Debt Funds’ Peaceful NAV Lie: Valuation Games That Cost Retail

Anil Vohra, a retired public-sector bank employee in Bhilai, chose a debt fund because he is a careful man. Equity swings; debt is steady — look at the NAV, a calm little staircase going up. What Anil cannot see is that some steps of that staircase are painted on. The bonds inside barely trade; their daily prices are, to a meaningful degree, estimates. And wherever there is estimation, there is room for optimism — especially when the optimist’s fees depend on the answer.

The machinery: model-priced serenity

A stock’s price is a fact, printed by an exchange every few seconds. A thinly-traded corporate bond’s price is a valuation-model output, because most corporate bonds in an Indian debt fund’s portfolio simply do not trade on most days. When a borrower starts wobbling, the honest move is marking the bond down immediately. The tempting move is holding it at 96 when the market would pay 85 — the NAV stays smooth, redemptions stay calm, and the problem is deferred. Retail investors, who choose debt funds precisely because they read NAV stability as safety, are the last to know the serenity was manufactured.

The rulebook behind the smoothness: mark-to-model versus mark-to-market

This is not a rumour about fund-house behaviour — it is a documented feature of how Indian debt funds are required to price their holdings. SEBI’s valuation framework for money market and debt securities lays out, in its own words, two different pricing regimes depending on how close a security is to maturity and how it is traded. Securities with a short residual maturity are permitted to be valued on an amortisation basis — the price is calculated by smoothly accruing the difference between the purchase price and the redemption value over the remaining days to maturity, regardless of what a buyer would actually pay for that bond today. Securities further from maturity, or wherever an active market price exists, are meant to be valued using prices from SEBI-empanelled valuation agencies, benchmarked as closely as possible to where the security would actually trade — a mark closer to mark-to-market, though still a model output rather than a live trade.

SEBI has tightened this over time precisely because amortisation-based smoothing was being used past its sensible shelf life: the residual-maturity window within which a security could be valued on the gentler amortisation basis was cut down from a longer window to 30 days, specifically to stop funds from carrying medium-term bonds at a smooth, accrual-based price when a real market price was available and would have shown a very different number. The rule change itself is an admission: the amortisation method, in isolation, was producing NAVs that understated risk.

The Franklin lesson: ₹30,000 crore of "safe"

In April 2020, Franklin Templeton froze six debt schemes overnight — about ₹30,000 crore of investor money, much of it sold as short-duration, liquid-ish parking for conservative savers. The funds had reached for extra yield through low-rated, hard-to-sell paper; when redemptions came, the “liquid” portfolio turned out to be a queue. Unitholders eventually recovered most of it, over years — but the lesson stands: in debt funds, the NAV tells you yesterday’s model estimate, not tomorrow’s exit price.

The asymmetry nobody prices

Here is the trade in plain numbers. A “high-yield” debt fund offering 8.5% against a 7% alternative earns Anil, on ₹10 lakh over three years, about ₹52,000 extra. One valuation write-down affecting 30% of the portfolio costs him ₹3,00,000. He is picking up coins in front of a steamroller, and the coins are taxed at his slab.

The timing games

Watch the sequence in past credit events: large institutional investors exit quietly; the write-down lands after; retail absorbs the marked-down NAV. Add month-end window dressing — risky paper swapped out just before portfolio disclosure dates — and the picture a retail investor sees is curated twice: once by the valuation model, once by the calendar.

Run your own numbers, right here

How to protect yourself

Decide what your debt allocation is for. If the answer is safety, buy the boring end — overnight, liquid, gilt funds, or plain FDs — where there is nothing to model and nothing to hide. Skip the middle: credit-risk and “high-yield” categories pay a taxi fare to take a truck’s risk. Check the portfolio, not the past return: anything unrated, unlisted, or concentrated in one promoter group is a warning. Look specifically for how much of the portfolio is valued on an amortisation basis versus a valuation-agency mark — a fund heavy in the former can look artificially smoother than its actual risk. And distrust any debt NAV that looks unnaturally smooth in a stressed market — calm is cheap to paint when the pricing rulebook allows it.

What this does not mean

This does not mean debt funds are secretly frauds, or that SEBI’s valuation framework is designed to mislead investors — the opposite is closer to true: the rules exist precisely because regulators recognised the risk and have progressively tightened the amortisation window to reduce it. It also does not mean every debt fund NAV is unreliable — gilt and overnight funds hold instruments with genuine daily market prices, and the valuation-model risk described here concentrates almost entirely in credit-risk and medium-duration categories holding thinly-traded corporate paper. What it means is narrower: “debt fund” is not one product with one risk profile, and a NAV chart that looks calm can be calm because nothing is wrong, or calm because a permitted pricing method has not yet caught up with something that is. Anil is a composite drawn from common patterns among conservative retired investors; the specific figures above are illustrative arithmetic, not one person’s real portfolio.

Frequently asked questions

Are all debt funds risky then?

No. Gilt and overnight funds hold government paper with transparent, actively traded prices — the games described here live mostly in credit-risk, medium-duration and “dynamic” categories, where estimation has more room to breathe.

How is an FD different from a debt fund?

An FD’s return is a contract; a debt fund’s is an outcome built partly from a valuation model. The fund can beat the FD — but the FD cannot be marked down by a valuation agency overnight. Run both through the calculator above and price the certainty gap yourself.

How would I actually check which valuation method my fund is using?

The scheme’s factsheet and SEBI-mandated portfolio disclosure list each holding’s residual maturity and rating; a short residual maturity on a large chunk of the portfolio suggests amortisation-based pricing, while longer-dated or lower-rated paper should be carrying a valuation-agency mark. If a fund’s disclosure does not make this easy to tell, that itself is worth noticing.

Regulatory source: SEBI‘s valuation framework for money market and debt securities sets out the amortisation-basis and valuation-agency pricing methods described here, including the tightening of the amortisation residual-maturity window. The framing of “mark-to-model versus mark-to-market” as the mechanism behind NAV smoothness, the arithmetic, and the character of Anil are this article’s own analysis.

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Disclaimer: This article is for general information only and is not financial or tax advice. “Anil Vohra” is a composite character based on common patterns among conservative retired investors, not a real person. Valuation rules and fund portfolios change — check a fund’s current factsheet and disclosure before investing, and consult a qualified advisor before making investment decisions.