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Factor Performance Across Different Macroeconomic Regimes in India

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India's Active vs. Passive Debate and the Rise of Factors

Webinar

Tuesday, April 24, 2018


Disclaimer

For Financial Professionals Only 3

S&P Dow Jones Indices emphasizes to participant that Anil Ghelani - DSP BlackRock

Mutual Fund & Shreenivas Kunte - CFA Institute are guest speaker and not affiliated with

S&P Dow Jones Indices or Asia Index Private Limited and that S&P Dow Jones Indices is

not providing endorsements as to the opinions expressed which are those of the guest

speaker for this webinar. S&P Dow Jones Indices offers no guarantees or warranties as to

the accuracy and reliability of opinions expressed.

Guest speaker are not affiliated with S&P Dow Jones Indices and S&P Dow Jones Indices

does not sponsor, endorse, sell, or promote any product based on an S&P Dow Jones index

nor does it make any representation regarding the advisability of investing in the products.


ANIL GHELANI

4

Senior Vice President,

DSP BlackRock Mutual Fund

Anil has been working with DSP BlackRock Group since 2003 and is currently

responsible for Products & Passive Investments. Previously, he served as the Business

Head & Chief Investment Officer at DSP BlackRock Pension Fund Managers and prior to

that leading the Risk and Quantitative Analysis team at DSP BlackRock Mutual Fund

responsible for monitoring of portfolio risk and buy-side credit research on companies

across various sectors.

He also worked at IL&FS Asset Management Company and at S.R. Batliboi a member firm

of EY. He is currently serving in volunteer capacity as a Director of the India Society of

the CFA Institute.



AKASH JAIN

5

Associate Director, Global Research & Design

Asia Index Private Limited

Akash Jain is part of the Global Research & Design group at S&P Dow Jones Indices,

which is responsible for conceptualizing and developing new investable index-based

products across different asset classes. He represents S&P Dow Jones Indices at media

engagements, conferences, and other client events.

Akash is an integral part of Asia Index Private Limited, which is a partnership between

S&P Dow Jones Indices and BSE Limited (formerly Bombay Stock Exchange).

Akash joined S&P Dow Jones Indices in 2016. He has been in the financial markets for

more than six years, including at Deutsche, Credit Suisse, and Edelweiss, with

experience in both the buy side and the sell side. He has worked extensively in

researching, back-testing, and trading portfolios across different asset classes.

Akash attained his Bachelor of Technology (B.Tech) degree from Indian Institute of

Technology (IIT Bombay) and holds a Masters of Business Administration (MBA) from

Saïd Business School (University of Oxford).



SHREENIVAS KUNTE

6

Content Director,

CFA Institute

Shreenivas Kunte, CFA, is a director for continuing education and advocacy at CFA

Institute. In this role he provides thought leadership across a range of topics and through

different delivery platforms.

He also serves as an external research scholar at the Indian Institute of Technology

Bombay. Prior to joining CFA Institute, Shreenivas worked as the country trading

strategist for Citi. Shreenivas holds a degree in computer engineering from Veermata

Jijabai Technological Institute.



1. SPIVA® India Year-End 2017 Scorecard

2. Factor Investing


Akash Jain


8

ABOUT SPIVA® SCORECARD

SPIVA® AROUND THE WORLD

PERCENTAGE OF FUNDS OUTPERFORMED BY THE INDEX

01

02

03

04

05

EQUAL VS ASSET WEIGHTED RETURNS

TIMELINE OF PERCENTAGE OF ACTIVE FUNDS THAT

UNDERPERFORMED THEIR BENCHMARKS

SPIVA - TABLE OF CONTENTS

06 QUARTILE BREAKPOINTS


THE SPIVA® (S&P INDICES VERSUS ACTIVE) INDIA SCORECARD

9

Source: S&P Dow Jones Indices, LLC. It is not possible to invest directly in any index

What is SPIVA® India

- Bi-annual report that attempts to capture performance of active funds domiciled in Indiaagainst S&P BSE benchmark indices

- Acts as an objective score keeper in the active funds performance vs indices

- Aims to aid investors & better equip them to take informed decisions in the market

Geographies SPIVA published in

- India, US, Australia, Canada, Europe, Japan, South Africa, Mexico, Chile, and Brazil

Methodology

- Capture fund categories from an independent data source MorningStar & map these categories to S&P BSE Benchmark Indices

- Net assets data is obtained from AMFI database

Features

- Identifies % of active funds that survive the investment horizon and are style consistent

- Performance against benchmark indices over 1-, 3-, 5-, and10-Yr time horizons

- Equal vs asset weighted performance- Performance spread of 1st quartile funds vis’-

a-vis’ 3rd quartile


10


INDIA SCORECARD –PERCENTAGE OF FUNDS OUTPERFORMED BY THE INDEX

11

Source: S&P Dow Jones Indices, SPIVA India Scorecard Year End 2017,. Data as of Dec. 31, 2017, Data from Dec 31,2007up to Dec. 31, 2017. Index

performance based on total return [INR]. All data prior to launch date are back-tested. Charts are provided for illustrative purposes and may reflect

hypothetical historical performance. It is not possible to invest directly in an index. Past performance is no guarantee of future results. Please see the

Performance Disclosure at the end of this document for more information regarding the inherent limitations associated with back-tested performance.

Indian Equity Large Cap vs. S&P BSE 100

Indian ELSS vs. S&P BSE 200

Indian Equity Mid/Small Cap vs. S&P BSE MidCap

Indian Government Bond vs. S&P BSE India Government Bond

Indian Composite Bond vs. S&P BSE India Bond

1-Year 3-Year 5-Year 10-YearFund Category Vs. Benchmark


TIMELINE OF PERCENTAGE OF ACTIVE FUNDS THAT UNDERPERFORMED THEIR BENCHMARKS

12

Source: S&P Dow Jones Indices LLC. Data as of June 30, 2017. Figures based on Mid-Year and Year-End SPIVA India scorecards since

December 2013 to June 2017. Past performance is no guarantee of future results. Reference:

https://www.indexologyblog.com/2017/10/10/timeline-of-percentage-of-active-funds-that-underperformed-their-benchmarks/

Percentage of active funds that underperformed their benchmarks (over a rolling 5-year investment horizon) In the LargeCap equity & two

bond fund categories, majority of active funds underperformed their respective benchmarks over a rolling 5-year investment horizon as can be seen in the exhibit

Equity Linked Saving Scheme (ELSS Tax Saving Funds) had the highest percentage of funds that beat the benchmark over the rolling 5-year period

Among all the fund categories, the Indian ELSS and Indian Equity Mid-/Small-Cap funds offered the most pronounced excess return over their respective benchmarks

https://www.indexologyblog.com/2017/10/10/timeline-of-percentage-of-active-funds-that-underperformed-their-benchmarks/


QUARTILE BREAKPOINTS

13

Source: S&P Dow Jones Indices, SPIVA India Scorecard Year End 2017,. Data as of Dec. 31, 2017 Data from Dec

31,2007 up to Dec. 31, 2017. Index performance based on total return [INR]. All data prior to launch date are back-

tested. Charts are provided for illustrative purposes and may reflect hypothetical historical performance. It is not

possible to invest directly in an index. Past performance is no guarantee of future results. Please see the

Performance Disclosure at the end of this document for more information regarding the inherent limitations

associated with back-tested performance.

Over the 10-year period, thespread in returns between thebest quartile vs 3rd -best quartileby performance is significant incase of Indian Equities across allcategories.

The spread in Indian EquityLarge-Cap funds was 3.23%,Indian Equity Mid-/Small-Capfunds was 4.44% whereasIndian ELSS saw a difference of4.25%.

Selecting the right fund canprove to be a key factor forinvestors to achieve superiorportfolio returns

Return Spread of active funds over a 10-year investment horizon

3.2%

4.4%


14

Source: S&P Dow Jones Indices, SPIVA India Scorecard Year End 2017,. Data as of Dec. 31, 2017, Data from Dec 31,2007 up to Dec. 31, 2017. Index




SURVIVORSHIP & STYLE CONSISTENCY

SURVIVORSHIP BIAS CORRECTIONOver the 10-year period, Indian Equity Large-Cap funds showeda survivorship rate of 70.1%, whereas Indian Equity Mid-/Small-Cap funds had a 70.0% survivorship rate where-as theIndian Government Bond and Indian Composite Bond fundshad even lower survivorship rates, at 48.3% and 68.2%,respectively.

STYLE CONSISTENCYOver the 10-year period, style consistency was fairly low forIndian Equity Large-Cap funds (28.3%) and Indian EquityMid-/Small-Cap funds (30.0%). On the other hand, Indian ELSSfunds have largely been style consistent.

Category

Indian Composite Bond

Indian Government Bond

Indian Equity Mid/Small Cap

Indian ELSS

Indian Equity Large Cap

Style consistency within the survivorship bias


EQUAL VS ASSET WEIGHTED RETURNS

15

Source: S&P Dow Jones Indices, SPIVA India Scorecard Year End 2017,. Data as of Dec. 31, 2017, Data from Dec 31,2007 up to Dec. 31, 2017. Index




10

-Ye

ar

1-Y

ea

r

EQUAL WEIGHTED RETURN

EXCESS ASSET WEIGHTED RETURNS

BENCHMARK RETURNS


KEY TAKEAWAYS AND OPPORTUNITIES FOR INVESTING VIA PASSIVE INSTRUMENTS

16

Source: S&P Dow Jones Indices, Past performances is not a guarantee of future results. It is not possible to directly invest in any index

1. Notable trend in convergence in excess performance and fees

2. Factor in Survivorship Correction and Style Consistency

3. Funds with higher AUM’s have historically performed better than their peers over

longer time horizon

4. Investors may see wide spread in returns even when investing within the same

category of funds

5. Passive instruments are designed to offer exposure to capital markets via systematic,

transparent and as a low-cost alternative


17

FACTOR INVESTING 101

EVOLUTION OF FACTOR INVESTING

01

02

03

04

RISK/RETURN CHARACTERISTICS OF SINGLE FACTORS

HOW DO SINGLE FACTORS PERFORM IN DIFFERENT

MARKET REGIMES IN INDIA?

TABLE OF CONTENTS

05 CORRELATION BETWEEN SINGLE FACTORS


18

Source: “Premia Partners https://www.premia-partners.com/what-is-smart-beta/”

Chart is provided for illustrative purposes.

FACTOR INVESTING 101

• A factor can be thought of as an element that helps to explain the risk/return characteristics of aportfolio. The broadly recognized factors are size, dividend, volatility, momentum, quality, andvalue.

• Factor investing seeks to identify and capture broad, persistent drivers of return

https://www.premia-partners.com/what-is-smart-beta/


19

EVOLUTION OF FACTOR INVESTING

Source: Fidelity Investments. # https://www.fidelity.com/bin-public/060_www_fidelity_com/documents/brokerage/overview-factor-investing.pdfChart is provided for illustrative purposes.

• Passive products enable market participants to implement their active views through transparentand cost-effective manner.

• For eg. Investors seeking to gain exposure to inexpensive companies can add value ETF’s to theirportfolio. Similarly, investors looking to invest in companies with strong balance sheet & highROE can gain exposure to quality ETF’s

https://www.fidelity.com/bin-public/060_www_fidelity_com/documents/brokerage/overview-factor-investing.pdf


20

The S&P BSE Dividend Portfolio and S&P BSE Equal-Weighted Portfolio are hypothetical portfolios. Source: S&P Dow Jones Indices LLC. Data from October 2005 to June 2017. Index performance

based on total return in INR. Past performance is no guarantee of future results. Chart is provided for illustrative purposes and reflects hypothetical historical performance. Please see the

Performance Disclosure at the end of this document for more information regarding the inherent limitations associated with back-tested performance. Note: Data points below each factor represent

risk-adjusted return.

Risk/Return Characteristics and Risk-Adjusted Returns of Single-Factor Indices and

Portfolios (October 2005 – June 2017)

RISK/RETURN CHARACTERISTICS OF SINGLE FACTORS


HOW DO SINGLE FACTORS PERFORM IN DIFFERENT MARKET REGIMES IN INDIA? (1)

21

Best-performing Factors in each ‘market cycle’ phase

Best-performing Factors in each ‘business cycle’ phase

Source: S&P Dow Jones Indices LLC. Data from October 2005 to June 2017. The S&P BSE Dividend Portfolio and S&P BSE Equal-Weighted Portfolio are hypothetical portfolios. Top 3 factors by performance in each period are shown in the chart. Index performance based on total return in INR. Past performance is no guarantee of future results. Chart is provided for illustrative purposes and reflects hypothetical historical performance. Please see the Performance Disclosure in the report for more information regarding the inherent limitations associated with back-tested performance. See Appendix A in the report for the OECD Composite Indicator business cycles. See Appendix B in the report to note the classification of the time horizon into three market cycles, namely—bull, bear, and recovery phases

http://www.asiaindex.co.in/documents/research/research-factor-performance-across-different-macroeconomic-regimes-in-india.pdf?force_download=true




22

Source: S&P Dow Jones Indices LLC. Data from October 2005 to June 2017. Index performance based on total return in INR. Past performance is no guarantee of future

results. Table is provided for illustrative purposes. Note: Yellow, upward triangles represent favorable performance (positive excess return with outperformance probability not

lower than 50%), while blue, downward triangles represent unfavorable performance (negative excess return with outperformance probability not higher than 50%) versus the

S&P BSE LargeMidCap. The two factors with the highest information ratio in each of the market cycle phases are circled.

HOW DO SINGLE FACTORS PERFORM IN DIFFERENT MARKET REGIMES IN INDIA? (2)


23

Source: S&P Dow Jones Indices LLC. Data from October 2005 to June 2017. The S&P BSE Dividend Portfolio and S&P BSE Equal-Weighted Portfolio are hypothetical portfolios. Correlation

calculated using excess price returns over S&P BSE LargeMidCap. Index performance based on price return in INR. Past performance is no guarantee of future results. Table is provided for

illustrative purposes and reflects hypothetical historical performance. Please see the Performance Disclosure in the report for more information regarding the inherent limitations associated

with back-tested performance.

EVOLVING FROM SINGLE-FACTOR TO MULTIFACTOR INVESTING

• Blending factors to form multifactor portfolios may potentially help to deliver smootherexcess return across business and market cycles

• Bucket factors into cyclical and defensive factors

• Correlation among factors is a common consideration in the construction of multifactorportfolios.

Correlation Matrix

of Factor vs S&P BSE

LargeMidCap

Value Momentum Quality Low-Vol Dividend Size

Value (32%) (29%) (45%) 85% 80%

Momentum (32%) 28% 25% (31%) (29%)

Quality (29%) 28% 75% (9%) (19%)

Low-Vol (45%) 25% 75% (24%) (34%)

Dividend 85% (31%) (9%) (24%) 78%

Size 80% (29%) (19%) (34%) 78%

http://www.asiaindex.co.in/documents/research/research-factor-performance-across-different-macroeconomic-regimes-in-india.pdf?


SUMMARY - FACTOR INVESTING

24

Source: S&P Dow Jones Indices, Past performances is not a guarantee of future results. It is not possible to directly invest in any index

1. Low Volatility & Quality were the best performing factors in the Indian context

2. Factors tended to exhibit cyclicality with periods of out-/under- performance

3. Value, dividend & size displayed pro-cyclical characteristics whereas low-volatility

and quality showed defensive characteristics

4. Factor can act as potential tools to implement active views

5. Blending factors in a portfolio to diversify factor exposure may help deliver smoother

excess return across market cycles

6. Correlation plays an important consideration when combining factors



Thank you

Akash Jain

[email protected]

mailto:[email protected]


PERFORMANCE DISCLOSURE

26

Charts and graphs are provided for illustrative purposes. Past performance is no guarantee of future results. These charts and graphs may reflect hypothetical

historical performance. All information presented prior to the launch date is back-tested. Back-tested performance is not actual performance, but is hypothetical.

The back-test calculations are based on the same methodology that was in effect when the index was officially launched. However, it should be noted that the

historic calculations of an Economic Index may change from month to month based on revisions to the underlying economic data used in the calculation of the

index. Complete index methodology details are available at www.spdji.com and www.asiaindex.co.in. It is not possible to invest directly in an index.

AIPL defines various dates to assist our clients in providing transparency on their products. The First Value Date is the first day for which there is a calculated

value (either live or back-tested) for a given index. The Base Date is the date at which the Index is set at a fixed value for calculation purposes. The Launch Date

designates the date upon which the values of an index are first considered live: index values provided for any date or time period prior to the index’s Launch Date

are considered back-tested. AIPL defines the Launch Date as the date by which the values of an index are known to have been released to the public, for example

via the company’s public website or its data feed to external parties.

Past performance of the Index is not an indication of future results. Prospective application of the methodology used to construct the Index may not result in

performance commensurate with the back-test returns shown. The back-test period does not necessarily correspond to the entire available history of the Index.

Please refer to the methodology paper for the Index, available at www.spdji.com and www.asiaindex.co.in for more details about the index, including the manner in

which it is rebalanced, the timing of such rebalancing, criteria for additions and deletions, as well as all index calculations.

Another limitation of using back-tested information is that the back-tested calculation is generally prepared with the benefit of hindsight. Back-tested information

reflects the application of the index methodology and selection of index constituents in hindsight. No hypothetical record can completely account for the impact of

financial risk in actual trading. For example, there are numerous factors related to the equities, fixed income, or commodities markets in general which cannot be,

and have not been accounted for in the preparation of the index information set forth, all of which can affect actual performance.

Index returns shown do not represent the results of actual trading of investable assets/securities. AIPL or its agent maintains the S&P BSE Indices and calculates

the Index levels and performance shown or discussed, but does not manage actual assets. Index returns do not reflect payment of any sales charges or fees an

investor may pay to purchase the securities underlying the Index or investment funds that are intended to track the performance of the Index. The imposition of

these fees and charges would cause actual and back-tested performance of the securities/fund to be lower than the Index performance shown. As a simple

example, if an index returned 10% on a US $100,000 investment for a 12-month period (or US $10,000) and an actual asset-based fee of 1.5% was imposed at

the end of the period on the investment plus accrued interest (or US $1,650), the net return would be 8.35% (or US $8,350) for the year. Over a three year period,

an annual 1.5% fee taken at year end with an assumed 10% return per year would result in a cumulative gross return of 33.10%, a total fee of US $5,375, and a

cumulative net return of 27.2% (or US $27,200).


GENERAL DISCLAIMER

27

© Asia Index Private Limited 2018. All rights reserved.

The S&P BSE Indices (the “Indices”) are published by Asia Index Private Limited (“AIPL”), which is a joint venture among affiliates of S&P Dow Jones Indices LLC (“SPDJI”) and

BSE Limited (“BSE”). Standard & Poor’s® and S&P® are registered trademarks of Standard & Poor’s Financial Services LLC (“S&P”) and Dow Jones® is a registered trademark

of Dow Jones Trademark Holdings LLC (“Dow Jones”). BSE® and SENSEX® are registered trademarks of BSE. These trademarks have been licensed to AIPL.

Redistribution, reproduction and/or photocopying in whole or in part are prohibited without written permission. This document does not constitute an offer of services in

jurisdictions where AIPL, BSE, S&P Dow Jones Indices LLC or their respective affiliates (collectively “AIPL Companies”) do not have the necessary licenses. All information

provided by AIPL Companies is impersonal and not tailored to the needs of any person, entity or group of persons. AIPL Companies receive compensation in connection with

licensing its indices to third parties. Past performance of an index is not a guarantee of future results.

It is not possible to invest directly in an index. Exposure to an asset class represented by an index is available through investable instruments based on that index. AIPL

Companies do not sponsor, endorse, sell, promote or manage any investment fund or other investment vehicle that is offered by third parties and that seeks to provide an

investment return based on the performance of any index. AIPL Companies make no assurance that investment products based on the index will accurately track index

performance or provide positive investment returns. AIPL and S&P Dow Jones Indices LLC are not investment advisors, and the AIPL Companies make no representation

regarding the advisability of investing in any such investment fund or other investment vehicle. A decision to invest in any such investment fund or other investment vehicle

should not be made in reliance on any of the statements set forth in this document. Prospective investors are advised to make an investment in any such fund or other vehicle

only after carefully considering the risks associated with investing in such funds, as detailed in an offering memorandum or similar document that is prepared by or on behalf of

the issuer of the investment fund or other vehicle. Inclusion of a security within an index is not a recommendation by the AIPL Companies to buy, sell, or hold such security, nor

is it considered to be investment advice. Closing prices for S&P BSE Indices are calculated by AIPL or its agent based on the closing price of the individual constituents of the

index as set by their primary exchange. Closing prices are received by AIPL or its agent from one of its third party vendors and verified by comparing them with prices from an

alternative vendor. The vendors receive the closing price from the primary exchanges. Real-time intraday prices are calculated similarly without a second verification.

These materials have been prepared solely for informational purposes based upon information generally available to the public from sources believed to be reliable. No content

contained in these materials (including index data, ratings, credit-related analyses and data, model, software or other application or output therefrom) or any part thereof

(Content) may be modified, reverse-engineered, reproduced or distributed in any form by any means, or stored in a database or retrieval system, without the prior written

permission of AIPL. The Content shall not be used for any unlawful or unauthorized purposes. AIPL and its third-party data providers and licensors and the other AIPL

Companies (collectively “AIPL Parties”) do not guarantee the accuracy, completeness, timeliness or availability of the Content. The AIPL Parties are not responsible for any

errors or omissions, regardless of the cause, for the results obtained from the use of the Content. THE CONTENT IS PROVIDED ON AN “AS IS” BASIS. THE AIPL PARTIES

DISCLAIM ANY AND ALL EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, ANY WARRANTIES OF MERCHANTABILITY OR FITNESS FOR A

PARTICULAR PURPOSE OR USE. In no event shall the AIPL Parties be liable to any party for any direct, indirect, incidental, exemplary, compensatory, punitive, special or

consequential damages, costs, expenses, legal fees, or losses (including, without limitation, lost income or lost profits and opportunity costs) in connection with any use of the

Content even if advised of the possibility of such damages.

NOT FOR MASS CIRCULATION - FOR DISCUSSIONS WITH INTENDED RECEIPIENTS ONLY

The matter contained in this material is based on the personal views of the author. No person or

entity, including the employer of the author, is in any way responsible for any matter contained in this

material.

This material is not, and should not be construed as, an offer or solicitation for purchase or

sale of mutual fund units or any other securities.

Rise of Factor Investing

Anil Ghelani, CFAHead of Passive Investments & Products - DSP BlackRock

S&P BSE Indices WebinarApril 24, 2018

Passive Investments Landscape - Globally

29

Source: BlackRock, Internal

First ETF launched in 1993; today close to $ 5 trillion AUM

Recent rise of Smart Beta:

Assets invested in Smart Beta ETFs listed globally touched $ 1 trillion AUM

- also referred to as Strategic Beta or Factor ETFs


Passive Investments Landscape - India

30

0

500

1,000

1,500

2,000

2,500

3,000

3,500

Dec-13 Dec-14 Dec-15 Dec-16 Dec-17

Index Fund AUM

0

10,000

20,000

30,000

40,000

50,000

60,000

70,000

80,000

90,000

Dec-13 Dec-14 Dec-15 Dec-16 Dec-17

ETF AUM

Mar-18 Dec-17 Dec-16 Dec-15 Dec-14 Dec-13

Index Funds 3,161 3,150 2,140 2,123 1,770 753S&P BSE

Sensex & Nifty

ETFs52,764 48,178 19,381 6,022 1,020 425

Banking ETF 6,575 7,481 4,134 1,797 1,452 47Fixed Income

ETF1,977 1,783 1,693 925 872 711

Gold ETF 4,852 4,904 5,414 4,419 5,439 6,389

Government ETF 10,724 13,733 2,284 2,081 2,478 0

Others 747 704 407 189 164 79

TOTAL 80,800 79,933 35,454 17,557 13,195 8,405

Source – MFIE. All figures are in INR Crore


Drivers of Smart Beta

31

RETURN

ENHANCEMENT

IMPROVED

DIVERSIFICATION

RISK

REDUCTION

SMART BETA

Cost Saving

Transparency

Convenience


Benefits for different investors

32

One stop solution to the various needs of investors

Ind

ivid

ua

l In

ve

sto

rs

• Diversification of portfolio resulting in reduction of stock specific risk at low cost.

• Allows customization in investor’s portfolio consistent with their financial needs, risk tolerance & investment horizon.

FP

Is, In

sti

tuti

on

s ,P

F, In

su

ran

ce • Allows easy &

convenient asset allocation to broad segments of equity markets.

• Excellenthedging and liquidity management vehicle.

• Cash equitisation at low cost.

Alg

oT

rad

ers

; A

rbit

rag

eu

rs

• Low impact cost to carry out arbitrage between the cash & futures market.

• Can be used to cover option strategies on the Index.

• Liquid ETFs can be used for parking cash in between trades


Factor Investing - Single Factor & Multi-factor Indices

33

21.4 lakh Cr 0.8 lakh Cr0.01

lakh Cr

MUTUAL FUND INDUSTRY AUM PASSIVE AUM FACTOR-BASED AUM

Source – MFIE, CAMS. Data as on March, 2018


Passive Investments - Complementary Strategy for Investments

34

CORE ALLOCATION

Provides market

participation

No fund manager bias

Useful specially in the large

cap segment

SATELLITE ALLOCATION

There is a potential to

generate alpha

Changing trends, especially

in the large cap segment

Actively manage

d Satellite

Passively

managed Core


Private & Confidential 35

Thank you

Anil Ghelani

[email protected]


Disclaimers

In this material author has used information that is publicly available and Information gathered and used in this material is believed to be from

reliable sources. The author however does not warrant the accuracy, reasonableness and/or completeness of any information. The data/statistics

are given to explain general market trends in the securities market; it should not be construed as any research report / research recommendation.

This is a generic update on passive funds. it has included statements /opinions / recommendations in this document, which contain words, or

phrases such as ”will”, ”expect”, ”should”, ”believe” and similar expressions or variations of such expressions that are ”forward looking statements”.

Actual results may differ materially from those suggested by the forward looking statements due to risk or uncertainties associated with our

expectations with respect to, but not limited to, exposure to market risks, general economic and political conditions in India and other countries

globally, which have an impact on our services and / or investments, the monetary and interest policies of India, inflation, deflation, unanticipated

turbulence in interest rates, foreign exchange rates, equity prices or other rates or prices etc. All figures and other data given in this document are

dated and the same may or may not be relevant in future.

Mutual Fund investments are subject to market risks, read all scheme related documents carefully.

36NOT FOR MASS CIRCULATION - FOR DISCUSSIONS WITH INTENDED RECEIPIENTS ONLY


37

APPENDIX - SPIVA® SCORECARD


PERFORMANCE OF ACTIVE-FUNDS IN DIFFERENT MARKET REGIMES –LARGE CAP EQUITY

38

BULL PHASE

BEARPHASE

RECOVERY PHASE

BULL PHASE

BEAR PHASE RECOVERY PHASE

BULL PHASE BEAR PHASE

RECOVERYPHASES

0

50

100

150

200

250

300Equi-Wtd Indian Equity Large Cap Asset-Wtd Indian Equity Large Cap S&P BSE 100

Market CycleIndian Equity

Large Cap

Funds Beta (against S&P BSE 100)

BULL 0.95

BEAR 0.89

RECOVERY 0.89

Excess Returns over S&P BSE 100 (Equal-Weighted), Annualized %

BULL (0.0)

BEAR 0.4

RECOVERY (3.0)

Excess Returns over S&P BSE 100 (Asset-Weighted), Annualized %

BULL (0.2)

BEAR 0.8

RECOVERY (1.6)

Source: S&P Dow Jones Indices. Data as of Dec. 31, 2016, Data from Dec 31,2006 up to Dec. 31, 2016. Index performance based on total return [INR]. All data prior to launch date are

back-tested. Charts are provided for illustrative purposes and may reflect hypothetical historical performance. It is not possible to invest directly in an index. Past performance is no

guarantee of future results. Please see the Performance Disclosure at the end of this document for more information regarding the inherent limitations associated with back-tested

performance.


PERFORMANCE OF ACTIVE-FUNDS IN DIFFERENT MARKET REGIMES –MID/SMALL CAP EQUITY

39

Source: S&P Dow Jones Indices. Data as of Dec. 31, 2016, Data from Dec 31,2006 up to Dec. 31, 2016. Index performance based on total return [INR]. All

data prior to launch date are back-tested. Charts are provided for illustrative purposes and may reflect hypothetical historical performance. It is not

possible to invest directly in an index. Past performance is no guarantee of future results. Please see the Performance Disclosure at the end of this

document for more information regarding the inherent limitations associated with back-tested performance.

BEAR PHASE BULL PHASE

BEAR PHASE RECOVERY PHASE

BEAR PHASE

BULL PHASE

RECOVERY PHASE

BULL PHASE RECOVERYPHASE

0

50

100

150

200

250

300

350

400Equi-Wtd Indian Equity Mid/Small Cap Asset-Wtd Indian Equity Mid/Small Cap S&P BSE MidCap

Market CycleIndian Equity

Mid/Small Cap

Funds Beta (against S&P BSE MidCap)

BULL 0.84

BEAR 0.82

RECOVERY 0.79

Excess Returns over S&P BSE MidCap(Equal-Weighted), Annualized

BULL 2.0

BEAR 6.7

RECOVERY (6.3)

Excess Returns over S&P BSE MidCap(Asset-Weighted), Annualized

BULL 2.3

BEAR 8.4

RECOVERY (5.9)


APPENDIX A: PERCENTAGE OF FUNDS OUTPERFORMED BY THE INDEX

40

Source: S&P Dow Jones Indices LLC, Morningstar, and Association of Mutual Funds in India. Data as of Dec. 31, 2016. Returns are shown in INR. Past

performance is no guarantee of future results. Table is provided for illustrative purposes.

Year-End 2017

Year-End 2016


APPENDIX B1: SURVIVORSHIP AND STYLE CONSISTENCY OF INDIAN EQUITY FUNDS

41

Source: S&P Dow Jones Indices LLC, Morningstar, and Association of Mutual Funds in India. Data as of Dec. 31, 2017 Returns are shown in INR. Past


Year-End 2017


APPENDIX B2: SURVIVORSHIP AND STYLE CONSISTENCY OF INDIAN EQUITY FUNDS

42



Year-End 2016


APPENDIX C1: AVERAGE FUND PERFORMANCE

43

Source: S&P Dow Jones Indices LLC, Morningstar, and Association of Mutual Funds in India. Data as of Dec. 31, 2017 Returns are shown in INR. Past


Average Fund Performance (Equal Weighted)

Average Fund Performance (Asset Weighted)

Year-End 2017


APPENDIX C2: AVERAGE FUND PERFORMANCE

44



Average Fund Performance (Equal Weighted)

Average Fund Performance (Asset Weighted)

Year-End 2016


APPENDIX D1: QUARTILE BREAKPOINTS OF FUND PERFORMANCE

45



Year-End 2017


APPENDIX D2: QUARTILE BREAKPOINTS OF FUND PERFORMANCE

46



Year-End 2016


For financial professionals. Not for public distribution. PROPRIETARY. Permission for distribute or reprint or distribute any content from this presentation requires the required

permission of S&P Dow Jones Indices.

Source: Asia Index Private Limited; For more details please log on to www.asiaindex.co.in; as of July 31, 2016

47

S&P BSE India Bond Index

S&P BSE India Government Bond

Index

S&P BSE India 10 Year Sovereign Bond Index

S&P BSE India Sovereign Bond Index

S&P BSE India Government Bill Index

S&P BSE India Agency Bond Index

S&P BSE India Provincial Bond Index

S&P BSE India Corporate Bond

Index

S&P BSE India Financials Bond Index

S&P BSE India Services Bond Index

S&P BSE India Utilities Bond Index

S&P BSE India Industrials Bond Index

Money market Index S&P BSE Liquid Rate Index

Bond indices

APPENDIX E1: S&P BSE FIXED INCOME INDICES

http://www.asiaindex.co.in/


48

APPENDIX – FACTOR INVESTING


FACTOR INDICES V/S MARKET-CAP-WEIGHTED INDICES?

49

MARKET-CAP-WEIGHTED/ BROAD-BASED INDICES

FACTOR INDICES

Represents the entire investable opportunity set for market participants

Portfolio constituent selection based on specific factor criterion and aims to reflect an investors active views. (Not designed to replace market-cap-weighted indices )

Aims to capture long-term equity risk premium Targeted exposure to specific risk-factors

Generally have low portfolio turnover, high trading liquidity, and large investment capacity.

Generally have relatively higher turnover. There is a tradeoff between investibility and factor strength

Generally well diversified portfolios Factor portfolios such as value and low volatility can be significantly biased towards few sectors

Most common weighing method is based on float market capitalization

Weights are usually in relation to the stocks’ factor scores, which are used to create factor tilts within the index portfolios

Broad market indices are viewed as a barometer of the state of the overall market & economy

Performance of factor portfolios, like active funds, should be evaluated in the long run against a market-cap-weighted benchmark

S&P BSE 500S&P BSE 100S&P BSE LargeMidCap

S&P BSE Enhanced Value IndexS&P BSE Quality Index S&P BSE Low Volatility Index


50

The S&P BSE Dividend Portfolio and S&P BSE Equal-Weighted Portfolio are hypothetical portfolios. Source: S&P Dow Jones Indices LLC. Data from

March 2006 to March 2017. Figures in the table are average figures for the semiannually rebalanced portfolios. Past performance is no guarantee of

future results. Table is provided for illustrative purposes and reflects hypothetical historical performance. Please see the Performance Disclosure at

the end of this document for more information regarding the inherent limitations associated with back-tested performance.

FACTOR PORTFOLIOS SECTOR BIAS VERSUS THE S&P BSE LARGEMIDCAP


51





FACTOR PERFORMANCE IN EACH BUSINESS CYCLE PHASE


52





FACTOR PERFORMANCE IN EACH MARKET CYCLE PHASE


53





FACTOR PERFORMANCE IN DIFFERENT INVESTOR SENTIMENT REGIMES


54


Sep. 2005 to Apr. 2016. Figures in the table are average figures for the semiannually rebalanced portfolios. Past performance is no guarantee of future

results. Table is provided for illustrative purposes and reflects hypothetical historical performance. Please see the Performance Disclosure at the end

of this document for more information regarding the inherent limitations associated with back-tested performance.

UP/DOWN MARKET ANALYSIS

Low Volatility

Quality

Momentum

Value



1. Cash Equitization (eg. if a fund witnesses solid AUM growth, the fund manager may

require a couple of days to deploy. To avoid cash drag or underperforming the

benchmark, they can temporarily park some of the cash amount in an ETF that offers

similar style exposure and target risk)

2. Portfolio diversification

3. Tactical adjustments to portfolios

4. Core-satellite investment approach (investors can add ETF’s to express their short

term tactical views eg. If an investor expects a short term speed block in a long term bull

market, due to policy decision raising government bond yields, than rather than shifting

entire portfolio, one can quickly implement a tilt towards quality via a factor ETF)

5. Hedging (Inverse ETFs, leveraged ETFs, and currency ETFs can be used to hedge the

broad portfolios )

HOW INSTITUTIONS ARE USING SMART BETA ?



Exhibit: Overview of the S&P BSE Single-Factor Indices and Hypothetical Portfolios

FACTOR INDEX DESCRIPTION

Low VolatilityS&P BSE Low

Volatility Index

The 30 least volatile companies from the S&P BSE LargeMidCap, weighted by

inverse proportion to their volatility and subject to a stock capping of 5%.

Volatility is defined as the standard deviation of a security’s daily price return over

the one-year period.

MomentumS&P BSE Momentum

Index

The 30 companies from the S&P BSE LargeMidCap with the highest momentum

scores. Constituents are weighted by the product of momentum score and float-

adjusted market capitalization (FMC) and subject to stock capping of a minimum

of 5% or three times the FMC weight in the eligible index universe. Momentum

score is computed as 12-month price change, excluding the most recent month,

divided by standard deviation of price return for the same period.

ValueS&P BSE Enhanced

Value Index

The 30 companies from the S&P BSE LargeMidCap with the highest value

scores, weighted by the product of value score and FMC and subject to sector

capping of 30% and stock capping of a minimum of 5% or 20 times the FMC

weight in the eligible index universe. Value score is calculated based on book-to-

price, earnings-to-price, and sales-to-price ratios.

QualityS&P BSE Quality

Index

The 30 companies from the S&P BSE LargeMidCap with the highest quality

scores, weighted by the product of quality score and FMC and subject to sector

capping of 30% and stock capping of a minimum of 5% or 20 times the FMC

weight in the eligible index universe. Quality score is calculated based on return

on equity, accruals ratio, and financial leverage ratio.

DividendS&P BSE Dividend

Portfolio

The 30 companies from S&P BSE LargeMidCap with the highest dividend yield,

weighted in relative proportions to their dividend yields subject to sector capping

of 30% and stock capping of 5%.

SizeS&P BSE Equal-

Weighted Portfolio

All constituents from S&P BSE LargeMidCap weighted equally constitute the

portfolio.

INDEX METHODOLOGIES

The S&P BSE Dividend Portfolio and S&P BSE Equal-Weighted Portfolio are hypothetical portfolios. Source: S&P Dow Jones Indices

LLC. Past performance is no guarantee of future results. Table is provided for illustrative purposes and reflects hypothetical historical

performance. Please see the Performance Disclosure at the end of this document for more information regarding the inherent limitations

associated with back-tested performance.

https://spindices.com/indices/strategy/sp-bse-low-volatility-index

https://spindices.com/indices/strategy/sp-bse-momentum-index

https://spindices.com/indices/strategy/sp-bse-enhanced-value-index

https://spindices.com/indices/strategy/sp-bse-quality-index


57

GROWTH IN AUM OF MARKET CAP BETA VERSUS SMART BETA PASSIVE PRODUCTS

Source: “ETFGI. https://www.researchpool.com/download/?report_id=1570482&show_pdf_data=true“Chart is provided for illustrative purposes.

https://www.researchpool.com/download/?report_id=1570482&show_pdf_data=true


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