hedged—meaning it must be long the stock in cash and short the same stock in futures. This requirement enables it to sell into buy-heavy auctions: it owns the shares, and unwinding the hedge is its primary activity. This allows it to provide the sell side without actually shorting any stocks. Now that the derivative window extends to 3:40 pm and stock derivatives settle based on the auction price, both legs of the transaction settle at a single price. Equity savings funds carry the same hedged approach.

Balanced advantage funds can adjust their equity exposure within a broad range on any day. This flexibility allows them to respond to shortfalls in the auction by buying during sell-heavy close and selling during buy-heavy close, framing these actions as normal asset allocation rather than trading strategies. Active equity funds do not need additional approval for such moves. For example, a flexicap or multicap fund that plans to reduce a position can place that order at market close instead of gradually throughout the day, and a cash-holding fund can do the same. Value, contrarian, and dividend-yield funds have the clearest case for this approach, since buying what the index is selling aligns with their mandates.

The ceiling is equally real and serves as a regulatory limit. No fund engages in naked short selling, and during a cash auction, a fund can only sell what it can deliver, making capacity limited to its owned assets. Specialised Investment Funds, the only structure allowed to intentionally short, are capped at 25% of the portfolio and were valued at around ₹17,858 crore in mid-2026. Stock lending is limited, with only about 176 of the roughly 2,600 listed stocks eligible. Passive funds typically hold almost no cash to facilitate purchases, but SEBI has proposed allowing them to borrow overnight against auction positions.

There are substantial advantages for funds. They can execute large transactions at transparent prices with minimal market disruption, which is why regulators promote the auction as an alternative to the block-deal window. This leads to a higher net asset value each evening. Furthermore, as SEBI broadens the auction to include stocks beyond derivatives, funds that adapt quickly will gain access to a much larger pool of resources.

Aligning with global standards isn’t only about having a global closing mechanism but also about making it robust through active participation for mutual benefit. By mid-2025, foreign investors’ passive money amounted to around ₹20.5 lakh crore, representing nearly 29% of their Indian equity investments, while domestic passive funds held about ₹9.18 lakh crore. This money moves based on tracking error, which is determined at market close. A close that behaves like London’s allows global allocators to size India without factoring in discounts for execution risk. Ellul and his co-authors showed what happens when nobody turns up. The funds can make sure somebody does.

Authors: Rachana Baid (Dean, NISM), V Shunmugam (Partner, MCQube)

 

Most retirement plans do not fail because of one bad decision. They erode because of a hundred reasonable ones.

Lifestyle creep, the slow upward drift of spending as income rises, is rarely a story of extravagance. The people it affects most are usually doing everything right. They earn well, invest consistently, and meet their savings targets year after year. Nothing in their spending looks reckless, and nothing in their portfolio looks fragile. That is exactly what makes it hard to see.

When income is high, and savings goals are being met, an increase in spending rarely feels dangerous. In isolation, it isn’t. An annual holiday abroad. A larger home in a better location. A more expensive car. Each is a defensible decision made by a competent person with the money to make it.

The problem is that they are neither isolated nor temporary. They are small, permanent resets of what “normal” means. You do not experience them as expenditure. You experience them as your life. And once something has become your life, it stops being reviewed. Nobody sits down at the end of the year to ask whether the car you upgraded to was worth it. Slowly, your baseline spending ratchets upward while the mental model of your savings and investment stays where it was.

The biggest impact will be on your retirement income. A retirement corpus is anchored to the lifestyle you intend to continue, not the one you had when you drew up the plan. A permanent increase of, say, ₹1.5 lakh a month in living costs requires much more than ₹1.5 lakh in savings. Even assuming a conservative withdrawal rate, it requires several crores more in capital. When spending has crept up, a drawdown forces withdrawals from a shrunken portfolio at exactly the wrong moment, or a sharp cut in living standards at exactly the moment you have least appetite for one. Sequence-of-returns risk is not purely a market phenomenon; it is a function of how much you must pull out while prices are down.

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The reason why lifestyle creep goes unnoticed is that nothing feels out of control. The savings rate may still look respectable in absolute terms. The SIPs are running. The portfolio is growing. However, the ratio between what you spend and your investment corpus is never on your radar. By the time it surfaces, the changes are difficult to reverse because any downgrade in your lifestyle feels like failure. Much of it is structurally locked in – a larger home means higher maintenance charges and property tax. Choosing a prestigious school means a decade of commitment.

To ensure that lifestyle creep does not erode your retirement savings, three habits can help. First, track your savings rate, not your savings amount. A rising rupee figure can conceal a falling percentage. Second, price the lifestyle, not the purchase. Before a permanent upgrade, convert the monthly figure into the capital it implies. Third, pre-commit your salary raises. Decide what share will be invested and what share will go to upgrade your lifestyle.

The answer to lifestyle creep is not austerity. The answer is to act on it intelligently.

How The KOSPI Index Fell off a Cliff — and Why India’s Markets Didn’t Follow

Between mid-June and late July 2026 the South Korean benchmark (KOSPI) staged one of the most violent reversals in its history. After hitting an all-time high of roughly 9,386 on 19 June 2026, the index shed close to 27% in a matter of weeks, with repeated single-session crashes of 8–11% that tripped the Korea Exchange’s automated circuit breakers. By late July the exchange had logged around eight market-wide circuit breakers and nearly thirty sidecar halts in a single year (a sidecar is a milder, five-minute brake that suspends only automated program trading when index futures swing about 5%, whereas a circuit breaker halts the entire market) — surpassing the previous record set during the 2008 financial crisis. The slide was driven not by a single shock but by a combination of global macro pressures, sector-specific vulnerabilities, and deep structural weaknesses in Korea’s market. This piece examines those weaknesses, and contrasts them with the guardrails that have kept Indian markets comparatively orderly through the same global turbulence.

What Broke in South Korea

• Extreme concentration in semiconductors. The KOSPI Index carries an unusually heavy structural tilt toward information technology and memory chips. Samsung Electronics and SK Hynix alone account for roughly 40–50% of the entire index. When global semiconductor sentiment cooled — amid missed earnings guidance from chipmakers and fears of AI-chip oversupply, sharpened by the rise of Chinese memory maker CXMT — these two stocks fell nearly 10–13% in single sessions and dragged the whole benchmark down with them. On the worst days, over 800 stocks declined against fewer than 50 that rose, showing how a two-stock problem became a whole-market problem.

• Unwinding of leveraged AI positions. Through the AI rally, both retail and institutional investors amplified their bets on chip and tech names using single-stock ETFs and margin trading. As prices plummeted, forced liquidations and margin calls cascaded the downward spiral rather than cushioning it.

• Global monetary policy and geopolitics. Stronger-than-expected U.S. data revived fears that the Federal Reserve would keep rates higher for longer. Combined with unexpected moves from the Bank of Korea and heightened friction in the Middle East, foreign capital exited Korean equities rapidly, adding currency pressure to the equity rout.

How India Absorbed the Same Shocks

The same global forces, the AI-chip wobble, persistent higher U.S. Fed rates, an oil-price scare, and a firm dollar struck Indian equities too. Yet the Nifty 50 Index and BSE Sensex moved close to flat, absorbing dips and recovering quickly, with no market-wide trading halts. Two structural features and a layered regulatory framework explain the difference.

1. 1- Broad sectoral diversification

Unlike Korea’s dependence on memory chips, India’s benchmarks are spread across roughly 13 sectors. Financial services is the single largest block at around 36%, followed by oil & gas (9.6%), Information Technology (8.37%), automobiles (7.13%), and consumer goods (5.7%), with no single stock dominating. Because the exposures are genuinely diversified, weakness in Indian IT was routinely offset by strength in banking, autos, or infrastructure, so no single theme could take the whole index down.

2. 2- A domestic institutional backstop funded by SIPs

India’s flow dynamics have shifted structurally. In the first half of the year Domestic Institutional Investors (DIIs) net-bought a record ₹4.3 lakh crore of Indian equities while Foreign Institutional Investors (FIIs) net-sold around ₹2.7 lakh crore. On individual panic days, DII buying repeatedly exceeded FII selling (for example, ₹9,283 crore of DII buying against ₹6,690 crore of FII selling over June 9–10, 2026). DII ownership has now structurally overtaken foreign ownership. As per NSE’s India Inc. Ownership Tracker data, DII ownership of NSE-listed companies surpassed their FPI counterparts. This reduces the “hot money” share of the market as SIP investors do not panic exit en masse.

Global market volatility creates both risks and opportunities.

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The Indian Regulatory Guardrails

Beyond market structure, SEBI and the exchanges (NSE and BSE) have built multi-layered rules that actively limit concentration and speculative leverage before they can destabilise the market:

• Index concentration norms. Since 2019, SEBI has required any index underlying an ETF or index fund to hold at least 10 stocks, cap any single stock at 25% (35% for sectoral/thematic indices), and limit the top three constituents to 65% combined. This directly forbids the kind of two-stock, 40–50% concentration that hollowed out the KOSPI Index.

• Real-time margining. Brokers must collect upfront (peak) margins before execution, and positions are marked-to-market continuously. This prevents the build-up of unchecked leverage of the sort that triggered Korea’s cascade of margin-call liquidations.

• Circuit breakers and price bands. Market-wide circuit breakers (at 10%, 15%, and 20% index moves) and scrip-level price bands halt runaway moves in an orderly way.

• ASM and ESM surveillance. The Additional and Enhanced Surveillance Measures, introduced in 2018, let SEBI flag stocks showing unusual volatility, concentrated client trading, or suspicious price-volume patterns. Flagged stocks face 100% upfront margin and curbed intraday leverage — curbing speculative froth before it turns systemic.

 Takeaway

Korea’s fall was not simply bad luck; it was the predictable failure of a market concentrated in two stocks, one theme, and leveraged, foreign-heavy flows. India faced the same global shocks but was cushioned by genuine sectoral breadth, a deep and non-panicky domestic investor base built on SIPs, and a stack of SEBI rules that cap concentration and leverage by design.

Disclaimer: Views are personal.

Authors: Mitu Bhardwaj and Kuldeep Thareja DGMs, Centre for Content Creation, NISM

Infrastructure Investment Trusts (INVITs): an Avenue to Earn from Infrastructure Investments

Infrastructure Investment Trusts (InvITs) sit in an interesting corner of the market: visible, listed, and yet not clearly understood. They are often pitched as “earn from toll roads” or “own power lines,” which is directionally correct but intellectually lazy. The reality is more nuanced, and more compelling if understood properly.

The Concept: what are you buying?

At their core, InvITs are trust structures that own and operate income-generating infrastructure assets – roads, transmission lines, gas pipelines, warehouses, telecom towers, etc. Securities and Exchange Board of India (SEBI) regulates them, and they are listed on stock exchanges, making them accessible like equities.

Think of them as the infrastructure equivalent of mutual funds. Instead of buying shares of companies, you are buying units of a vehicle that owns real assets i.e. differentiated from financial assets like stocks or bonds owned by mutual funds.

The structure is:

• A sponsor (usually a developer like a power or road company) transfers assets into the trust;

• An investment manager does financial management and capital structuring, declares distributions;

• A project manager operates and optimizes these assets;

• A trustee safeguards investor interest.

The key feature, and the real attraction, is distribution. InvITs are required to distribute at least 90 percent of their net distributable cash flows to unitholders. In simple terms: these are yield vehicles.

Investment Rationale

InvITs solve one basic portfolio problem: how to generate predictable cash flows without taking equity-like volatility.

There are four reasons why they deserve a serious look:

1. 1. Predictable income (the core appeal)

InvIT cash flows come from contracted or regulated assets – toll collections, transmission tariffs, or lease payments. These are not cyclical earnings in the traditional sense. This makes them closer to a high-yield bond than equity.

2. 2. Inflation linkage

Many infrastructure contracts have built-in escalation clauses (e.g. toll rates linked to inflation). This gives InvITs a rare characteristic: income that can keep pace with inflation, unlike fixed deposits.

3. 3. Diversification benefit

InvITs have low correlation with equities. They don’t move because of earnings upgrades or downgrades; they move based on interest rates, asset performance, and yield expectations.

4. 4. Accessibility at small ticket size

For a small ticket size e.g. one unit in the secondary market / as per your corpus, you can access this asset class. Historically, infrastructure was a playground for sovereign funds and pension money. InvITs democratize access i.e. retail investors can now participate in these infrastructure assets.

The macro case for InvITs in India is:

• India is entering an infrastructure buildout cycle;

• Government programs like national monetization pipelines are feeding assets into InvIT structures;

• The market itself is expected to grow significantly.

This creates a steady pipeline of new assets – roads, renewable energy, transmission networks, that can be monetized via InvITs. In essence, InvITs are becoming the financial bridge between public infrastructure needs and private capital.

How does the structure work?

At the core of every InvIT is Net Distributable Cash Flow (NDCF).

Cash flow waterfall illustration:

Step	Component	Typical Range (% of EBITDA)
1	EBITDA from assets	100%
2	Less: Interest cost	(25–40%)
3	Less: Principal repayment	(10–20%)
4	NDCF	~30–55%

Regulation requires ≥90% of NDCF to be distributed, which drives distribution yield mentioned earlier.

Implication:

• Higher leverage → higher distributable yield

• Stable assets → tighter yield band (8–10%)

• Riskier assets → wider yield band (10–14%)

InvITs and expectations

Some of the InvITs in India are:

• IndiaGrid Infra Trust (IndiGrid): Invests in power transmission, renewable energy and energy storage;

• National Highways Infra Trust (NHAI InvIT): Backed by NHAI, focusing on road projects;

• Vertis Infra Trust and Cube Highways Trust: Primarily holds road and highway assets;

• Energy Infrastructure Trust: Involved in energy and gas pipeline projects;

• Altius Telecom Infra Trust & NDR InvIT Trust engaged in telecom and warehousing sectors

Infrastructure Investment Trusts (InvITs) are often slotted into ‘alternatives’ for easy reference but they behave like listed yield instruments with embedded leverage. The leverage is, they avail of funding from banks or issuance of bonds, and deploy. The market narrative tends to oversimplify them as stable income products.

The distribution is largely a function of (a) distributable cash flow, (b) extent of leverage (funding availed) and (c) interest rate spreads i.e. difference between cost of funds and earnings from assets. As an example, if cost of funding is 8 percent and asset yield is 12 percent, interest spread is 4 percent. This spread drives equity yield and distribution growth potential.

Interested in exploring listed investment products like InvITs with greater confidence?

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Taxation

Nature of income	Taxation for InvIT	Taxation for unit-holders
Dividend	Exempt	Taxable or exempt, depending on SPV taxation regime. If the SPVs are operating under the old tax regime, it is exempt, otherwise taxable at marginal slab rate.
Interest Income	Exempt	Taxable at marginal slab rate
Capital Repayment	Not an income, hence not taxable	Non-taxable until the cumulative capital repayment exceeds the cost of acquisition, after which it is taxed at marginal slab rates.
Capital gain on sale of InvIT unit	NA	Same as equity / equity mutual funds, taxable at 12.5% after a holding period of 12 months, beyond Rs 1.25 lakh per financial year. Short term capital gains, for a holding period less 12 months, taxable at 20%.

The implication is, you need to track the breakup of distributions, not just total payouts. Not to worry, it is mentioned in the statement accompanying the distributions.

Where InvITs fit in a portfolio

For a perspective on how to look at InvITs, the broad guideline is:

• A fixed-income alternative with relatively higher risk-return but, not an equity substitute;

• A cash-flow generator, not a compounding machine like equity over a long period of time;

• A portfolio diversifier, not a core growth allocation.

As an illustration, you may refer the following:

Asset Class	Expected Return	Volatility	Correlation to Equity
Equity	12–15%	High	1.0
Debt	6–8%	Low	~0.2
InvITs	10–12%	Medium	~0.4–0.6

Inference:

• Higher return than debt

• Lower volatility than equity

• Moderate diversification benefit

InvITs won’t outperform equities in a bull market. These won’t protect fully in a rate shock. But in a portfolio context, they offer something rare: visible cash flows with moderate return certainty. And in markets where most returns are narrative-driven, that kind of predictability is a feature, not a limitation.

Author : Joydeep Sen is a corporate trainer (financial markets) and author

What Are Behavioural Finance Biases? Types and How to Fix Them

The uncomfortable truth about behavioural biases and how to fix them.

Introduction

We have all experienced it at some point. We invested in a stock because everyone around us was investing in it. We were convinced it would be the next big thing, a multi-bagger. Then the stock price kept falling. Instead of selling it and cutting our losses, we held on. We hoped and prayed that it would bounce back. Instead, it kept falling. Frustrated, we finally decided to sell the stock. The stock price started rising a week later.

Here’s the uncomfortable truth about what we have experienced: it’s not lack of intelligence or financial knowledge. It is something far more subtle: our behavioural biases. Our brain is wired to take mental shortcuts that overpower logic and rationality. It is not difficult to understand why it happens. After all, the human brain has evolved for survival. It’s those deep-rooted survival instincts that push us to follow the crowd for safety.

But the good news is we can recognise these behavioural biases and learn to overcome them.

Understanding the origin of behavioural finance

Traditionally, it is assumed that individuals are rational, which means they make decisions purely on logic and self-interest. This is based on the principles of Rational Choice Theory, which states that individuals will always act in self-interest to maximise their own benefit. And collectively, this leads to the overall good of society.

Later on, economists like Amos Tversky, Daniel Kahneman, and Richard Thaler found many limitations of the assumption that individuals are rational. According to them, individuals are highly emotional and can be easily influenced by external factors. So individuals can not always make the best decisions. This led to a new branch within economics known as Behavioural Economics. It explores how psychological factors affect our economic decision-making and lead us to make suboptimal choices.

Behavioural finance is a sub-field of behavioural economics. It studies how psychological factors, such as biases, influence our financial decisions. It challenges the idea that investors always act in their self-interest. Instead, it recognises that individuals are emotional, irrational, and heavily influenced by others.

Breaking down core behavioural biases

One of the key aspects of behavioural finance is the study of behavioural biases. In this section, we will talk about three core biases that quietly influence our financial decisions.

Overconfidence Bias

We almost always fail to gauge our own abilities accurately. This is known as the Dunning-Kruger effect. Two renowned psychologists, David Dunning and Justin Kruger, conducted a study by asking Cornell University students to predict their test scores. When the actual results were declared, they found that those students who ranked in the bottom 25% of their test scores had predicted themselves to be at the top of the class. Conversely, students in the top 25% had predicted their test scores to be lower than their actual score.

In investing, this particular phenomenon is known as overconfidence bias. Traders and investors overestimate their ability by quite a bit. In fact, a recent SEBI statistic stated that 9 out of 10 individual traders (in the F&O segment) lose money. Yet, people continue to trade because they feel like they have a chance at being that 1. It’s our overconfidence bias that gets us to take all sorts of risks. Another common example of this bias is when about 80% of drivers rate themselves as above average, which is mathematically impossible.

Simply knowing about this bias can help us minimise its influence on our decisions. We can actively seek alternative perspectives, analyse worst-case scenarios, and be open to feedback, which is easier said than done.

Loss Aversion Bias

We hate losing. We really, really hate losing money. In fact, behavioural economists have found that the pain of losing money is twice as intense as the happiness of winning it. You see, we are biologically wired to avoid the pain. So, we actively try to prevent our losses, so much so that we do not mind taking extra risk for it. This is known as loss aversion bias.

An example of this bias is when we are offered a choice between a guaranteed win of ₹500 and a 50% chance to win ₹1000; we would always take the ₹500. But if we are offered a choice between a guaranteed loss of ₹500 and a 50% chance to lose ₹1000, we would choose the latter. We can clearly see that by choosing the latter, we may end up losing ₹1000, but we are willing to take the risk. Again, we do this because we cannot stand the idea of losing money.

Another classic example of loss aversion bias at work is when we hold on to a losing stock, hoping it would recover, rather than accepting our mistake and booking the loss. Conversely, we sell the stock whose price has gone up in fear that our profits may disappear. Loss aversion bias also forces many of us to avoid investing in the stock market and keep our savings in the bank, in the process losing purchasing power because of inflation.

Sure, we want to avoid losses. At the same time, we must also realise that losses are inevitable. We can learn a great deal from our losses if we analyse them strategically without being emotional. Focus on the long term, learn to automate investments, spread the risk, and make decisions based on data and research rather than emotions.

Herd Mentality Bias

It’s our primitive survival instinct that tells us to follow the crowd. Because standing alone, while others are running away, can be dangerous- what if there is a predator? We have all seen this on National Geographic. A large herd of wildebeests running away from a chasing lion pride. It’s a visual masterclass. We all appreciate how flocking together works in the wildebeest’s favour. This behaviour is prevalent in humans too; after all, we are social animals.

Wilfred Trotter, a social psychologist, has compared human societies to animal packs. He said he noticed this during World War I, when nations used propaganda to manage mass populations like livestock. In his famous work, Instincts of the Herd in Peace and War, he stated that our mind rarely questions the rules handed down by the group we belong to. Instead, we make up logical reasons to justify what the group wants.

Call it social pressure, fear of missing out, or safety in numbers, herd mentality bias guides much of our behaviour, particularly in the stock market. And the key reason is social media and its role in the information cascade. Influencers, guided by personal profit, deliberately share information that their followers use to make investment decisions. And as more and more followers join in, the cascade effect multiplies.

Okay, so following the herd is a problem. But the psychological pain of going against the herd is very intense too. So how can we avoid the problems of herd mentality bias? Let’s start by remembering what Warren Buffett famously said: “Be fearful when others are greedy and greedy when others are fearful.” This requires that we focus only on the things we can control, treat our mistakes as useful lessons, trust our ability, and stay the course when others are leaving.

Why this matters in India

Let us see exactly how these biases are playing out in India today. In 2025, SEBI surveyed over 50 thousand households across the country to understand how these households engage with the securities market and what influences their financial decisions. This is one of the most comprehensive reports on investor behaviour in India. Some of the key findings from this report directly relate to what we are discussing in this blog.

• 50% of existing investors were classified as having low knowledge of the securities markets, including basic concepts such as inflation. (Overconfidence Bias)

• 53% of affluent investors have high to moderate knowledge, meaning almost 50% are making investment decisions without adequate understanding. (Overconfidence Bias)

• 34% of non-investors consider fear of losing money to be one of their top reasons for not investing in the stock market. (Loss Aversion Bias)

• 80% of Indian households consider capital preservation to be their top priority over growth. (Loss Aversion Bias)

• 71% of existing stock investors and 74 % of existing mutual fund investors identify themselves as low-risk tolerant. (Loss Aversion Bias)

• 62% of investors make their investment decisions based on recommendations from social media influencers. (Herd Mentality Bias)

• 63% of investors in rural areas and 52% in metro cities rely on friends and family to make their investment decisions. (Herd Mentality Bias)

Conclusion

So behavioural biases exist. They are like built-in features of our human brain. They will continue to influence our decision-making process. We can not simply delete them. As discussed, being aware of these biases and understanding why we make the decisions that we make is very important. And that is exactly what this NISM eLearning module “Behavioural Finance: Psychology of Financial Decisions” aims to do.

NISM eLearning Module on Behavioural Finance

The “Behavioural Finance: Psychology of Financial Decisions” Skill Development Module (SDM) offered by NISM, comprehensively covers different aspects of behavioural finance, including:

• The psychology of irrational behaviour and the role of emotions.

• Origins of behavioural finance and Nudge theory.

• A deep dive into various types of behavioural biases.

• Understanding market anomalies and asset bubbles.

• Examining individual and institutional investor patterns.

• Practical strategies to counter bias-driven decisions.

The video-based learning content is around 2 hours long and offered at a fee of just ₹500 plus taxes. When you complete the course, you receive a downloadable and shareable certificate from NISM.

To enrol or learn more, visit the NISM website or contact the eLearning helpdesk.

Authors: Sandeep K Biswal & Jinal Rohit

 

The Death of the “Screenshot Track Record”: How SEBI’s PaRRVA Disrupts Mis-Selling

There is a familiar moment to almost all of us. It usually arrives on WhatsApp. A forwarded image or a Telegram screenshot claiming that a stock recommended has “delivered 312% returns in 9 months” or that an advisor’s “model portfolio” has “beaten the Nifty for three straight years”. The numbers look tempting especially when the geo political situation has eaten away around 10 per cent of your portfolio. There is no way to verify any of it.

If you have ever paused, tempted with your finger hovering over that subscription link, the good news is that the regulatory ground under that screenshot is shifting.

SEBI’s April 29, 2026 circular operationalises the Past Risk and Return Verification Agency (PaRRVA), with Care Ratings Limited as the recognised verification agency, NSE as the data centre, and May 4, 2026 as the date services begin. By August 3, 2026, every Investment Adviser, Research Analyst and algorithmic trading service provider who wants to show past performance must be enrolled. By May 3, 2028, only PaRRVA-verified numbers can be displayed to clients. This arrives alongside the RBI’s parallel reforms — draft directions on advertising, marketing and sales of financial products by regulated entities, aimed at preventing mis-selling through explicit consent requirements, transparency in third-party product distribution, and controls on staff incentives from third parties, set to come into effect from July 1, 2026. Together, they represent the most coherent investor-protection architecture India has ever attempted.

How Mis-Selling Actually Works — and How SEBI PaRRVA Framework Disrupts Each Mechanism

To appreciate what changes on May 4, it helps to understand the specific ways that have flourished in the absence of independent verification. There are four of them, and PaRRVA blunts each.

1. 1- The first is survivorship bias in marketing.

Let’s say a research analyst makes 100 calls in a year. Twenty are spectacular. Thirty are mediocre. Fifty lose money. The marketing material features only the Twenty. Nothing in this is technically a lie — every screenshot is a real call that really happened. Until now, no one had the data, the authority, or the methodology to demand the full ledger. PaRRVA changes this fundamentally. With NSE as the PDC holding the complete record of recommendations, verification is performed against the entire universe of calls, not the curated highlights. The forty winners cannot be shown without the hundred losers in the same frame.

2. 2- The second is the conflation of backtests with live performance.

“Our strategy returned 47% annually since 2021” — except the strategy was designed in 2026 and applied retrospectively to historical data. Backtests can get flattering because they can be constructed with the answer key in hand. A standardised verification framework forces a clear distinction between what a model predicted and what it actually delivered to real subscribers in real time.

3. 3- The third is benchmark shopping.

An advisor may compare a mid-small cap heavy portfolio to the Nifty 50 in years when mid-caps outperformed, and quietly switch to the Nifty Midcap 150 in years when large-caps led. The benchmark moves; the marketing message stays the same: “we beat the market.” A standardised verification methodology — applied uniformly across all enrolled IAs and RAs — discontinues this game. You can no longer pick your scoreboard after the match.

4. 4- The fourth, and arguably the most damaging, is the unverified finfluencer-celebrity ecosystem.

YouTube channels with hundreds of thousands of subscribers casually display return claims that have never seen an auditor. Affiliate links push paid subscriptions for advisory services on the strength of testimonials and screenshots. Once PaRRVA verification becomes the norm, the absence of verified numbers becomes itself a signal — and investors will learn that unverified is the new red flag.

Notice what each of these mechanisms shares: they all exploit the asymmetry of information between seller and buyer. The seller knows the full picture. The buyer sees only what the seller chooses to show. Mis-selling is, fundamentally, a problem of asymmetric information — and verification is the textbook remedy to reduce the problem of adverse selection. Honest advisors, who could not ethically inflate returns, have been quietly losing ground for years to louder operators making claims they could not substantiate. PaRRVA finally lets quality become visible.

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The Governance Safeguard, and the Larger Architecture
One may ask: who verifies the verifier? SEBI’s circular addresses this through the composition of the Oversight Committee. The committee must include representatives of PaRRVA, the PDC, at least two intermediaries, a SEBI-recognised investor association, and an eminent individual with regulatory experience as Chairperson. Crucially, independent members must outnumber the combined representatives of PaRRVA and the PDC. This structurally guards against the verifier-capture problem that has plagued regulated industries everywhere, from credit ratings before 2008 to every audit scandal since.

Place PaRRVA alongside the broader picture. The RBI framework addresses mis-selling at the point of distribution — the branch counter, the relationship-manager call, the loan-bundled insurance policy. PaRRVA addresses mis-selling at the point of decision — when investors evaluate an advice based on its claimed track record. Together, they form a layered defence.

What Investors Should Do Now

After May 4, ask one direct question: Is your past performance PaRRVA-verified? The answer tells you almost everything. After August 3, 2026, treat non-enrolment as a negative signal. After May 3, 2028, treat the display of pre-PaRRVA performance data as a violation.
The most important thing about PaRRVA is not the mechanics. It is the philosophical shift. The burden is shifting to where it belongs: on the people selling financial products to prove that what they are selling is what they say it is. The investor is no longer the last line of defense. The investor is the person being defended.

Authors: Prof. Rachana Baid, Dean – NISM

The Silent Casualty of Market Chaos; How Geopolitical Turbulence Is Eroding Health, Not Just Wealth

Investors in India, and elsewhere, are alarmed at the many global shockwaves that hit them in recent times. Arbitrary US tariffs, US-Israel-Iran war and the consequent disruptions to global trade, shipping, destruction of energy sources, infrastructure, and the demolition of even a semblance of global order. However, the financial media is largely focused on wealth erosion: portfolio losses, FPI outflows, and currency depreciation.  They are almost blind to the parallel casualty: erosion of physical and mental health among investors and savers. Despite it being of global magnitude these days, this harsh reality is almost entirely getting ignored. It is high time finance factor in such real costs to the people, and fine-tune its advice, rather than defaulting to the tired exhortation: stay invested, the sun will shine again.

How Market Volatility Affects Mental and Physical Health

Classical asset pricing theory holds that in frictionless financial markets, households should always allocate a fraction of their wealth to equities, since expected returns substantially exceed the risk-free rate. What the finance theories do not price in is the human body and its functioning.

Stock prices not only reflect investor psychology — they also determine it. Enough has been said about how investor behaviour influences market prices. Far less attention has been paid to the reverse: how market fluctuations shape investor psychology and physical health. There is empirical evidence that price movements directly influence instantaneous well-being — not gradually, not metaphorically, but measurably, on the same day.

Research published in reputed journals, in the last two decades, spanning both  finance and health demonstrates that market volatility directly raises cardiovascular mortality, suicide rates, and psychiatric hospital admissions.  A study titled “Worrying About the Stock Market: Evidence from Hospital Admissions” published in the Journal of Finance (2013) examined patient records for hospitals in California over nearly three decades and found a direct link between market declines and hospital admissions — particularly for anxiety, panic attacks, and major depression. When markets fell nearly 25 percent, hospital admissions spiked by over 5 percent immediately. The researchers’ conclusion was stark: stock market declines today result in psychological distress today. A separate study from Fudan University (2024) demonstrated that a 1 percent decrease in daily stock returns is associated with a 1.77 percent increase in suicide mortality, concluding that stock market volatility is a significant public health issue.

Why Indian Retail Investors Are More Vulnerable

India’s unique demographic structure— a rapidly expanding retail investor base, a large proportion of first-generation investors with low income levels, many without any safety nets or behavioural guardrails, necessitates urgent attention to these issues.  These are not seasoned institutional investors who could manage geopolitical volatility and many other risks well. These are households for whom a 10-15 percent portfolio drawdown is a real existential pain, not an abstraction. It is a visceral psychological emergency. Though no study on the health cost burden is available in the Indian context, it would be reasonable to assume substantial financial costs of medical care and income loss. The true burden, including stress-induced illness that never reaches a hospital, is undoubtedly far larger.

Navigate Market Volatility with Confidence

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The Hidden Paradox of Modern Investing

The financial and investment planning industry, backed by decades of research, advocates that increasing life expectancy requires individuals to take equity exposure. A longer retirement demands higher real returns. Avoiding risk, we tell investors, is itself the biggest risk.

But that same research now confronts us with an uncomfortable finding – that sustained exposure to market volatility, particularly in environments of geo-economic uncertainty and sharp drawdowns, measurably increases cardiovascular mortality, psychiatric hospitalisation, and suicide rates. A stressed investor makes poor decisions. Poor decisions create more stress. The cycle is its own kind of compounding. We are, in effect, prescribing a medicine that treats one condition while aggravating another.

Financial wisdom tells us to take risk — because a long life needs a bigger portfolio. But that same risk may shorten the life it was meant to fund. You might build the wealth. You may not live to spend it.

Wealth Can Recover, But Health May Not

The financial services industry has sophisticated tools for wealth protection: stop-losses, diversification, hedging, rebalancing. We have no equivalent vocabulary for health protection during financial stress. No brokerage firm sends a wellness alert alongside a margin call. No star cricketer reminds investors that their mental health matters as much as their SIPs. No market intermediary addresses the physiological dimension of investor protection.

The investment industry — its advisors, analysts, and media — has collectively treated investor wellbeing as a finance problem— measured in risk and returns, managed through asset allocation, and solved by staying invested. The health dimension has barely entered the room.

The evidence now demands a broader definition of investor wellbeing.Investor education seminars, financial planning frameworks, and advisor training curriculum need to formally incorporate a component on overall health — physical, mental, and emotional. A longer, healthier life is not just a personal aspiration; it is a financial variable. How long you live, how well you live, and what your medical costs look like in your later years will shape your retirement corpus requirements just as directly as your asset allocation decisions. Investors who maintain social support networks, limit their portfolio-checking, operate within pre-committed financial plans rather than reacting to daily movements, and hold genuinely diversified portfolios may show significantly lower stress biomarkers during market downturns.

The ongoing geopolitical situation will eventually resolve, as all crises do. Markets will recover. Portfolios will be rebuilt. But the hypertension quietly developed over months of market anxiety, the sleep disorder that began the night arbitrary tariffs were announced – these do not disappear with market recovery. They will remain and worsen as the invisible ledger of our current times. In the relentless focus on what the market is doing to our wealth, let us not lose sight of what it is doing to our health, our lives.

Author: Prof. Rachana Baid, Dean – NISM | Dr. CKG Nair, Former Director – NISM

What is Bear Market? Lessons from Bear Markets

Bear markets leave marks on charts and on investor behaviour. Over the last three decades the NIFTY 50 has endured multiple deep drawdowns – from the Asian Crisis to the COVID-19 crash – and each episode taught us different lessons. Investors must use these lessons to build more resilient portfolios.

Market cycles are measured from peak to trough, so a stock index officially reaches bear territory when the closing price drops at least 20% from its most recent high (whereas a correction is a drop of 10% – 19.9%). A new bull market begins when the closing price gains 20% from its low. A snapshot of the bear markets in the last 30 years and the movement of the Nifty 50 is given below.

Event	Peak Date	Peak Level	Trough Date	Trough Level	% Decline	Days to Trough	Days to recover to Previous Peak
Asian Crisis	Feb-96	1,260	Oct-98	760	39.68%	996	260
Dot-com Bust	Feb-00	1,818	Sep-01	846	53.47%	588	773
2004 Election Shock	Jan-04	2,014	May-04	1,292	35.85%	124	189
2006 Liquidity Crunch	May-06	3,773	Jun-06	2,595	31.22%	34	138
Global Financial Crisis	Jan-08	6,287	Oct-08	2,524	59.85%	293	739
Eurozone Debt Crisis	Nov-10	6,312	Dec-11	4,544	28.01%	410	731
Commodity Crisis	Mar-15	8,996	Feb-16	6,825	24.13%	344	400
COVID-19 Crash	Jan-20	12,430	Mar-20	7,511	39.57%	63	246
Average					38.97%	357	435

The data shows us that the average decline across episodes is roughly 39%, with extremes near 60%. What we learn from this is that we should build portfolios’ assuming severe drawdowns are possible. Portfolios designed only for small corrections will be forced into bad decisions when markets fall sharply.

The data shows us that the time to trough ranges from 34 days to 996 days. COVID-19 compressed fear into 63 days. What that teaches us is that maintaining liquidity can help us avoid forced selling. While fast crashes punish leverage and illiquidity, slow declines test patience and conviction.

The data shows us that the days to recover to previous peaks vary widely – from 138 days to 773 days. The average recovery in the dataset is about 435 days. The key lesson to investor is that having a long-term horizon is important. Investors who sell in panic will lock in their losses and those who stay invested or add during troughs capture the recovery.

The data shows us that bear markets are triggered by different causes – regional crises, tech bubbles, liquidity squeezes, global financial contagion, commodity shocks, and pandemics. The deepest drawdowns often followed leverage, credit stress, or concentrated exposures. It is important to understand that sector concentration will magnify losses. Diversification across asset classes, with exposure to debt, gold, and alternative assets, will cushion idiosyncratic shocks.

The data shows us that timing the exact bottom is nearly impossible. Systematic Investment plans and rupee-cost averaging are the best strategies in any markets.

The data shows us that despite repeated bear markets, the NIFTY’s long-term trend has been upward. The recovery eventually restores and exceeds prior peaks. Over multi-decade horizons, staying invested and compounding returns outweighs short-term pain. Bear markets are part of the price of long-term equity returns.

Stay Ahead of Every Market Cycle

Markets change, but informed investors make better decisions. Subscribe to the NISM Newsletter 2026 for expert insights, practical investing lessons, market education articles, and the latest updates from NISM.

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The bear markets in the last 30 years have taught us that trying to predict markets is futile. Drawdowns are inevitable, their causes are varied, and their depths and durations unpredictable. Only disciplined planning, liquidity, diversification, and systematic investing, can turn volatility from a threat into an opportunity. Investors who learn these lessons will be better positioned to survive the next bear market and benefit from the recovery that follows.

Author: Shri Shashi Krishnan, Director – NISM