About Target Maturity Debt Funds

This week will see the NFO of a target maturity debt fund, that has also been billed as India’s first debt index fund.  Open-end target maturity debt funds are a product category that merits serious consideration, and one that we should see a lot more of.  However, based on some of the commentary that I have seen in the media (mainstream and social), as well as what I’ve been hearing from advisors and investors, I feel that some of the wider understanding could be enhanced, and expectations tempered. In this post, I want to touch upon a couple of less-talked-about points.

It might be worth mentioning that open-end target maturity debt funds were first launched in India over two decades ago.  Back in the day, they used to be referred to as ‘serial plans’.  Unfortunately, this category (like some others) didn’t quite take off.  Perhaps it was an idea whose time had yet to come.

The first point that I want to bring up is that, conceptually speaking, such a fund doesn’t have to be an index fund or an ETF and even if it is structured as such, it may not be purely passively managed.  From what I have gathered, unlike equity index funds and ETFs, it is quite common for bond index funds and ETFs worldwide to not replicate the complete set of index constituents.  Instead, they follow what is referred to as a ‘sampling’ approach whereby the fund manager seeks to match the more fundamental characteristics of the index such as credit profile, duration, and yield.  To be fair, in India, SEBI has put in guidelines that limit the deviation from index constituents.  But it still leaves room for some degree of active bond selection. 

As a point of contrast, take the original ‘serial plans’. These were typically single-security gilt funds whose maturity coincided with the maturity of the underlying security.  Consequently, despite not being index funds, they were perfectly passively managed.  The same can also be said for any fund that follows a hard-coded list of issuers, and a pre-defined credit and maturity profile.  Thus, a part of me wonders if the index structure currently in vogue, might just be a way to work around the inflexibility of SEBI’s open-end scheme categorization.  Regardless, with the growing interest from investors, advisors, as well as fund houses, it may be worthwhile for SEBI to expand the existing scheme classification to include this category. 

The second point that I want to talk about is the predictability of return in these funds, as represented by the yields that are reported.  No doubt, this is a prominent reason to invest in these funds.  However, investors need to be careful in relying upon the disclosed yield.  For one, there is the question of how the yield might be impacted if there are large flows into or out of the fund.   For another, there is the extent of the gap between the maturity of the fund’s underlying securities and the actual maturity of the fund.  As an example, in the case of one existing fund, I noticed that around 10% of the portfolio is scheduled to mature 7 months or more, before the actual maturity of the fund.  As and when those bonds mature, it is a moot question as to whether the fund will be able to earn the same yield as what it is getting on those bonds today. 

In this context, it might be worth looking at the evidence shared by BlackRock in the US, with respect to its target maturity iBonds ETFs that have matured.  Among other things, it shows the difference between the initial net yield and the final return that investors got.  So far, the difference across all matured funds has ranged from +0.19% pa to -0.30% pa.  In absolute terms, that may or may not seem much but when seen relative to the yields (and the time horizon), that is certainly not a small difference.  For example, one of its ETFs started off in December 2014 with a net yield of 2.64% pa.  When it matured 6 years later, the total return to investors was 2.35% pa.

As a side note, I don’t know what to make of the fact that SEBI doesn’t allow fund houses to offer any indicative yield on FMPs yet it seemingly has no issue with the disclosure of yields on open-end target maturity funds.  All things equal, FMPs offer a more predictable return than these funds.

Observations On Recent Fund Returns

The last ten months or so have been an extraordinary period for those whose fortunes are linked to the stock markets.  It isn’t often that frontline indices fall by close to 40% and then completely recover from there, all within such a short span of time.  If I am not mistaken, it was way back in 1990-91 that we last saw something quite like this. 

But leave aside the rarity of that: there is a fair bit to take away from fund returns over these past ten months.  In this post I’d like to offer a few assorted observations that stood out for me.  Some are high-level observations while some are scheme-specific.

All calculations are for the period 14 January (Nifty 50 TRI: 17,349) to 6 November (Nifty 50 TRI: 17,392).  Unless mentioned otherwise, the calculations pertain to direct plans.  Data sources: Value Research and FundzBazar.

The inconsistencies of Index Funds
As one might expect from the dates that I mentioned, point-to-point, index funds and ETFs tracking the major domestic indices- Nifty 50, Sensex and Nifty 500-  gave little to no returns.  If you look beyond those indices, the returns across other non-sectoral index funds and ETFs are both much better, and much worse.  On the positive extreme, the lone ETF tracking the Nifty 50 Shariah index gained ~19%.  On the negative extreme, the CPSE ETF fell by ~28%, and Bharat 22 ETF fell by ~25%.  Dubious diversification, perhaps?

Luck, skill, or something else?
Over this period, actively managed Large-cap funds gave returns ranging from +8.3% to –10.9%.  However, Value Research and other websites, list one other open-end large-cap scheme that gave a return of –11.4%.  Strictly speaking, this is a Focused fund with a mandate to invest in stocks regardless of their market cap.  Be that as it may, going by this scheme’s month-end portfolios, through these ten months, on an average, 97% of its equity holdings were large-cap stocks.  If you think it is worth including in the list of large-cap funds, then consider this: it is managed by the fund house that also managed the large-cap scheme that gave the highest return.

Differences across Dynamic Asset Allocation Funds (DAAFs)
More than any other category, DAAFs have the freedom to adjust their allocation in a way that preserves value when markets crash, and cashes in on market recoveries and rises.  Leading from that, these funds have been frequently positioned as a sort of panacea.  Thus, these past ten months represent an excellent period to look at what DAAFs can accomplish.  It turns out that, over this period, the returns of these funds ranged from +17.8%  to –12.6%.  So, what explains this vast difference? To some extent it was on account of stock selection which, contrary to the spiel on the importance of asset allocation, isn’t an insignificant variable.  In addition, and quite obviously, it had to do with the differences in when and how much the funds shifted from equity to debt and vice versa.  To be fair, no one can perfectly time the market, so I personally didn’t expect any fund to shift its allocations perfectly.  However, the evidence suggests that some of the funds got that right a lot better than others.  

ICICI Prudential Equity & Debt Fund
Over this period, this scheme gave a return of -8.4% which made it one of the worst performing Aggressive Hybrid funds.  What’s more, its return was worse than that of any of the open-end, actively-managed, diversified pure equity funds from ICICI Prudential.  Its return looks even more disturbing when you dissect its asset allocation.

Going by this scheme’s month-end portfolios, over these ten months, its average allocation to cash and debt instruments was around 30%.  If we assume a return of 10% (that’s what the fund house’s short duration fund has delivered), that would imply that the equity holdings gave a return of –16.3%.  In contrast, the worst performing, open-end, actively managed, diversified pure equity scheme from the fund house, gave a return of -7.8%.  That raises the question: was this hybrid scheme pursuing a divergent and riskier equity strategy than all other pure equity schemes from this fund house?  If so, why?

SBI Dynamic Asset Allocation Fund
This is one of the most unique and well-meaning funds across the industry, and it breaks my heart to say that over these ten months, it utterly failed to live up to its promise.  For those who don’t know, its equity allocation seeks to mirror the Nifty 50/ Sensex while the debt allocation is exclusively held in the 10 year g-sec. As I stated earlier, point-to-point, over these ten months, the Nifty 50 and the Sensex delivered little or no return.  Thus, the contributors to this scheme’s return had to be the return from the cash and debt component (SBI MF’s 10 year g-sec ETF gained 8.8%), and whatever gains it could make by switching from equity to debt when the market peaked (and as it rose again), and from switching from debt to equity around the bottom of the market.  Unfortunately, all of this came to nought.  For reasons that only the fund house can really explain, this scheme’s return was –0.2%, which is just a tiny bit better than that of the Nifty 50 index fund managed by the fund house: –0.6%.  The only explanation that I can think of is that the algorithm used by the fund house, did a terrible job of deciding the switches between equity and debt.  Talk of good intentions going bad.

Correction: An earlier version incorrectly stated that the 10 year g-sec gained 10.8%. Actually, it was SBI MF’s 10 year Constant Maturity g-sec fund that gained 10.8%.  SBI MF’s 10 year g-sec ETF gained 8.8% over the period.