Interview with Rukun Tarachandani | PPFAS | Young Manager Series S01E01

Hinzugefügt: 2026-05-30

[00:00:00]So, we have to just to So, basically this is on behalf of the CFA Society India Research and Advocacy Committee.

[00:00:07]Uh This is our debut discussion on the Young Manager series. So, this is our initiative basically to look beyond the usual uh terminal and look at the philosophy, the how have you grown over the years and uh your evolution as a fund manager.

[00:00:26]Uh so, just for the for our viewers, this is I'm Shitesh Jain uh and joining today I have someone who brings an interesting uh multi-disciplinary perspective on the table. Uh Rukun uh is an equity fund manager with PPFS uh mutual fund and uh while uh uh Rukun's journey has been unique. I think you started as uh with a BTech in IT and now uh you've transitioned yourself into a financial background. I think you've done your MBA from MDI and masters in data science from Northwestern University and you're also a CQS holder. Uh So, before joining PPFS, uh Rukun has honed his skills at Goldman Sachs and Kotak Mutual Fund.

[00:01:15]Uh and so, Rukun, it's a pleasure to have you here.

[00:01:19]Uh we will skip the usual market outlook today and uh we will uh only want to dive deep into the how and why of your journey.

[00:01:28]Uh so, welcome to the session. Uh let us begin. Right, let me start with uh in the early years.

[00:01:35]Uh so, so you as I can see it's not something so so finance was not the as in you've been engineered by uh as when you started your educational journey.

[00:01:47]So, was there any specific moment or time or a book you read uh which made you interested into analyzing businesses or looking from an as in uh making interested into this journey towards an equity fund manager?

[00:02:03]Uh and I'll probably combine this uh you you also in your probably uh response if you can look something in your early years uh which made you prepared as in uh which which now that you look back and you realize that this is the reason which made you uh uh interested into this or which you developed the skills which you which are needed uh uh for for an equity fund manager to perform in this industry.

[00:02:31]So, it's over to you.

[00:02:32]Thank you, Shitesh. Thank you for having me.

[00:02:35]>> [clears throat] >> So, uh if I look back at my journey, you're right. So, I uh I did my undergrad in IT engineering.

[00:02:45]Um when So, I was good at tech. I was good at coding. But at the same time, while I was going through it, I had realized that, you know, uh this is sort of putting me in a silo when it comes to businesses. There are again There are people who are happy being in that tech space, but uh I wanted to understand more. I wanted to understand, you know, how businesses operated. So, one So, which is where I uh I decided to do an MBA at that point of time. I had no clarity that I would end up doing uh getting into investments. It was just about uh learning more about businesses and so on.

[00:03:24]Uh During my MBA, there are two things that happened.

[00:03:28]>> [clears throat] >> One, uh there was a equity research club at MDI uh which was called Unnati.

[00:03:35]Uh And uh you know, it was just serendipity that I ended up there wherein uh they had a written test and my roommate was going to give that test and he said, "You know, why don't you come and join me?"

[00:03:48]So, until that time, I had no idea about Unnati or what it does.

[00:03:52]He told me, "Come give me give the test or even if you don't do well, what's to lose?" So, I gave the test. I ended up doing very well and that is when I realized, "You know, this is something I can do." Um and uh but what really made me interested in investing was Professor Sanjay Bakshi's course on behavioral finance and business valuation at MDI Gurgaon. So, uh you know, till that time, uh I did not have an investment philosophy per se. You know, it was just reading stuff and trying to figure things out.

[00:04:25]But uh when he introduced us to the teachings of uh Warren Buffett, Charlie Munger, and Benjamin Graham, that is when I you know, it just clicked for me wherein you know, it's it was like this is something I uh uh that is intuitive to me.

[00:04:42]Uh I believe in uh this kind of investing and this is what I want to do.

[00:04:47]So, uh that is what really clicked for me.

[00:04:52]I think uh he introduced us to the books that he uh that a value investor typically starts reading, you know, like uh security analysis or uh you know, margin of safety and all of those books. So, uh I think that is when it really clicked for me.

[00:05:10]Uh so, anything uh in the early years growing up, you you probably assigned that that that could have helped you in your journey?

[00:05:19]Uh any hobby or or any non-financial influence, family?

[00:05:25]Yeah, so uh one thing was that uh I I used to read a lot uh across, you know, so like uh I [clears throat] would read I would read fiction novels. I would read non-fiction novels. Uh I was generally very well aware on uh you know, uh general markets and you know, what was happening. So, business newspapers and so on. So, uh again, I you know, as I said, when I was going to give in that test for Unnati, I had no I had no preparation. It was just that, you know, because I had read and I realized it later that, you know, because I had read all that that, you know, it just helped, you know. So, uh I think reading was one thing that uh really helped me get a wider perspective of things.

[00:06:14]Right. Right. I think reading is something which we we I I read the journey of most of the uh experienced and successful fund managers, I think reading is one common trait everybody has.

[00:06:29]So, yeah, you rightly pointed that out.

[00:06:32]Uh another thing is that now that you you have I I can see in your journey there's a lot of focus on data science and uh quant side of investing. Uh so, uh So, what we and especially now that you've done a MS in data science, so how do you see So, sometimes people in our industry see quant and value investing are like two polar opposites. Uh And how do you use uh as in and I know for a fact that they are probably not so much polar opposite.

[00:07:04]They are more can be used in conjunction. But uh so, how do you use your as in skills in data science and how has that helped you or supported in in your process in value investing? And uh how do you how do you actually combine the two? And uh good to hear It would be good to hear from you how have you achieved that process?

[00:07:29]I'll start with why or how I got into it.

[00:07:33]Uh so, as I said, I started with uh you know, pure value investing reading uh you know, Buffett, Munger, Graham, Seth Klarman, and everyone.

[00:07:45]>> [clears throat] >> As I started investing uh during the journey, I realized that you know, a lot of things in the market keep evolving, right? So, uh one of the things that at that point of time uh and even quite recently was very popular was quality at any price or buy at any price, you know, like uh and the idea was that you could buy anything at a quality business at any price and still end up making money. And this was a very popularized concept, right?

[00:08:15]Uh So, one of the things that I wanted was to have some kind of a historical context or some kind of >> [clears throat] >> a lab, you know, wherein I can see what has worked historically, what has not worked historically.

[00:08:32]Does this thing really work?

[00:08:34]Does something that I really believe in?

[00:08:37]How would that have worked over history, you know? So, one of the things that uh data science gave me was the ability to do that wherein, you know, I could see that, you know, how would value investing have done during the dot-com bubble?

[00:08:52]How did it do after that?

[00:08:54]Uh you know, What were the times wherein buy at any price really worked and what happened subsequently. So, it gave me a kind of a lab wherein I could test or see historically what had happened with these ideas. So, that is one of the things that uh The other thing was that I came into data science actually from value investing wherein Joel Greenblatt read wrote that book called The Magic Formula. The Now, if you know the Magic Formula, he essentially ranked stocks based on, you know, return [clears throat] on capital and uh valuation. Combine those two ranks and form a portfolio.

[00:09:35]Uh again, Joel Greenblatt was a person who did special situations for the start of his career, did a lot of value investing, and then he moved on to this.

[00:09:43]So, uh A lot of value In fact, if you read uh Benjamin Graham's Security Analysis uh and his interviews, a lot of times what he's saying seems very much like value factor investing wherein he's say, you know, buy a large portfolio or buy a group of, you know, 50-60 stocks which share a certain characteristic which are extremely cheap on valuations or something. So, I found a lot of similarities between what some of the value investors were saying and doing and what is now getting termed as factor investing. So, that is a second reason and finally the third reason that keeps me interested in it is that it gives me a very objective view of the markets and what is happening. So, you know, let's say as a fund manager, you know, there's an analyst who has recommended a stock and you know, that stock is now down 30%. The fundamentals have deteriorated, growth has not come in.

[00:10:50]Now, if you ask that analyst what should you do with this stock, that analyst has a very strong bias to stick to that buy recommendation and not say that, you know, sell it now with a 30% loss.

[00:11:02]But, a quant model gives you an objective view of things that based on fundamentals and everything, this is not something that should be there in the portfolio or should be there in the portfolio. So, it is one of the inputs in the process which is a fairly objective input in the entire process of how I approach investing.

[00:11:19]Also, how do you look at like So, now as a matter of fact, PPFS invests not only in India but globally also. So, and most of the value investors strongly advocate circle of competence. How do you ensure when you're investing globally and domestically, how do you ensure that that the circle of competence is maintained? So, are you as a team are you guys sector-wise you do kind of develop circle of competence or how do you go about it? Just just from that I wanted to understand.

[00:11:56]So, uh one of the core philosophies that the investment team at PPFS has had right from the start is that investing is increasingly a global endeavor wherein, you know, if you look at, let's say, an auto sector, if you understood or if you analyzed the Tesla and what it was doing with electric vehicles, you were much better prepared as to how that evolution is going to take place or you looked at, you know, how the Chinese EV space is taking place. Or if you are an Indian IT analyst, you know, you need to know what an Accenture and a Capgemini and everybody is doing. So, increasingly a lot of sectors and a lot of companies are essentially global companies and, you know, it's no longer just about India-specific demand or growth trends that influence them. It is what is happening globally that influences the company. So, we do believe in circle of competence which is where, you know, the team is divided into sector-specific analysts.

[00:13:00]So, analysts develop that circle of competence within their specific sector, they get an in-depth understanding of that sector.

[00:13:08]But, we also believe that that understanding would not be complete if you do not look at the entire global picture.

[00:13:15]You need to understand not just Indian companies in that sector, you also need to understand what companies across the globe are doing.

[00:13:23]And that gives you a much better understanding of the entire process. So, an auto analyst at PPFS covers not just Indian auto stocks, also covers US, European or Japanese auto stocks.

[00:13:35]Similarly, an IT analyst covers not just Indian IT companies but also other companies across the world. So, fair fair. I think you made it quite an interesting and persuasive argument. I think most of the companies in India are increasingly become becoming global.

[00:13:54]You you cannot have cannot do away with not not actually reading or analyzing companies on a global scale. Once you do that in any case, you need to study global companies. So, yeah, fair fair point.

[00:14:12]Another thing which I wanted to understand is that PPFS as the as a as a as a fund house is known to be contrarian and in the recent past they've been they've been having a lot of pressure or whatever you want to call it from from or queries from clients regarding your cash higher cash balances, right? So, so how do you as a manager, how do you mentally handle that pressure of holding a large chunk of your portfolio in cash when the market is booming? So, so how do you as a team, how do you handle it and how personally you want how do you handle it? So, so I think first and foremost what helps is being up front in your communication with your investors and distribution partners.

[00:15:03]At PPFS, we've been we've been extremely clear on two things. One, an investor should invest in the fund when we're talking about the flexi cap fund, only when they have more than a five-year kind of a time horizon. And secondly, we've also been extremely clear that we will invest only when from a bottom-up perspective we are able to find opportunities that justify the risk-return trade-off. If we are not able to do that, we will for that time period stay in cash. So, one we've been extremely clear with our investors, we've also been, you know, if you hear our CIO, he's been clear that, you know, we are we are fine losing half of our clients but we are not fine losing losing half the clients' money. So, you know, if the risk-reward is not favorable, it's much better to, you know, hold cash in that interim rather than go out and aggressively deploy.

[00:16:03]If you look at the history of the fund, you know, we've had, you know, whenever markets have become extremely expensive, we've had 25-30% cash but when markets do correct, that cash [clears throat] actually helps you make the most of that opportunity. So, you know, it's like playing defense when when you need to play defense. And in my view, that defense really helps you to play aggressively when the right opportunity comes across. If you are, let's say, if the markets are extremely expensive and you're fully deployed and then the markets correct 20-25%.

[00:16:41]The your job is that much more difficult because then you need to find what do I sell at these depressed valuations to be able to invest further versus if you have that cash, you can immediately deploy and take advantage of those opportunities. So, like at COVID times, you know, the team could buy really attractive stocks at, you know, bargain valuations aggressively. So, when you combine defense at the right time and aggressiveness at the right time, I think it works. All right, very completely with you on the point that as in history is quite a bit of you have history with with you on that.

[00:17:27]You've done I just want to add one So, I'm I'm sorry but I think that is important that the because you also asked that, you know, how personally I manage it. I think what makes it easy is that the entire organization is aligned towards it.

[00:17:46]So, you know, if the sales head was constantly telling me that, you know, what Yeah.

[00:17:56]You know, clients are telling me why are you not in fully deployed, you know, you know, the performance is not in the first quartile for the last three or four months. And so, you know, if all those short-term pressures are there from the rest of the organization, then you know, it adds to a lot of pressure.

[00:18:14]But, if the entire organization is aligned towards it, which thankfully in the case of PPFS it is, wherein, you know, like our CIO said or CEO even said the last year wherein that, you know, we are happy to underperform in a market like this. So, when the entire organization is aligned towards it, the pressure is much much lesser.

[00:18:37]Very very pertinent point. I think that is one of the I would say issue or the that's how the industry is structured to a large extent. So, yeah, that's a very differentiating point from from a fund manager perspective that organization is also aligned. So, great good to hear that.

[00:19:01]Another thing which moving on I wanted to ask is that early in your career or even now, sometimes we get into that trap of trying to be the smartest person in the room. And so so, we end up making mistakes and can you give any any example? I'm not asking you to take some specific company name but just a just where you you fell into a value trap or misread the management, something which and which made you actually rethink and made your fundamentally change your view how you look look at certain companies or certain in events in the company. So, yeah, you can share some insight on that part. Yeah, so if I look at the early part of my career.

[00:19:53]The biggest mistake or mistakes I made were because I was uh too focused on the narrative around either that business or that sector and not as much focused on the balance sheet and the cash flows. Uh so, one of the things that uh you know, a quantitative process does or did was essentially helped me create a checklist. So, either you [clears throat] do it manually or you put it put those rules into your uh system or something like that, but essentially uh you know, uh it's like I'm not compromising on the balance sheet strength of a company.

[00:20:33]Uh you know, no matter how good the P&L looks like, no matter how rosy the future looks like, if the cash flows are not been supportive, if the the profit P&L has not translated into, you know, cash profits, uh then I'm happy letting that opportunity go. So, And third was and third has been that uh uh being very cognizant of corporate governance and management incentives uh when you're investing.

[00:21:05]So, uh I think these three things have uh evolved as I've invested. So, now there are clear filters on balance sheet, on cash flows. Uh again, if there's a history of corporate, you know, misgovernance, you know, it uh again, one thing you learn, you know, as you uh uh grow as an analyst is that in the initial years, it feels that every opportunity is the opportunity you need to take. You know, like uh I can't miss this, you know, uh this looks really interesting, I can't miss this. Over time, you realize that a lot of opportunities will come by. It is okay to miss some of them. Uh so, uh it's fine, you know, the filters might mean that there are some good opportunities that will pass by, but that's okay. So long as you avoid the really big errors, you end up doing fine. So, that's that's one of the learnings that has been there.

[00:22:03]Now, maybe to the the hot topic of the day. Uh so, as an as a as a data science, someone who's studied data science and have have have a quantitative background, how do you think AI is impacting the industry, especially on the research and fund management side of it? And do you think it will there is that that risk and like that the a lot of significant alpha will be eroded because everybody would like that effort to the water for analyst or fund manager who's ready to make that effort, that effort time will collapse. Maybe a lot of people will come on the same plane.

[00:22:46]So, do you think is there uh or or or do you think there are parts of human judgments which an LLM will never be able to replicate? Uh what's your view?

[00:22:57]Uh so, uh you know, there are it is about how you generate alpha.

[00:23:04]It is about what is your edge in the market. So, there is, let's say, an informational edge, right? Wherein you are able to analyze information much faster or you are right there on the Bloomberg terminal looking at news and, you know, trying to make the best of it.

[00:23:18]Uh That edge over time has been decreasing and, you know, I think it practically will practically collapse. Wherein with LLMs or with uh you know, agents and all, uh they will be able to pass information much faster, much quicker uh than others.

[00:23:36]>> [clears throat] >> In terms of the research process, even at our firm, >> [clears throat] >> it has helped increase the productivity of the analyst wherein, you know, you can now quickly analyze and go through, you know, 20 transcripts.

[00:23:55]And so, you can filter through a lot of stuff very quickly.

[00:23:59]Uh it acts as a filter wherein, you know, you can reach a point wherein you realize that is this worth a deep diving in or is this not? You know, so that time period has collapsed materially.

[00:24:12]So, earlier, probably took an analyst a week or 10 days to go through all that material, today it might take two, three days. And where at which point the analyst knows that this is a firm worth a deep diving in, this is a firm worth wherein there is an opportunity in.

[00:24:27]Right.

[00:24:29]The edge that has not gone away so far in my view is the edge on interpreting or judgment of that information, especially when it comes to longer term investing.

[00:24:42]So, I have so far not found, you know, LLMs, you know, uh that uh wherein you can say how good things evolve in the next four, five years or things like that. Uh they're extremely good at interpreting history, they're extremely good at, you know, uh I mean, if I was trading on a if I was a day trader or if I was a short-term trader, again, AI systems and, you know, wherein it's all about interpreting data and all that, I think those kind of uh places, the alpha will get quickly taken away. Uh if you the longer you are on that uh time horizon curve, I think the more difficult it is for AI to take that away as things stand today.

[00:25:27]So, uh I mean, I if I have to evaluate whether I could should invest in a firm from a five-year basis or not, uh I don't think there is an LLM today that can help me give me that answer. Yes, they can help me pass information and, you know, I can ask the right question. So, asking the right questions is very important uh uh to help me get to that answer, but it is still my judgment that will be needed to get to that answer.

[00:25:56]So, just to add a probably an extension to this, so if you were building a research team now at your firm or at at any other place, uh so, what will be the characteristics you look into an research analyst? Like, if will it be purely financial knowledge or now do you prefer someone now who can code and understands more or someone who understands behavioral psychology? What are the top three or four characteristics would you probably look at in somebody who's uh if you are building a from scratch a research team?

[00:26:33]Yes, so those haven't changed as in what we look for is curiosity.

[00:26:42]The person should be curious to learn new things. Uh the ability and the willingness to learn new things.

[00:26:49]Uh basic financial knowledge. So, you know, understands the three systems, understands how systems flow, understands basic financial accounting and, you know, valuation process and so on.

[00:27:02]Diligence, somebody who has a good work ethic. Uh >> [clears throat] >> And beyond that, we believe that, you know, uh we can train and teach them.

[00:27:12]I don't think an analyst today needs to know or let's say an auto analyst needs to know how to code. Uh you know, uh uh Fortunately, the LLMs or the wrappers around them or various apps that have come through, uh you know, don't need uh the analyst to actually code anything. They can still use all these tools which are fairly intuitive to use and be far more productive about it. Uh So, so so long as the analyst is curious, they'll they'll themselves, you know, find a way to use it and, you know, to uh to be more productive around it.

[00:27:47]And now, so we spoken about your early part and uh about your to a certain extent about the investment philosophy and how it has evolved over the years and the impact of AI. Uh probably I would probably to the part of this why we started that series is that how do a young manager, what insights a young manager or a young analyst can take from uh from from from the leaders of future.

[00:28:15]Uh is that So, so so, my first in that direction was that we all like every analyst or even for any senior fund manager or a senior research analyst, everybody reads annual reports and brokerage notes and So, but if you if I have to ask you and what what should be the outside all these, like the the annual reports or brokerage notes, we have to I have to ask you what are the three things an analyst should do outside maybe the Excel sheets and everything.

[00:28:49]What are the three things which which which can help them have a much uh multi-faceted app uh maybe uh outlook or what will help them to grow into this profession?

[00:29:02]Uh besides the typical uh I would say uh annual reports or Excel and I think uh if you're starting off, uh first of all, read very widely.

[00:29:16]So, uh and when I say read very widely, I mean, you know, uh read Buffett-Munger, also read George Soros, also read other uh styles.

[00:29:29]It is in the initial years that you need to try and figure out what works for you.

[00:29:34]Mhm. Not everything works for everyone.

[00:29:37]Right? So, if you are inherently wired to identify trends or short-term trends and ride on them, then probably value investing is not for you.

[00:29:49]And vice versa. So read very widely in the initial years.

[00:29:54]Try and read as many different, you know, types of investors I would say and see what you know wherein you fit within that entire gamut.

[00:30:06]Right.

[00:30:07]The other thing I would say is It is important to understand or have a second order view of things. Right, in the sense that you know Investing is an extremely competitive endeavor.

[00:30:28]The smartest minds are all trying to do the same thing. You know, when you are buying something somebody else is selling it. So first order thinking often does not help. You know This is a company that is in XYZ sector and this sector is going to grow by multiple bounds over the next 10 years and hence it's a buy is a first order thinking.

[00:30:53]You know, what can go wrong in that process? If everybody thinks it's a buy then what is the valuation that you are ultimately ending up paying for it?

[00:31:03]That second order thinking of what the market is missing.

[00:31:07]Right.

[00:31:08]Is something that one needs to cultivate.

[00:31:12]The third thing I would say is a very good understanding of valuation principles.

[00:31:20]I see most analysts or most new analysts don't have that piece in their mind. Wherein you know, why is something a buy?

[00:31:34]Because the sector is trading at 50 times multiple. This is trading at 40 times multiple. So on a relative basis this is a buy.

[00:31:44]Okay.

[00:31:45]Or you know, historically this company has traded at 70 times multiple. It has corrected to 50 times multiple and hence it's a buy.

[00:31:54]You know some amount of absolute valuation framework in my view is absolutely necessary for you to have conviction in your investment over time. Right, if you buy something at because the sector is trading at 70 and you bought it at 50.

[00:32:16]And a year later the sector is derated to 20 times.

[00:32:21]And your thing is now at 30 or 25. You are not going to be able to stick through it.

[00:32:27]Probably that decision itself was incorrect in the first place. But the point is a very good understanding of valuations from an absolute value perspective.

[00:32:39]I think it can really help an analyst to stick through or their convictions over a period of time.

[00:32:46]Very very very very important. Just one The final point I would make is that go out in the sense that uh meet competitors.

[00:32:59]Meet channel partners.

[00:33:02]Uh you know, do on ground work.

[00:33:05]The thing is as technology is evolving quantitative modeling or Excel modeling is going to become more and more commoditized. It is already quite a bit commoditized. A lot of models will create, you know, all these LLM models can create Excel models for you.

[00:33:25]Right? Uh that informational edge is going away.

[00:33:30]The edge that you can still have is, you know, talk to competitors. Try and understand what really is the competitive advantage of that firm. Talk to channel partners.

[00:33:41]That on ground uh research or analysis.

[00:33:45]That is something that an LLM might not be able to compete with you.

[00:33:51]So that's other thing that I would highly encourage new analysts to do. Quite insightful. I think on that front. On on your first point when you say reading widely just just taking a cue from there and so that I What I'm trying to ask is any book which you have read in the last 6 months which you think not necessarily on finance. You just generally which you think it as as a it was very interesting or something you would recommend our viewers to read.

[00:34:26]I I really enjoyed the book A Brief History of Intelligence.

[00:34:32]So that's something that, you know, it correlates how human intelligence evolved over billions of years.

[00:34:41]Okay. With the evolution of how AI systems are thinking. So you know, what are the parallels? What are the differences?

[00:34:50]So that is one book I really enjoyed.

[00:34:53]So I think on the just to end up and something which I have been very curious about and is that so so as a fund house you I think your CIO and you probably other fund managers come out and say that investing should be a little bit boring. I think in that sense that inaction is also part of action. So so how do you So a lot of especially for young analysts like you already I think covered that sometimes you feel that every opportunity needs to be captured. So how do you tone out that that urge? Or is it something you will learn over the years? Or is it something you can do? Can you Can you do something about it as an young analyst? Is there Is there a way you should come maybe something on on as a on on your daily lifestyle?

[00:35:46]Can you do something which will make you a better investor?

[00:35:50]Anything in your daily schedule can you incorporate some certain things which you which makes you a better value investor or a an investor in general. I'm probably say I'm not just a value.

[00:36:03]So I think one of the things you can do is have a checklist. Right? A checklist inherently you know is meant to prevent you from taking you know spur of the moment actions.

[00:36:17]Have a checklist based on whatever works for you based on your investment philosophy or trading philosophy or whatever. But before you take a decision, you go through that checklist and that inherently stops that system one thinking and moves you to system two thinking which is more deliberate and gradual.

[00:36:39]So I think that can really help in you know preventing spur of the moment kind of decisions.

[00:36:48]Second thing is Again, this is one of the investors I think it was Dalio or somebody who had said it and I think it's really useful.

[00:36:59]It's that I think it was Mohnish Pabrai. But Don't make decisions during trading time. Again, if you are a trader, you know, probably it does not work for you.

[00:37:10]But if you are an investor, you know, if you can buy it today, you can also buy it tomorrow. Right. So you know, just because a stock is down 10% I do not need to buy it today itself. Once the trading day ends, you will have enough space to think through it that, you know, what happened? Why is this down?

[00:37:30]What needs to be done? Was it justified that it is down? In which case, you know don't rush in to buy it uh Right. even if it is down 10% or whatever. Uh so take decisions in the calm of the moment rather than you know when things are calm rather than during the trading day itself.

[00:37:51]Right.

[00:37:53]>> [clears throat] >> So yeah, that can help Third is Again, I think one way to learn is obviously to go through it yourself. Wherein, you know, you you have a 10, 15, 20 year investing experience and you start to realize that, you know, opportunities will come by.

[00:38:15]Again, this is something that I've repeated a lot of times in this podcast.

[00:38:19]But the other way to learn is read.

[00:38:23]You know, so I was I've been somehow heavily influenced by what has happened in the dot-com crisis and the 2007. While I was not investing at that point of time but reading books like there's a brilliant book called The Bull which describes the dot-com bubble and its burst. So you read through it and you feel like you're actually living through So you know, it So that is other way to learn wherein, you know learn about learn from books that describe historical market events.

[00:38:58]You know So that will also tell you that, you know, opportunities will come by in the future.

[00:39:05]Interesting. I think it's a good place to end our discussion. Like history probably like I think I don't know who said it. But I think history may not repeat but it will rhyme. Right?

[00:39:18]So So I think there you That's a very very I mean a good point to end. I think for a young analyst I think it's important to read history. Especially financial markets.

[00:39:30]I think now that markets and a lot of things are getting integrated.

[00:39:34]Probably history in itself is a good learning point. Financial markets and general.

[00:39:40]Yeah, the thing about markets is it is human behavior. So you know uh Indian market says it is human behavior. So, I mean, you can read about US market history in the late late '90s and you know, Indian markets were not very different. So, it's not necessary for you to only read about Indian market history or Indian sector history or things like that.

[00:40:05]Human behavior does not change. So, you know, when you read about history even from other geographies, it I think it's still as helpful as reading about it from India's context.

[00:40:15]No, I think good good to hear a lot of I think I think for especially for someone starting in in his career, I think it would be at least I hope this will be a good starting point to listen and take insights from future leaders in the asset management industry.

[00:40:36]Thank you for doing this. Pleasure to have you on this on this call.

[00:40:42]And let's see how how I'm hoping that this is very useful for our for our at least for our members, non-members alike.

[00:40:52]Uh Thank you. Thank you once again. And thank you for taking out time during market hours.

[00:40:59]Now that you told me that you do anyways take decisions post market [laughter] hours. So, >> [clears throat] >> So, so that's also good. So, you you have time during market hours. So, that's that's fine.

[00:41:13]You know, whatever decisions you've taken yesterday, you still have to execute.

[00:41:16]>> [laughter] >> Yeah, that is that is true. That is true.

[00:41:20]Thank you. Thank you, Rukun. Thank you for your time.