Dividend Payers and Growers: Resilient During Periods of High Inflation and Rising Rates (feat. Sri Iyer, Guardian Capital)

[00:00:00] Pierre: 2022 has been a challenging year so far, for most investors. Both stock and bond prizes have taken a beating, marking perhaps the abrupt end to a 40-year period of gains like no other and a rate of inflation not seen since 1983. It’s time for advisors and investors to take steps to immunize their portfolios against the challenge of the current environment of inflation volatility and rising interest rates. Investing in companies with consistent and growing dividends can provide core building blocks to grow your capital while managing risk in the current environment and over the long-term, regardless of changing market conditions.

Our very special guest is Sri Iyer, managing director of i3 Investments at Guardian Capital, who now oversees the management of in and around $4 billion in assets under administration, of systematic dividend investing strategies. Prior to joining Guardian Capital Sri was responsible for a variety of portfolio management and financial engineering roles at Global Value Investors in New Jersey and has over 25 years under his belt. I know we’re gonna have a terrific conversation to share with you, so stay tuned.

[00:01:06] Speaker 1: This is the Insight is Capital Podcast.

[00:01:06] Speaker 2: The views and opinions expressed in this broadcast are those of the individual guests and do not necessarily reflect the official policy or position of AdvisorAnalyst.com or of our guests. This broadcast is meant to be for informational purposes only. Nothing discussed in this broadcast is intended to be considered as advice.

[00:01:26] Pierre: Sri, welcome back. It’s terrific to see you again and have you on again.

[00:01:30] Srikanth Iyer: Thank you, Pierre, always my pleasure.

[00:01:33] Pierre: Sri, I’m really looking forward to our conversation. For those who don’t know you, tell us about the span of your career, how you got into the business in the first place and what you and your team are doing these days.

[00:01:45] Srikanth Iyer: My career started obviously with my education. I was a chartered cost accountant in, in, in more into the accounting side. And when I came to the United States for my graduate degree in applied finance and statistics, I saw this pretty good intersection between numbers that I’m good at. And the application numbers through statistics talk about the prelude to data science 25 years later. So what attracted me into finance was my gearing into the world of numbers. And as I further got into finance and statistics and then got myself a a business administration MBA degree, I was able to start applying a lot of the knowledge I’ve known in the world of numbers and statistics, into the world of investments.

So I started out in Princeton, New Jersey, in a small hedge fund, which was focused on global tactical asset allocation, in the sense. The world in the ’90s was very different than the world today, in the sense. You had a lot of dispersion-

[00:02:52] Pierre: Absolutely.

[00:02:52] Srikanth Iyer: … you had a lot of dispersion-

[00:02:53] Pierre: Yeah.

[00:02:53] Srikanth Iyer: … in the market. So my job was to figure out when to go into the United States and when to shore Japan and when to go into France and when not to go into Germany. So there was a lot more dispersion. So that’s where I started my career in, as a top-down tactical asset allocation hedge fund. And then I moved into bottom-up stock-picking models and generating alpha through stock-picking through the ’90s and then right around tech bubble just about the midst of the tech bubble, I moved to Canada and I joined Guardian Capital primarily as a global equity manager.

But in those days, Canada didn’t know what global was because Canada knew EFI, United States, International United States, and they put that together. So I had a pretty big Herculean task to convince Guardian Capital and our management to say that there’s a different way to skin this cat, and we should be agnostic to size, style, country, region, and let’s create a global solution. So we launched a global solution at Guardian Capital in early 2001.

And the rest is history now. In 2022, we’re running $4 billion with a spectrum of global equity solutions covering all the way from accumulation strategies in the realm of quality growth and asset preservation and deaccumulation in the form of dividend growth. So we cover the whole spectrum. And that’s been the journey from zero assets to about $4 billion currently at Guardian Capital.

[00:04:24] Pierre: Sri, that’s pretty awesome. I’m guessing-

[00:04:27] Srikanth Iyer: Yeah, it’s a Canadian dream.

[00:04:28] Pierre: Yeah.

[00:04:28] Srikanth Iyer: It’s a Canadian dream, I could say that.

[00:04:30] Pierre: [laughs] Absolutely. I’m I’m guessing that you must be pretty darn excited about the change of regime that started at the beginning of this year or last year, if you will with the return of inflation and monetary policy. I-

And we have dispersion again. We have price discovery again. For a decade, none of that. I remember we had I’ll tell you, I’ll give you a little… We had a we did a pod… No, we did a webinar with Craig Lazzara from S&P, and in that presentation, he made this point that just rested with me for, I guess it’s been four years now, five, almost five years since we did that presentation. And he basically showed this chart that pointed out that dispersion was at a historical low-

… like an all-time historical low.

And, that was like the clarion call, just give up. Yes-

[00:05:34] Srikanth Iyer: I’ll take it to next, I’ll take it to the next level for you.

[00:05:36] Pierre: [laughs] Yeah.

[00:05:37] Srikanth Iyer: The function of dispersion is just one part of the equation.

Alpha is defined as the product of dispersion, active share and the square root of skill times-

[00:05:52] Pierre: Yeah.

[00:05:52] Srikanth Iyer: … transfer coefficient. In the world of convergence, where we are seeing correlation one happen in the world today forget correlation one within as… within equities. You’re seeing correlation one between bonds and equities right now.

So in a world where there is convergence, there is no dispersion. This lack of dispersion has been prevalent in the stock market for a very long time now, almost a decade and a half-

[00:06:14] Pierre: Yeah.

[00:06:14] Srikanth Iyer: … with the formation of the European Union, further convergence into MSCI world index and further into ACWI, with the inclusion of China into the WTO. So the deverticalized supply chain has seen the conventional methods of equity management, whether it is style, size, country, region, beta timing, momentum, all these factors have been less relevant in active management. As dispersion collapse, you saw active management move more and more into what we call active share. They started to concentrate-

… their portfolios more and more because you could not get any insight beyond the concept of converged dispersion.

[00:06:54] Pierre: Yeah.

[00:06:54] Srikanth Iyer: So what is left here is, the only thing that really matters is your IC times TC, is your information coefficient, that do you know something the market doesn’t know? And can you transfer the knowledge that you know. into a portfolio? That is IC times TC, which is called skill, by the way. So in the-

[00:07:12] Pierre: Yeah.

[00:07:12] Srikanth Iyer: … in the world of last decade, while skill has been finite and dispersion has converged and gone so low, the only thing left with active share, that’s all the emergence of concentration-type mandates out there. Now, after a decade, you’re seeing a lot of things change with the rise in interest rates, because the primary principle component of equity, valuation or valuation of any class, asset class, is the discount rate. And there’s been-

… two generations who have not figured out how to value assets when discount rates go from zero to one, let alone to three or four in the near future. So that has created a disintermediation and asset class pricing across multiple asset classes. That is the most biggest impact of lack of dispersion in global markets today.

[00:08:03] Pierre: Yeah. The reaction has been seismic.

[00:08:06] Srikanth Iyer: It has.

[00:08:07] Pierre: Really when you’ve had no price discovery for, since the great financial crisis, since GFC, there’s been absolutely no price discovery, everything has been driven by this enormous liquidity-

[00:08:18] Srikanth Iyer: Absolutely.

[00:08:19] Pierre: … that’s been injected into the market. So in a, in that respect, dispersion just got completely,

[00:08:25] Srikanth Iyer: I joke around with clients who do not get this kind of concept.

[00:08:30] Pierre: Yeah.

[00:08:30] Srikanth Iyer: I just say, very simplistic way, I say the bond booth at church is closed. You can make every asset allocation sin-

[00:08:37] Pierre: [laughs] Yeah.

[00:08:40] Srikanth Iyer: … And you could be pardoned because of a falling yield curve, that is falling interest rates. Now with rising interest rates and bond volatility, as a multi-asset manager, or as a liability-driven manager, as a financial advisor, if you don’t get your asset mix right between stocks and bonds and cash, in a balanced, on typical balance and format-

[00:09:00] Pierre: Yeah.

[00:09:01] Srikanth Iyer: … You could have a decade worth of mismatched liability going forward. So it’s become extremely crucial amidst bond volatility that you cannot go for confession anymore because a bond asset class is not coming to bail you out, especially in the beginning of this year. So what we see is copula here, that is the correlation between the bond asset class and the equity asset class amidst an inflection point in the rising interest rates. It’s a very different regime that we’re entering in over the last six months, that at least two generations in investment industry have not been in.

[00:09:38] Pierre: I completely agree with you. I think the, I was raised on value investing as an advisor and on favoring value investing, whether it was right or wrong in, in hindsight. It was right for quite some time until, at least until the 2000s. And I… Fundamentals mattered and earnings mattered. And so it was very strange. I think one of the conversations, we had with Jeffrey Sherman at Double Line he pointed out something really interesting.

At least it was a perspective on how the market had been functioning and he runs an interesting… They run an interesting strategy at Double Line for equities as well. And that’s part of the thinking, but he actually said that it was a scarcity of growth. That the term growth is misused or misunderstood, or it has double, it has double-speak meanings. And the idea was that during the period of where there was an actual scarcity of growth stocks did extremely well. So we had a period, this 10-year period of no growth the Fed pumping tons of liquidity into the market inflation was, non-apparent. It was not, it was it was nowhere to be found. No matter what they did, they couldn’t get inflation to happen.

Finally, it took COVID, of course for the whole, globalization mechanism or framework to fall apart-

… and to lead to these supply chain disruptions that are at the core of this inflationary volatility that we’re having. But this was in the… Jeffrey Sherman’s point was that it, that’s why duration stocks, high duration stocks did extremely well. It was because the discount rate was so low for so long and it was declining for so long.

It was a trend of continu- continuous decline, that capital was becoming easier and easier to obtain, and that was driving all of these, long duration investments that are, 10, 15, 20 years out into the future where you might actually get your money back.

But the reopening trade exposed the inflation, the growth in the economy which, it’s confusing if you… At best, it’s confusing, right? To say that the economy is growing when we have, the kind of unemployment that’s out there, we have this bifurcation of the economy. I know I’m we’re, I’m getting into the weeds here, but [laughs], I think the point was that, what he was trying to, the point he was trying to make was that the return of growth-

[00:12:44] Srikanth Iyer: Pierre, I’ll add to that in a much more visceral way.

[00:12:49] Pierre: Yeah.

[00:12:50] Srikanth Iyer: Our approach to investment management is about optimizing duration and credit.

[00:12:55] Pierre: Yeah.

[00:12:56] Srikanth Iyer: We are not speaking the word duration, we actually calculate duration foreign equity, where we are calculating the sensitivity of a stocks valuation to its free cashflow over 10 years, its terminal value assumptions and the discount rate we use. The discount rate have been impotent for over a decade, so only thing that mattered was either cashflow growth. And what cashflow growth became was a proxy for long duration because people could not get upfront growth in cashflow because much of it was being paid out in the context of a Verizon or an Enbridge or anything else.

So the only way you got growth scarcity came from the fact that you had to go way out on the spectrum 10 years and beyond, to get that cashflow growth amidst low interest rates, because you are discounting something way further out and the error term did not matter because your interest rates were so low. Now with the rates starting to go up, your error, that is your prediction error further out, has become a lot more sensitive. There’s also another thing I would like to mention. You talk about growth scarcity, let me talk about value investing.

In my opinion, as compliance would say it, in my opinion-

[00:14:09] Pierre: [laughs]

[00:14:10] Srikanth Iyer: … value investing is lazy investing, priced earnings is not value investing.

That’s what the industry proxy is value-investing into. But PE ratios are not a definition of value. In today’s market cycle, with rising interest rates, you’re seeing PE compression. So what is value? Is a moving goal post and is like quick stand. So value investing is lazy in the sense simplicity of tagging a stock as being value or not. In my opinion, is nonsensical. Let’s talk about valuation investing rather than value investing.

And when you talk about valuation, then it comes down to the bras racks of looking at free cashflow growth, mapping the discount rate, talking to management, looking at the sensitivity of the stock, the mode around it, as well as the duration risk and the credit risk, if you’re trying to capture some dividends out of it. Bold spectrums of the industry is lazy. The thematic response, just buying the long beta of extreme long duration stocks and getting 90% one year and then 80% down this year, is also as lazy as buying cheap stocks and expecting them to go up.

[00:15:27] Pierre: Yeah.

[00:15:28] Srikanth Iyer: The real asset management, as you rightly said, that is being disintermediate now is, how do you map the true valuation of an equity and a company, and what are the true risk premia that you need to capture holding onto a company? That aspect makes you extremely different from the traditional products that are pushed into the market. The market lives in the tails, product cycles live in tails.

[00:15:53] Pierre: Yeah.

[00:15:55] Srikanth Iyer: What is needed today is the middle and not the tails. That is the core essence of active management today, where we, I think the industry is going, is the tail aspects, which was being buttressed by low interest rates, is now gone. So your tails are gonna get a lot more volatile while the middle is gonna be a somewhat more relatively relevant to equity asset pricing and fixed income pricing on a go-forward basis. It’s time to get to the middle and move away from the tails.

[00:16:23] Pierre: [laughs] Awesome. [laughs] Thank you Sri for for sharing that. Sri, did you did you ever imagine when you were younger that you’d be doing this?

[00:16:41] Srikanth Iyer: The more I think about it, I would say the answer is a big yes. Because when my parents put me into accounting, it means at the highest level of accounting, you become a charter accountant and charter cost accountant. It’s not like it’s that-

[00:16:57] Pierre: Yeah.

[00:16:57] Srikanth Iyer: But it never, I never got endure to that aspect, but it really taught me what a profit-loss balance sheet cashflow is, and I truly understand what a company is. Today, people think that a company is some kind of like… People treat an equity like Bitcoin, they don’t even understand the valuations, they become a speculative instrument rather than a fundamental instrument. When you try to own a company, it’s much more fundamental than people understand.

So for me, my journey from going from accounting and understanding profit-loss balance sheet and cashflow and corporate finance, to the depths that one should understand, and then applying statistics and data science as I do right now I truly feel emancipated of being who I am. This is what I was destined to be, is being a data scientist who could combine fundamentals of profit-loss balance sheet and cashflow, which is what I call traditional fundamental data, with alternative data like new sentiment analytics management transcripts, as well as digital datasets that cooperate fundamentals of a company and use these two together and predict the earnings potential and growth of a company as well as its payout sustainability.

The whole journey of my education and what I’ve been trying to do is culminated into a very strong process where now I am the dumbest person in my team that consists of engineers, data scientists-

… mathematicians, statisticians, and we are a team of individuals and engineers and data scientists who are now using all the skillset that we have, and I’m basically an architect that is spearheading the formation of what I call, in my opinion, the new way of investing or the renaissance of investing, that combines data science or big data with fundamental investing. That intersection is what I feel, all along I felt, is what I needed to be. So the answer is-

[00:18:50] Pierre: Yeah.

[00:18:50] Srikanth Iyer: … a big yes, that, yes, this is what I wanted to do.

[00:18:54] Pierre: I was really excited to ask you that question, by the way.

[00:18:57] Srikanth Iyer: Thank you. Thank you for asking, yeah.

‘Cause, [laughs]

[00:19:00] Pierre: Speaking of which, I think, the last time we spoke, you talked about how you and your team were teaching the AI how to find dividend growers and dividend initiators-

[00:19:22] Srikanth Iyer: And cutters.

[00:19:23] Pierre: … And cutters. And it seems to me that technology has accelerated maybe in several orders of magnitude over the last five years. And I wonder, it made me wonder, has it become… As the s- the speed of processing has increased and the tools or the hardware available for processing, like the GPUs, that are backing AI, from companies like Nvidia and for example has it made your work even more profound or easier or faster? Or how have things changed just in a couple of years since we last spoke, in that respect?

[00:20:15] Srikanth Iyer: So I would say, it hasn’t made my work easier, but it has made my work profound. I know we use those-

[00:20:20] Pierre: Yeah.

[00:20:20] Srikanth Iyer: … two words side by side, but they have very different meanings.

[00:20:22] Pierre: [laughs] Absolutely, yeah.

[00:20:24] Srikanth Iyer: I think it has-

[00:20:25] Pierre: Yeah.

[00:20:25] Srikanth Iyer: … made our investment process profound. And the reason I say that is, in our industry, the noise to signal ratio is very high. Much of the data is noisy and very distracting. Before, the predating data science, we used to call it behavioral finance, as in, in a quantitative sense. What we are seen is, with the abundance of big data and digital data right now, there’s much more distractions to the investment world than there was about a decade ago. So even if you look at some of our volatility prediction models, we have 17 asset classes now in our volatility models. When I started the business about 25, 30 years ago, I should have six asset classes. So there’s a lot of noise out there and the intermediation between different asset classes. The emergence of artificial intelligence or machine learning has made it profound in the sense that guys like us, who are held to high degrees of precision are now able to move away from that shackle and move into higher degrees of accuracy.

Now, when I talk about precision, what I mean is, as a money manager, I’m expected to know everything about a stock and know the future in its perfection. That’s not the way investment management works, that’s not the way stock selection works. Stock selection works based on certain past history, past analysis, and some degree of a prediction of what you expect it to do forward. That could be biased based on the kind of data you look at. Whether you’re a statistician like myself, or a fundamental money manager, what you read could bias you in a certain direction.

[00:22:13] Pierre: Okay.

[00:22:16] Srikanth Iyer: What artificial intelligence has done for us, it has moved us away from the concept of being biased in our opinions, to using massive amounts of big data across every spectrum and aspect of the market and come up with a more accurate response to a prediction. That is extremely profound in its impact for money managers, where we no longer need to carry the football from our own 20-yard line and try to score a touchdown. Artificial intelligence takes the ball all the way to the 20-yard line of the opponent, and I can walk in as a human being at the red zone level-

… in playing the game. So the probability of this PM or quarterback scoring a touchdown at the opponent’s 20-yard line is significantly higher than a traditional asset manager who’s starting on his own 20-yard line, who has to sift through a bunch of information, bunch of distractions and then score a touchdown. So it’s all a measure of probability of success. And a probability of success can be measured by accuracy, not by precision. So that is the cornerstone of the profoundness of investment management and what the impact of AI is to the investment industry. And in my opinion, it’s only starting. We have been-

… In my opinion, pioneers in the space over the last four to five years and we have been training our artificial intelligence models to think like humans, and to look for things that any prudent individual like myself and you would look for in a company to grow its dividends, but it’s easier said than done because you need domain knowledge, accounting knowledge-

[00:24:09] Pierre: Yeah. [laughs] … experience, you need statistical knowledge to understand how the statistics work in an artificial intelligence framework. So in training an artificial intelligence system, to think like a human or to look through fundamental data and come up with a recommendation that is intuitive to a human being’s far more complex brain, is a very profound journey. And I would say myself and my team, Adam, Yvonne and hopefully a couple of new data scientists joining our team, are just starting and improving ourselves exponentially, year after year.

[00:24:44] Srikanth Iyer: So it’s not an, it’s not a given end to that pro- process, it is very much a journey in investment management that started about four to five years ago and continues to grow at a very fast pace. That’s my answer to-

[00:24:57] Pierre: That’s-

[00:24:57] Srikanth Iyer: … your impact of AI and how profound it is to investment management.

[00:25:01] Pierre: [laughs] That’s fascinating.

[00:25:02] Srikanth Iyer: It is fascinating.

[00:25:03] Pierre: I I just want to go back to something that you said in, in in responding to that question, which was that the problem of behavioral finance that existed prior to the work that you’re doing maybe, have that be the demarcation based on what you were explaining, is that we’re not agnostic. Human beings, we’re not agnostic to our belief systems, we’re not agnostic to our biases. We’ll read, we’ll pick up five articles, we’ll read five articles from five different sources, and we’ll tend to favor the pieces that agree with our biases. Right?

And that’s a problem, that’s problematic because then it can wrongfully increase our bias or incorrectly increase our bias-

[00:26:10] Srikanth Iyer: It’s co- confirmation bias. Yeah.

[00:26:12] Pierre: So it’s, it creates a conflicted system of decision-making. But the way that you are training your AI to gather data and assimilate it and put it all together, is in a- agnostic fashion, which ignores those bias traps, those behavioral traps and flattens or levels the playing field for all of those risks-

Correct.

[00:26:44] Pierre: … In, in, in the, determination of making a conclusion about something-

[00:26:49] Srikanth Iyer: Correct.

[00:26:50] Pierre: … whether a stock is a dividend grower or continue to grow or cut or initiate, a company, not a stock. But so that, that’s very interesting because I think that’s also been a big part of the idea of systematization in the first place, was just to eliminate the, eliminate luck from the investing equation-

[00:27:15] Srikanth Iyer: Correct.

[00:27:15] Pierre: … to eliminate supposition and subjective biases from that in order to make all the evaluations as clean as possible.

[00:27:26] Srikanth Iyer: Correct.

And-

[00:27:28] Srikanth Iyer: If you contextualize in the world of statistics, it’s called underfitting and overfitting.

If you are just reading fire articles and making a decision, you’ll underfit your process, that is, you’ll build a confirmation in your head, but which might not be true in the real world. The other side of it is, once you realize it’s not, I’m not reading the right things, or I’m not read enough, you read too much and you get too much variance.

[00:27:58] Pierre: Yeah.

[00:27:58] Srikanth Iyer: So you go from bias to variance. Both are suboptimal in the world of vestment management. When you have bias, you think you’re very precise. The problem with being precise is that you could be precisely wrong. And being precisely wrong-

[00:28:13] Pierre: [laughs]

[00:28:13] Srikanth Iyer: … in the investment world is very dangerous.

[00:28:16] Pierre: Yeah, absolutely.

[00:28:17] Srikanth Iyer: On the other hand, if you have too much variance and your predictions are all over the place, then you do not show any kind of conviction to your end client. And the client will perceive yourself as a money manager all over the place. Or you can see style drift, as we know in our industry, or we see performance chasing, all that happens when there’s too much variance. What artificial intelligence does is, it takes away the bias-variance equation out of the human’s hands and gives it to a machine who can optimize the trade-off between maximum variance and maximum bias. The optimization of bias and variance in a very simplistic statistical world is called artificial intelligence. It’s nothing more profound than that.

[00:29:02] Pierre: Yeah. So this goes back to what you were saying earlier about bringing the range of possibilities to the center-

[00:29:10] Srikanth Iyer: Correct.

[00:29:10] Pierre: … of a distribu- of the distribution curve. And how do you bring the center? You take an average-

[00:29:15] Srikanth Iyer: … of many things-

[00:29:17] Pierre: Yeah.

[00:29:17] Srikanth Iyer: … to bring it to the center.

[00:29:19] Pierre: So I have this picture in my head of when, you see the NOAA reports about hurricanes and on the weather map, they show you the future, the range of possibilities happening, for where that hurricane is gonna go.

And it gets wider and wider with each day. Because there’s no way to know exactly-

[00:29:41] Srikanth Iyer: Its, its path.

[00:29:41] Pierre: It’s path. But when you say you want to find closer to the center then you’re doing is trying to narrow-

That-

[00:29:50] Pierre: … Down to a more, a narrower band. And I know we’re talking about the distribution curve with, the left and right tails. But it’s-

[00:30:00] Srikanth Iyer: And how do you come to the most probable, how do you come to the most-

[00:30:03] Pierre: Yeah.

[00:30:03] Srikanth Iyer: … probable path of the hurricane? By taking the average-

[00:30:05] Pierre: Yeah.

[00:30:05] Srikanth Iyer: … of all the predictions. The more predictions you make and you take the average of more predictions, more accurate your actual path becomes. So in our world, when we are predicting dividends for say a McDonald’s-

[00:30:17] Pierre: Yeah.

[00:30:18] Srikanth Iyer: … we have 2,000 paths for the hurricane of dividends, for McDonald’s.

[00:30:22] Pierre: [laughs] Yeah.

[00:30:23] Srikanth Iyer: We have 2,000 paths for more than 3,000 companies, which then self-learn from it. So when you average our 2,000 paths of the hurricane of dividends, you get one average dividend growth rate for a company, and that’s as close to the real scenario as you could possibly be.

[00:30:41] Pierre: Yeah.

[00:30:42] Srikanth Iyer: We not only do that for dividend predictions, now we have improved ourselves to do 2,500 hurricane paths for earnings one year out. Earnings are a lot more harder to predict than dividends. Dividends are sticky. Generally, when a company pays dividends, it continues to pay dividends, unlike, unless there’s a subprime or COVID-type event that happens.

But earnings could be affected by a myriad of things. So to predict earnings path is as hard as predicting a hurricane’s path. So you predict 2,500 times every day and you average it out, and then when you look at Nvidia’s predicted one-year earnings growth, or Google’s one-year earnings growth, or Airbnb’s earnings growth, you could then get a little bit more of a better perception of where that storm is going, that earning storm is going.

The earnings storm in Europe is very bad today. If I show you my artificial intelligence output today, Europe is in a deep recession, and we have been saying this-

… for the last six months in Europe. United States is heading into a recession, its earnings are converging. There was some separation early on in the year, late last year, but now you’re starting to see all 11 gig sectors starting to converge. Even energy, which was way about the dispersion path, its storm path, hurricane path-

[00:32:05] Pierre: Yeah.

[00:32:06] Srikanth Iyer: … way about everybody else in a good way, has started to now moderate itself because of the subjected conversation of demand destruction coming out of out of a recession, impending recession, which is then being conflicting against the supply disruption that we’ve seen over the last decade of under investments in the commodity space. So the battle between supply shock and demand destruction is being played out in front of eyes, in the storm of energy-

[00:32:36] Pierre: Yeah.

[00:32:36] Srikanth Iyer: … and commodities. So we are predicting that. So everything is connected. An innocuous statement, like building out a storm path through AI, is very similar to what we do with our predictions.

[00:32:51] Pierre: That is absolutely just mind-boggling and fascinating. So that’s a perfect segue to set the table for, what we’re here to actually talk about today which is dividends, dividend growers, dividend payers-

[00:33:09] Srikanth Iyer: Dividend cutters.

[00:33:10] Pierre: … dividend cutters. Yeah. And so in your wider research as a firm you’ve called out three findings. The first is that dividend stocks have typically earned higher historical returns with less risk, the second is that payments from dividend payers are an effective buffer against volatility, and the third is that dividend growers and payers are resilient during periods of high inflation and rising rates, outperforming relative to non-payers and dividend cutters. So now, that’s the really… That’s what we’ve been talking about up until now. Is how do you, how do you-

[00:33:53] Srikanth Iyer: I couldn’t have said it better myself. I couldn’t have said it better myself.

[00:33:56] Pierre: [laughs] How do you narrow the range of selection possibilities for your portfolios given those three outcomes? So Sri, let’s spend some time here. I’ve brought some of your charts to the conversation.

How do you like that? [laughs]

[00:34:16] Srikanth Iyer: That wasn’t surprise to me.

[00:34:17] Pierre: [laughs]

[00:34:18] Srikanth Iyer: So I will try to interpret the charts as you bring it up on the screen.

[00:34:22] Pierre: All right. All right. So here’s the first one. Gimme one second here.

[00:34:29] Srikanth Iyer: It would be my team’s charts, not my chart. So let’s see if I could, This is like the aggregation of a lot of your research, but it’s… I mean-

Yeah.

[00:34:40] Pierre: … the findings, this is the purpose of-

[00:34:43] Srikanth Iyer: Speaks to itself, it speaks to itself.

[00:34:44] Pierre: This is the the precursor to, why would you want to identify the best dividend stocks you can possibly identify? And so here’s a chart from Ned Davis Research.

Companies that can grow dividends have historically led in performance.

[00:35:02] Srikanth Iyer: So here’s the secret sauce, here, in my opinion. When you look at dividends as an asset class, the first thing people’s mind goes to is towards beta. That is own dividends. My, my father-in-law owns BC and Enbridge, somebody owns a Verizon in the United States. That’s what your… first thing you think, when you think of dividends. You think of the market beta. The problem with the dividend as an asset class, is it always underperformed your expectations over long-term cycles. I’m talking the beta aspect.

And the reason for that is, dividend as a asset class has a lot of dispersion within it. So on this chart, you could clearly see the spread or separation between dividend growers, just dividend-paying stocks with not much volatility and dividend cutters. When people do it by themselves, or when people start looking at dividends as an asset class and buy dividend strategies, they tend to chase yield, because that’s the only number that is intuitive to them. Chasing dividend yield is like value investing. It’s a lazy approach to investing.

When you buy dividend beta, you invariably get exposed to the dividend cutters and you could see how devastating the performance is when you own a di- dividend cutting stock in your portfolio, that one bad stock or one bad apple in the basket to take away the whole liability experience that you’re trying to get into dividends in the first place. So in this chart, where do you see subprime in 2009? You could see-

… where dividend cutters just did not hold up, or during COVID. This is the experience most people get when they own dividend stocks during crisis period like COVID, as well as subprime, is because they have a lot of companies that cut their dividends, their total return experience is highly jaded. What we did in our research through artificial intelligence is we’re able to see the granularity and the risk premia within the dividend asset class, and we’re able to find out that stocks with mid to long-term duration that have an upfront payout do extremely well because they have less credit risk and better duration risk, while companies that pay a lot of dividends have very little duration risk, but have very high credit risk.

So what we train our artificial intelligence systems to do within the three core buckets of growth, payout and sustainability feature sets, we define what growth should be for a dividend-paying stock, we define what sustainability should be for a dividend-paying stock, and we define what a payout should be for a dividend-paying stock, and we teach an artificial intelligence system to take all dividend-paying stocks in the world and separate them into dividend growers, dividend cutters, high dividend-paying stocks with low credit risk and high dividend-paying stocks with high credit risk, and of course, stocks that don’t pay dividends.

In our analysis and in our AI systems and in our back test, we can corroborate the evidence that Net Davis is showing you here. This is just a simple linear, Yeah.

… of CAGR chart. But our analysis, and we have put a paper on that and we have shown to the industry, that our paper shows that chasing yield is not the right liability match in the world of dividends. Optimizing duration and credit within the asset class of equities, where you demand an upfront payout with a mid to long duration of cashflow, growth, visibility, and avoiding dividend cutters completely, is the approach to create superior risk-adjusted returns in the world of dividend investing.

I don’t even think we are a dividend manager, we are a duration credit manager. And when you optimize duration and credit, it just so happens you’re looking for positive cashflow and positive cashflow growth. And when you see positive cashflow and positive cashflow growth, invariably, a company pays out a dividend and grows its dividend.

That is where we feel, as an asset class and as an intellectual properties response, we are far ahead of the market, in my opinion.

[00:40:06] Pierre: So let’s talk about the next chart, which accompanies that first chart that we, that you were just, that we were just on. I- is the other side of the coin. You showed return-

Yeah, for volatility.

[00:40:18] Srikanth Iyer: … now you’re showing volatility. And you could see, it’s a double whammy. Not only do you get bad returns, but you get excessive volatility with dividend cutters.

So the exposure to credit risk is intense. I’ll give you one more indication today on this podcast. A dividend cut is a credit risk. One of the risks that we have not seen just yet happen, which we saw doing subprime, is liquidity risk.

Do not for one second think that high dividend-paying stocks are immune to liquidity problems. So as we head into this protracted negative earning cycle and other aspects of PMI deteriorating, in macroeconomic deterioration, amidst a war in Europe and a recession in Europe, one of the known unknowns in the market will be liquidity. I think liquidity will be a bigger, I think my opinion… Whatever compliance would say was the right word. In my opinion, liquidity is a bigger risk than recession to the stock market and bond market on a go-forward basis.

And when you have a liquidity crunch, high-yielding asset classes generally tend to underperform. We teach an artificial intelligence system these aspects using historical data, be it subprime or COVID or anything else. So stay away from high-yielding instruments amidst a recession because liquidity crisis could be around the corner and focus on high quality, mid to long-duration companies with free cashflow, defensible modes and pay upfront dividends and grow their dividends, while also owning high-quality companies in certain industries that do pay high yield, whether it be energy, commodities, or insurance companies that are paying anywhere from four to 7% yield.

You should also own those companies because there is a tailwind when it comes to the supply shop in the form of commodities in energy and in and commodities like copper and steel, while at the same time-

[00:42:34] Pierre: Yeah.

[00:42:34] Srikanth Iyer: … insurance companies that benefit significantly from equity and bond volatility and increasing in interest rates, you can actually get a payout from benefiting from insurance companies in the form of better yields and better shareholder-friendly responses to the market. Dividend growers are significantly more shareholder-friendlier than dividend cutters and high dividend-yielding stock.

[00:42:58] Pierre: That’s a terrific insight. I think you’re right. I think investors look at the dividend yield universe and they think, "Oh, here’s one that’s, yielding a high, providing a high dividend yield. Why don’t we do, why don’t we just take that?" But it doesn’t pay attention to the things you just explained, which is that dividend growers have significantly better returns over the long-term and significantly lower volatility as well. Dividend cutters are a high credit risk?

[00:43:29] Srikanth Iyer: Yes they are.

[00:43:30] Pierre: Thank you thank you for sharing that. How dividends impacted the returns by decade?

[00:43:35] Srikanth Iyer: Here the… The context here is just showing that, again, if I use a very simple word, for the last decade, you mentioned, did you preface it to say that, let me use this word again. The church of dividends was empty for 10 years because everybody is going-

[00:43:53] Pierre: Yeah.

[00:43:53] Srikanth Iyer: … to Bitcoin and any asset class that were supported by low interest rates and speculation was where we went in. Speculating is laziness. It’s nothing to do with understanding why you’re owning something. So a generation of free asset, free money, has moved into speculative asset classes. As a result, as the duration risk grows, the contribution of upfront payouts reduces in an asset class. Now what we’re seeing with rising interest rates, just mathematically, you’re seeing the duration of an asset class equity starting to fa… shrink.

When your duration shrinks, the upfront payout or the dividend payout that you’re getting from these companies start to become a larger component of your total return. In a rising interest rate cycle, where long bonds will give you anywhere from three and a half to 4%, equities in general are gonna have a pretty interesting time competing against a 4% yield out of the bond asset class on a go-forward basis, where your risk premium, how much? A 7% inflation is so low right now. Equity owners are going to demand a higher-risk premia out of equities on a go-forward basis, given the 7, 8% inflation and rising interest rates.

So the opportunity set amidst lower return profiles out of equities on a go-forward basis, by itself makes the case for dividends becoming a larger portion of the total return of owning equities into the next decade, which was not the case in the previous decade. So you’re gonna see-

… the church of dividends getting a lot more full. I’m gonna put pews on the street now and, because-

[00:45:43] Pierre: [laughs]

[00:45:43] Srikanth Iyer: … people are gonna rush in. So it’s not about dumb investing in dividends, you gotta understand the kernels of DCF modeling-

… and duration and credit, and you could see that high-quality dividends will trade out a premium going into next cycle of both fixed income and equity volatility.

[00:46:01] Pierre: And we see, if you’re looking at the last two columns on the chart, 2010s, versus 1930 to 2021, you’re looking at the previous decade versus the mean.

And what you’re expecting in a way is that there’ll be a reversion to the mean of the importance of dividends as a component of total return.

[00:46:21] Srikanth Iyer: Very much but it’s not also… What is not, what not to be s-

[00:46:30] Pierre: Well-

[00:46:30] Srikanth Iyer: … not ignored here is, if you look at the 2000s, you could see that when you go through a negative asset cycle-

[00:46:36] Pierre: Yeah.

[00:46:36] Srikanth Iyer: … price appreciation can be negative, but dividends are positive. You could see that also-

[00:46:42] Pierre: And that’s a buffer.

[00:46:43] Srikanth Iyer: That’s a buffer.

[00:46:44] Pierre: That’s a buffer against the drawdowns-

[00:46:45] Srikanth Iyer: Correct. Exactly. Exactly.

[00:46:47] Pierre: … of the period. Yeah.

[00:46:50] Srikanth Iyer: Get paid while you wait.

[00:46:51] Pierre: Sorry. And I said… I think I need to correct myself ’cause I said reversion to the mean of the importance of dividends as a component of total return. But I think what I meant to say was that it’s a reversion, it’s a reversion-

[00:47:03] Srikanth Iyer: Of price.

[00:47:03] Pierre: … to the mean of… Yes.

[00:47:03] Srikanth Iyer: Of price return.

That’s the right way to… There’s a reversion of mean, of price return that was inflated over a decade of free money. Dividends of blue bars have been reasonably constant and will play a bigger role depending on where the price appreciation goes or not. So you’re talking about optimal credit duration when you have a carrier. So let’s say the market beta pays you 2%, we pay 3%, or the market pays… beta pays you 3%, we pay 4%, having that 1% payout higher than the market buffers a lot of the alpha volatility of price appreciation volatility that people have to endure. So dividend is not-

[00:47:49] Pierre: Amazing.

[00:47:49] Srikanth Iyer: … the icing on the cake, dividend is the cake. Alpha and price appreciation is the icing.

[00:47:58] Pierre: Interesting. Very interesting. And I think people, I think most investors have it backwards, how you pointed it out.

[00:48:04] Srikanth Iyer: Most investors have it backwards. Can’t blame them. So when-

You have-

[00:48:08] Srikanth Iyer: … you got free money, you can’t blame people.

[00:48:11] Pierre: [laughs] that… We’ve turned the corner on that. Haven’t we?

[00:48:15] Srikanth Iyer: I think there’s an inflection point in the market with bond yields at 300% and breaking out.

[00:48:20] Pierre: Yeah. I’ll soften that. We may have turned the corner on that. [laughs]

May have.

[00:48:27] Pierre: So now here, we’re talking about the difference in volatility between dividend growers and non-payers.

[00:48:36] Srikanth Iyer: Here again, the real essence of this chart here is, when we back-tested this information, also we found out, is I can only speak to our dividend growth strategy while we do-

Our duration credit portfolio is highly positively correlated, its alpha or its ability to beat the stock market is statistically significantly correlated to volatility. Higher volatility, greater the chance of outperformance, lower the volatility, greater the chance of underperformance. We have had low vol regime for a very long time, as our high… Very low volatility regime for a very long time. Now you’re starting to see equity volatility start to rise again because we are positively correlated to volatility.

You start to see our outperformance starting to look a lot better. Now, this is not us, this is just Net Davis’ research to show that-

… that VIX about 20%, average outperformers of dividend growers versus non-dividend payers is about 2%. We can corroborate that in an actual sense in what, how we manage money, but that regime has not been around for a long time, the greater than 20%. It happened during COVID, it happened during subprime, but now we’re starting to see it being a little bit more prolonged than we normally see during say a black swan-type event. So if you feel that we are heading into a higher volatility, VIX regime or turbulence regime, then dividend growth and an optimal duration credit strategy should continue to do like it has done.

For the last two years we have had some pretty good outperformance. While you also notice at the bottom, average, in general, when VI- VIX increases, we do well too. And this has been corroborated by the passive response. I’m saying we’re doing even better in an active response. So liability-

[00:50:37] Pierre: Yeah.

[00:50:37] Srikanth Iyer: … matching has to happen in this realm, where you have returned and risk on the same sites, where the industry has not been in because we had free money. It was all about returns, not about risk. I think that is changing, in my opinion.

[00:50:52] Pierre: Yeah, but so the conclusion of this finding here in this graph or this table, is that periods of higher volatility are beneficial or, or-

[00:51:08] Srikanth Iyer: Periods of higher volatility are beneficial for cashflow visibility.

And cashflow visibility is equal to dividend growth and dividend yield.

[00:51:17] Pierre: Now, does that have anything to do with investors flight to safety, looking for quality or flight to quality?

[00:51:25] Srikanth Iyer: To a large extent, yes.

[00:51:27] Pierre: Yeah.

[00:51:27] Srikanth Iyer: Upfront, that’s what the biggest principle component is. People sell and buy proxies. The initial round of allocation goes into proxy asset classes, which is basically beta. It’s only after a protracted regime that people f- flee away from beta to alpha, to active management. So if you really look at… I don’t know if you have their chart, but there’s the chart that shows that upfront, when you start to see the rate-hike cycle, dividend cutters or high yield does the best in the first three to six months of a rate-hike regime, but then it starts to peter out because you start to see the sensitivity of the long bond hurting high yield, like it does any other asset class.

Not only does it hurt bond proxies as interest rates start to go up, because people start to say, "Why am I owning this high credit risk instrument paying me four and half, 5% dividends while I can own a bond, a 10-year treasury at 4%?" So that asset class starts to see its clientele move back into bonds when bond yields have gone up to a level where the market thinks it’s sustainable and it’ll stay. As bond yields start to go up and interest rates start to go up, you start to see volatility and equity markets go up because your error term of your long duration stocks starts to go up and you start to see a lot of volatility in the market, like we saw in the technology space or in moonshot stories in thematic.

So even non-dividend-paying stocks start to underperform the market amidst a rising interest rate regime on a go-forward basis. And dividend growers start to outperform every other asset class, is because they have that optimality of a cashflow buffer, a dividend buffer, and you cannot grow your dividend without earnings growth or cashflow growth. So invariably, you reside back into the world of Johnson&Johnson, McDonald’s, Nestlé, Apple, Microsoft-

… and you get away from the Bitcoins and all the other tail tech stocks, as well as thematic moonshot stocks. That migration is happening, I don’t think so in a very knee-jerk way, I think it’s happening in a… In my personal opinion, it’s happening in a very protracted and sustained way. The wild beasts are migrating. The wild beasts are migrating.

[00:53:57] Pierre: That is quite a picture. [laughs] That’s quite a picture. Yeah.

[00:53:59] Srikanth Iyer: It’s quite the picture. It should happened two years ago, but we had COVID and we had $35 trillion worth of cashflow infusion. And at the peak of COVID, we had 1000 rate cuts in subprime. Now we’re heading into 200-plus rate-hikes over the last six months. So the wild beast is migrating.

[00:54:16] Pierre: Staggering. That’s that is amazing. That’s an amazing insight.

[00:54:24] Srikanth Iyer: Even you pause. That’s… I’ll take that as the credit

[00:54:27] Pierre: [laughs] Yes, absolutely. And now what are we looking at here? Excess return of dividend-paying stocks versus S&P 500 in different inflation buckets, from 1970 to 2021.

[00:54:42] Srikanth Iyer: Excess return of dividend-paying stocks versus S&P index in different inflation buckets. So I think what, what-

[00:54:49] Pierre: Just from Goldman Sachs.

[00:54:50] Srikanth Iyer: Yeah. I think what is being said here, I think what we’re trying to tune here, try to explain here is, pick your regimes of inflation. So let’s start with that.

So are we in a 4 to 5% inflation? And let’s say that’s your normative distribution, but obviously we’re under 6 to 7% inflation. And what you’re seeing here is, what… against the S&P 500-

[00:55:19] Pierre: Yeah.

[00:55:19] Srikanth Iyer: … which asset class has the largest excess returns? And what it… I think what this chart is saying here, I don’t know what period it was, it, it doesn’t tell you how far back it goes.

[00:55:33] Pierre: No, it just… I think it just looks at historical periods, where-

[00:55:35] Srikanth Iyer: 19- yeah, 1970 to 2021. It’s basically trying to say very much what we have said in multiple charts before, that when you have high inflation, which leads to the Fed starting to aggressively go to combat that inflation, the rising interest rates re- results in volatility rising as well as impending recessions. And when that happens, and when you try to fight the Fed in that space, generally, dividend stocks do better than non-dividend-paying stocks. It is intuitive, and this is just a linear response to say that amidst any kind of inflation scenario, beyond 4 to 5%, it looks like getting an upfront rent out of companies without expecting too much in the future, seems to be a very effective way of adding value.

[00:56:26] Pierre: The conclusion of all this empirical data or charts that we’ve been talking about here is that dividend growers, dividend initiators provide resilience to a portfolio and dividend cutters are a credit risk-

Yes.

[00:56:47] Srikanth Iyer: … And a… Yeah.

Dividend growers and sustainable dividend payers both provide resilience and income, while chasing yield without getting the understandings of duration risk and credit risk generally leads to underperformance.

[00:57:05] Pierre: Okay. And I think this is our last chart.

[00:57:07] Srikanth Iyer: This is the chart I was explaining already, in the sense that if you look at the-

… Performance X months after the rate-hike regime start, first Fed rate-hike, you could clearly see that initially, dividend cutters are what we call high dividend yielders, outperform, but then they give up the leadership to dividend growers, which have optimality in credit risk and duration. So in the end, I would say in a very simplistic way, don’t fight the Fed, always seek moderate to long duration to stay vested in the stock market and avoid credit risk in the form of high dividends and demand an upfront cashflow payout by these cashflow-rich companies that are growing their dividends. Those would be the cornerstones of outperforming the stock market, in our opinion, for a dividend-based strategy.

[00:58:04] Pierre: In a nutshell, dividend stocks are more resilient during periods of inflation and inflation volatility, as well as rising rates.

Very much so Sri we’ve talked about these empiri- we’ve looked at some empirical data now, and I think just to, to clarify, the empirical data really provides an impetus for all the work you’ve been doing. I think if you can conclude from the charts we’ve looked at, because these aren’t your charts, these are charts from Net Davis and Goldman Sachs that, there’s a reason for why you do what you do. There’s a reason-

[00:58:42] Srikanth Iyer: Yeah.

[00:58:42] Pierre: … for why you’re in, you’re seeking dividend payers, dividend growers, dividend initiators and seeking to also identify dividend cutters. And so these five charts provide the, the empirical impetus to do this work and to do it to, to find a way to improve on it.

[00:59:06] Srikanth Iyer: Correct.

[00:59:07] Pierre: When did you and colleagues realize, when did you first realize that you were onto something?

[00:59:16] Srikanth Iyer: I would say 2017, 2016, 2017. When we went through the maturation cycle of high yield, in the sense we used to get invariably disappointed in buying high-yield stocks for our clients and provide them a higher yield because while the sticker looked good, the implied risks in those stocks showed up consistently crisis after crisis or cycle after cycle. So we were at an inflection point to figure out, how do we avoid these dividend cutters? How do we avoid this mesmerizing yield number that people seem to gravitate towards while it is injurious to their health?

So how do you create a solution that is counterintuitive to get people to come to you? In 2016, 2017, with the emergence of alternative datasets and artificial intelligence and machine learning, our data scientists took on the task of researching the principle components of dividend investing through our back testing models to find out what aspects are principle components of dividend investing really work over the long term cycles.

And we were shocked to see how poorly dividend investing did if you continue to stay lazy and just chase higher-yielding stocks and create a proxy as a bond proxy for investors. We then ran an exercise to figure out, how do we exclude risky stocks from the high dividend universe? In doing that, we found out, through machine learning and artificial intelligence system, that what the machine learning system was using, because machines don’t overfit humans do, machines don’t.

What we found out it, what it starts to use was features like historical earnings growth, historical cashflow growth, lower payouts, lower yield, all of these features were being used by the artificial intelligence system to tell us to avoid certain, highly risky, high dividend-yielding stocks. As we continue to do that research, we found out that the classification of stocks had the fourth quintile of dividend payout rather than the fifth quintile of dividend payout, the fourth quintile of dividend yield, rather than the fifth quintile of dividend yield was the sweet spot that not only gave you a fair yield, but also gave you sustainable yield, supported by cashflow growth and a good duration.

That allowed us to refinance, I use the word correctly, refinance our alpha and use the artificial intelligence system to get implemented in our stock selection models. And it pivoted away from the lazy aspects of linearly chasing after higher dividend-paying stocks and moving us aggressively into predicted cashflow growth and sustainable dividend yield. That migration was profound and completely changed the way we looked at dividend investing and we became, in my opinion, pioneers of quality growth-

[01:02:57] Pierre: Yeah.

[01:02:58] Srikanth Iyer: … and high dividend yield without a dividend cut. Our history of our strategy, we have not had a dividend cut since inception, and we have had no dividend cuts during subprime, no dividend cuts during COVID, especially COVID. There were a lot of dividend cuts in the universe. So we are quite fortunate to use artificial intelligence systems and high-grade our investment process to eliminate the probability of disappointment on a go-forward basis.

[01:03:31] Pierre: That’s absolutely remarkable. I I [laughs], I guess my last question about the, my, my question, one of my followup questions about the AI was, will it will they ever become self-driving? Will your AI ever become self- self-fulfilling and self-driving or is the aim just… I think that there’s… I don’t wanna make the mistake of leaving our, leaving advisors with the impression that this is something that happens on its own.

I think just to reinforce the point you made earlier, which is that, all of this artificial intelligence groundwork that’s happening is to get you to the 20-yard line.

Correct.

[01:04:20] Pierre: It’s not to carry out the decision-making, the final decision-making, it, It doesn’t replace humans, it augments humans.

Yeah.

[01:04:29] Srikanth Iyer: Investment management on a-

[01:04:30] Pierre: So-

[01:04:30] Srikanth Iyer: … go-forward basis is what I call augmented reality. That is, the realities in front of you, the markets, we see what’s going on, but if you can be augmented by artificial intelligence, you see more clearly. Artificial intelligence allows you to seek more than see. Seeing leads to hubris-

… seeking leads to knowledge.

[01:04:52] Pierre: I love it.

[01:04:52] Srikanth Iyer: If you have knowledge, then you could do a better job for your client. My job is to improve my batting average, not hit a home run. Improving a batting average increases the probability of winning. A home run looks pretty exciting, it might draw the audience in, but is not a guarantee to win the game.

[01:05:13] Pierre: Yeah. See, I had this whole analogy I told you before, we got started in our pre-chat. I had this whole analogy about, baseball-

To preface our conversation. And then I abandoned it because I thought it wasn’t good enough. But the idea was that, we had 10 years of Major League hitters facing a Fed that wa- was playing a very long, slow-pitch game. So imagine, home runs everywhere.

Yes.

Yeah.

[01:05:46] Pierre: Because every ball, you can swing at every ball, just Casey at bat, Warren Buffet’s favorite quote, just because someone throws a ball at you doesn’t mean you have to swing for it. And but in a baseball game where the Fed is constantly throwing you easy pitches, you can swing at everything and you’ll get a home run almost every time, especially if you’re a Major League hitter. But now the Fed has returned back to the hard, the fast-pitch game. The fast-pitch game is a different game. You got curve balls, you got sliders, knuckle balls.

Absolutely. Ball strikeouts.

[01:06:21] Pierre: They’re a lot faster, you can’t even… The balls come at you so fast, you can barely see them. And I learned this by the way, in a batting cage where, a ball was coming at me at 90 miles an hour, and I couldn’t even see it, and I realized, this is why, this is the difference between Major League Baseball and baseball. But now, the game has gone back to a pearl level, has gone back to where, you can’t, no, you can no longer feel certain about the idea that you could do it yourself.

And that’s why, that’s really a big part of why we wanted to revisit our conversation with you, because the regime does appear to be changing or has turned a corner towards that. It will take investors a very long time to turn that ship, realizing, the market dynamics are completely upended now by interest rates, inflation, supply chain disruptions, deglobalization, reshoring, all these things these fundamental things that are happening in our lives-

[01:07:35] Srikanth Iyer: You talk about broad, passive… You talk about investing and we know passive investing is big. Let me ask a question.

[01:07:42] Pierre: Yeah. It’s a big shift to turn.

[01:07:43] Srikanth Iyer: Do you know your beta-

[01:07:44] Pierre: It’s a big shift to, to write, yeah.

[01:07:45] Srikanth Iyer: Do you know your beta? When you invest passively, do you know and understand the beta you’re investing in?

[01:07:53] Pierre: Yeah.

That data-

[01:07:54] Pierre: That’s a terrific question.

[01:07:55] Srikanth Iyer: … is changing.

[01:07:57] Pierre: Yeah. I think I’m not even gonna try to weigh in on that question. I know it was a rhetorical question.

[01:08:01] Srikanth Iyer: Yeah, was a rhetorical question.

[01:08:02] Pierre: [laughs] but Sri, that’s, this has been an absolutely fascinating conversation. I’m so excited to… I’m so looking forward to sharing this. I I have one last question for you and it’s it’s nothing to do with investing, or maybe it is. [laughs], if it turn… It might turn out to be. So here it goes. What is an interest or a hobby that you could talk about for hours?

[01:08:45] Srikanth Iyer: Yoga.

[01:08:49] Pierre: Okay.

[01:08:49] Srikanth Iyer: It’s neither… It’s not a hobby, it’s my interest right now. COVID was transformational for me as, individually, as a human being. As a data scientist, I used to always engineer outwardly to everything I do. It’s about time I started to do, engineer myself inwardly. So for me, one of the most interesting things is about inner-engineering myself and trying to not get impacted by external circumstances over the next stage of my life, to stay removed from events that have no bearing on my self-happiness and self-discovery path.

I’m on a journey of self-discovering myself through the eight stages of yoga, which goes all the way from your daily life of how you lead your life in a good way, to the ultimate-

[01:09:58] Pierre: Yeah.

[01:09:58] Srikanth Iyer: … end of what you say it, what we say is samadhi or full renunciation. That journey of s- self-engineering and inner-engineering is what has consumed me and has kept me going beyond my work life. It has had positive responses for me, with my team, with my management, with my mandate, my portfolio, as well as the clients that I serve. So it has brought a big sense of humility, sincerity, credibility, accountability, and fiduciary responsibility. And all of these things are not taken lightly by myself or my team.

So that’s what has become the most interesting aspect of my life in the context of where I see my interests lie. If I may also add one more aspect to this in a investment connotation, because this is an investment conversation, what I’ve realized in our industry is, our industry always fo… In my opinion. Our industry always focuses on maximization. This is an analogy-

… of the softball, slow balls or low interest rates. We always focus on maximizing sales, maximizing returns, maximizing relationships, maximizing wealth, maximizing presence, maximizing everything. Our philosophy is to minimize, not maximize, because the glide path from point A to point B can be reached in a more fluid and less volatile state by minimizing, than by maximizing. You still get to the same point B, but the journey is significantly more painful when the only a- approach to it is maximization.

If you try to minimize certain things in your life as a person or in the form of investing, you generally lead to a superior end path to your solution. So those are the two summarized philosophies or interests that I gear towards with my engineering team to motivate them, to make sure that there is no hubris, and there’s always questioning of what we do. We always debate, we always have different angles to what we do, and then motivate my leaders and pioneers in my team to come up with solutions, to give people the glide path to reach point B from point A, in the least volatile fashion. That’s the biggest goal of myself on a go-forward basis, as a money manager, as the head of i3 Investments and someone who’s responsible for people’s money.

[01:13:14] Pierre: Wow. Sri, thank you so much for sharing that. That was that was profound.

[01:13:22] Srikanth Iyer: You asked a question-

[01:13:23] Pierre: [laughs]

[01:13:23] Srikanth Iyer: … I gave you my honest answer.

[01:13:25] Pierre: That that’s something that I want to give our audience a a real sense of who you are and what you do. And I think that’s, I think that’s a really important dimension of building a a sense of, your presence in the industry. Sri, thank you so much. I I anticipated a great conversation, I don’t think I anticipated how great of a conversation it was gonna be. I wanna thank you again, so much for your incredibly valuable time, and likewise, your incredibly valuable insight. It’s been enthralling talking to you today.

[01:14:13] Srikanth Iyer: Pierre, as usual, we have had great conversations over the years, and I always look forward to chatting with you on these concepts, about investing and the philosophy of investing. So it’s been a pleasure and look forward to seeing you next time.

[01:14:29] Pierre: Yeah, likewise. I’m ready when you are. [laughs]

[01:14:31] Srikanth Iyer: Cheers.

[01:14:32] Pierre: All right.

[01:14:32] Srikanth Iyer: Bye now.