Current NAV: The Current Net Asset Value of the Axis Quant Fund - Regular Plan as of Mar 07, 2024 is Rs 15.47 for Growth option of its Regular plan. 2. Returns: Its trailing returns over different time periods are: 42.83% (1yr) and 17.63% (since launch).Current NAV: The Current Net Asset Value of the Axis Quant Fund - Regular Plan as of Mar 07, 2024 is Rs 15.47 for Growth option of its Regular plan. 2. Returns: Its trailing returns over different time periods are: 42.83% (1yr) and 17.63% (since launch).

1. Axis Quant Fund
(An open ended equity scheme following a quantitative model)
This product is suitable for investors who are seeking*:
• Capital appreciation over long term.
• An equity scheme that invests in equity and equity related instruments selected
based on quant model.
*Investors should consult their financial advisers if in doubt about whether the product
is suitable for them.
The product labelling assigned during the New Fund Offer is based on internal assessment of the Scheme Characteristics or model
portfolio and the same may vary post NFO when actual investments are made.

2. 2
Equity investors path to wealth creation
Identify quality
companies using
Quantitative and
Qualitative parameters
Buy them at a
reasonable price
Invest for
the long term

3. 3
Avoiding wealth destructors can help in
achieving long term wealth creation
Source: Bloomberg, An investment of INR 1 lakh considered in BSE 100 for the 10 year period from 31st Dec 2010 to 31st Dec 2020.
Past performance may or may not be sustained in future.
1 1 1
2.3 (8.6% CAGR)
10.9 (26.9% CAGR)
0.9 (-0.8% CAGR)
0
2
4
6
8
10
12
BSE100 Index Top Quartile Bottom Quartile
(INR Lakh)
Investment (Dec 10)
Value After 10 years (Dec 20)
Avoiding stocks in the bottom quartile is a critical as selecting winners in the Top quartile.

4. 4
Data increasingly driving Fund Management
decisions
Data explosion:
A change in
investment
paradigm
Structural recording of data
Transparency in data disclosures
Deeper data history
Better analysis and
assimilation of information
Accelerated decision making Efficiency in investment process

5. 5
Usage of Quantitative data can compliment
Traditional Fund Management Process and
can be an alternative to Alpha generation

6. 6
A Quant approach can provide a strong framework
Better risk
adjusted
performance
Robust
investment process
Performance
across market
cycles
Data usage in a
structured
format
Rules
based
approach
Systematic
decision
making Enhanced
risk management
Discipline

7. 7
Presenting
Axis Quant Fund
(An open ended equity scheme following a
quantitative model)
A fundamentally driven quant based approach

8. 8
Axis Quant Fund
Fundamental
approach
Rule based
criteria
Axis
Quant Fund
Use of factors like Quality,
Growth, Value
Usage of risk factors like
sector/ stock constraints,
rebalancing frequency
The parameters given above are for explaining quantitative model proposed to be used by the Scheme. The fund manager at his discretion may modify
parameters to be used in quantitative model. Investors are requested to refer to detailed asset allocation and investment strategy given in Scheme
Information Document for complete details.

9. 9
Investment philosophy
Using Q-GARP (1/2)
A philosophy that aims to identify Quality stocks in combination with the tenets of Growth and Value investing
The approach focuses on selecting a portfolio of Quality stocks with good Growth but At a Reasonable Price
The parameters given above are for explaining quantitative model proposed to be used by the Scheme. The fund manager at his discretion may modify
parameters to be used in quantitative model. Investors are requested to refer to detailed asset allocation and investment strategy given in Scheme
Information Document for complete details.
Parameters comprising Q-GARP
The tendency of lower risk and higher quality assets to generate
higher risk adjusted returns
Quality
A parameter that captures the excess return on stocks due to improving
growth prospects
Growth
An important parameter that acts as a safety net by identifying the
difference between market price and the fair value
Valuation

10. 10
Investment philosophy
Using Q-GARP (2/2)
The parameters given above are for explaining quantitative model proposed to be used by the Scheme. The fund manager at his discretion may modify
parameters to be used in quantitative model. Investors are requested to refer to detailed asset allocation and investment strategy given in Scheme
Information Document for complete details.
Quality
Growth
Valuation
Parameters
• ROE / RoCE
• Debt / Equity (Leverage)
• Volatility
Parameters
• Earnings improvement
• Change in profit margins
• Analyst forecasts
Parameters
• P/E
• P/B
• Dividend yield
• Price to sales
All
Seasons
Portfolio
capturing the
best of the main
styles

11. 11
From theory to practise: Application of Q-GARP
The parameters given above are for explaining quantitative model proposed to be used by the Scheme. The fund manager at his discretion may modify
parameters to be used in quantitative model. Investors are requested to refer to detailed asset allocation and investment strategy given in Scheme
Information Document for complete details.
Name Sector Quality Growth Valuation Composite
Score*
Stock A Industrials 2.27 2.61 1.92 6.8
Stock B Financials 0.4 1.21 3.33 4.94
Stock C Financials 0.75 1.8 1.3 3.85
Stock D IT 1.58 0.74 1.21 3.53
Stock E Consumer Staples 3.31 0.16 -0.94 2.53
Stock F Utilities 1.46 -0.23 0.06 1.29
Each stock is assessed along all the dimensions of Q-GARP and a composite score is calculated based on the individual metrics
Higher the score, higher the probability of weight to a stock

12. 12
Portfolio construction, review and monitoring
The portfolio will be reviewed & monitored on
a pre-defined frequency
Composite
Ranking
Stock
level
constraint
Sector
level
constraint
Stock
Risk
Portfolio
Stock level constraint is based on the liquidity of
the stock
For detailed asset allocation and investment strategy, please refer Scheme Information Document of the Scheme
Ad-hoc rebalancing only in case of exceptional
situations (Adverse news, Management or Board
issues, Material litigation issues)

13. 13
Case study: Efficient risk management
The parameters given above are for explaining quantitative model proposed to be used by the Scheme. The fund manager at his discretion may modify
parameters to be used in quantitative model. Investors are requested to refer to detailed asset allocation and investment strategy given in Scheme
Information Document for complete details.
Weight allocation process(*) Stock B Stock C
Sector Financials Financials
Composite Score (A) 4.94 3.85
Risk of the stock (B) 11 4
Composite Score to Risk ratio (A/B) 0.45 0.96
Other risk aspects Low liquidity stock Highly liquid large
in the mid cap space cap stock
Weight in the portfolio Lower Higher
• Risk plays an important role in
determining the sizing of the stock
in the portfolio
• Stock C has a higher allocation
compared to Stock B as the
incrementally higher composite
score in Stock B doesn’t
compensate for higher risk
• Expected return is one of the
inputs in the process, risk is
also an equally important
consideration
The risk of the stock is a function of its volatility

14. 14
In Summary
Stocks are eliminated from the universe based on
• Minimum criteria for
• Data
• Market Cap
• Liquidity
• Companies with Red Flags also eliminated based on input from sector experts
• Stocks are evaluated along multiple parameters and across different styles
• Each stock gets a ranking along each of the parameters
• Composite final rank/score is calculated from individual ranks
Portfolio of 50-60 stocks constructed using an optimization process that utilizes
• Composite Rank
• Risk of the stock
• Stock sizing constraints
• Sector Constraints
Universe of Listed Stocks
Elimination Criteria
Scoring &
Ranking
Portfolio
Portfolio
review
and
monitoring
For detailed asset allocation and investment strategy, please refer Scheme Information Document of the Scheme.

15. 15
Model Performance
and Attributes

16. 16
Model performance: Historic record
Source: AceMF, Axis AMC Research. Quant model performance is post fees and expenses of 2.5% p.a. Past performance may or may not sustain in future. All
information contained in this slide is for illustration purpose only to show how quant models function. The model performance is derived based on back tested result
considering Quality, Growth and Value as parameters. The back tested result does not in any way indicate the performance of the Scheme. The actual model and the
Scheme portfolio shall be constructed based on the provisions in the Scheme Information Document. Data is from 31st Dec 2006 to 31st Dec 2020.
The model has managed to beat the benchmark 10 times in the last 14 years with
an average outperformance of 7.6%
Period Quant Model BSE 200TRI (B) Outperformance
(A) C = A-B
CY 2020 25.7% 17.9% 7.80%
CY 2019 9.6% 10.4% -0.80%
CY 2018 -0.4% 0.8% -1.20%
CY 2017 41.2% 35.0% 6.20%
CY 2016 6.7% 5.2% 1.50%
CY 2015 9.6% -0.2% 9.80%
CY 2014 49.3% 37.4% 11.90%
CY 2013 10.5% 6.1% 4.40%
CY 2012 30.1% 33.2% -3.10%
CY 2011 -16.3% -26.0% 9.70%
CY 2010 29.3% 17.8% 11.50%
CY 2009 85.5% 90.9% -5.40%
CY 2008 -52.4% -55.9% 3.50%
CY 2007 72.4% 62.3% 10.10%

17. 17
Model performance: Rolling return
Source: AceMF, Axis AMC Research. Quant model performance is post fees and expenses of 2.5% p.a. Past performance may or may not sustain in future. All
information contained in this slide is for illustration purpose only to show how quant models function. The model performance is derived based on back tested result
considering Quality, Growth and Value as parameters. The back tested result does not in any way indicate the performance of the Scheme. The actual model and the
Scheme portfolio shall be constructed based on the provisions in the Scheme Information Document. Data is from 31st Dec 2006 to 31st Dec 2020.
-5.0%
0.0%
5.0%
10.0%
15.0%
20.0%
25.0%
30.0%
35.0%
40.0%
3 Year rolling return
Model S&P BSE 200 TRI
On a 3 year rolling return,
the model has never
delivered negative
returns
In the past 17 years,
the model has
outperformed the
benchmark on 99.2%
instances
3
years
17
years

18. 18
Model performance: Recent experience
Source: AceMF, Axis AMC Research. Quant model performance is post fees and expenses of 2.5% p.a. Past performance may or may not sustain in future. All
information contained in this slide is for illustration purpose only to show how quant models function. The model performance is derived based on back tested result
considering Quality, Growth and Value as parameters. The back tested result does not in any way indicate the performance of the Scheme. The actual model and the
Scheme portfolio shall be constructed based on the provisions in the Scheme Information Document. Data is from 31st Dec 2006 to 31st Dec 2020.
-40.00%
-35.00%
-30.00%
-25.00%
-20.00%
-15.00%
-10.00%
-5.00%
0.00%
Jan-20 Jan-20 Mar-20 Apr-20 May-20 Jun-20 Jul-20 Aug-20 Sep-20 Oct-20 Nov-20 Dec-20
Drawdown Experience in 2020
Portfolio BSE 200
During the pullback, the
portfolio recovered the
initial capital 3 months
earlier (Aug-20) than
benchmark (Nov -20)
During the market
correction in Mar-20,
the portfolio fell lesser
compared to the
benchmark

19. 19
Source: Axis MF Research, Bloomberg. All information contained in this slide is for illustration purpose only. The actual model and the Scheme
portfolio shall be constructed based on the provisions in the Scheme Information Document
Portfolio Characteristics
0.0
0.5
1.0
1.5
2.0
2.5
Dividend Yield
Quant model S&P BSE 200
0.0
5.0
10.0
15.0
20.0
25.0
Weight average RoE
Quant model S&P BSE 200
40.0
50.0
60.0
70.0
80.0
90.0
Model allocation to Large caps
Model allocation to Large caps

20. 20
Why invest in Axis Quant Fund?
• The strategy will appeal to investors looking to diversify their existing portfolio of funds through a novel approach to investing
• The key reasons to invest in the fund include
Diversified portfolio across sectors and
market capitalization
A unique proposition of a fundamentally driven
quantitative approach
Unbiased approach to portfolio management
Aims to outperform across cycles
Target Audience/
Client Base

21. 21
Product details
Scheme
Name
Axis Quant Fund
Scheme
Benchmark S&P BSE 200 TRI
Investment
Objective
To generate long-term capital appreciation by investing primarily in equity and equity related instruments selected
based on a quantitative model. However, there can be no assurance that the investment objective of the Scheme will
be achieved.
Fund
Manager
Deepak Agrawal and Hitesh Das (Foreign securities)
Asset
Allocation
Equity & Equity related instruments of selected companies based on a quantitative model: 80% to 100%; Other Equity
and Equity related instruments: 0% to 20%; Debt & Money Market Instruments: 0% to 20%; Units issued by REITs &
InvITs: 0% to 10%
Exit Load
If redeemed/ switched-out within 12 months - For 10% of investment: Nil, For remaining investment: 1%
If redeemed/switched out after 12 months from the date of allotment: Nil
Minimum
Application
Amount
Rs 5,000 and in multiples of Rs 1/- thereafter

22. 22
Disclaimer
Past performance may or may not be sustained in the future.
The data/statistics / information given are to explain various concepts and general market trends in the securities market.
The information on sector(s)/stock(s)/issuer(s) mentioned in this presentation is provided on the basis of publicly available information
illustration purpose only and should not be construed as any investment advice / research report / recommendation to buy / sell / hold
securities by Axis AMC / Axis Mutual Fund. The Fund manager may or may not choose to have any present / future position in these
sector(s)/ stock(s)/ issuer(s).
Statutory Details: Axis Mutual Fund has been established as a Trust under the Indian Trusts Act, 1882, sponsored by Axis Bank Ltd.
(liability restricted to ` 1 Lakh). Trustee: Axis Mutual Fund Trustee Ltd. Investment Manager: Axis Asset Management Co. Ltd. (the AMC).
Risk Factors: Axis Bank Limited is not liable or responsible for any loss or shortfall resulting from the operation of the scheme.
This document represents the views of Axis Asset Management Co. Ltd. and must not be taken as the basis for an investment decision.
Neither Axis Mutual Fund, Axis Mutual Fund Trustee Limited nor Axis Asset Management Company Limited, its Directors or associates shall
be liable for any damages including lost revenue or lost profits that may arise from the use of the information contained herein. No
representation or warranty is made as to the accuracy, completeness or fairness of the information and opinions contained herein. The AMC
reserves the right to make modifications and alterations to this statement as may be required from time to time.
Mutual Fund Investments are subject to market risks, read all scheme related documents carefully.

23. 23
ICICI Securities Ltd. Disclaimer
ICICI Securities Ltd.( I-Sec). Registered office of I-Sec is at ICICI Securities Ltd. - ICICI Centre, H. T. Parekh Marg, Churchgate, Mumbai -
400020, India, Tel No : 022 - 2288 2460, 022 - 2288 2470. AMFI Regn. No.: ARN-0845. We are distributors for Mutual funds. Mutual Fund
Investments are subject to market risks, read all scheme related documents carefully. The contents herein above shall not be
considered as an invitation or persuasion to trade or invest. I-Sec and affiliates accept no liabilities for any loss or damage of any kind arising
out of any actions taken in reliance thereon.

24. 24
Thank You