Beware of “Consistent Performance”

We frequently hear fund houses, advisors, even the media talk about certain mutual fund schemes as having given “consistent returns” or having shown “consistent performance”.   In its rankings of schemes, CRISIL has a category called “Consistent Performers”.  But what exactly does being “consistent” mean?  Can scheme returns or performance really be described as “consistent”?

I have come to believe that most people who use the word “consistent” in the context of a mutual fund scheme’s returns or performance, actually misuse the word.  What makes matters worse is that this is a word that is easy to misunderstand.  Thus, through a combination of misuse and misunderstanding, many of those who promote schemes with such a claim are able to convey an impression of good performance even when none exists. 

Till some years ago, I used to ascribe most such claims to ignorance.  But the dubious and widespread nature of these claims has now made me suspicious of any scheme whose returns or performance is dubbed as “consistent”.  An industry insider whom I know, is fond of saying that “it is the best word to use when you don’t have good performance to show.”  In this post, I make the case to be wary of any claims of “consistent” performance or returns, and to not accept such claims at face value.

For returns or performance to be called “consistent” these have to be, to quote the Merriam-Webster’s dictionary, “marked by harmony, regularity, or steady continuity :  free from variation or contradiction” (emphasis mine).  Thus, to make a claim of “consistent returns,” the returns should be identical, day after day or month after month or year after year etc.  Is there any mutual fund scheme that can make such a claim?

Performance is different from returns, and the term “consistent performance” gives a lot more latitude.  But even so, in itself, it is a vague description.  For one, it needs to be clarified as to how performance is measured (e.g. returns relative to a benchmark index, quartile ranking etc.)  For another, it needs to be clarified as to how consistency is measured (e.g. it could be day after day, or month after month, or year after year etc.)  The total period over which consistency is measured also needs to be clarified i.e. over how many days/ months/ years. Simply describing a scheme as being a “consistent performer,” therefore, is misleading.

But if all of this is sounding too theoretical, let me offer you a couple of real-life instances of misleading communication that I recently observed.

The first instance relates to one of the largest fund houses by AUM.  In a recent marketing communication, they implied that one of their debt schemes had given better returns than any PSU bank deposit over any 3 year period over the scheme’s 14 year existence.  They highlighted it as “consistent outperformance”.  Prima facie it met the requirement of being adequately clarified, and free from contradiction.  But there was one other problem: the claim appeared too good to be true.

Not surprisingly, when I looked closely, I realized that the data they were using to make the claim, represented just 6 years of the 14 years that the scheme had been in existence.  And when this was subtly pointed out to them, they opted to unabashedly continue with the assertion but without mentioning that the scheme had been around for 14 years.

The second instance relates to an exchange that I had earlier this week with a certain mutual fund salesperson.  He was trying to convince me of the merits of investing in one of the equity funds managed by his fund house.  As readers of this blog would know, I select schemes based on qualitative factors rather than performance.  Regardless, this gentleman was keen to draw my attention to the actual returns of the scheme.  The thrust of his pitch was that if I looked closely enough, I would see that this scheme had delivered “consistent performance” over the years.  As I mentioned earlier, any such claim sets alarm bells ringing for me.  And when someone emphatically pushes such a claim in my direction, as this person was attempting to do, I tend to react strongly.  Luckily for this person, I was in a good mood that day.

So when he made his remarks about “consistent performance,” I responded by saying, “Forgive my ignorance but how do you measure performance?”

He replied, “It has consistently beaten its benchmark index.”

“So you’re saying that it has beaten the index year after year, right?”

“Over the last 1 year, 3 years and 5 years.” 

Any claim of consistency based on trailing returns can be safely assumed to be a deception.  On any other day, I would have halted this person in his tracks and compelled him to consider that either he didn’t know the definition of “consistent” or else he was lying.  For good measure, I might have even pulled out a dictionary and read out the definition aloud.  But that day, as I said earlier, I was in a good mood.  I took a few minutes to check something on my laptop, before replying. 

“Well, it seems that this scheme gave less returns than the index in 4 of the last 7 calendar years.”

He appeared adamant.  “But it has beaten the benchmark over the last 1 year, 3 years and 5 years.”

“So it has.  But that’s because of end-point bias,” I said politely. 

He did not seem to be aware of that term.  Worse, he chose to hide his ignorance by holding his ground.

“That may be, but the performance is still consistent.”

This is where I lost it.

“If it has given better returns than that index in only 3 of the last 7 calendar years, then how the f**k can you call it ‘consistent’?”

The forcefulness of my response put him on the defensive, and he chose to retreat.

“I’ll need to check and get back to you.”

I don’t expect to hear from him anytime soon.

How important is a fund’s return?

There are some who may dismiss this as a pointless question with an obvious answer.  But if you are willing to read this with an open mind, it might just be worth your while.  Some of the thoughts presented here have been shared in the past, across different posts.  In this post, I’m attempting to connect these together to suggest an answer to the question in the title.

Do past returns really matter?

Most of us, when deciding on a scheme to invest into, look at its past returns.  Whether we admit it or not, most of us believe that a scheme’s past returns (relative to its peers) are a reliable indicator of its future relative returns. In other words, we believe that if Fund A has given a better return than Fund B in the past, it is likely to give a better return in the future as well.

Frankly, I have not seen any data that would compellingly support such a view.  On the contrary, based on the data that I have examined, I question such a belief.  As evidence, I’ve given below some observations from a study that I recently updated.  In this, I looked at the relative returns of domestic, diversified equity schemes over four market phases, listed below.

• 8 January, 2008 to 9 March, 2009 (Falling)
• 9 March, 2009 to 5 November, 2010 (Rising)
• 5 November, 2010 to 20 December, 2011 (Falling)

• 20 December, 2011 to 29 January, 2015 (Rising)

The study covered 141 schemes that had been around across all these four phases.  Based on their return in each phase, I grouped these schemes into quartiles.  These are a few of my findings:

• 33 of the 35 schemes in the top quartile in 2008-09 were not in the top quartile in 2009-10.  Of these, 26 dropped to the third or fourth quartile.
• 29 of the 35 schemes in the top quartile in 2009-10 were not in the top quartile in 2010-11.  Of these, 19 dropped to the third or fourth quartile.
• 30 of the 35 schemes in the top quartile in 2010-11 were not in the top quartile in 2011-15.  Of these, 19 dropped to the third or fourth quartile.
• Not a single scheme managed to be in the top quartile across all four phases.  Only 7 schemes consistently ended up in one of the top two quartiles in each of the four phases.

To me, what emerges from this is that the past ranking of a scheme is not a reliable indicator of what its future ranking will be.  In case you’d like to take a look at the data supporting these findings, please send me an email. 

Do future returns matter?

Once we invest in a scheme, it should be correct to believe that the scheme’s returns will impact our returns, right?  Well, yes and no.  If we make a single investment, then yes.  If we make multiple investments, then maybe not.  Let me illustrate.

Let’s say that 10 years ago, someone decided to start SIPs of an equal amount in the growth options of these schemes:

• Reliance Regular Savings Fund-Equity Option (RRSF)
• SBI Magnum Midcap Fund (SBIMMF)

Over these 10 years, RRSF ended up giving a higher return than SBIMMF.  However, the investor would made more money in SBIMMF than in RRSF.  The table below shows the difference.

Period: 1 May 2006 to 30 Apr 2016	Scheme Return (p.a.)	Investor Return (p.a.)
RRSF	13.8%	13.4%
SBIMMF	11.3%	18.0%

Scheme returns and investor returns have been calculated using the tools at Advisorkhoj and assume a monthly SIP on the first business day of each month.  Loads are not considered. 

Let me try and give these numbers a bit more context.  The growth in the NAV of RRSF over this period was 36% more than the growth in the NAV of SBIMMF.  Yet, the gain to the investor from investing in SBIMMF was 57% more than the gain from investing in RRSF.  I look at this as proof that investing in a scheme that gives better returns, in no way, guarantees that we will get better returns.  Indeed, the returns to us can be far less than what we may imagine.

The role of returns in building wealth

I remember a thought shared by a stock broker in my early days in the business.  I paraphrase: “You may earn a 100% in a year but if all you invested is Rs.100, all you will have at the end of the year is Rs.200.  By no stretch of imagination will you be wealthy just by seeking high returns.”

I have regarded that as a useful comment on how wealth is built.  To refine it a bit, the wealth that we build is most influenced by the amount that we save and invest, and the timeliness of our investments (i.e. our ability to invest regularly, without delay).  We can, and must supplement these with good investment choices.  However, we need to realize that there are practical limits to the rate of return that we can earn from our investments on a sustained basis.  And if the points made earlier are anything to go by, we have limited control over the return that we will end up getting.

Putting all of this together, I would like to suggest that a scheme’s returns are not as consequential as most of us might believe.  But I’ll let you be the final judge of that.  And along with what I have, so far, shared in this post, I’d like to offer you a parting thought that puts a whole different spin on the question in the title.

Most good things in life come at a price.  Generally speaking, the more important something is to us, the higher is the price that we are willing to pay.  Conversely, the higher the price that we are willing to pay for something, the more important it can be considered to be to us.  Thus, the importance of a scheme’s returns to us can well be judged by the price we would be willing to pay or, more accurately, the compromises that we are willing (or not willing) to make.  Let me explain with a personal example.

I have taken a stance to not invest my money with HDFC mutual fund.  To be clear, I have great respect for their Chief Investment Officer as an equity fund manager.  I have no reason to doubt his ability to generate better returns than most of his peers.  On the flip side, I have regarded their disclosures around expense ratios as inconsistent and opaque.  Nonetheless, a few years ago, I went ahead and invested a small portion of my portfolio with them.  I was clear that I was making a compromise.  But then, a series of service issues started popping up which left an extremely bitter taste in my mouth.  To put it bluntly, I felt like I was being yanked around.  After a bit of deliberation, I came to the conclusion that this fund house did not deserve my business, and pulled out my investments.  In other words, this time around, I refused to compromise.

Yes, I am a small investor, and my stance may not affect them.  Some of my well-wishers have argued that I have had more to lose than them by depriving myself of good returns.  Fact is, that doesn’t bother me.  For my part, I am clear on where I draw the line on making a compromise, and my actions reflect that.  And that’s really the question we have to ask ourselves.  Would you be willing to chase the promise of ‘good returns’ at any cost?  Or would you want to draw the line somewhere?  And, if so, where would you draw it?

From High to Low

As readers of this blog may be aware, I am a sucker for statistics.  I frequently go digging into historical data.  But it isn’t something that I do for entertainment.  Every now and then, looking into data, I find something that sharpens or enhances my understanding of the nature of risk.  It is with the intention of sharing some of that, that I present below the results of my latest effort, which looks at the returns of some equity schemes over a 16 year period.  In such studies, it is often the case that some schemes end up with far more impressive returns than others- that is but to be expected.  While there may be a case to raise eyebrows and ask questions, I wouldn’t suggest passing judgment on any scheme without further investigation.  As I have maintained in the past, there is more to performance than what returns may convey. As I have also previously mentioned, one should be careful about drawing any inferences from such observations other than on the merits of diversification. 

Almost a month ago, on Feb 11, the BSE Sensex hit a new low, relative to its last high.  It may well fall further but at the time of writing, that has not (yet) happened.  Its closing value on Feb 11, was over 22% below the last closing high on 29 Jan 2015.  As far as I can make out, this was the 11th time since its inception that the Sensex has fallen 20% or more from a previous high.  The first time this happened, it fell just over 20% before rebounding.  On the subsequent nine occasions, the fall to the bottom has ranged from 27% to 61%.  On five of these occasions, the fall was in excess of 40%.

Feb 11 also happened to be the anniversary of an earlier high.  In 2000, the Sensex peaked on this date.  The identical date brought back the memory of something that I had heard many years ago, from a certain advisor.  He had said something to the effect that the acid test of the long-term performance of an equity scheme was the return that it generated from a market peak to a market bottom.  In that light, I thought it might be interesting (even if premature) to check out the returns of equity schemes over these 16 years.  I am aware of the vagueness of the term, “long-term” and the mixed feelings that people have about its use.  But I doubt if anyone would question the validity of a period of 16 years being “long-term.”  Using data from Value Research, ICRA Online and Moneycontrol, I give below some of my observations.  Do note that the scheme returns do not consider loads.

• Currently, there appear to be 49 actively managed, diversified, domestic equity schemes that were in existence in Feb 2000. 
• The return on these schemes over these 16 years ranged from 18.7% pa to 5.2% pa.
• The CAGR of the BSE Sensex Total Return Index (TRI) over this period was 10.6% pa.
• The return on 14 of these schemes was less than the CAGR of the BSE Sensex TRI. At least 4 of these were once positioned as flagship schemes, so to say, of their respective fund houses. 
• Amongst schemes that are currently rated with 5-stars by Value Research, the lowest return was 9.7% pa.
• Amongst schemes that are currently rated with 1-star by Value Research, the highest return was 18.5% pa.
• The preceding 13 months (i.e. preceding Feb 11 2000) was a period of extraordinary returns for equity schemes.  One scheme, it appears, had delivered a higher absolute return over the preceding 13 months than it did over this entire 16 year period. Its absolute return over the preceding 13 months was 326% while over the entire 16 year period, it was 297%.
• At least 4 other schemes delivered an absolute return over the preceding 13 months that was over 50% of what they did over this entire 16 year period.
• At the time, there was only one index scheme, which continues to be in existence.  This scheme tracks the NSE-50.  As against a CAGR of 10.6% pa for the NSE-50 TRI, the return on this scheme was 8.3% pa.

Fund Volatility and SIP Returns

A few readers of my previous post have said that I was wrong in suggesting that all funds are equally suitable for a SIP.  According to them, if an investor who is proposing to start a SIP, had to choose between two funds, he/she would be better off choosing the fund that is likely to be more volatile (i.e. the fund that is likely to see greater fluctuations in its NAV). 

This is not the first time that I have heard this argument.  Over the years, I have heard many advisors voice a similar view.  Unfortunately, this is a flawed perspective that is, paradoxically, the result of intelligent thinking.  In this post, I propose to clear the air on this.  But since this may not be easy to explain or even follow, let me first cut to the chase, and state my position:

a.       There is no conclusive or compelling evidence that supports this argument.

b.      Pursuing such a strategy can potentially have disastrous consequences if one is forced to redeem one’s investment in a bear phase.

If you’d like some elaboration on this, do read on.

Let me start by questioning the mathematical validity of the volatility argument, if I may call it that.  Imagine, if you can, two equity funds that, over a certain period, start with an identical NAV, and end with an identical NAV.  Let’s further assume that, over this period, these funds have an identical average NAV.  This may be a hypothetical scenario but it is one that immensely favors the volatility argument.  If the argument truly has merit, then in such a scenario, an investor opting for a SIP in both funds, should always gain more in the more volatile of the two funds.  Yet the fact is that even in such a favorable scenario, there is no certainty that that will happen.

For those who prefer empirical evidence, I’d like to present some data on three of the oldest equity schemes in the country.  The table below gives the data for the period from April 2012 through March 2015.  All the data has been taken from the fund factsheets.

Apr 2012 - Mar 2015	Fund A	Fund B	Fund C
Standard Deviation*	14.2	16.5	15.8
Fund Return (p.a.)	18.6%	17.1%	34.9%
SIP Return (p.a.)	24.9%	25.2%	35.2%

*Standard Deviation (SD) is a measure of volatility. The higher the SD, the more volatile a fund.

Over this period, Fund B was more volatile than Fund A, and despite its lower return, an investor opting for a SIP would have gained more in this fund than in Fund A.  One may say that this data supports the volatility argument.  However, when we compare Fund B with Fund C, the picture appears to be somewhat different.  Fund B was also more volatile than Fund C but an investor opting for a SIP would have gained less in this fund than in Fund C.  One may think that this was because of the much higher return of Fund C over the period.  But before drawing any conclusions, let’s look at the data for the preceding 3 year period.

Apr 2009 - Mar 2012	Fund A	Fund B	Fund C
Standard Deviation	22.5	27.9	28.3
Fund Return (p.a.)	27.9%	26.7%	34.6%
SIP Return (p.a.)	8.8%	4.5%	9.3%

 

This period was marked by a significantly higher level of volatility across all funds.  Yet when you look at Funds A & B, despite a much higher return over this period (compared to Apr 2012 – Mar 2015), an investor who opted for a SIP in these funds over this period would have gained much less than a similar investor in these funds over the subsequent 3 year period.  Fund C had almost the same return across both periods but here, too, an investor who opted for a SIP over this period would have gained much less than a similar investor in this fund over the subsequent 3 year period.  Clearly, the volatility argument does not hold good.

You may also note that during this period, Fund C was more volatile than Fund B.  However, in the subsequent period, Fund B was more volatile than Fund C.  Thus, even if volatility were to matter, to whatever extent, historical volatility of a fund (absolute or relative) can be no indicator of future volatility.  Just to be clear, the investment objectives of these funds did not change over these years.  In fact, these are among the most consistently well-managed funds in the industry.

Let me now flip back another three years to a period that highlights some of the risks of investing in highly volatile funds.

Apr 2006 - Mar 2009	Fund A	Fund B	Fund C
Standard Deviation	28.4	31.5	33.2
Fund Return (% p.a.)	-3.1%	-2.7%	-17.5%
SIP Return (% p.a.)	-13.9%	-13.7%	-30.2%

To put these numbers into context, the value of a SIP over this period in Fund A or Fund B would have been almost 20% below the amount invested, by the end of the period.  The value of a similar SIP in Fund C would have been almost 40% below the amount invested.  So much for the volatility argument.

SIP Returns

A number of investment portals offer tools that enable one to calculate the so-called ‘SIP returns’ of mutual fund schemes.  Most fund houses also offer similar calculators for their schemes.  Some offer these calculations in their monthly fact sheets.  But does looking at the SIP return of a fund serve any purpose?  In this post, I will attempt to show that SIP returns are of little use, and that one is better off not using these returns to draw any conclusions.  To keep things simple, I will restrict my thoughts to SIP returns of equity funds.

The SIP return of a fund is not a representation of its performance. It only tells us the return that an investor would have got if he/she had opted for an SIP in that fund, over a particular period.  The SIP return from investing in a fund can be, and indeed often is, very different from the fund’s actual return over the same period.  As an illustration of this, I have given below some data of two of the oldest diversified equity funds in India. (PS: All the SIP calculations in this post assume equal monthly investments made on the first business day of each month from the starting month till the penultimate month.  Loads are not considered in any of the calculations.)

	Fund A	Fund B
NAV- 01 July 2004	70.67	47.73
NAV- 02 July 2007	228.91	142.70
Absolute Fund Return	223.9%	199.0%
Absolute SIP Return	65.4%	75.9%
Fund Return (p.a.)	47.9%	44.0%
SIP Return (p.a.)	35.5%	40.3%

Over the 3 year period mentioned above, investors in both funds who opted for a SIP saw a lesser return than those who put a similar amount at one go, at the start.  You may also notice that while Fund A gave a higher return than Fund B, investors who opted for a SIP in that fund saw a lesser return than those who opted for a SIP in Fund B.

If we now look at the 3 year period that immediately followed, a pretty different picture emerges.

	Fund A	Fund B
NAV- 02 July 2007	228.91	142.70
NAV- 01 July 2010	263.45	195.03
Absolute Fund Return	15.1%	36.7%
Absolute SIP Return	41.7%	35.1%
Fund Return (p.a.)	4.8%	11.0%
SIP Return (p.a.)	24.0%	20.6%

Investors in Fund A who opted for a SIP over this period, saw a better return than those who put a similar amount at one go, at the start.  Investors who opted for a SIP in Fund B saw a lesser return, in absolute terms, than those who made a lump sum investment, at the start.  However, if you consider the time value of money, as reflected in the annualized returns, the SIP investors benefitted more.  In contrast to the previous 3 years, over this period, Fund B gave a higher return than Fund A, but investors who opted for a SIP in that fund saw a lesser return than those who opted for a SIP in Fund A. 

In the examples above, both the fund returns and the SIP returns were positive.  Yet, it is possible for one or both of these to be negative.  The data below, of another diversified equity fund, illustrates the possibility of a fund’s return being negative, and SIP return being positive.

NAV- 01 Jan 2008	40.71
NAV- 01 Jan 2013	33.49
Absolute Fund Return	-17.7%
Absolute SIP Return	24.9%
Fund Return (p.a.)	-3.8%
SIP Return (p.a.)	8.8%

There is also the possibility of a fund’s return being positive, and SIP return being negative, as the data below, of yet another diversified equity fund, shows.

NAV- 01 Dec 2003	29.86
NAV- 02 Mar 2009	51.98
Absolute Fund Return	74.1%
Absolute SIP Return	-2.3%
Fund Return (p.a.)	11.1%
SIP Return (p.a.)	-0.9%

So, what explains these numbers?

While a fund’s return does influence the SIP return, the extent of that influence depends on the pattern of NAV movements over the period.  Odd as it may sound, some patterns cause the SIP return to exceed the fund’s return, while others bring down the SIP return to below the fund’s return.  But knowing the effect that a particular pattern has, doesn’t really help because neither can a fund manager control the pattern of NAV movements for a fund, nor is it possible to predict the future pattern for any fund.

In this backdrop, consider this: even if we believe that a more competent fund manager is likely to generate better fund returns than a less competent one, the pattern of NAV movements may make it possible for a SIP in a poorly performing fund to give a better return than a SIP in a well performing fund.  The only thing resembling any kind of certainty is that the longer we carry on a SIP, the more likely it is for the SIP return to mirror the fund’s return. 

Yet, every now and then I come across supposed advisors who wax eloquent about how some funds are “more suitable for a SIP.” At the start of each year, and occasionally in-between, I also see recommendations pop up for “the best funds for SIPs.”  To anyone who understands the maths of SIP returns, these are flawed notions which consciously or not, capitalize on the misconceptions of investors.  But all of these pale in comparison to a remark that was brought to my attention, that The Economic Times attributed to the CEO of a fund house: “our CIO-equity runs… …the number 1 fund in the country in 10-year SIP (systematic investment plan) returns.”  The statement may be factually correct, but to me, the mention of SIP returns in that sentence is nothing short of deception.

As I see it, SIP returns serve little purpose and are best ignored.

Remembering the Tech Boom

This month, fifteen years ago, signalled the end of the bull run that has come to be referred to as the dot-com boom or the tech boom by some, and the dot-com bubble or the tech bubble by others.  As the monikers suggest, it was a period that was marked by the steep and questionable rise in the share prices of technology companies.  As I see it, what happened during that phase, and what followed afterwards, has a lot to offer current investors in equity schemes to think about.  In this post, I propose to take a walk down memory lane, and share some observations.

A number of people trace the start of this boom to December 1996.  But it was two years later that the boom truly gained momentum.  And though the biggest gains were seen by investors in the shares of ICE companies (information technology, communications, and entertainment), investors in equity schemes also saw significant gains, on account of the investments made by their schemes in these companies.  Consider this: over the fifteen month period from 1 Dec 1998 till 1 March 2000, 25 equity schemes and 2 balanced schemes saw their NAVs at least triple, while another 9 equity schemes and 4 balanced schemes saw their NAVs double.  There were 8 equity schemes whose NAVs went up 5 times or more, during this period.  Leading the pack was Kothari Pioneer Infotech Fund (now, Franklin Infotech Fund), whose NAV (adjusted for bonus units) astoundingly went up over 10 times during the same period.

An industry observer with whom I was speaking recently, had this to say about the gains during that period:  “Never before, or since then, has there been such an opportunity for the masses to legitimately make so much money, in so short a time.”

While the opportunity may have been there, the fact is that when the boom took off, very few people actually had investments in any of these schemes. Most investments in these schemes happened much after their NAVs had surged.  While this may be somewhat true of any bull market, in the case of the tech boom, this was partly because the sharpness and suddenness of the rise caught most investors by surprise, and partly because of a general lack of trust in mutual funds.

To go back a bit in time, the bear market from 1994 to 1998, on account of its prolonged tenure, had tested the patience of most investors,  particularly those in mutual fund schemes.  Funds such as UTI’s Mastergain 1992 (now, UTI Equity Fund) and Morgan Stanley Growth Fund (now, HDFC Large Cap Fund) had attracted large numbers of investors, but their investment performances had left a lot to be desired. Then there was the news of CRB Mutual Fund being wound up under charges of fraud.  Lastly, and probably, most significantly, UTI’s reputation took a major dent when it announced that the reserves on its flagship scheme, US 64, were wiped out and there loomed the possibility that it might not be able to meet commitments to unitholders in the scheme. 

It was not surprising, therefore, that most investors were naysayers or skeptics when it came to mutual fund schemes.  There were very few investors for whom the conceptual merit of investing in mutual funds remained intact in spite of all of these episodes.  When the tech boom took off (quite out of the blue, within months of UTI’s announcement), it was these few investors who gained the most.  In contrast, the naysayers and skeptics were left out for most of the rally.  By the time they shed their reservations to enter these schemes, the markets were into the last few months of the boom.  Given how late they entered the boom, the vigor with which these investors pumped in money, was truly astonishing .  To give some perspective, the gross investments into equity schemes in the quarter Jan-March 2000 were more than the total gross investments made into these schemes across the previous 11 quarters.  The net investments into equity schemes in that quarter were over 13 times the total net investments across the previous 4 quarters.  Obviously, these investors had no inkling of the brutal downslide that was to follow.

Over the nineteen months that followed the bursting of the tech bubble, most equity schemes saw their NAVs fall by over 60%, with some seeing a fall of over 80%.  As would be expected, investors who put most of their money around the peak were the worst affected.  Those who preferred tech funds (or funds with an overdose of tech stocks) were much more affected than those who preferred diversified equity schemes.  The differences were all the more starker for those investors who chose to hold to their investments for longer.  For instance, if an investment in a diversified equity scheme made at the peak of the tech boom were to have been held till today, the return on such an investment (without adjusting for loads) could range from 22% p.a. to 7% p.a. (most diversified equity schemes have given a return in excess of 15% p.a. over this period, which is the equivalent of growing one’s money by over 8 times). On the other hand, if an investment in a tech fund made at the peak of the tech boom were to have been held till today, the return on such an investment (without adjusting for loads) could range from 5% p.a. to 6% p.a. That would be equivalent to just over doubling one’s money.

But what about those people who were already invested by the time the boom gained momentum?  Returns in equity schemes over the 34 months from 1 December 1998 to 1 October 2001 ranged from 51% p.a. to –24% p.a. (without adjusting for loads).  Most equity schemes had gained enough on the upside to weather the downside and generate positive returns, with 10 schemes clocking returns in excess of 20% p.a.(without adjusting for loads).  Returns in Franklin Infotech Fund (the lone tech fund over this period) were close to 18% p.a.(without adjusting for loads).  If investments in any of the diversified equity schemes were to have been held till today, the returns would vary from 32% p.a. to 11% p.a. (without adjusting for loads) with as many as 28 schemes showing returns in excess of 20% p.a. (this would be equivalent to growing one’s money by over 19 times).  If an investment made in Franklin Infotech Fund were to have been held till today, the returns would be close to 22% p.a.(without adjusting for loads).  That would be equivalent to growing one’s money by over 24 times.

Would investing through a SIP have helped?  Obviously, those investors who invested large sums at the peak of the boom would have been better off staggering those investments. It would have particularly helped in the case of schemes which fell the most.  Consider this: A one-time investment on March 1, 2000, in the worst-performing, diversified equity scheme (based on returns over the entire cycle), would have taken nearly 8 years to double in value.  A monthly SIP in that scheme for 1 year from that date would have taken less than 6 years to double in value. 

Should investors have timed their investments?  As I see it, good timing involves getting two things right: the time of exit and the time of re-entry.  Getting even one of these wrong can have a significant negative impact on one’s returns.  Given the odds against getting both right, I do not advocate such an approach.  I do, however, recommend that one rebalance one’s portfolio in line with one’s asset allocation.  Looking back, I remember that some of my clients, against my advice, did indeed try to time their exit, and re-entry.  As far as I recollect, all of them would have been better off not doing so.

I’d like to share one last observation before I close this post.  It’s about two diversified equity schemes and highlights the fickle nature of equity performance and fund manager success.  The first was a scheme that did exceedingly well during the tech boom.  It was an iconic fund, managed by a ‘star fund manager,’ as people like to say. In the last fifteen months of the boom, its NAV went up over 5 times, and by some accounts, its performance in calendar year 1999 was a world record of sorts.  In the downturn, it fell sharply, losing over 70% of its value from the peak.  In the years since the boom, its performance has been patchy.  The scheme still exists but is all but forgotten, its past glory relegated to a footnote in the annals of history.  The other scheme was one whose returns during the tech boom placed it in the bottom quartile of equity schemes.  In the downturn, its performance continued to be unexceptional.  Yet, in the years since, it has delivered spectacular returns that have caused investors to regard it as an iconic fund, and its fund manager as a legend.  For those of us who like to predict future winners among funds, the tale of these two schemes should serve as food for thought.

How should Star Ratings be used?

Given the extent to which financial advisors and investors refer to the Star Ratings of mutual funds (particularly, those by Value Research), I find that there is surprisingly little awareness of how these ratings are derived, or what these really signify.  In fact, in all the years that I have discussed this topic with advisors and investors, I cannot remember meeting anyone who knew the methodology behind these ratings.  I find this particularly worrying because the perceptions that most advisors and investors seem to have regarding these ratings are deeply flawed and the clarity needed can easily be gathered.  Value Research prominently displays links to an explanation of its methodology and an FAQ on the home page of its website. 

While I encourage readers to check those out, in this post, I offer my thoughts on how to use, and how not to use the ratings.  Important: What I have given below will make most sense only after you have familiarized yourself with the methodology and have seen the FAQ.  Also, do note that my thoughts on using these ratings somewhat differ from what Value Research suggests in the FAQ.

Purpose
Like Value Research, I recommend using Star Ratings as  a quick way of comparing the past performance of similar funds.  However, if the intention is to select a fund to invest into, I strongly suggest not using the Star Ratings as the primary basis for doing so.  In my understanding, the primary basis for selecting a fund should be the qualitative aspects such as the quality of the fund management team, their investment process, and the investment philosophy behind each fund.  Once you build a shortlist of funds using these parameters, Star Ratings can be used to further refine that list. 

Fair Comparison
The Star Rating of a fund is based upon its performance relative to other funds in the same category.  Hence, before comparing the Star Ratings of two funds, it would make sense to be sure that these funds are in the same category, as defined by Value Research.  In the case of equity funds or hybrid funds, I would go a step further and divide the funds in each category into two sub-groups: a. those that have been around for 5 years or more, and b. those that have been around for less than 5 years.  This is because the data used to determine a fund’s Star Rating is different for these two categories of funds.  In other words, before comparing the Star Ratings of two funds, I would want to be sure that these are in the same category as well as the same sub-group.

Bear in mind…

1. Funds with adjacent Star Ratings (e.g. 5 star and 4 star funds, or 4 star and 3 star funds etc.) can often have negligible differences in performance.
2. Star Ratings are just one way to compare the past performance of similar funds and shouldn’t be regarded as the only way or the best way to do so. 
3. Star Ratings, like most standardized tools of analysis of past performance, do not capture the role of luck in the performance of a fund.

The Illusion of Underperformance

A few days ago, a friend came to me with a question.  He had invested in a couple of funds in August, last year.  According to his calculations, one of these had so far delivered absolute returns of around 88%  whereas the other had delivered absolute returns of around 42%.  As is often the case with people who observe or experience such a difference, he had praise for the manager of the first fund and had doubts about the competence of the manager of the second fund.  His question: should he exit the underperforming fund?

During phases of rising stock prices (or ‘bull runs’), it is often seen that some equity funds deliver astronomical short-term returns.  We also get to see huge differences between the returns of funds.  What is not so well understood is that what appears to be underperformance may not actually be so.  Secondly, a number of investors miss seeing the bigger picture of fund performance (or underperformance).  In this post, I propose to expand on these thoughts.

Is it really underperformance?

I have previously shared my thoughts on this, although in fragments, across multiple posts.  In this post, I’ll gather these together.

Most experts agree that actual returns represent one aspect of performance, and that the risk attached to these returns also needs to be considered.  Thus, analyzing risk-adjusted returns is considered a better way of assessing the competence of a fund manager.  Even so, there is likely an element of luck that is far more difficult to understand and assess.

If we are still seized with an urge to compare, the least we could do is to be sure we are comparing funds which are comparable (i.e. they have similar investment objectives).  Consider, for instance, a fund that has the objective of investing in some stocks or sectors where prices have happened to rise much more sharply than others.  Comparing its performance with a fund which, say, cannot invest in the same stocks or sectors, is a pointless exercise.

One way to check if there is a case for a meaningful comparison, is to see how online research agencies such as Value Research or Morningstar categorize these funds.  Any fund is best compared with other funds in the same category, rather than with funds in other categories.

If it is underperformance…

In the stock market, we can be certain that every bull run will inevitably be followed by a phase of falling prices (or ‘bear run’) and vice versa.  What we cannot be certain about is as to when one phase will end and the other begin.  Thus, unless we choose to exit an underperforming investment in a bull run (for the purpose of a financial obligation, or lack of faith in a fund manager), we will get to see a bear run.  If so, then the odds favour a fund with a below-average performance in a bull run to have an above-average performance in a bear run. 

Recently, I did a study on the relative performance of diversified domestic equity funds from 2007 till date.  I divided this period into five smaller periods that represented either a phase of rising prices or a phase of falling prices.  These were:

• 5 March, 2007 to 8 January, 2008 (Rising)
• 8 January, 2008 to 9 March, 2009 (Falling)
• 9 March, 2009 to 5 November, 2010 (Rising)
• 5 November, 2010 to 20 December, 2011(Falling)
• 20 December, 2011 to date (30 June, 2014) (Rising)

I looked at open-end equity funds that were a part of the following categories of Value Research:

• Equity – Large-Cap
• Equity – Large and Mid-Cap
• Equity – Small and Mid-Cap
• Equity – Multi-Cap
• Equity – Tax Planning

There were, in all, 157 funds across these categories, which had been around since 5 March, 2007. Based on their returns in each phase, these were grouped into quartiles.  Here are some observations that can be linked to this post:

In the 2008-09 phase of falling prices, only 5 of the 39 funds in the top quartile were those that had been in the top quartile in the preceding bull run of 2007-08.  25 of the 39 funds had been ranked in the bottom half of that bull run.

In the 2010-11 bear phase, 9 of the 39 funds in the top quartile were those that had been in the top quartile in the preceding bull run of 2009-10.  20 of the 39 funds had been ranked in the bottom half of that bull run.

There was evidence supporting the reverse as well i.e. the lists of funds in the top quartile in the periods 2009-10 and 2011-date were overwhelmingly dominated by funds that been ranked in the bottom half in the bear runs that preceded each of these periods.

In case you’d like to analyze this data on your own, email me and I’ll send you an Excel file.

To keep the record straight, while there were no funds that remained in the top quartile across all five phases, there were 3 funds that remained in the top half all throughout.  With due respect to the skills of  the fund managers, I believe luck had a role to play in that.  Given the contentious nature of luck and the difficulty to quantify it, it is up to each one of us to draw our own inferences. 

I want to close this post with one last bit of food for thought.

In phases of falling stock prices, fund returns never appear to be earth-shattering, so to speak.  Additionally, the differences between returns of funds do not appear to be much.  This is essentially an illusion.  For illustration, let me share the absolute returns on two funds during the 2007-08 and 2008-09 phases.

	2007-08	2008-09
Fund A	90%	-55%
Fund B	38%	-35%

It might be easy to believe that over the complete cycle, an investor in Fund A was better off than an investor in Fund B.  Fact is, an investor in Fund A would have ended up losing around 15% of his wealth whereas an investor in Fund B would have lost about 10% of his wealth.

Using Past Performance Data to Select a Fund

A number of people analyze the past performance data of funds to determine which funds to buy. If you are one of them, and if your analysis has been working well for you, don’t bother to read any further. If not, here are three guideposts that you might want to use. These are not absolute truths but merely a personal opinion of some of the things to bear in mind.

1. Performance analysis is best done in the context of fund strategy.

Not knowing a fund’s strategy carries the risk of misjudging the fund’s performance. For instance, given their strategy, certain equity funds are expected to do better than market indices in periods when share prices are falling while others are expected to do better than market indices in periods when share prices are rising. Lack of awareness of the strategy may result in giving more credit to a fund manager than is necessary, or less credit than he/she deserves.

2. Be careful of performance snapshots

Most of us use performance snapshots in one form or another. Tables showing the trailing returns (e.g. returns for the last 3 years/ 5 years etc.) are a common example of such a snapshot. Charts showing the NAV movement over a period of time are another common example of such a snapshot. While, these are easily available and appear easy to understand, these have limitations that can also lead to misjudgment of a fund’s performance. Here’s an example. Table 1 below gives the trailing returns of two funds as on 31 Dec, 2010.

Table 1: Trailing Returns (Annualized) as on 31 Dec, 2010

	Fund A	Fund B
Last 1 year	17.9%	14.6%
Last 2 years	54.0%	59.3%
Last 3 years	13.2%	15.3%
Last 4 years	23.5%	24.4%
Last 5 years	24.2%	24.7%

A number of people are inclined to conclude that except for the immediate previous year, Fund B had mostly given better returns than Fund A. The truth is somewhat different. Table 2 below gives the quarterly returns of these two funds from 2006 to 2010. You may notice that other than in the second quarter of 2009, Fund B had never beaten Fund A in any of the remaining quarters.

Table 2: Quarterly Returns 2006-2010

2006	Fund A	Fund B
Q1	14.7%	14.7%
Q2	-11.2%	-11.8%
Q3	15.8%	15.2%
Q4	7.7%	7.7%

2007	Fund A	Fund B
Q1	-3.4%	-3.5%
Q2	20.5%	19.6%
Q3	15.0%	14.6%
Q4	19.6%	18.3%

2008	Fund A	Fund B
Q1	-15.9%	-16.2%
Q2	-12.9%	-13.4%
Q3	2.6%	2.5%
Q4	-18.7%	-18.8%

2009	Fund A	Fund B
Q1	2.7%	2.5%
Q2	52.1%	68.5%
Q3	20.1%	20.0%
Q4	7.3%	6.8%

2010	Fund A	Fund B
Q1	4.8%	2.4%
Q2	0.1%	0.1%
Q3	11.9%	11.5%
Q4	0.4%	0.3%

In effect, one recent month or quarter of good returns or bad returns can have a cascading effect on the trailing returns.

3. Performance is more than just returns

Actual returns represent one aspect of performance. While to some, this may be enough, the fact is that these returns were never assured and that there was always a degree of uncertainty attached to these returns (technically referred to, as ‘risk’). Most experts agree that the actual returns need to be seen in light of these risks. Technically speaking, they refer to this, as examining ‘risk-adjusted returns.’ In my opinion, too, analyzing risk-adjusted returns represents a better way of assessing the competence of a fund manager.

It may appear, from the above, that analyzing fund performance data isn’t as simple as one may have thought. If so, I suggest using the services of a good financial advisor. However, if you would like to understand more on this subject, Morningstar has put together an excellent article that offers multiple perspectives from their in-house experts on how to use fund performance data to evaluate funds. Here is the link.