Investor Issues
Three reasons why S&P-CRISIL’s rating of mutual funds based on fixed period is flawed

The majority of actively managed equity schemes for 1-year, 3-year and 5-year periods ending June 2012, have underperformed their benchmarks over the last five years, says a study. But does it make sense to do a fixed period analysis of a product that is not fixed income in nature? Here are three reasons why the study is flawed

 

S&P Indices Versus Active Funds (SPIVA) scorecard, produced by S&P Dow Jones Indices in partnership with CRISIL, highlights that the majority of actively managed Indian equity mutual funds have underperformed their respective benchmark indices over the last five years’ period ending June 2012. According to the research report, majority of large-cap equity schemes failed to beat the S&P CNX Nifty benchmark index for large-cap companies, 53.33% underperformed their benchmark over the last five years, 57.14% over the last three years and 52.63% over the last year.
 

Over 53.10% of diversified schemes outperformed the benchmark S&P CNX 500 in the one year period ending June 2012. This number increased to 61.6% in the three year period but again dropped to 49.5% in the five year period.
 

This has becomes headlines everywhere leading confirming to fence-sitters and believers of bank fixed deposits that equity mutual funds are best avoided.
 

However, this kind of analysis and conclusion carries a few fundamental flaws. Nobody has suggested that equities have to make money no matter when they are bought.
 

One, it is pertinent to note that the returns taken are for just a fixed period from June 2007 to June 2012. So which investor would have underperformed by buying mutual funds? Exactly those who had bought in June 2007. If their investment was made in June 2006, the results would have been different. Take June 2003 and it would have been different still. Returns vary, depending on the start and end date. This is natural because equity funds are not fixed income products. It is obvious that to come to any conclusion, one will have to take into account different periods. This is simply done by calculating what is called rolling returns.
 

According to our analysis over the last five rolling periods with a quarterly frequency, the average returns of 63% of the schemes were better than that of the Nifty index. The large-cap oriented equity schemes averaged a return of 7.59% compared to the Nifty which returned 6.62%. The headline should have read “A majority of schemes beat the market index”.
 

Two, no investor jumps into a scheme with all his money at one go. He is consistently advised to invest systematically.
 

Three, no investor invests in all the schemes. He is advised to invest in the better ones. There is no shortage of good schemes to choose from. In the rolling periods taken for our analysis, the top 10 schemes returned an average of 13.13%. While one can always argue that we know which of the schemes are better only with the benefit of hindsight, the fact is choosing good quality and index-beating schemes in India has been surprisingly easy compared to the US market.

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COMMENTS

Vipul T Hindocha

5 years ago

This ratings at best help churning and create a herd rather than wealth creation.The problem is we seek the pleasure of an One Night Stand from a long term marriage. When we invest for the long term there is no point in tracking the NAV and index day to day but if you are convinced on the fund objective we need to use every dip in NAV to average. A good Stock or fund with well defined objective and adherence to the objectives will any day give better return's.Our regulators Education program is flawed it is all about the NAV but none talk of the portfolio and other parameters to choose a fund suitability to person. A magazine says so many stars and the heard goes there the magazine as mention in your article changes the period the next month and shows a different figure and the herd move out to a new scheme with a new objectives which could be a high risky sectoral fund. It happened in Power then Infra then FMCG then Pharma and god knows which sector next. This can be exhaustive.

Nilesh KAMERKAR

5 years ago

In case of equity funds, their performance figures is of little help to the investors. they mislead more than they guide.

1)Although the figures are factually correct, people draw wrong conclusions from these figures by extrapolating them into the future. But, what works most of times is reversion to mean, although the mean may shift slightly upwards to adjust for inflation & normal growth.

2) Even though some schemes, fund houses, fund managers have consistently outperformed the benchmark, it would be a mistake to presume that they would continue to do so.

3) Because data is numerically expressed and mathematical or statistical formulas can be applied it still cannot be a pointer to the future performance. We simply do not know. (same is with ratings too) For most, volatility is a measure of risk . . . but risk is the probability of being right and the consequences that you may suffer if you are wrong.

A mutual fund investor will do well to disregard such ratings and focus on the basics; long term investing, asset allocation, diversification & periodic re-balancing. If he saves enough and invests for the long haul he will do well. Investing in mutual funds is never a race, between funds.

Even if the fund manager's poll is conducted they (the fund managers themselves) may not be able to predict which of their schemes will outperform the rest & over what period of time.

REPLY

Debashis Basu

In Reply to Nilesh KAMERKAR 5 years ago

Excellent comments. Appreciate it

Amit Patani

5 years ago

This reminds me of an article published for mutual funds performance for oldest mutual funds http://www.moneylife.in/article/how-have...
The database is purchased from moody's rating agency - mutual funds india and Madam Megha vora published how old funds are bad.
I that time also pointed out that Mastershare generated 18% cagr since 1986..but till on date u have not confirmed..
How reliable your research is when u claim that mastershare generated only 7% cagr since launch..
You have also based your article on rating agency data.. Whereas lessed aware news paper & other media has taken crisil data reseach and published..whats the difference?

Amit Patani

5 years ago

This reminds me of an article published for mutual funds performance for oldest mutual funds http://www.moneylife.in/article/how-have...
The database is purchased from moody's rating agency - mutual funds india and Madam Megha vora published how old funds are bad.
I that time also pointed out that Mastershare generated 18% cagr since 1986..but till on date u have not confirmed..
How reliable your research is when u claim that mastershare generated only 7% cagr since launch..
You have also based your article on rating agency data.. Whereas lessed aware news paper & other media has taken crisil data reseach and published..whats the difference?

Madhur Kotharay

5 years ago

Very good observations, folks.

I have been planning to tell Dhirendra Kumar and his Mutual Fund analysis to change their valuation methodology.

1. They don't take rolling returns.

2. They take 1-year, 3-year and 5-year returns. However, these include the latest year's returns thrice and the last 3 years' returns twice. That is called Double Counting.

If you did badly in the last year, you did badly in all the 3 numbers. That is why funds that betted on infra and cap goods in the last year have languished at the bottom. Recency Bias is not only wrong, it is downright dangerous, if you believe in 'reversal to the mean'. If the market bounces back in the next year, the funds that will outperform are exactly the ones at the bottom of the list that Dhirendra Kumar posts. And the reason is the mathematical lacunae in calculating the outperformers.

3. Mathematically, they should take only 1-year rolling returns for the full period of existence and take Geometric mean of those returns. That is because gains are compounding in nature and multiply over a period of time.

In fact, to be really rigorous, they should calculate 1 - Geometric Mean of (1 + %Gain) for all one year rolling-periods the fund has been existing.

After all, an average (which is also the arithmatic mean) is a lousy way to treat gains. If I gain 60% one year and gain -60% next year, the average is not 0% (If you put Rs 100, at the end of the first year, you have Rs 160. And at the end of the second year, you have Rs 160 x (1-60%) = Rs 160 x 40% = Rs 64 in hand. You are actually down 36% in two years or a loss of 20% per year (100 to 80 and 80 to 64).

The only way to get this picture cleared is if you take the geometric mean of (1+60%) and (1-60%)
= square root of 1.6 x 0.4
= square root of 0.64
= 0.8
= (1-20%)
Or on an 'average', 20% loss a year.

Now, it will be interesting to see which funds outperform after this new criterion for evaluation. :-)

REPLY

Pravesh Pandya

In Reply to Madhur Kotharay 5 years ago

I have been thinking about this over the weekend. And I guess the theory behind this is bit like this.

If we want to calculate the real rate of return of an investment over a period of time, then the final value of the investments is PRINCIPAL*(1 + RATE_OF_RETURN/100)^(NO_OF_YEARS). This is derived from the formula of compound interest. First year you earn PRINCIPAL * (1 + RATE/ 100), second year you earn PRINCIPAL * (1 + RATE / 100)^2 and likewise. The NO_OF_YEARS parameters explains the reason why we have to take the geometric mean here. So instead of multiplying the returns on a yearly basis and then doing the geometric mean, one may just do ((FINAL_VALUE / PRINCIPAL)^(1/NUMBER_OF_YEARS) -1).

An example might make more sense. In the above case, an investment of 100 is 64 after 2 years. So the real return is square root of (64/100) -1.

Actually this formula can also be applied to SIP. Only thing is that we have to thinking of it a bit like a recurring account where we have a fixed rate of return. Some websites have their own formula for dollar cost averaging which relies on the average cost - which I think is not the right way to calculate the returns on SIP.

In order to apply the above formula for an SIP, you will have to think of this like a series of investments growing gradually over time.

The final formula is bit length but it is bit like this

P*(1+R/100/12)^(NUMBER_OF_MONTHS) + P*(1+R/100/12)^(NUMBER_OF_MONTHS -1) + P* (1 + R/100/12)^(NUMBER_OF_MONTHS-2) and so on for the entire period. What you are doing here is for every monthly investment you are calculating the return and then adding the returns for all the months. Also note that the rate of return is divided by 12 to cater to monthly investments. If you observe this sequence, it is a geometric progression and it can be shortened easily.

While doing all these calculations, I have assumed a constant return on investment - which is of course not the case in equities. My intention was here to calculate what return I would have earned had I invested the same amount in a fixed income product which would have given me the same return.

Welcome any suggestions or comments.

Debashis Basu

In Reply to Madhur Kotharay 5 years ago

Excellent points. Will try to do an article based on this approach

Madhur Kotharay

In Reply to Madhur Kotharay 5 years ago

OK, some more points:
1. Coming to theoretical nitty-gritty, you actually want geometrical mean of DAILY gains over the entire period of the fund's existence (adjusted for holidays in between, i.e. Friday to Monday gains are to be taken as over 3 days and so adjusted to CDGR, Compound Daily Growth Rate).

Thus, even the geometric mean of rolling 1 year periods is not right (as it gives less weightage to the boundary values of performance, i.e. the first 11 months and the last 11 months of the fund's performance).

2. For the sake of simplicity, you can take monthly gains over the entire period and take their geometric mean to get the monthly returns.

3. I used the rolling 1-year returns because people understand returns in terms of annual gains.

4. The starting point of the fund can bias the comparison. The funds that started at 2003 will do better than the funds that started in 2000 or Jan 2008, even after taking averages the way mentioned earlier. I have no answer to that challenge.

5. A great addition would be to plot monthly gains above or below benchmark gains over a period of time. That would tell how the fund performs overall. Is the outperformance due to one big 'matka', like Kwality Dairy or is it a regular small outperformance, adding into big gains. Of course, the risk is that some funds don't adhere to their mandate (some infra funds invest in Apollo Hospitals & Lupin calling them 'Healthcare Infrastructure' stocks and in ICICI Bank calling it 'financial infrastructure' stock).

6. One could compare performance over a business cycle. But that would exclude many of the new funds.

7. Probably, nothing to substitute proper detailed checkup and your judgement.

Pravesh Pandya

In Reply to Madhur Kotharay 5 years ago

Hi Madhur,

I think we don't need to do a daily or monthly or yearly comaprison to get the actual numbers. You can just take two points in time and still get the same value as rate of return whether you use monthly gain or daily gain. Perhaps my comment posted above might shed some light.

Debashis Basu

In Reply to Madhur Kotharay 5 years ago

The start and end date issue is solved by comparing like and like. We do not analyse funds that are in existence for less than five years. We also do not compare a 7 yr performance with a five year one. One international study found that more than 5 years, performance data stops being meaningful. Strangely, more data is not better for funds. One reason is managers change and even styles change. I think 5 yr rolling with monthly geomean should be a good approximation. It should of course be tested whether it has any predictive value

Milind Chitnis

In Reply to Madhur Kotharay 5 years ago

Very good analysis sir, do pass this on to Valueresarch people, if the do incorporate this model, it would help general public & followers of the site greatly.

It would be interesting to see "top rated" funds with your methedology.

Debashis Basu

In Reply to Milind Chitnis 5 years ago

Shouldnt Value Research be doing its own "research." :)

Jayant

In Reply to Madhur Kotharay 5 years ago

I don't know what you do Mr Kotharay but you've hit the nail on the head. All these so called analysts just rate funds based on this absurd calculation and SEBI wants that direct investors follow these raitngs and invest in funds by bypassing the distributor. Distributors have to pass an exam and go through a refresher every few years. Apart from that, being their full time jobe they stay in touch with informed articles and opinions like the one you have expressed. So called analysts like Mr. Dhirendra Kumar have nothing to lose and have a free hand in saying anything they want since most of their audience is relatively ignorant. It's high time SEBI did something to stem this and had in place a rational and standard rating system for Mutual Funds.

Coal block allocation: Indian ‘elGordo’!

Essar Power’s acquisition of Navabharat Power is one of the many facets of the Indian ‘elGordo’ where the windfall gain will run for decades, unlike its Spanish counterpart!

 
Since 1812, the Spanish Public Administration has carried on a national lottery system, which eventually became popularly known as the Christmas Lottery, also called, as “elGordo”—the fat one! This is the biggest lottery world wide.
 
The top prize money amounts to 540 million euros and 180 series of tickets sold at 200 euros apiece. As the cost is rather high, and in order to facilitate everyone to afford a purchase, the ticket is further divided into one-tenth or also known as the ‘decimos’.  The Spaniards look forward to getting a piece of the action by buying the tickets.
 
Looks like the Indian version of the ‘elGordo’ is in getting a coal block allotment and actually commencing the mining operation after overcoming all the hurdles put up by the state and MOEF (ministry of environment and forests), and cap it by discovering millions of tonnes of high grade thermal coal!
 
In reality, however, the 58 allottees that are under the CBI (Central Bureau of Investigation) scanner and also answering the various queries raised by the Inter Ministerial Group may have many different things to say in their defence. It will be a while before the final outcome of these investigations, FIRs, etc are made public!
 
The enthusiastic press have gone deep into the bowels of the earth and have discovered much more muck than coal. For example, a report that has appeared in the Times of India gives an in-depth detail of the several transactions that have taken place.
 
In the case of Navabharat Power, it was registered with a capital base of just Rs1 lakh, which signed an MOU (Memorandum of Undertaking) with the Orissa government to invest Rs9,675 crore in two—1,060 MW and 1,200 MW—power plants in Dhenkanal. It got a 4.7 million tonne (MT) of coal linkage in May 2006. Two years later, in January 2008, it got an additional 112 MT allotment from Orissa’s Rampia and Dipside coal block. Although 108 applications were received for this block, only two were invited (why?) to make a presentation and the final allotment went to Navabharat, although there were some real heavy-weights in the fray. Anyway, by 2011, the stakes were sold to Essar Power, for an enormous sum of money.
 
This is one of the many facets of the Indian ‘elGordo’ where the windfall gain will run for decades, unlike its Spanish counterpart!
 

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Quality of solution is the clincher for Infosys in its sales strategy, not necessarily pricing, says Nomura

Infosys is likely to lag behind its peers in the cost-efficiency segments and higher exposure to discretionary segments will continue to drag growth, says Nomura Equity Research

 
Infosys has a value design initiative, and its focus is on winning competitive deals with an emphasis on improving the quality of solution presented to clients. Solution is the clincher according to the company, not necessarily pricing. This is part of the quick note of Nomura Equity Research following a call with the company’s head of sales, Basab Pradhan. Further in going to market, the IT company has a focus on selling differentiated offerings like products and platforms and steering the conversation with clients away from plain outsourcing, observes Nomura in its quick note.
 
According to Nomura, the tasks involved in value design are qualification of which deals to chase; assembling the right team from across the organization for deal pursuit; accountability of the team (attribution of credit for contributing to non-sales people participating in this initiative); and knowledge management—i.e. drawing from past proposals, so as not to rediscover the wheel.
 
Infosys also has a star account program, where the focus is on managing star accounts or what management identifies as the 47 accounts which are $100 million plus or have the potential to reach $100 million. The 47 star accounts of Infosys contribute 60% of its revenue, narrates Nomura.
 
According to the research note, the Infosys’ sales team has 11 people looking at global markets (covering alliances, marketing and large deal outsourcing), and 16 regional heads overseeing the field force—who report to the sales head and the unit heads. In all, there are 800-900 people in sales, and pre-sales activities with responsibilities across  new account opening; account management or client servicing which has the largest allocation of resources (large accounts have five to six people manning an account); and practice sales (experts in certain domain area/pre sales)
 
Infosys says the recent sluggish growth is not necessarily due to hunting issues but more related to mining, as account-led growth has not contributed as much in the high growth areas. Infosys has been adding close to 40-50 accounts on a quarterly basis over the last four quarters, but many of those have been the non-Global 2000 clients. The company has found that clients falling below the Global 2000 have a mortality rate of about 90% by the fourth year. Hence, Infosys has refocused its hunting efforts towards the Global 2000 segment and sales bonus structures are being aligned to getting these clients.
 
The company believes there is greater flexibility currently in terms of structuring deals or taking over people. Deal pricing is largely decentralized with the unit heads taking a decision on deal go no go. The company does not believe its higher margin thresholds compared to competition is leading them to forego deals.
 
The focus on growing outsourcing, irrespective of the growth in higher value-added segments (consulting, system integration segment), continues and the company is not foregoing growth in outsourcing despite the aspiration to increase contribution of higher value-added segments in the longer term. The company continues to participate in deal churn and has been successful in the same and gave instances of two deals recently won – one in a major UK bank where they were a smaller player and have expanded footprint and another in a hi-tech company where they were the incumbent vendor and are expanding their footprint.
 
The company does not see blanket pricing reductions as seen during the global financial crisis, but believes some clients are taking advantage of the environment through rebids, wherein competitive pressures are pushing pricing down. The management says Infosys is not leaving deals on the table purely because of pricing.
 
The company’s view remains that Europe continues to be shaky and US has dependence on European demand and does not have enough momentum on its own to counter the European sluggishness. Transformational deals continue to be elusive and outsourcing deals is where the opportunity remains. From a verticals perspective, only hi-tech within manufacturing and retail is seeing good demand, while clients within the rest of manufacturing have more global businesses and are seeing slowdown/ uncertainty. The company continues to see softness in BFSI.
 
Nomura’s view on the performance of Infosys is as follows: “We continue to expect Infosys to lag peers like HCL Technologies, Tata Consultancy Services and Cognizant in the cost-efficiency segments and believe Infosys’ higher exposure to discretionary segments (about 36% of revenues) will continue to drag growth. We believe the increase in flexibility is likely to be more aimed at saving volume share, but will not necessarily drive significant incremental volumes.” 
 

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