A Short ‘Tail’ of Active and Passive Investing
The first test match between India-Pakistan at Lahore, Gaddafi stadium in 2006 has been etched into our minds when the polar opposite duo - Virendra Sehwag and Rahul Dravid milked runs off a flat wicket and came close to register the best opening partnership, but for the fearless nature of Sehwag. Sehwag was always known as a non-conformist but was a destructive batsman to say the least. With his foot firmly planted to the ground he could either send the ball out of the park or seemingly play a lofted shot straight into the fielder hands. Rahul Dravid on the other hand, without any fanfare with his solid front foot defense could tire out the best of opposition.
The 2 investing styles- Active investing and passive investing are similar to the polar opposite duo. The active vs passive debate has been raging on since decades but picking any one investment style may not serve the purpose.
For the uninitiated, Active funds aim to beat the benchmark and provide excess positive returns (also known as alpha / ‘α’) over the benchmark. This requires the portfolio manager to independently assess each investment and choose the most attractive/high conviction securities. It requires expertise and dedicated resources thereby increasing the management cost. In order to generate α, the fund manager takes active calls and the underlying portfolio is tilted in comparison to the benchmark. Thus causing it to outperform/underperform the benchmark.
Excess Returns are returns achieved above and beyond the return of a proxy. In our study excess returns refers to the returns delivered by the each of the scheme/portfolio of active scheme/50-50 active passive, over the respective proxy benchmark.
While passive investing is based on a zero sum game concept - One person’s gain is another person’s loss and these both form the total market. It believes that earning excess returns / alpha consistently over longer terms is difficult and expensive too. Empirical studies have noted that consistently outperforming the benchmark over a long term is difficult. So a passive portfolio manager simply tries to earn market return by holding securities in the same weight as in the index. It does not require the portfolio manager to take active calls and thus are effective low cost instruments.
As Mr. Buffet would say “Our favorite holding period is forever”- wealth creation is a slow process and requires discipline. Over short to medium term, when an active fund underperforms relative to its benchmark, an investor who was in the game for long term, finds it tough to stay disciplined and commit further funds or may even consider redeeming existing investments.
Any investment has 2 aspects: risk and return, investors look to maximize returns at minimum risk. In portfolio management, a bell curve (normal distribution) plots the likelihood of achieving certain returns. In a normal distribution, majority of the observations are clustered around the averages while some extreme observations lie away from the average (i.e. tails). Investors although love significant outperformance (right tail) but more than that they hate to experience significant underperformance (left tail). Left tail observations are hereto referred as ‘tail risk’.
Exhibit 1: Understanding Tail Risk
Disclaimer- The above graph is for illustration purpose only
We evaluated performance (CAGR) of SEBI classified active schemes (Large Cap, Mid Cap, Small Cap and Multi Cap) for a 5 year period from 31-Aug 2015 to 31-Aug-2020. For the sake of consistency, each active scheme have been benchmarked as below, basis it’s SEBI Category.
Exhibit 2: Category Benchmarks
|Sr. No||Scheme Category by SEBI||Benchmark|
|1||Large Cap||Nifty 50 TR Index|
|2||Mid Cap||Nifty Midcap 150 TR Index|
|3||Small Cap||Nifty Smallcap 250 TR Index|
|4||Multi Cap||Nifty 500 TR Index|
Disclaimer- Actual benchmark used by each scheme may differ. For fair comparison each active scheme has been benchmarked according to SEBI categories.
Historically, active mutual funds schemes has noted wider range of returns across all categories as shown in the exhibit 3 below. However, due to the very nature of passive investing (i.e. tracking benchmarks) the range of returns tends to be much narrower.
Exhibit 3: Range of returns (5 Year CAGR) of Active Schemes
|Particulars||Large Caps||Mid Caps||Small Caps||Multi Caps|
Source- ACEMF. Annualized returns of active scheme, for a period of 5 years as of close of 31-Aug-2015 to 31-Aug-2020.
On evaluating active funds excess returns, barring smallcap all other categories noted negative median excess returns (see exhibit 4). During heightened market volatility, active funds may potentially experience higher dispersions of excess returns. Investors in active funds typically invest with the mindset of “In it to win it” (i.e. to earn excess returns); however their risk tolerance is put to test during volatile times.
Exhibit 4: 5-Year Excess Return Noted by Active Scheme across categories
Source- ACEMF, Glide Invest internal research. Excess returns noted by active schemes over relative category benchmark during the period 31-Aug-2015 to 31-Aug 2020.
What is Significant positive / negative excess returns?
Any excess return more than +/- 2% is assumed to be ‘Significant Excess Returns’. For example - Assuming 5 Yr CAGR for ‘ABC Largecap Active Fund’ is 7%, ‘XYZ Largecap Active Fund’ is 12.5% and Nifty 50 TR Index is 10%; in this case ‘ABC LargeCap Active Fund’ has noted significant negative excess returns of 3% (i.e. 7% - 10%) whereas ‘XYZ LargeCap Active Fund’ has noted significant positive excess returns of 2.5% (i.e. 12.5% - 10%).
Exhibit 5 demonstrates the excess return distribution across all categories of active schemes. Of the total 89 active schemes spread across large cap, mid cap, small cap and multi cap categories, 67 (~75%) schemes noted negative excess returns. Remaining 22 (~25%) scheme managed to outperform the benchmark and achieve its objective of generating α. Out of 22 schemes that managed to generate α, 9 schemes delivered significant excess returns, whereas staggering 42 schemes (47% of total schemes) noted significant negative excess returns.
Exhibit 5: Distribution of Excess Returns by Active Schemes
Source- ACEMF, Glide Invest internal research. Distribution of excess returns noted by active schemes over relative category benchmark during the period 31-Aug-2015 to 31-Aug 2020.
Exhibit 6: Category-wise Excess Return Distribution of Active Schemes
|Data in number of schemes|
|No. of schemes||Large Caps||Mid Caps||Small Caps||Multi Caps|
|Positive excess return||3||2||11||6|
|Negative excess return||24||19||3||21|
|Total number of schemes||27||21||14||27|
|Significant positive excess return||0||0||7||2|
|Significant negative excess return||16||13||0||13|
Source: ACEMF, Glide Invest internal research. Considered excess returns noted by active schemes over relative category benchmark during the period 31-Aug-2015 to 31-Aug 2020.
As mentioned earlier, significant underperformance may elevate the risk of investor not committing further funds or redeem the existing one. The question that bears asking is how an investor can avoid significant underperformance?
To address this question - We created a ‘50-50 Active-Passive Portfolio’ by combining each active mutual fund schemes with its respective Total Return (TR) of benchmark in equal portion. (Note – In order to closely reflect the passive fund performance, we have adjusted benchmark performance with total expense ratio)
As pointed out earlier that passive investment try to mirror the benchmark which is why the excess return is in a tight range thereby reducing the left tail (i.e. significant underperformance) but it also shorten the right tail (i.e. significant outperformance).
As shown in Exhibit 7, the 50-50 Active-Passive portfolio has helped reduce the left tail risk (i.e. significant underperformance) to not more than -4% from earlier -6%. However, one may also note that, the Passive funds are expected to have small negative excess returns due to expense ratio and tracking error, lead to marginally increase in number of schemes with negative returns to 75 from earlier 67.
Exhibit 7: Distribution of excess returns noted by 50-50 Active-Passive portfolio over 5 year period ended August 2020
Source: ACEMF, Glide Invest internal research. Considered excess returns noted by ’50:50 Active:Passive’ portfolio over relative category benchmark during the period 31-Aug-2015 to 31-Aug 2020. Benchmark values adjusted for annualized TER of Motilal Oswal passive schemes.
The 50:50 portfolio has helped reduce significant underperformance by 50% to 21 schemes from earlier 42 schemes (see exhibit 8). Large Cap, Mid Cap and Multi Cap category, where significant portion of AUM is invested, were the most benefited with 50-50 Active-Passive portfolio.
Exhibit 8: Number of Portfolios with Significant Negative Excess Returns
Source: ACEMF, Glide Invest internal research. Considered negative excess returns noted by active schemes and ’50:50 Active:Passive’ portfolio over relative category benchmark during the period 31-Aug-2015 to 31-Aug 2020
In case of Active only, when wild market swings causes investors portfolio to note significant negative returns, it often becomes ‘advisors nightmare’. Advisors often risk losing investors, mitigating such risks with passive allocations may help advisor in not just retaining the investor but further may help in generating wealth over a longer term.
Exhibit 9: Adding Passive Funds to Portfolio may Reduce Excess Return Distribution, Thereby Reducing Flight Risk: A Graphical Illustration
Source: Vanguard; Paper - Enhanced practice management: Investor risk and the case for active/passive combinations
The two styles of investing should not be viewed as mutually exclusive, but should be adopted basis an investor’s risk appetite, risk tolerance and excess return expectation. Investors seek outperformance but more than that they dislike underperformance. The unpredictable nature of market coupled with lack of consistent performance by funds prompts the need to introduce a flavor of passive investing to an investor portfolio.
Disclaimers & Risk Factors - This research note has been prepared and issued on the basis of internal data, publicly available information and other sources believed to be reliable. The information contained in this document is for general purposes only and not a complete disclosure of every material fact and terms and conditions. The information / data herein alone is not sufficient and shouldn’t be used for the development or implementation of an investment strategy. It should not be construed as investment advice to any party.
All opinions, figures, charts/graphs, estimates and data included in this research note are as on date and are subject to change without notice. The statements contained herein may include statements of future expectations and other forward-looking statements that are based on our current views and assumptions and involve known and unknown risks and uncertainties that could cause actual results, performance or events to differ materially from those expressed or implied in such statements. Readers shall be fully responsible / liable for any decision taken on the basis of this research note. Investments in schemes are subject to market and other risks and there is no assurance or guarantee that the objectives of any of the schemes will be achieved.
The material is based upon information that we consider reliable, but we do not represent that it is accurate or complete, and it should not be relied upon as such. Opinions, if any, expressed are our opinions as of the date of appearing on this material only. Recipient shall understand that the aforementioned statements cannot disclose all the risks and characteristics. The recipient is requested to take into consideration all the risk factors including their financial condition, suitability to risk return, etc. and take professional advice before investing.
Mutual Fund Investments are subject to market risks, read all scheme related documents carefully
 Significant outperformance/underperformance = Excess Return greater than +/- 2%
 Relative benchmarks have been adjusted with the following TER: Large cap - 0.50% (Motilal Oswal Nifty 50 Index fund), Mid cap/Small Cap/Multi Cap - 1.03% (Motilal Oswal Nifty Midcap 150 Index fund/Motilal Oswal Small cap 250 Index fund/Motilal Oswal Nifty 500 Index fund)