Your current stock screening method has a flaw. Find out the solution.
Summary
TLDRIn 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
😀 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.
😉 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.
📈 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.
💹 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.
🤔 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.
📊 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.
🤝 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.
🔍 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.
📉 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.
🏁 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.
🌟 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.
Mindmap
Keywords
💡Webinar
💡Attrition
💡DIY Investors
💡Factor-Based Investing
💡Quant Investing
💡Screening Method
💡Risk-Adjusted Return
💡Mutual Fund
💡Growth Quality Valuation (GQV)
💡Drawdown
💡Exit Strategy
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
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