Your current stock screening method has a flaw. Find out the solution.

Summary

In this webinar, Par, a co-founder of Ban Research, introduces B, Quant, a quantitative investment tool designed to streamline stock screening and enhance returns. The tool focuses on three key factors: growth, quality, and valuation, using mutual fund holdings as a proxy for quality. Par explains the model's simple yet effective rules, demonstrates its historical outperformance, and discusses strategies for managing risk and avoiding bankruptcy-prone companies. The session also addresses questions about the tool's application, exit strategies, and potential adaptations for different market cap criteria.

Takeaways

• 😀 The webinar was hosted by Par, one of the co-founders of Ban Research, along with his colleagues Na and Sanjay.
• 📈 Ban Research was launched in early 2022 with the aim to provide quality research and serve as an extended research team for institutions, family offices, PMS advisers, and investment advisors.
• 🏆 The response to Ban Research since its launch has been overwhelming, with a focus on delivering value to early subscribers.
• 💡 The founders identified a gap in the market for DIY investors who lack the time and resources to generate quality research-based insights, leading to the creation of Ban Core.
• 📚 Ban Core aims to empower investors to make informed decisions by understanding what they own, why they own it, and the risks involved.
• 🔍 The presentation highlighted the limitations of traditional stock screening methods, which often result in an unmanageable number of companies to analyze.
• 🤖 The introduction of Ban Quant aims to streamline the investment process through factor-based or quantitative investing, which can lead to significant outperformance.
• 📉 The webinar discussed the importance of not just chasing growth but balancing it with quality and valuation to avoid poor risk-adjusted returns.
• 📊 The use of the Alman Z-score and Sharpe ratio in the model helps to address risk and reward, aiming to provide a robust investment strategy.
• 📝 The model's strategy involves ranking stocks based on growth, quality, and valuation, which has historically outperformed the market with less drawdown.
• 🔄 The model is updated regularly, and the top 25 to 30 stocks are selected monthly, with the potential to adjust the number of stocks as per subscriber needs.

Q & A

What is the purpose of Ban Research and how was it initiated?

Ban Research was initiated by Par, Na, and Sanjay in early 2022 to deliver quality research and serve as an extended research team for institutions, family offices, PMS advisers, and investment advisors. The idea was born out of the common problem faced by employers in hiring and retaining good talent, especially in core research teams.

What is the main goal of B, Quant in the context of Ban Research's offerings?

B, Quant aims to address the problem of traditional screening methods that yield too many companies to screen effectively. It provides a manageable list of 25 to 30 companies, which have been back-tested for returns, giving investors more conviction in their screening process.

How does Ban Research address the gap for DIY investors?

Ban Research aims to fill the gap for DIY investors by providing detailed reports and insights that these investors may not have the time or resources to generate themselves. The goal is to enable informed decision-making, ensuring investors know what they own, why they own it, and the risks involved.

What is the significance of the detailed reports provided by Ban Research?

The detailed reports are intended to ensure that investors have a comprehensive understanding of the business they are investing in. The level of detail is meant to convey everything that Ban Research knows about the business, allowing investors to make informed decisions.

How does the speaker view the role of automation in investing?

The speaker is a big fan of automating things that can be automated in investing. He believes that factor-based or quant investing allows for the creation of significant outperformance through a structured, simple process.

What is the strategy behind limiting the number of companies in B, Quant to 25 to 30?

Limiting the number of companies to 25 to 30 creates a manageable list for investors. This makes it easier for investors to screen and select potential investment opportunities, thereby increasing the efficiency of the investment process.

How does Ban Research's model address the issue of company quality in investment decisions?

Ban Research's model uses a combination of growth, quality, and valuation metrics to rank companies. The Return on Capital (ROC) is used as a powerful measure of business quality and capital allocation, helping to ensure that the companies selected are of good quality.

What is the role of mutual funds in Ban Research's investment strategy?

Mutual funds are considered 'smart money' in the strategy. The model follows the smart money to capture qualitative aspects of a business that may not be directly captured through quantitative metrics alone.

How does the speaker suggest managing the risk while chasing growth in the market?

The speaker suggests balancing growth with valuation and quality metrics to manage risk. By not investing at absurdly high prices and avoiding low-quality companies, the model aims to catch growth opportunities while controlling risk.

What is the exit strategy for stocks selected through Ban Research's model?

The exit strategy is not explicitly detailed in the script, but it is implied that stocks would be exited based on changes in their growth, quality, and valuation metrics that no longer align with the model's criteria.

How frequently is the Ban Research model updated and how are new stock ideas generated?

The model is updated regularly, and new stock ideas are generated every month. The team works on three to four ideas each month and shares compelling ones with subscribers.

Does Ban Research have plans to provide video content alongside their research reports?

While there are no concrete plans mentioned in the script, the team is deliberating the idea of providing video content to enhance understanding and confidence in their research and quant model.

Outlines

00:00

😀 Introduction to B.research Webinar

Par, a co-founder of Passion Research, welcomes participants to the first B.research webinar. He expresses gratitude for the trust placed in Ban, Core by early subscribers since its launch a month ago. Par introduces himself and his colleagues Na and Sanjay, and shares their background, which includes meeting at a CFA coaching institute in 2015 and working with industry stalwarts. They identified a common problem in hiring and retaining talent in core research teams, leading to the launch of Ban, Research in early 2022. The platform aims to provide quality research to institutions, family offices, and investment advisors, ensuring business continuity despite team attrition. They also address the gap in research for DIY investors, aiming to enable informed decision-making and portfolio management.

05:03

😉 Challenges of Traditional Screening Methods

The speaker discusses the limitations of traditional stock screening methods, which can yield an overwhelming number of companies to analyze, even for full-time investors. The introduction of Ban, Quant aims to streamline this process by providing a more manageable list of companies to consider. The speaker emphasizes the importance of a disciplined approach to investing, using simple yet effective rules to generate investment ideas. The session also clarifies that the recommendations are not buy-sell advice but are meant to aid in the idea generation process.

10:06

📈 B. Quant's Approach to Investment Screening

The speaker outlines the B. Quant system, which uses a limited number of companies to create a manageable list for investment screening. The system incorporates historical performance data and applies various financial metrics to narrow down the investment universe. The focus is on quality, valuation, and growth, with an emphasis on risk-adjusted returns. The speaker also discusses the use of mutual funds as a proxy for 'smart money' and how their holdings can inform investment decisions.

15:09

💹 Performance Metrics and Data Analysis

The speaker delves into the performance metrics used by B. Quant, such as return on investment, draw-down, and risk-adjusted metrics like the Sharpe ratio. The goal is to select companies that have a history of good performance and are likely to continue doing so. The use of the Altman Z-score for bankruptcy prediction is also mentioned, as well as the strategy's performance compared to market indices like the Nifty 500.

20:17

🤔 The Pitfalls of Chasing High Growth

The speaker warns against the risks of investing solely in high-growth companies without considering valuation. They explain that the market often prices in high expectations, and when growth does not meet these expectations, stocks can be severely derated. The summary highlights the importance of balancing growth with valuation and quality to achieve better risk-adjusted returns.

25:21

📊 The Strategy's Historical Performance

The speaker presents data on the strategy's historical performance, showing that it has outperformed the benchmark index nearly 100% of the time. They also discuss the strategy's draw-down compared to the market and highlight the top winners and losers based on the strategy. The speaker emphasizes the importance of sticking with a proven strategy for the long term.

30:21

🤝 Engaging with the Audience

The speaker opens the floor for questions and engages with the audience, addressing concerns about mutual fund benchmarks, the exclusion of certain companies from the model, and the frequency of stock selection. They also discuss the possibility of adjusting the model to include more stocks or to focus on different market capitalizations.

35:22

🔍 Evaluating Quality and Using Tools

The speaker discusses how quality is evaluated in the context of the investment model, mentioning the use of Return on Capital (ROC) as a key metric. They also talk about the use of mutual fund scores and the importance of protecting against downside risk. The speaker emphasizes the regular use of the tool and the stability of the model.

40:23

📉 Managing Risk and Growth

The speaker addresses how the model manages risk while chasing growth, highlighting the importance of valuation in the investment process. They explain that the model balances growth with quality metrics and valuation to ensure that investments are not made at absurdly high prices or in low-quality companies.

45:27

🏁 Exit Strategy and Future Research

The speaker outlines the exit strategy for stocks within the model, which is based on ranking and not on technical indicators. They also discuss the frequency of releasing new stock ideas, which is based on the compelling nature of the research rather than a set schedule. The speaker mentions that there are no restrictions on market capitalization for the companies covered and that they are open to covering a wide range of companies.

50:28

🌟 Closing Remarks and Next Steps

The speaker thanks the participants for their engagement and answers a final question about providing video content to complement the research reports. They acknowledge the suggestion and indicate that they are considering it. The speaker concludes the webinar with a positive note, expressing hope that the team can continue to deliver valuable research and insights.

Keywords

💡Webinar

A webinar is an interactive online seminar or workshop that allows participants to learn or discuss a topic while being in different physical locations. In the context of the video, the webinar is the medium through which the presenter is sharing insights on investment strategies and discussing the launch of Ban Research, which aims to provide value to investors.

💡Attrition

Attrition refers to the rate at which employees leave a company, often due to various reasons such as better job opportunities, personal reasons, or dissatisfaction. In the video, the term is used metaphorically to describe the loss of key team members in a research team, emphasizing the importance of a stable core team for consistent business performance.

💡DIY Investors

DIY investors, which stands for 'Do It Yourself' investors, are individuals who manage their own investment portfolios without the help of a financial advisor. The video discusses the challenges faced by such investors, particularly the lack of time and resources to generate quality research-based insights, which is where Ban Research aims to assist.

💡Factor-Based Investing

Factor-based investing is an investment strategy that focuses on specific characteristics or 'factors' of stocks to achieve outperformance. In the video, the presenter discusses how even a simple structured process of factor-based investing can lead to significant outperformance in the market, emphasizing the potential of systematic investment strategies.

💡Quant Investing

Quant investing, short for quantitative investing, involves using mathematical models and algorithms to analyze and make decisions on investments. The video mentions the presenter's excitement about Quant investing as a method to automate investment decisions to a large extent, which aligns with the theme of systematic and data-driven investment strategies.

💡Screening Method

In investing, a screening method is a technique used to filter a large universe of investments down to a smaller list based on specific criteria. The video discusses the limitations of traditional screening methods, such as the inability to manage a large list of companies effectively, and introduces Ban Quant as a solution to provide a more manageable list of investment opportunities.

💡Risk-Adjusted Return

Risk-adjusted return is a measure that takes into account the risk undertaken to generate returns, often used to compare the performance of different investments. In the video, the presenter uses risk-adjusted metrics like the Sharpe Ratio to illustrate the effectiveness of their investment strategy in generating returns relative to the risk taken.

💡Mutual Fund

A mutual fund is an investment vehicle that pools money from many investors to invest in a diversified portfolio of stocks, bonds, or other assets. The video discusses the use of mutual funds as a proxy for 'smart money' in the investment strategy, suggesting that following the investment trends of mutual funds can be a wise approach.

💡Growth Quality Valuation (GQV)

Growth Quality Valuation is a term used in the video to describe a balanced approach to investing that considers the growth potential, quality of management, and valuation of a company. The presenter explains that their model ranks stocks based on these three factors to identify good investment opportunities.

💡Drawdown

Drawdown in investing refers to the peak-to-trough decline in the value of a portfolio. It is used as a measure of the largest loss from a peak before a new peak is achieved. The video mentions the importance of managing drawdown to ensure that investors remain comfortable and committed to the investment strategy.

💡Exit Strategy

An exit strategy in investing is a plan for selling off investments to realize gains or minimize losses. The video touches on the importance of having a clear exit strategy, although it does not delve into specifics, emphasizing the need for a systematic approach to both entering and exiting investments.

Highlights

Introduction to Ban Research's first webinar, expressing gratitude to early subscribers and outlining the commitment to adding value to their investing journey.

Par, one of the co-founders of Passion Research, introduces himself and his colleagues Na and Sanjay, highlighting their shared journey in investing since 2015.

The founders discuss their realization of the opportunity in addressing the common problem of hiring and retaining talent in core research teams within investment firms.

Launch of Ban Research in early 2022 with the purpose of delivering quality research and serving as an extended research team for institutions, family offices, and investment advisors.

Identification of a significant gap in serving DIY investors who lack the time and resources to generate actionable research-based insights.

Emphasis on the importance of informed decision-making for investors, knowing what they own, why they own it, and the risks involved.

The presentation of detailed reports by Ban Research to ensure investors are well-informed about the business they are investing in.

Introduction of B, Quant, a tool for automating investment processes and creating outperformance through factor-based or quantitative investing.

Discussion on the limitations of traditional screening methods and the introduction of Ban Quant to provide a more manageable list of companies for investment consideration.

Explanation of the rules and methodology behind Ban Quant, emphasizing simplicity and the exclusion of overly complex financial metrics.

Use of mutual fund holdings as a proxy for 'smart money' and a strategy to follow this smart money for investment insights.

Improvement in risk-adjusted returns by excluding companies with low mutual fund holdings and applying the Z-score bankruptcy rule.

Highlighting the importance of balancing growth with valuation and quality metrics when selecting investments to avoid overpaying for growth.

Demonstration of the strategy's historical performance, showing consistent outperformance over time with a controlled drawdown.

The founders' commitment to a disciplined, systematic approach, avoiding unnecessary complexity and maintaining simplicity in the investment process.

Openness to subscriber feedback and willingness to adjust the model, such as increasing the number of stocks in the output from 25 to 30 to 40 if requested.

Discussion on the exclusion of BFSI sector initially but plans to incorporate it in the future with a different set of rules.

Suggestion from a participant about the potential of applying the model to companies with a market cap below 10,000 CR and considering relaxation of certain criteria.

Acknowledgment of the challenge in identifying a starting universe for the model that includes all companies, including bankruptcies, and the ongoing efforts to refine this aspect.

The webinar concludes with a Q&A session where the founders address questions regarding the model's exit strategy, frequency of stock recommendations, and potential inclusion of video content for further clarity.

Transcripts

so hello everyone and uh welcome to B

research first uh webinar and thank you

for joining us with us today and taking

time out and first of all you know we

would like to

thank you all for placing trust in Ban

Core and being the early subscribers

since we have launched only a month or

so back and the response has been

overwhelming right and we are excited

and committed to delivering or adding a

good amount of value to your investing

Journey so my name is par and I'm one of

the co-founders of passion research with

me I have my colleague Na and Sanjay uh

so you know before we get started let me

just give a brief backr round about us

so uh I met NAIT Sanjay uh way back in

2015 you know when we started our

investing journey together and we met at

some CFA coaching Institute and since

then we have been in touch and luckily

for us uh we had the opportunity to work

with few of the industry stals in last 5

seven years right and uh so one F day

you know we were discussing all the

problems that the employers were facing

and uh you know one of the thing a

common problem that all of our employees

were facing was

of hiring a good talent and at the same

time retaining you know the talent uh

especially in the core research team and

that's when we realize that there's an

opportunity here and uh so in early 2022

we decided to launch ban research with a

sole purpose that we would be delivering

good research as well as be an extended

research amp

for the institutions family offices uh

PMS advisers or investment advisor as

such so that even if there's an

attrition in the core team uh you know

the main business of research does not

get impacted right but as we you know

progressed in our journey uh we realized

there was another significant Gap and

that was with DIY investors where you

know diligent and you know committed DIY

investors did not have time and the

resources to generate acable research

based insights and uh so that's where

you know we la to Bion core with a sole

purpose that investors should make

informed decision making right they

should know what they own it why they

own it and what are the risk involved

and they should be updated with whatever

is you know happening in their portfolio

and uh so that was the intention behind

it and as you can see most of you must

have gone through our reports that they

are quite detailed and that is the

reason why you know there are detail

that we want you to know everything and

everything that we know about the

business you should also know about

about the business if you you know read

the report right and that was the sole

purpose that the reports are so detailed

so the intention is not just to give you

buy and sell recommendation I think the

number of platforms giving that

intention is that you should be aware

right okay so uh after that also you

know so um today's session is about B

Quant and you know I'm very excited

about this session to be honest the sole

reason is so I am a big uh fan of

automating things that can be automated

to a large extent right and this is

where you know Factor based investing or

Quant investing uh comes into picture

where even if you follow a structured

simple structured process of investing

you can create a huge amount of

outperformance and uh many people

believe that's not possible and you know

they have their own apprehensions and

which is fair but you know if a simple

strategies can create huge amount of

performance uh you know if you just

stick with it for a long duration and

you know don't chicken out at the wrong

time right and that is what you will

also start Believing by the end of this

uh you know session so you know without

further Ado let me you know just start

so the reason you know we decided to add

a ban Quant type of a product was the

problem with today's screening method so

you know if if you you know let's just

uhu do an experiment and run a screener

uh let's say I run a screener where I

say that average return on Capital

employed is more than 15% sales growth

is around 10% which is a decent task not

to aggressive my p ratio is less than 20

and I don't want leverage companies and

essentially all the banks and nbfcs will

get weed out so if I run this query what

I get is almost get 152 companies to

screen from and to be honest uh for you

know full-time person like me also it is

difficult to screen for ideas from the

152 companies let alone you know

inv right

and right and

asol again we don't have any idea about

it so this is you know a a drawback that

this tradition screening method is

because we point in time right so this

is where you know ban cont comes in and

uh

so what uh this essentially gives me is

first number of companies Limited at 25

to 30 right and so 27 companies right 25

to 30 companies manageable list

right screen has been

backed invested what kind of returns I

would have generated the what CB I can

you know easily see

now I have much more conviction in the

screen

finally

performance right that was the sole

reason you know for adding this B con

and so you know for you to appreci

iate

outut so we will you know get basically

get into the rules and decode the rules

rules they very simple rules right and

you will be

surprised and so let's you know get

started uh so mandatory disclosure uh

that we are analist stock recommendation

don't take it as a buy sell

recommendation

um okay so you know when you are looking

for a stock you know idea generation

time then you find find trying to find a

new stock yeah you are trying to find a

new bride or groom you know to get

married we want everything right

but at least for the for

quality valuation

expensive is fantastic business

valuation probably you might I think

working

capital so again valuation quality grow

Market is not giving that kind of

respect to the business absence of

quality so any kind of business like

bright cor group or any that has some

issues CG issues or something like that

growth valuation but quality right but

since we need all three of them so what

we have tried to

do but you cannot

randomly sole reason is will

be before you know start going about and

you ranking the companies

clean set of

comp I would be more I would have more

good

conviction

so but before that let me

just starting

univers stared

second right and deta

fin what

March

model number October

out performance return you know

basically right so

datab so you know let's get into each

and

every so H just for a like to like

comparison Nifty 500 15% return generate

with a draw down basically

2

right

ma un starting

universe so

compar and this number should improve so

just for Simplicity this number is

higher the better right calmer also

higher the better and standard deviation

basically lower the better right and

higher the better just for the

perspective

sh sh is basically risk adjusted return

ke more than one is considered to be a

good number currently number and will

see

naturally

returns so again it's more of a

conservative

apprach number based Quant based

factored investing qualitative aspect of

a business does not get captured right

and sub smart way to do that to capture

it in your data is follow the smart

money which is your mutual funds right

and these are considered to be smart

money and mutual

funds if there is a sign of

trouble secondly

compies any

mut

lowf so just to give you over when I

exclude companies that have low mutual

fund holding

ex

secondly 47

4%

41 standard deviation

improve risk

adjusted impr basically right so so this

is all the Improvement that has happened

just by simple R this compy

obviously number of

compies

141 be at the same

time now just to appreciate what kind of

compan M fund rle so if you can

see as you can see 90%

plus ilfs Reliance communication

Reliance power all future retail all

kind of companies are coming in if you

look at the top 20

losers discuss Alman Z score now Alman

score bankruptcy rule

score is

below when I do that obviously number of

companies May which is natural

progression but say significant

Improvement I don't that's a good part

but what I'm you know

notice sorry down1 2 standard deviation

signicant risk adjusted metric almost

close to one

and

large as you can see average Market

19,000

19,000

right small midcap companies good

quality companies out and returns

improve you know increase right this is

just PL Simple Rules

mut finally if you can

see 47 26 0.46 close to double 0.93 simp

rules now let's move

on as you can see

right sharp

Improvement now so one of the data

cleaning exercise that we have done is

cannot Beed

model we'll move on finally

High Roc company is good for a business

right higher the r to probably company

would be a good wealth Creator and all

those more than 5%

more than

5%

2 as you can clearly

see stop risk adjusted return

basically what this tells me

right and as you can clearly

see low

sales everything is red everything is

more or less there's shades of green

here right so what this tells me is ke

when you in solely try to invest in a

high Growth

Company you are more likely to generate

low risk adjusted return return I

generate

reations

because Market any premium valuation and

when you invest at those premium

valuations and growth does not turn out

to be as it was expected by The Market

stock gets derated which results in this

kind of Po

performance data clearly

showc secondly why this kind of you know

poor standard deviation and sharp ratio

is generally small midap high grow

compies compared to large cap so

naturally the portfolio of companies

small grait as you can clearly

average

Market

obviously so you went down the map curve

which again increased the volatility in

your portfolio even if

you so let's say

July and July

because top 10 EPS growing company

second highest third highest fourth

highest

fifth

buckets on

basically simply

downward low

comp

naturally high growth

companies price to

bis

compies what we are trying to see

right and as you can clearly

see Ed up

[Music]

underperforming and there was no

expect this clearly shows just now just

imagine had you invested in any of the

basket

High Valu

and

earning the amount

ofu unprecedented and this is what

generally you know we end up recent

earning trajectory we EXT too far into

the future assuming

and uh which results in all the blenders

that we see right so um so this clearly

shows and sends my message simply

chasing growth doesn't help but the

question is ultimately Market only

respects rewards growth companies

rightow Market gives a higher valuation

multiple so for that you can the only

thing you know we have found we can do

is balance it with valuation and RC and

this is what exactly this model does so

we rank the stock on the basis of growth

quality and valuation as I

showed

perity

Val performance tremendously so this are

my final stats this so as you can see

almost

historically right compared

standard at the same

time

performance as can

clearly

29 and good quality companies and good

Compounders

chipping a few more stats about

this if

you if you invested in this strategy at

any point in time I mean any point

in you would have 100% of the time

created out

performance so this uh clearly shows a

message

right in a strategy and have a

conviction strategy for a long period of

time it clearly rewards

us uh secondly if you look at the draw

down so blue line is our strategy so

generally the strategy has you know been

draw down has been commens with 50y 500

or sometimes even during the covid it

was relatively better

june22 but this clearly shows more or

less draw down

historically and just to see the top 20

winners and

losers persistent kpr Sonata torrent

compies generate prash sh Heritage

destroy but if you

apprciate it's not that better strategy

uh in terms of number of stocks

performing poly right and just to

see it healthare capital goods

automobile

top and mcap

wise small and midcap focused

and which is

natural mut

funding

smaller but as I you know showed in the

past in the previous

slide small small it's a huge size

company right it's not 1,500 CR

companies invest

you're trying to invest in a decent size

30,000 is a decent size classification

is now set small in midcap and

everything but it's a good size company

this brings me to end of my brief about

how the strategy generates return and I

I hope you are able to appreciate just

by applying few Simple Rules there were

no complicated rule or new

andreen basically I canuse for IDE

generation uh so I think that's all from

my side I'll just uh stop the screen

sharing and uh allow for question answer

so what you guys can do is basically uh

raise your hands and I will you know

unmute

you if anyone has any

questions yes Shashi

H good

session I like uh how you passionately

you know take this data and try to you

know make a story out of it and you know

uh historically match it with what is

what has happened in the past and how it

has unfolded um I found couple of things

uh quite interesting that is something

to do with mutual fund uh is this along

the lines of cloning if I'm I think it's

not cloning exactly but uh my question

is do you have a set of mutual funds

that you consider as Benchmark and then

say that these funds exit that's when we

consider you know exiting or yeah yeah

yeah no so yes so fair question so now

what we have done is we have taken the

entire universe of mutual fund so we

have not segregated HDFC balance

Advantage

fund fun because they perform well in

the past

dat what we have essentially done is

let

xist

system bottom 70% of the

companies

companies so that's how I'm getting

those 140 OD companies based on that so

again coming to question M

fund univ mut funds okay because in that

case there would be few good companies

like for example you showed Amba right

in your first slide that is not owned by

any mutual fund so how do you compensate

for you know missing out on good quality

companies with good valuation but uh you

know a mutual fund is not not uh

invested or bunch of mutual funds have

not shown any interest but wouldn't that

lead to valuation discrepancy and that

is where you find

Value uh so I agree that

probably but at the same time when you

know this is human free trying to create

a portfolio where you know there's no

human intervention you want a certain

amount of

conviction

Lo basically is going to take care of

when I do

that

definitely

down ultimately when you are you know

trying to create a strategy where uh

it's human intervention free it comes

down to a basic

equation what is the percentage of My

Success ratio if I'm making 100 KES am I

making 50 60% 40 30% whatever that

number number is let's say it's at 50%

which is a very good number to be honest

so even if at 50% am I able to generate

let's say for every single trade am I

gener able to generate 10% return and

for every loss am I able to lose five

keep it at 5% or 7%

so

ma Bally impr risk

reward right with that intention all you

know the strategy is designed but

yes

focus Mak definitely definitely when

when you're so when uh you are going to

have a human intervention and

your can actually go down that curve

oftion need to be

minim yeah my second question is U with

regards to the number of stocks that

would show up out of this filter is it

25 uh is that something that you have

fixed or if I as a subscriber want to

say if I ask for 40 stocks for example

because I want increase it how does it

work so what we have done is 81

compies quality growth or valuation com

top 25 to 30

compies so we can obviously improve

increase that list we can essentially

ask the model to give next best 40

companies best 25 companies sufficient

diversification at the same time

both specification it's a reasonable

amount of list for a

portfolio

but it's not a t and this you run every

month every month on 15th 15th of every

month 15th of every month and the reason

for selecting 15th is because mutual

fund Nifty 500 and mutual

fund okay

yes got it and if there is any upup

Market reaction do you rebalance it or

you let it pass through like currently

we there is this space where the

election and other things are you know

right constantly being debated so do you

make some changes to no so again so the

part of this process is keep keep it

simple keep it systematic and

discipline

just it's our view

so keep it as It ultimately

outform I think that was one drawback

with magic formula also right where

whenever the human intervention was

higher the returns were not that great

make correct absolutely yeah okay thanks

part if I have any questions I'll join

back sure good luck yeah thank you uh

yes Kunal I unmuted

you yeah hi p and excellent presentation

you

your so I wanted to ask on that there

are three things right growth quality

and value right so first and third which

believe that it's a quantitative method

right but how do you

evaluate quality which includes you know

corporate governance or management

checks and all of those things which

includ even the ground research or such

things if you do as a fundamental thing

how do you evaluate these particular

things

mhm with the help of your tool okay so

uh if you have read this book uh so

Kunal if you must have read the book of

pulak Prasad so that I simplified in

such manag

decision work Capital decision profit

sub boil Downs to one single metric

which is RC right so it's RC is such a

powerful

measure bus Capital

allocation single number basically so in

that case is a very you know powerful

number

secondly mutual fund or score

basically

fund two

basically rules are there which are to

protect me against those kind of cases

again my entire focus is to protect my

downside upside generally takes care of

itself it's not you know tall

task so yeah have I answered your

question understood okay and second

question on that how frequently you use

this tool because see anyways during the

quarterly numbers it must have you know

reject over the last like the numbers

are pretty low over the last one one and

a half years what how do you know

frequently use this tool and the

companies which comes under your

criteria and which goes out the criteria

on the base of quality or earnings are

the three metrics which you guys are

using

right how so so this to has so I use it

rigorously and regularly so that is the

whole purpose ke you have to stay

invested

whatever have to invested

so in that sense the model is stable

right the

extent to the extent you guys you know

track all these companies qu numbers and

yes huh yes so we keep looking for ideas

from this list as well

okay okay and the lastly on this market

cap matter as of now you have a great

exp major exposure in the mid and small

cap the large cap is only 11% this so

these things also keeps going change

according to the market scenario and

according

to yeah so this is again so yeah so this

is not at my description to be honest so

model automatically decides large

hon cannot

ask investing is different this kind of

smart bet and Spector based investing is

different probably my VI can be

neglected my VI can be probably Pro

right either model

perform any other questions thanks

thanks okay not

now

second Krishna you can unmute

yourself hey par thank you hi uh hi so

sorry I missed the initial part of the

session so I just have uh want to know

know your views on you mentioned you can

chase the growth by managing the risk so

how is the model going to do about it is

it valuation based or purely uh mutual

fund allocations is it increasing

decreasing how is that model going to

catch the trend at the same time manage

the

risk so when the model is trying to

invest in high growth companies uh we

are trying to balance it out obviously

with the valuation valuation is single

most important thing so what I observed

when I was you know and number of

iterations is if I exclude the valuation

part uh and you try to invest at any

price uh your model does not perform as

well so I think valuation is you know a

good important factor while which

determines your you know returns so when

you try to balance your growth with a

quality basically your RC or any other

quality metric that you can choose

probably you can you know since men we

single

sity you can even use multiple

you can do that as

well so answer to your

question

Val so that finally when you're

investing in

a but at the same time you're not uh

absurdly high price to it yeah absurdly

investing at absolutely low quality

company

so p

tech that's a part of the

model on the single metric that I have

used Los

making single digit number so that's

fine got it so basically uh cyclicals

will be avoided to an extent and

uh Commodities will be avoided to an ex

correct

okay

performing understood so then in that

case how can we catch the commodity

reversal or sectoral

reversal so to be honest uh I have

actually failed in that so I tried that

thing as well so what I did was and I

will

Val commodity catch you play the margin

game margin operating margin game so

what I used to do I created a different

model not this one I was essentially

trying to

invest

to right this was a strategy I tried to

apply but the returns for pathetic draw

Downs uh or he uh

to be honest I failed trying to catch

the

Cals I even tried to merge it with

momentum that is basically the model is

acting dumb right so I don't want that

as well I failed to be honest on that

part I'm think sure to figure out no no

yeah I just uh I mean I thought of

discussing your views on it uh

understood sure I mean uh that's it from

my side if anything else I'll come back

on

this thanks

yeah sorry to interrupt there's one

question in the chat box by K he's

asking what is the max amount of draw

down you feel comfortable with your

strategy can you please answer

this so uh generally I want the draw

down to be less than what my Benchmark

is uh so generally your benchmark will

have draw down of 25 30 35% maximum I

think anything about that is too

uncomfortable for even for you to stick

around with the strategy because

portfolio portfolio so you will start

questioning the strategy at that bottom

and when you start questioning the

strategy you will not stick with the

strategy and if you don't stick with the

strategy ultimately you are likely to

underperform right the main thing about

any this kind of

strategy of underperformance and

underperformance would not be

like and when that happens you have to

have conviction

as long as benmark better per in terms

of draw down so I would be

comfortable not too much deviation from

there yes j i unmuted

you yeah hi par am I audible yes you're

audible okay thank you par first of all

to like you know it it you made it very

easy the complex subject you made it

very easy and yet it is very effective

so uh I don't know whether I missed that

part or not but for my understanding if

you can just repeat so in this strategy

what is the exit uh like you know how do

how do we exit the stock so what is the

so there would be a times where the

stocks

have uh when do we exit these

stocks so exit strategy is simple so I

think as some asked I think sashikant

asked he we select the top 25 to 30

stocks so when

rank 1 2 3 4

5

number at that point in time

conditions everything based F and

nothing on the technicals no no no

nothing technical so uh maximum you can

do is you can

actually growth value and momentum is

sorry growth value

and valuation so you can even merge it

with

momentum

momentum so that is the technical part

that you can I think you can capture

but got it got it okay thank you and can

we also ask questions about the research

or that we can take it offline uh no you

can ask I think that's fine okay so so

just to uh like you know ask you so what

is the like is there any frequency like

will you be coming out with a new stock

every month every quarter something or

as in when you finish your study and you

get any

conviction so to be honest every month

we are anyways working on three to four

ideas and any idea that we find

compelling enough we will you know

inform our

subscribers I think that is the strategy

that we currently following we're not

committing companies you know we'll

upload it only it's not possible humanly

because it would be that's the time

research we do not want like you know

number of ideas but whatever we generate

it should be quality I

think there only second like is there

any criteria over there also that we'll

not be covering any companies which are

less than 5,000 or 2,000 any any kind of

a this thing and we'll be covering only

in a market cap of because most of the

companies what I see is in a market cap

of range of 10 to

20,000 no so as such we have not put any

uh restriction we are completely open

for 500

to compy

perfect perfect we do thank you thank

you

yeah yes

Ravi RI I unmuted you hi part amazing

presentation and very informative also

so I was like wondering like you know

have you applied the same model and I

categorically like the use of Alman Z

score and sharp ratio to you know

address two major factors but have you

tried applying the same model if I put

in a criteria of like you know companies

not above 10,000 CR market

cap okay I relax the criteria that

mutual fund participation should be

there okay but I put in a different

market cap idea so have you tried that

uh not so far but probably I can try

that so so I so I tell you currently the

problem uh I'm facing is of the starting

universe so I want my universe to

include all the bankrupt and you know

all those kind of companies so that

Survivor and the problem is what

companies past exist and

bankr is a difficult task currently

because of datail issue so I'm just

trying to figure that part out once I do

that then I will you know try all those

kind of things that you are talking

about definitely we can sign

significantly reduce the numbers by if

we put in a criteria that sharp ratio

should be greater than one and Al Z

score should be greater than three okay

so like that reduces the universe

considerably and I mean again I'm just

asking from you you know like because

your model is pretty uh good like you

know it tries to combine various

elements from like you know value

investing growth investing coupled with

you know Factor based investing so

that's why the intersection has given

given such robust

numbers just wondering you know you know

Towing around with with an idea because

primarily I'm a value investor and like

you know I prefer looking at companies

which can grow and I need not pay for

that growth right so just an idea but

yeah again uh very uh like you know well

explained model and uh good work I must

say thank you RI thank you thank you

yes k i unmuted you yeah yeah thanks for

the followup just one question on that

you have excluded the bfsi so will you

be going to you know add this particular

sector in your model because anyways in

the mutual fund side it's contributing

33 35% of the entire weightage right so

how will you like look at this

particular sector so uh I'm already

working on it so BF a different set of

roles through I'm passing that set of

companies so it's wib basically so in

sometime I release that part as I don't

think there are any other questions is

there

n uh nothing if if anyone still wants to

ask a question uh you can raise your

hand and we'll unmute you and then you

can ask a question we'll wait for a

minute or so and then if there are no

questions we'll close sure sure

[Music]

think looks good uh no questions pa okay

uh we can wrap this up uh you can give

your closing comments if any uh sure so

thank you guys for joining in and uh

wait I think uh J has one question okay

yeah okay just yes J

uh whenever you cover any uh like you

know Stu we definitely get your detailed

research report and all so are you also

planning to conduct a short video like

you know where you like say the thesis

and the antithesis also because see when

you talk like you know it it gives us

more confidence and all like on this

Quant model when I just go to your

website it doesn't give me that kind of

a confidence but post today's meeting

like you know it definitely gave lot of

confidence that he can go out and try

that particular thing but also on the on

the stock specific ideas that you

generate so are you planning any kind of

a video or short 30 minutes video or

something so n would you like to take

that answer question yeah sure J I mean

that's a relevant question and to be

very honest we also have deliberating

this idea amongst ourselves but uh I'll

tell you what's the thought process

whatever uh you know so far we have been

doing we have made sure that

uh there's a continuity aspect to it we

don't want to you know um we have one

trick pony kind of you know organization

or a platform so your point well taken

suggestion well taken uh we are

deliberating this internally U not sure

when we'll you know put this idea into

action but hopefully we'll put it soon

so uh thank you guys for joining in I

think it was overwhelming response uh

from you guys and hopefully me and my

team can continue you know doing this

good work uh okay thank you so much uh

bye-bye see you next time