Howard Marks: AI, Debt vs Equity & The Next 40 Years Of Investing | Nikhil Kamath | People by WTF

0:05 Mhm.

0:15 [music] [music]

0:52 Could you also say that indexation and [music] ETFs have

0:55 taken over because the markets have been in an uptrend?

1:01 My answer is that indexation has taken over, as it has,

1:05 not because it's so good, but because active management was so [music] bad.

1:10 Cuz a lot of the distressed bonds that you

1:13 are in, is the chance of a downside zero?

1:33 So, I'll give you a little bit of a background.

1:35 So, most of these are like conversations.

1:37 Most of the interviews that we do are conversations.

1:41 They're fairly free-flowing.

1:43 And the audience we cater to are entrepreneurs of Indian origin Mhm.

1:49 who are around the age of 25 to 30.

1:52 Mhm.

1:52 Everyone's looking to invest in the market, trade the market,

1:57 start a business, building something from the bottom up.

2:01 So, we are speaking to them.

2:02 So, most of today is around that.

2:05 Can we start with a little bit about you and uh

2:09 how your own journey began from Queens to Wall Street?

2:13 Maybe like a How do you describe your story in your words?

2:20 Your story, your origin story.

2:22 Well, um you know, I was born in Queens, New York, as you know,

2:29 one of the what one of what are called the outer boroughs.

2:33 Uh middle-class upbringing.

2:35 Mhm.

2:35 Uh neither parent uh went to college.

2:40 Um but my father was uh very intelligent man and and and an accountant.

2:48 Mhm.

2:49 And I think he did his job well,

2:52 and so we lived a uh comfortable middle-class uh existence.

2:58 Mhm.

2:59 Um I went to the public schools of New York at a time

3:03 when you could get a good education in the public schools of New York.

3:07 Uh and I think I got one.

3:09 Uh and [snorts] uh oddly enough ended up

3:14 taking courses in business law and then accounting Mhm.

3:19 in high school.

3:19 Mhm.

3:20 And uh really connected with accounting, with the orderliness and the symmetry.

3:25 Uh it it it just clicked for me.

3:29 [snorts] So, I decided to go to uh uh business school.

3:32 I applied to Wharton as the best business school for undergraduates in America.

3:38 Uh I was told I wouldn't get in, but I did.

3:41 Uh went to Wharton as an accounting student, switched my major to finance.

3:45 Mhm.

3:47 Uh uh then went on to get a an MBA

3:53 in accounting from the University of Chicago Business School.

3:57 Uh [clears throat] and uh between years of business school,

4:00 I had a job in the investment research department of Citibank.

4:03 Liked it, went back.

4:05 Mhm.

4:05 That That's my That's my background.

4:08 Is Wharton would you say it's still one of the better schools?

4:12 No, I think it's I I I I have no

4:14 reason to believe it's not still the best undergraduate business school.

4:18 There are other good graduate schools Mhm.

4:21 uh that are uh uh very competitive with Wharton.

4:27 uh Mhm.

4:29 I'm not I'm no expert.

4:30 I'm going to say that 100 times on this tape.

4:32 Mhm.

4:33 uh but uh I believe that Wharton

4:35 is still the best undergraduate business school.

4:38 And you studied Japanese literature at Wharton?

4:41 Yes.

4:42 Uh When I went to Wharton, uh there were two very enlightened requirements.

4:53 Mhm.

4:54 You had to have a a semester of the literature of a foreign country.

5:00 Mhm.

5:01 And you had to have a non-business concentration, what we call a minor.

5:05 Right.

5:06 And you know, the [snorts] the wonks would take stat or economics or poli sci.

5:11 are the wonks?

5:12 Wonks?

5:13 Yeah.

5:14 Oh, you know, people who just think about making money.

5:16 Okay.

5:17 Or or or or just think about numbers and business.

5:23 Uh But uh for my uh literature requirement,

5:27 for some reason I don't remember, uh I took Japanese studies.

5:31 Mhm.

5:31 uh Japanese literature.

5:33 uh uh per- I think perhaps it was the uh exoticism.

5:40 Mhm.

5:40 uh And uh I just fell in love with it.

5:43 Uh and so and then up taking a second semester of Japanese literature,

5:47 then two semesters of Japanese civilization, then one semester of Japanese art.

5:53 And what did that teach you?

5:54 Well, it taught me a lot.

5:57 Uh uh but the main thing I've carried away

6:02 have been some aspects of the Japanese uh philosophy.

6:06 Mhm.

6:07 Uh the most important one, the most relevant one, is uh something called mujo.

6:12 Mhm.

6:13 Uh which uh uh literally means the turning of the wheel of the law.

6:21 And what it means in in everyday life

6:26 is it means the i- inevitability of change.

6:33 That change is uh inevitable, unpredictable, and uncontrollable.

6:42 And that we have to accommodate to it and make

6:48 the most of it rather than think we can control it.

6:54 Should one expect it?

6:56 One should.

6:57 It's inevitable.

6:58 Yes.

6:58 Of course, one should expect change.

7:00 One should not expect a specific change because it's unpredictable.

7:06 I once read somewhere that a Western man,

7:10 if it rains for 5 days, will expect it to rain on the sixth.

7:15 Whereas a East Asian person, say Japanese for example, if it rains for 5 days,

7:21 will expect no rain on the sixth because the pendulum,

7:25 like you say, it swings back to the mean.

7:27 Is that culturally true?

7:30 Uh I have no reason to know.

7:32 Mhm.

7:32 I don't know.

7:33 Uh but uh what I would say is if

7:42 if the probability of rain is let's say 50/50, Mhm.

7:47 if some people think 5 days of rain means the sixth will rain Mhm.

7:51 because of continuation of trend,

7:54 and some people think 5 days of rain means that it won't

7:59 rain the next day because the rain has all been used up.

8:03 What I think is on the sixth day it's 50/50.

8:08 The previous days do not matter for the sixth day.

8:10 Well, I mean and in weather that may not be precisely true,

8:15 but but I'm a big believer in in the independence of events.

8:20 And I think that that's what Mojo is about.

8:22 Mhm.

8:22 Independence of events.

8:24 So, you know, if you flip 10 a coin 10 times,

8:28 better example coin than rain cuz rain

8:31 there are some physical properties at work,

8:33 but if you flip a coin 10 times and you get 10 heads,

8:38 the probability of heads on the 11th flip is

8:40 still 50/50 cuz the cuz the trials are independent.

8:45 Do you believe in game theory?

8:47 In?

8:47 Game theory?

8:49 Uh well, I believe that uh I believe that uh it you can strategize.

8:57 Mhm.

8:58 And you [clears throat] can uh figure out

9:01 uh which action has the highest expected payoff Mhm.

9:05 or the highest maximum potential payoff

9:10 or the least probability of a really bad payoff.

9:15 Mhm.

9:15 And you can perhaps even strategize about what your uh opponent is going to do.

9:22 Mhm.

9:23 I so I I believe in strategy.

9:25 I don't know if that's exactly the same as game theory, Mhm.

9:28 but I I think um I think that you know,

9:34 uh I a- as I've suggested in my comments so far,

9:41 what I really don't believe in is predictions.

9:44 And I believe that uh uh given human nature and the uh dislike for ambiguity,

9:56 uh people pursue uh predictions so that they can understand what world

10:02 they're going to be operating in and and deal with it accordingly.

10:08 Uh and if they do this to excess,

10:14 then they theorize about a world uh they'll be operating

10:21 in uh which is not as likely to obtain as they think.

10:29 Which means that their predictions can be misleading.

10:32 Mhm.

10:33 And um about 20 odd years ago,

10:36 I wrote a memo called you can predict you can't predict, you can prepare.

10:42 And that's really the essence.

10:43 And that that you can tell

10:44 that that comes directly from the understanding of Mojo.

10:49 Um we can't predict the future.

10:52 We can't control the future.

10:55 But we can prepare for the future.

10:57 Now that raises an interesting contradiction in terms.

10:59 If you can't predict what the future will be, how can you prepare for it?

11:04 And the answer is you can prepare for a future which is unpredictable.

11:09 So you can in investing, you can put together a portfolio rather than one

11:15 that will produce maximum success if a certain future unfolds,

11:21 you can put together a portfolio which will do fine if several any

11:30 of several futures unfold and not too

11:34 terribly if a bunch of other futures unfold.

11:37 Now, you can't prepare simultaneously for the uh

11:44 positive tail and the negative tail.

11:47 Mhm.

11:48 If you If you prepare for a total disaster,

11:53 then you're unprepared for a great future.

11:58 If you prepare for enormous success and you're

12:02 going to maximize your outcome should this success unfold,

12:08 then you're probably totally unprepared for a very negative.

12:12 But you can prepare if you if you uh sub optimize

12:20 for a number of possible outcomes in the middle of the probability distribution.

12:25 Isn't that a bit contrarian to the coin example?

12:29 You said if you toss a coin and it comes heads 10 times Yes.

12:34 and I toss it the 11th time, you still expect the odds to be 50/50.

12:39 So, I can't look at past data to predict the future or prepare for the future.

12:44 Then how do I prepare?

12:45 I I think that the I think that the uh

12:49 the difference is that the coin tosses are independent.

12:54 Mhm.

12:54 The result of the preceding coin tosses has no impact on the next one.

12:58 Mhm.

13:00 [clears throat] That's not true in the areas I work in.

13:03 Uh most importantly, uh history, the things that have happened so far,

13:13 and people's reaction to history have

13:20 semi predictable implications for the future.

13:27 Not history, but people's reactions of it.

13:29 Well, not history itself [snorts] as much.

13:33 I mean, if you if you knew history But but well

13:37 but but I mean history is the history of what people did.

13:46 And what people did in the past by itself has implications

13:52 for the things that will unfold tomorrow and next month and next year.

13:56 So, in a way, are you saying the psychology of people mass mentality in a manner

14:02 remains the same and that can be modeled for more so than events can be?

14:10 Well, of course, events are largely the things that people

14:16 do which is largely the result of their psychology.

14:20 But I do think that that events

14:28 in the future are somewhat predictable because be

14:33 because the implications of past behavior are

14:37 somewhat predictable and future behavior is somewhat predictable.

14:44 The things that have happened for example,

14:46 in the economy and the markets are

14:53 likely to induce certain behavior in the future.

14:57 And you can know a little bit about that.

14:59 And but when when the history and the past behavior

15:05 has been extreme the ability to infer from that rises.

15:17 In other words, I wrote a book about cycles and that's

15:21 the one where I referred to my experience traveling in India.

15:25 And uh cycles are induced primarily by behavior.

15:36 By you know the up cycle is exaggerating over generalizing.

15:45 The up cycle that there's a trend line.

15:47 Let's say it's GDP growth.

15:49 There's a trend line.

15:51 But sometimes uh the economy grows more than that.

15:58 Why?

16:00 Largely, I think, because of optimism.

16:03 Because people are optimistic, so they spend a lot of money.

16:08 Producers are optimistic about demand for their products,

16:11 so they build new factories and hire labor and buy machinery.

16:16 And the sum of these things produces a period of above trend growth.

16:23 But then when producers have more than prepared for the coming growth

16:35 and consumers have been sated by consumption then the then things will ease off.

16:50 And maybe it results in a period of below average growth.

16:55 So, you know, I wrote the book I was about 2/3 through

16:59 writing the book and I've been studying cycles for almost 60 years now,

17:03 living through cycles.

17:05 And I said to myself, just why do we have cycles?

17:11 Why doesn't GDP, if if the average growth in GDP is two,

17:14 why isn't it always two?

17:16 Why is it three or four or one or zero or minus one?

17:20 Uh and the answer is excesses and corrections.

17:25 And then you go to a negative which is

17:28 an excess and then it corrects back to the trend line.

17:31 So rather than thinking of cycles as as ups and downs,

17:34 which I think most people do,

17:36 think of them as excesses and corrections, excesses and corrections.

17:41 Fluctuations around the trend line.

17:44 I mean Uh this is most easily seen in in in the stock market, for example.

17:48 You look at the S&P 500.

17:51 The S&P 500 has returned about 10% a year on average for the last 100 years.

17:59 But the constituents of the S&P have changed many times in that period.

18:03 the but the average rate of return doesn't change.

18:06 Average rate of return.

18:07 I don't know about the S&P.

18:08 I know in India the indices, I'm a stock investor.

18:11 That's my full-time job.

18:15 Yes.

18:13 We have returned about 11% over the last couple of decades.

18:20 But we have depreciation of currency which is about 4 5% a year.

18:24 So I'm assuming the S&P would have returned 6%

18:28 if you were to ask me to wager a guess.

18:30 But I don't think it's a fair benchmark because the companies in the S&P,

18:34 like the indices back home, change by virtue of market cap.

18:39 They do.

18:40 But my point is that the S&P, however constituted,

18:46 has returned an average of 10% a year for the last 100 years.

18:51 But um not steadily.

18:58 Mhm.

18:59 In the '90s, it returned 20% a year.

19:04 And in the '00s, it returned zero per year.

19:08 So certainly not steady.

19:10 And not only is that an interesting phenomenon to think about, but even more so,

19:17 the fact that the return on the S&P which

19:21 averages 10 is almost never between 8 and 12.

19:27 Mhm.

19:28 This is a very interesting datum.

19:29 Mhm.

19:30 Uh uh why is it that the norm is not the average?

19:42 Greed and fear.

19:44 Excess and correction.

19:46 Do you think

19:47 Excess of optimism?

19:49 Correction.

19:50 Excess of pessimism.

19:52 Can I ask you a a small digression in a question?

19:57 If humans were no longer in the picture Yes.

20:00 and AI models are trading in the market

20:05 would 10% be 10% every year because there would be no optimism and pessimism?

20:10 Uh I This is another of those times when

20:13 I'm going to say I'm not smart enough to know.

20:16 It stands to reason that it would.

20:18 Mhm.

20:19 If America if if we programmed AI to find the elements and expect

20:35 uh the patterns that produced success in the past and left it alone

20:43 and since we're told AI does not have greed or fear or optimism

20:49 or pessimism you would think that that the returns would be uh steadier.

20:59 I think it makes it makes sense to think that.

21:03 I heard your interview a year ago

21:06 with Nikolai from the Norwegian sovereign fund.

21:08 He's a friend of mine.

21:10 And when he asked you,

21:12 "Where are we in the cycle?" you said somewhere near the middle.

21:20 Well, I think that was 2 years ago.

21:22 Okay.

21:23 Yes.

21:23 Where are we now?

21:24 Um well, we're Guess what?

21:27 It's 2 years later.

21:28 Mhm.

21:28 That's the only thing I know for sure.

21:31 But uh I believe that I I So, I believe that interview was April of uh '20 4.

21:39 And the market continued upward from April '24

21:50 through I think it's fair to say January Mhm.

21:55 of '26.

21:55 So, another uh 21 months took it considerably higher.

22:01 Um and uh of course, the uh the economy people when you look at the economy,

22:10 people think of the age of the recovery.

22:13 So, the the economic recovery is 2 years older.

22:15 The the the the bull market in stocks went on another almost 2 years.

22:21 So, um I would I would say that the uh You see,

22:29 it it First of all, as the economy, it's very very hard to date or talk about

22:34 the age of this cycle because we had the pandemic Mhm.

22:39 where we did something unique.

22:41 We closed the world economy Mhm.

22:44 to produce the spread to reduce the spread of the disease.

22:48 Mhm.

22:49 And so, that interfered with the normal workings.

22:52 Mhm.

22:53 And it according to the people who make these decisions,

22:58 it produced a recession.

23:01 It was in a very unusual recession because it was only one quarter.

23:04 I always thought and a recession was two quarters of negative GDP growth.

23:09 Uh and of course, it didn't occur for the normal

23:12 reason of excess optimism leading to a correction.

23:16 It was man-made.

23:17 Mhm.

23:19 And was readily corrected.

23:21 Mhm.

23:21 So, the second quarter of 2020 was the worst quarter

23:24 in the history of the world uh for for US for GDP.

23:29 Uh and then the third quarter was the best.

23:31 Mhm.

23:32 So, was it really a recession in the in the functional

23:36 terms of determining cyclicality uh or or just some noise?

23:44 Uh and Can I ask another question here?

23:47 I would see GDP if I were to consider

23:50 it the total produce going into the economy.

23:56 Yeah.

23:55 And consumers consume as much as we can.

23:59 I could argue that a recession is truly when there is

24:03 more production in an economy and the consumption is organically lesser.

24:08 So, do you think GDP is a good benchmark

24:10 to figure out when there is a recession or not?

24:13 Because the consumers went away then artificially.

24:19 Well, I think it's I think um I think your definition of recession

24:24 isn't isn't right because what you said was uh there's more production.

24:30 But, that's not Less consumption.

24:32 Less consumption.

24:32 That is That's the main element of of uh of a recession in my opinion.

24:39 Uh uh Manufacturers are always happy to produce goods to meet demand.

24:46 It The recession it means primarily a reduction of demand so that uh which

24:54 which discourages manufacturers from producing and the reduced

25:00 production is really what causes the recession.

25:06 Fewer people are at work.

25:08 Uh etc.

25:09 Fewer goods are produced and consumed.

25:11 So, in the pandemic production went down,

25:14 but the demand for consumption did not actually go down,

25:18 but just that the markets were shut for a period of time.

25:20 Because when they opened people really consumed.

25:22 Well, I mean yes, the the underlying demand didn't go down,

25:25 but people I mean in the sense that people would have liked to have parties.

25:34 Mhm.

25:35 They just weren't allowed to have parties.

25:37 So, the demand that the psychological demand for a party was there,

25:42 but the economic demand for rental halls and bands and food

25:48 and uh party dresses and things like that uh didn't exist.

25:55 Uh so, that's that So, but this is why I say that the GDP was

26:00 kind of artificially depressed uh by a decision of government, really.

26:09 So, So, when we say that what How old is this recovery?

26:14 Was that a real recession?

26:16 If that was a recession, then this recovery is now 6 years old.

26:22 If that wasn't a recession, 20 8 years old.

26:27 [clears throat]

26:27 This Then this recovery is 17 years old,

26:29 which is the longest in history is 10 years.

26:33 Why 17?

26:34 Because the last recession was in '09.

26:36 Mhm.

26:37 So, it's 17 years since then.

26:39 But can you just tie recessions and cycles down to tenure time?

26:46 You can't and that's one of the reasons why I don't believe in predictions,

26:49 but there seems to be a norm.

26:52 Mhm.

26:53 Uh we always said that the average was eight years Mhm.

26:58 for a for a recovery.

27:00 And uh in the 2010s uh it went on for 10 plus years.

27:08 So we called that the longest in history.

27:09 So So and and and normally if we have

27:13 a recession uh in year one X we don't expect

27:18 another recession two years later because recovery goes

27:23 on for some period of years which seems to average eight.

27:26 I can't explain why.

27:28 Mhm.

27:28 I don't think anybody can tell you why.

27:30 Maybe maybe the answer is on average eight years is long

27:33 enough from the last one to prevent to permit the next one.

27:36 Uh but uh So I don't believe you can uh Uh you know somebody

27:41 I I I I wrote the book about cycles and and somebody in England said,

27:45 "Oh no, these aren't cycles because they're not predictable." Mhm.

27:48 You know, cycles like radio waves or sine waves

27:51 or or or something like that, these are predictable.

27:54 And and I think that uh it it patterns in the in the in the real world,

28:01 the the non non non-scientific,

28:03 non-mechanical world uh certainly aren't regular Mhm.

28:09 but they do occur.

28:10 Ups and downs.

28:11 They do it predictably but not necessarily

28:15 predictable in time or predictable in uh amplitude.

28:20 But they certainly occur predictably.

28:23 So if I can bring you back Howard to the question What question?

28:26 It's so long ago.

28:27 The [laughter] Where are we in the cycle now?

28:30 Well, I think I think that the uh the recovery is uh I think

28:39 it's uh it's gone on a good while and uh it's uh it's not nascent,

28:49 it's not adolescent.

28:51 Uh it's but it's also not uh uh geriatric.

28:56 I think it's in middle age.

28:58 Uh and and I think I think the US economy,

29:02 if that's what you're talking about, is healthy.

29:04 And and uh doing quite well.

29:08 Uh If if the thing that presages uh a downturn is excesses to the upside,

29:18 you don't find too many of those.

29:21 You know, uh when I go to a city,

29:23 I I look for construction cranes in the sky

29:25 to tell me if there's a building boom.

29:27 Most booms are followed at some point by busts.

29:31 I don't see it in most of our cities.

29:34 Uh I don't see uh inventories growing.

29:39 Uh inventory growth is i- i- i- In- inventories grow for two reasons:

29:46 in times of uh weak consumption because

29:50 people don't buy the things that manufacturers produce,

29:53 in times of uh uh of strong consumption,

29:57 uh inventories grow because manufacturers amp up production

30:01 to get ahead of some anticipated surge in demand,

30:05 and those often pre- presage downturns when they turn out not to be warranted.

30:10 I don't see that.

30:12 In some sectors, do you?

30:15 Well, I mean, maybe I I don't I don't

30:17 look at the data finely enough to tell you that.

30:20 In AI, maybe?

30:21 Pardon me?

30:22 In AI, maybe?

30:24 Uh well, of course, we don't talk about inventory in AI,

30:27 but there's certainly a boom in capital investment for AI.

30:30 One could say hardware, energy, computers inventory.

30:35 Yeah.

30:35 Well, I mean, look, there's massive construction of infrastructure for AI.

30:41 Much like buildings.

30:42 Yes.

30:43 And planes.

30:44 Yes.

30:45 That's right.

30:46 That that Well, that is that is the area that's booming in our economy.

30:51 And I need people who know more about AI

30:54 than me to tell me whether it's going to bust.

30:57 You know, the question is is all

30:59 of this or is some of this construction unwarranted?

31:03 Um I don't think anybody can tell us that.

31:08 We do know we certainly know that it is an area of of boom.

31:16 How do you stay so sharp, Howard, at your age?

31:18 Like I have watched a whole bunch of your interviews

31:22 and read a lot of what you have written over the years.

31:25 As a stock market investor all my life I

31:30 think there's so much I can learn from you.

31:32 But how do you stay this sharp today?

31:36 Well, I don't think I don't I mean I'm lucky.

31:42 I have Genetically?

31:43 Well, I think I'm I think I'm very lucky genetically.

31:46 Okay.

31:47 Yes, because my dad lived to 101 and he was quite sharp at the end.

31:52 Mhm.

31:52 Um and um you know, uh we all face a decline at some point in time.

32:02 Mhm.

32:02 And the only question is when does it start

32:04 and and and at what rate does it progress?

32:07 And uh you know, you look at uh Warren Buffett, Charlie Munger,

32:12 some of my uh role models and friends and you know,

32:20 they were or are uh sharp in their mid-90s and late 90s.

32:29 So, it's just a I mean, I didn't When you say,

32:32 "How do you stay sharp?" I don't go to the gym

32:35 and work can I do do a lot of puzzles,

32:38 and I read, and I read in fields that are not my fields.

32:43 I you know, I I'm still trying to gain knowledge and broaden myself.

32:48 And I guess I'm make some effort to to plow new ground.

32:54 And the question is when do you stop doing that, at what age?

32:57 But you know, I my last two memos uh I hope your audience knows about the memos.

33:04 Yeah.

33:04 But I wrote one December 9th and one I think February 25th.

33:09 Uh Um about AI.

33:13 Mhm.

33:14 And I had to do a lot of learning.

33:16 You changed your mind on the AI as well.

33:17 I changed my mind, but first I first I challenged my mind.

33:22 Mhm.

33:22 And you know, I had for the second one in particular,

33:26 I had a extensive conversation with Claude and and and and learned a great deal.

33:32 Mhm.

33:32 Um and uh you know, it was very exciting to be plowing new ground at almost 80.

33:41 Um and Do you think it could be ambition and hunger?

33:47 Well, it it's it's it's it is definitely a hunger.

33:51 It's a hunger to learn and to stay relevant.

33:54 And and to stay stimulated.

33:58 Uh when [snorts] you say ambition, that that usually starts with dollar signs.

34:04 Not necessarily.

34:05 Yes, well, it's it's an ambition to stay relevant.

34:09 And and and to to use your terminology,

34:15 to stay sharp rather than start to atrophy.

34:20 I think staying relevant is the core ambition of everyone.

34:25 The dollar is a means that people pick in the beginning.

34:30 Not at the end, maybe.

34:33 Well, I think I think that most ambition starts with the dollar sign.

34:43 Mhm.

34:43 In enlightened cases it transitions Mhm.

34:48 to non-dollar.

34:49 Not every case.

34:51 Uh-huh.

34:51 The you know, there are people are different.

34:53 You can't you Mark Twain,

34:55 I think it was said all generalizations are flawed including including this one.

35:02 But you can't generalize.

35:04 Uh Like you say very well,

35:07 I heard you speak about the role luck plays in our life.

35:11 Mhm.

35:12 Would you say enlightened or lucky?

35:15 The ones who transition.

35:17 Uh well, now now you're really getting

35:20 deep because now you're talking about determinism Mhm.

35:24 Uh versus uh intention.

35:27 Mhm.

35:28 Um and I think there are some of both.

35:31 Mhm.

35:33 I mean, some people kind of I mean

35:36 I mean these things are hard to parse, Nikhil.

35:39 And but some people I think transition naturally.

35:43 And as they grow, maybe they become wiser.

35:47 And they start to understand that that there are things that are more important

35:52 than money or uh let's say things that are important in addition to money.

35:58 And so they do it let's say that naturally, not intentionally.

36:07 Mhm.

36:07 I would imagine there are people who do it intentionally.

36:10 People who go to the mountain and meditate Mhm.

36:15 and think about it and conclude, you know what,

36:18 I really should change my focus at this point in my life.

36:21 Have you even to have you been able to ever pull that off?

36:24 Like I've been fascinated with the idea of going to a mountain and arriving

36:30 at some kind of evolutionary thought in my mind

36:32 which makes me actively transition into something.

36:38 Mhm.

36:39 Have you been able to touch that?

36:41 Well, I I I I haven't physically gone to the mountain,

36:45 but I I think the key uh I've got I've written the first pages of a book.

36:53 Mhm.

36:53 Uh I think the I think the the the key

37:01 to all of this to all of life is to behave thoughtfully.

37:08 With your mind engaged.

37:10 Not just uh let the river take you.

37:15 But give thought to what's going on.

37:18 Why is it going on?

37:21 What does it mean?

37:25 Why did it happen?

37:27 What does it imply for me?

37:30 What should I do about it?

37:33 And uh it's the That's That That is

37:40 I think going through life with your eyes open.

37:45 Uh and that's how you can intentionally get

37:53 to a higher stage in life by doing that.

37:57 And and the the the uh the image that comes back

38:06 to me is the image of whether you let the river take you.

38:11 Or whether you uh try to figure out a a better

38:17 place to get to and then try to get there.

38:22 Maybe once or twice in my life I have felt like I could see the river.

38:29 See the river?

38:30 The river, yes.

38:31 Can you actively?

38:33 Um I I think at this stage I I

38:38 I am able to think about this progression constructively.

38:44 When I think about my early decades, not years,

38:49 decades and I think about uh you know what I did from let's

39:00 say I would say from the beginning of let's say high school Mhm.

39:08 1960 Mhm.

39:10 until starting Oak Tree in in 95.

39:16 Mhm.

39:15 So that 35-year period which took me up to age uh let's say 49.

39:22 I was adrift.

39:27 I did not make proactive decisions.

39:31 I let the river take me.

39:33 I'm very lucky that it took me to some good places.

39:36 Mhm.

39:37 In in in several different aspects of life.

39:40 But I don't consider when I look

39:43 at my behavior I don't consider it thoughtful or intentional.

39:49 And so I'm just lucky that I got to a good place despite my own inattention.

39:55 Uh I think that uh starting Oak Tree was the biggest

40:03 and maybe first I thing I really did with intention.

40:08 And I and I've tried to be more intentional since then.

40:12 But when I look back and I describe uh how I selected my career,

40:16 how I selected my first job, how I decided to go to graduate school,

40:20 uh uh and and and and and how I transitioned

40:26 from from the the equities department to the bond world

40:32 uh in 1978 uh in time to uh in time

40:39 to have the benefit of the birth of high-yield bonds.

40:45 It was all happenstance.

40:47 Serendipity, coincidence, uh passivity.

40:52 You know, I I I was not making intentional decisions in that period.

40:57 What changed?

40:57 How did you become intentional from being unintentional when you began Oaktree?

41:07 Because other people people can maybe learn from it.

41:09 Maybe I can learn how to catch it.

41:11 Well, the easy answer is that my wife pushed me.

41:14 Uh uh to to uh think about it more and to uh independently start Oaktree.

41:25 My partner Bruce Karsh uh uh and I did it together.

41:32 He he So, his participation uh encouraged mine.

41:37 Uh but that that required a proactive decision.

41:41 Uh you know, uh the the biggest change I made

41:45 before that professionally was moving from Citibank to TCW in '85.

41:49 They approached me.

41:51 Mhm.

41:52 Uh that was not proactive on my part.

41:54 Not the act of starting Oaktree,

41:56 but from being adrift the river to seeing the river.

42:02 Well, I think I think uh once I made

42:09 the decision to participate in the starting of Oaktree,

42:14 I I couldn't drift anymore.

42:17 Cuz now I was uh the person leading Oaktree.

42:22 I had to make uh proactive decisions.

42:25 I mean, it it became my job.

42:27 Uh and uh and maybe I maybe I warmed to it.

42:32 Uh maybe having made the proactive decision to start Oaktree and having done it,

42:37 maybe I said, "Hey, this is this is good.

42:39 I think I I think that I maybe

42:42 I like leadership." And leadership is by definition proactive.

42:48 It is It's It It It seems like an oxymoron to say he led passively.

42:54 Those two words are in opposition.

42:57 So, I think that I think that uh Thank God I I rose to the occasion

43:05 and and left TCW with Bruce and and my other partners to start Oaktree.

43:10 And then, I think that it was I don't I don't think I ever said,

43:15 "Well, now I'm going to start taking control of my life.

43:18 Now I'm going to start acting intentionally.

43:20 Now I'm going to become a leader." I just think it was inescapable.

43:29 That's very interesting cuz it sounds

43:31 like you're saying entrepreneurship and taking

43:35 risk can trigger the riding the river to seeing the river.

43:42 Some people are driven entrepreneurially.

43:45 I think that entrepreneurship is the epitome of intentionality.

43:53 It's It's taking the bull by the horns, as we say, proactively.

44:01 So, I think the entrepreneur naturally,

44:08 innately does the opposite of drifting down the river.

44:14 Uh and um my inclination was not entrepreneurial.

44:22 You know?

44:23 Uh I I uh I liked most of what I was doing at TCW.

44:30 Uh but uh with with encouragement from Bruce

44:37 Karsh and my wife and with a little encouragement

44:44 from TCW to leave in terms of how

44:48 I thought I was treated my inertia was overcome.

44:52 That's what I would describe, you know?

44:54 It wasn't a proactive decision, "Hey,

44:56 let's let's get going." It was the unlikely overcoming of my innate inertia.

45:06 It's a very different story.

45:07 It could be like a chicken and egg thing?

45:09 Oh, it's very chicken and egg.

45:11 Yes.

45:11 But but uh I think the important thing is for the purposes

45:17 of your audience that my departure from TCW

45:23 did not start with an entrepreneurial spirit.

45:28 And some people I know I know people who,

45:30 you know, who were entre- I mean uh you know,

45:37 always dreamed of making a lot of money always dreamed

45:41 of running their own business chafed at being an employee,

45:46 had to get out and start their own.

45:49 Uh that that that was never descriptive of me.

45:52 Mhm.

45:53 So, I kind of I I kind of uh did something that you might call entrepreneurial.

46:02 Uh despite myself is the way I would describe

46:06 it rather than the cause of my uh innate drive.

46:14 So, Howard, my job for 20 years has been that of a stock investor.

46:18 Mhm.

46:19 You've been a debt person almost all your life.

46:25 Why would you be in a asset class which has finite upside?

46:31 And the downside I guess is finite because in most

46:35 cases it's zero versus equity where you could have exponential upside.

46:40 Well, that's a great question.

46:42 And uh I I I haven't really been asked that question much in the past.

46:46 My answer may take a while.

46:48 Settle in.

46:49 Uh the the question as you pose it is

47:03 an interesting question if you assume rationality and objectivity.

47:16 But that ignores personal let's say kinks.

47:24 So, I'll return to that.

47:26 But first of all, my decision to move

47:28 from I I spent 9 years in the equity department.

47:31 So, it wasn't really at the very beginning.

47:32 It felt like a long time.

47:34 But my decision to move from the equity department in '69

47:37 to to the bond department in '78 was not my decision.

47:42 And it it it it uh it wasn't because I figured out it would be better for me.

47:49 Uh the the the the Citibank I joined in September

47:53 of '69 was an investor in what was called the Nifty 50.

47:56 Mhm.

47:57 The 50 supposedly best and fastest growing companies in America.

48:03 Companies where nothing bad could ever happen.

48:05 There was no price too high for the stock.

48:09 And if you bought those stocks the day I got to work in September '69,

48:12 if you held them tenaciously for for 5 years, you lost about 95% of your money.

48:18 95%.

48:20 Because for many of them, something did go wrong.

48:23 And for all of them, the price was too high.

48:26 The PE ratios, as I recall, were mostly between 60 and 90.

48:33 So, it was a uh and and So,

48:36 that was a real disaster for the people who invested in the Nifty 50,

48:42 which was most of the money center banks.

48:45 And I was uh director of research by the mid-70s, so I was part of the process.

48:53 And we hired a new CIO who wanted to have a new head of research.

48:58 And uh I helped him hire my successor.

49:02 And then he said, "What do you want to do next?" I said, "I don't know.

49:06 I could do this.

49:07 I could do that." Typically, I didn't think it over very much

49:10 or or assess my strengths and weaknesses very well.

49:14 And he said, "I'd like you to move

49:16 to the bond department and start a convertible bond

49:18 fund." Cuz he had come from a place

49:20 that had a had one and it was very successful.

49:23 And we didn't have one.

49:25 And I said, "Yes." So, that was the extent of my intentionality.

49:29 Which is almost non-existent.

49:31 It was you know, uh and I and I say now,

49:34 and it may be an exaggeration, but I was lucky I didn't get fired.

49:38 Uh but American companies gave pretty much lifetime employment at that time.

49:43 Anyway, so so number one, my move to to the bond department was not voluntary.

49:51 Other than I could said no.

49:53 Uh Uh but number two, you talk about the fact that bonds have

49:59 uh capped upside and some downside from default.

50:04 Certainly true.

50:05 But it hit me because I was brought up to be very conservative.

50:11 My parents were adults during the depression.

50:16 Now, your parents probably weren't alive during the depression.

50:20 Or and most people I know who are old,

50:23 their parents were children during the depression.

50:26 My parents were adults during the depression.

50:29 Which meant that when I grew up, what did I hear?

50:31 Mhm.

50:32 Don't put all your eggs in one basket, save for rainy day, avoid risk, etc.

50:37 So, I think Indians Indian parents

50:40 lived through pseudo socialism in the country.

50:42 Mhm.

50:42 Similar.

50:43 Yeah.

50:44 Not as bad.

50:44 Yeah.

50:45 Yeah.

50:46 But but um You see, you as a stock

50:56 guy look at bonds and say no upside some downside.

51:04 I say predictable outcome which is achieved almost every time.

51:12 Is that true though?

51:13 Cuz a lot of the distressed bonds

51:15 that you are in, which have fairly high coupons,

51:21 is the chance of a downside zero?

51:24 I said almost every time.

51:26 Mhm.

51:26 And you know, uh uh First of all, uh so as I said,

51:34 I moved to the bond department in '78, uh May of '78.

51:37 In A- August of '78, I got the phone call that changed my life

51:41 from the head of the bond department who

51:43 said there's some guy in California named Milken

51:45 or something who deals in something called high yield bonds.

51:48 Do you think you can figure out what

51:50 that is cuz the client had asked for a portfolio.

51:53 Junk bonds.

51:54 Pardon me?

51:54 Junk bonds.

51:56 Milken, Michael Milken, junk bonds?

51:58 Yeah, junk bonds.

52:00 So, so I said yes.

52:04 Mhm.

52:04 I can do it.

52:06 And that put me here today.

52:11 48 years later.

52:13 Um but but um so I I if you've read Malcolm Gladwell,

52:21 Outliers, you know the importance of right time, right place.

52:25 I was in the right place at the right time.

52:28 I was in and that put me in high yield

52:30 bonds at the beginning of the high yield bond movement.

52:34 I've met Michael Milken and because he got unlucky later in life,

52:39 it couldn't have just been right place,

52:41 right time cuz it didn't go that way for him.

52:44 For a period of time.

52:45 Well, that's right, but things in his existence

52:49 conspired to produce a bad result for a while.

52:53 Uh but not for me.

52:57 I got there at the beginning.

52:59 The What Malcolm Gladwell's book is really about, Nikhil,

53:02 is about it's great to be at the front of the line.

53:06 That's really what it's about.

53:07 He talks about demographic luck.

53:09 Mhm.

53:09 Right?

53:10 Right time, right place.

53:12 I think the question is how do you figure out where is the front of the line?

53:15 Well, you [clears throat] Well, I didn't.

53:17 Somebody said, "Would you please stand on that line?" And I

53:19 looked around and I was the first person in the line.

53:22 Mhm.

53:23 You see?

53:24 So, that's luck.

53:25 Uh figuring out is is much harder

53:29 and by the way not all the people who got Well,

53:33 who were first in the line were there because they

53:38 figured out that that was the line to be on.

53:40 A lot of it is serendipity.

53:42 You know?

53:43 And not all of them did well, either.

53:45 That's right.

53:46 That's right.

53:47 Not all of them did well.

53:48 But anyway, the point is I've been in high yield bonds for 48 years.

53:53 Mhm.

53:54 And in our experience,

53:56 99% of the bonds have paid interest and principal as promised.

54:00 Mhm.

54:01 So, I think I can say almost every time.

54:05 And if you earn on average 10%, you only needed to be right 90% of the time.

54:11 No, that's not right.

54:12 Because if you if if 10% of your bonds defaulted and you lost

54:16 10% of principal and the made 10% of interest on the ones that paid,

54:20 you had a zero return.

54:22 Yeah.

54:22 You You had to You had to constrain your losses to a much lower figure than 10%.

54:28 You had to be right 90 at 7 8 9% of the time, and we were right 99% of the time.

54:37 Because I think we did it in an above average way.

54:40 But the point is that reliability appealed to me.

54:46 And uh I'm not a futurist or optimist.

54:51 And uh so, I was well suited to it.

54:55 Um and then, of course,

54:56 we got into the distressed debt business when Bruce Karsh joined me in '87.

55:01 We brought out what I believe was the first distressed

55:03 debt fund from a mainstream institution or one of them.

55:08 And you know, he He runs those funds.

55:11 He's managed about 70 odd billion dollars since 1988 in that field.

55:18 By far the biggest.

55:19 And uh of of his total profits and losses, well over 90% are profits.

55:29 Less than 10% are losses.

55:30 So, again, I think you can say most of the time.

55:34 And so, the regularity the contractual nature

55:40 of returns on bonds appealed to me.

55:43 Um and so, this is why I've been very comfortable in that in that field.

55:50 The other thing is, frankly, a lot of your success [snorts]

55:57 in investing is determined by other people.

56:01 If if if you go into a field that everybody likes

56:04 and they like it a lot and have bid up the price,

56:07 then your returns are not likely to be high.

56:11 If they If you go into a field where

56:13 everybody else has been blind to the merits and says,

56:17 "I wouldn't touch that with a 10-ft pole." and you figure

56:20 out that it's good and it turns out to be good,

56:23 uh that's how you get an exceptional return with low risk.

56:27 Uh so, um I think that uh for the most part,

56:35 uh well, I was lucky at I should say,

56:38 at the time I made these decisions uh actively or passively,

56:43 took these steps, shall we say.

56:45 Um uh I went into fields other people didn't like.

56:51 You You used the term junk bonds.

56:53 Derogatory term.

56:54 Nobody talks about junk stocks, right?

56:56 But I mean, junk bonds are much more

56:59 predictable than stocks and yet they called them junk.

57:01 We call them distressed bonds.

57:03 Yes, but that was a that was that was

57:04 a bias that that made them available to me cheap.

57:08 Mhm.

57:09 And and that was that was a very good thing

57:11 and and I could see that and take advantage of it.

57:14 Can you contextualize distressed bonds?

57:18 Let's say the US Treasury, US government borrows at 4%.

57:22 Let's say I read somewhere that Google is

57:25 borrowing 100-year paper at 6%, which sounds crazy.

57:28 And we'll get to that.

57:30 What kind of companies are in this distressed bond

57:36 ecosystem and what rate of return are they paying?

57:38 Rate of interest.

57:39 Well, let's We have to clarify.

57:41 Mhm.

57:42 Oaktree and I have two businesses.

57:46 Mhm.

57:46 One we perform we call performing credit Mhm.

57:49 and one we call opportunistic credit.

57:51 That's the new euphemism for distressed.

57:55 Mhm.

57:55 So, but Wouldn't you benefit from calling it junk so you have

57:59 a higher margin because more people would stay out of it?

58:03 Yes, if they listened to me.

58:06 If I was that influential.

58:07 But and and that's the right kind of kind of counter thinking.

58:12 But on the other hand, a big part of our business now is making

58:17 loans to companies that need what we call rescue loans.

58:21 Mhm.

58:22 They don't like to be associated with the word distressed.

58:25 Fair.

58:25 So, we're more likely to get their business Mhm.

58:29 if we call it opportunistic.

58:31 Fair.

58:33 Um So, uh you know, in the performing credit area, Mhm.

58:43 we lend money to companies that the world thinks has

58:51 a let's say 3 4 5 6% of not paying us.

58:57 Mhm.

58:58 Prob- 3 4 5 6% probability of not paying us.

59:03 Mhm.

59:06 We lend them money if we think it's 1 or 2%.

59:13 So, if the world thinks they're 5% likely to not pay us

59:19 and we conclude that they're only 2% likely to not pay us,

59:23 then the world requires them to pay an a rate

59:27 of interest which is commensurate with their 5% probability of non-payment,

59:33 which means if we're right and it's only two,

59:35 we're getting something for nothing.

59:37 And that thing is called excess return.

59:39 So, so that's what we do.

59:42 That's the essence of lending money.

59:45 I mean, why would you lend money to a company

59:47 that has a non-zero probability of paying you back?

59:50 Mhm.

59:51 And the answer, Mike Milken's answer, was you can demand a rate of interest

59:56 which is compensatory or more than compensatory.

1:00:00 And when you get when you get payment in life

1:00:04 for doing something which is more than compensatory that's called excess return.

1:00:12 So, is the skill set at Oaktree calculating that spread?

1:00:16 And how how do you do that?

1:00:19 Well, when you say the spread,

1:00:20 the the the the skill set at Oaktree, the the base,

1:00:24 the most important fundamental skill set is predicting

1:00:29 the probability of default better than other people.

1:00:34 That's That's where Mhm.

1:00:36 if if we don't have that that's

1:00:38 the necessary condition for for superior performance.

1:00:42 And is this skill set company specific or are you able to call

1:00:47 the larger cycle in the market and hence you do it better?

1:00:50 Mhm.

1:00:52 No, that skill set is separate from the latter

1:00:56 thing you talked about is what we call macro.

1:00:58 Mhm.

1:00:59 The that skill set is not is micro.

1:01:02 Mhm.

1:01:03 We have great analysts who look at companies.

1:01:06 We have a framework for analysis.

1:01:10 The framework is essential, necessary but not sufficient.

1:01:15 Mhm.

1:01:16 The the the what makes it sufficient

1:01:19 is having brilliant people to operate the procedure.

1:01:26 The procedure itself is nothing without superior implementation.

1:01:31 But we have both.

1:01:33 And so, over the last 40 years, on average, something like 3.6 or 3.7% of all

1:01:40 high-yield bonds have gone into default every year.

1:01:44 And our default rate has been uh roughly uh a third.

1:01:55 That's our superiority.

1:01:57 And that is a case-by-case, bottom-up uh uh superior implementation.

1:02:08 And when you say superiority, not the process,

1:02:12 of the people running the process, do you mean attention to detail?

1:02:16 Do you mean thinking out of the box?

1:02:19 No.

1:02:20 Um Why Why do we have a lower default rate?

1:02:24 Mhm.

1:02:24 Well, I think we have institutionally more experienced than anybody else.

1:02:31 We've been doing it longer.

1:02:32 We have a uh a a work environment that allows

1:02:39 people to stay in that job for their lifetime.

1:02:41 You know, when I started at Citibank in '69,

1:02:44 every analyst goal was to become a portfolio manager.

1:02:49 Mhm.

1:02:49 Cuz that's where the That's where the luster was.

1:02:52 So, so, and as long as that's the case, then on the analytical side,

1:02:57 you don't build up institutional excellence because it's people

1:03:01 are always trying to get out of that job.

1:03:03 You want people to build up excellence and stay in the job

1:03:06 so that you can get the benefit of their excellence.

1:03:09 Mhm.

1:03:09 And and uh we set up that system.

1:03:13 So, you know, you can be a lifetime analyst

1:03:16 and be very successful if you're great at it.

1:03:19 So, that's one important thing.

1:03:21 So, we have people who've been doing it for years and years, decades.

1:03:25 And we have the benefit of their expertise.

1:03:28 Uh we have the institutional experience which gives us stability in times

1:03:33 of rocky uh psychology when people get too excited or too depressed.

1:03:39 We tend not to.

1:03:39 That's a great help.

1:03:40 Mhm.

1:03:41 We have a a process which enumerates a eight areas of investigation

1:03:48 and many subsidiary questions within that and everybody has to follow it.

1:03:53 Now, people might say, "When I when I started doing something like

1:03:55 this at Citibank as director of research, people said, 'Oh,

1:03:58 you're taking away our creativity.'" But we we we

1:04:05 told them that a process they had to follow,

1:04:08 but they could follow it creatively.

1:04:10 But the process consisted of covering the bases.

1:04:14 You got to cover the bases consistently.

1:04:16 You got to ask the same questions of every company every time.

1:04:20 Rather than, you know,

1:04:21 in in the equity world where you live you'll get a research report that says,

1:04:26 "Buy this company, great management." Mhm.

1:04:28 Doesn't talk about the product.

1:04:29 "Buy this company, great product." Doesn't talk about the management.

1:04:32 "Buy this company, uh great tax shelter."

1:04:35 Doesn't talk about the product or the management.

1:04:38 I felt that it was important to cover every base every time.

1:04:42 And when when you when you look at a a at a at a portfolio

1:04:48 and you see a a a a stock

1:04:50 that's down 80% it's usually because something wasn't covered.

1:04:57 Mhm.

1:04:58 And cuz the the the analysis was not disciplined enough to touch all the bases.

1:05:05 And again you know you're talking about the difference between stocks and bonds.

1:05:12 Mhm.

1:05:12 That's one of the differences, right?

1:05:15 We're we're we're bean counters.

1:05:18 We're green eye shade types, but at least we should do it well and consistently.

1:05:22 The equity investor has imagination and foresight and entrepreneurial spirit

1:05:30 and but doesn't do it as consistently as we do our analysis.

1:05:36 If you had to begin a new career today for the next 40 years Yes.

1:05:41 would you pick debt over equity again?

1:05:43 For me or for or for the average watcher?

1:05:46 Let's say for the average watcher.

1:05:50 Well, I think that I think that we were

1:05:54 very fortunate in getting into some debt markets before

1:05:57 they were discovered and before people understood them

1:06:02 and we benefited from people's uh antagonism toward those markets.

1:06:08 Those opportunities are in the past.

1:06:11 Mhm.

1:06:12 So Where is the front of the line today?

1:06:16 Well, I mean who is the person in the investment business

1:06:20 today who will find the most success in the next 10 years?

1:06:26 The answer is in my opinion the person who best understands AI Mhm.

1:06:32 and its capabilities and implications.

1:06:38 So but What if a contrarian doesn't believe in AI?

1:06:42 Pardon me?

1:06:43 Or he could be a contrarian and bet against AI.

1:06:45 Well, that's what I said.

1:06:46 I said best understands.

1:06:47 I didn't say is most in favor of.

1:06:50 So if if AI is going to disappoint the expectations are very high.

1:06:57 And when you as you know from being a stock picker when you go into something

1:07:05 [clears throat] where the expectations are very high,

1:07:07 it's very [snorts] easy to lose money if those uh expectations aren't rewarded.

1:07:14 Mhm.

1:07:15 So, yes, maybe maybe if you're the person who best understands AI today,

1:07:21 maybe you'll make a lot of money

1:07:22 by understanding that it's overdone and betting against it.

1:07:26 The current expectation with AI is almost dystopia.

1:07:31 Or utopia.

1:07:32 Yes.

1:07:33 Which is crazy, I think.

1:07:34 Well, I don't know.

1:07:37 If you read my memos, especially the last one,

1:07:41 you know that I was shocked by my experience with AI

1:07:47 and and Claude and what it But you also said you haven't fired anyone,

1:07:52 nor do you intend to because of AI.

1:07:55 Uh I believe I don't know enough to be confident in this.

1:08:09 But I believe that AI's excellence

1:08:15 is in discovering past patterns, extrapolating them,

1:08:23 and applying them with discipline and with let's say calculations or logic,

1:08:31 which is almost always correct and not subject to psychological ups and downs.

1:08:39 But I think there's more to investment excellence than that.

1:08:42 It's the innovation of new patterns.

1:08:45 It's seeing the potential of things that have never, you know,

1:08:49 how if if if what if what AI does is uh pattern matching, shall we say?

1:08:59 Mhm.

1:09:01 Pattern completion from Yeah.

1:09:03 Mhm.

1:09:03 Then how how will it deal with something where there's no pattern?

1:09:09 Something that's that's brand new.

1:09:11 And you know, I wrote a memo Is there such a thing?

1:09:14 Well, look, I wrote a memo nine

1:09:18 or 10 years ago called investment without people.

1:09:22 Investing without people.

1:09:24 And it was pretty early days.

1:09:26 I So, it had three levels.

1:09:28 Indexation and passive investing.

1:09:33 Algorithmic or systematic investing.

1:09:37 AI and machine learning.

1:09:40 And my revisionist memory or I should say my my memory,

1:09:46 which could be revisionist,

1:09:48 tells me that in that memo I said I posed some questions.

1:09:54 I may not have posed them.

1:09:56 But I wish I had if I didn't.

1:09:58 Can AI sit down with five business plans and figure out which one is Amazon?

1:10:07 Mhm.

1:10:08 Can AI sit down with five CEOs and figure out which one is Steve Jobs?

1:10:18 That goes beyond pattern recognition.

1:10:22 I would bet not.

1:10:23 Well, I would bet not, too.

1:10:24 Mhm.

1:10:25 So, if that's true if we're right that means there's still a role for people.

1:10:31 Mhm.

1:10:32 And but before you go on to the next question, I have to interject something.

1:10:38 Neither can most people.

1:10:40 Mhm.

1:10:41 So, so what that says is there is

1:10:43 a role for exceptional people even in an AI world.

1:10:52 And that's my conclusion.

1:10:54 I hope I'm right.

1:10:55 I hope to be one of them.

1:10:56 Uh I hope my firm is is is still one of them.

1:11:00 But if that's true, if there are things that AI can't do

1:11:07 that some people can then that's what I want to keep doing.

1:11:11 Now, you look, you're a stock picker.

1:11:16 When I went to graduate school at University of Chicago in let's say '66,

1:11:21 no no, '68 the professor said most mutual funds underperform the S&P.

1:11:30 So, and they charge high fees.

1:11:33 So, why don't they just buy one share of every stock in the S&P?

1:11:36 There were no index funds or concept of indexation

1:11:40 that came along in '74 primarily with Jack Bogle.

1:11:44 And now most mutual fund equity capital is run by passive or index.

1:11:54 Why?

1:11:55 Low fees.

1:11:58 Is that the only reason?

1:12:00 No.

1:12:01 It also the active management didn't work.

1:12:06 They they were unsuccessful and charged high fees for it.

1:12:10 But even if they had low fees even if they had charged the same fee

1:12:15 as the index fund if the passive decisions

1:12:18 are inferior indexation is still better than active.

1:12:23 So, it's not the low fees.

1:12:25 That was that exact that exacerbated the problem.

1:12:28 It was really So, my answer is that indexation has taken over as it

1:12:33 has not because it's so good but because active management was so bad.

1:12:41 And but I believe that people can do some things that AI can't.

1:12:49 Could you also say that indexation and ETFs have taken

1:12:52 over because the markets have been in an uptrend largely.

1:12:58 In a more volatile time, active might make sense.

1:13:02 In a depression, active might make sense.

1:13:04 You know what?

1:13:07 The bad times create an opening for active management.

1:13:13 But it's still hard.

1:13:15 And not many people can do it well.

1:13:19 Why do bad times create an opening?

1:13:23 Because panic drives down let's say stock prices.

1:13:28 But the same panic causes most people to panic,

1:13:31 which means that most people can't stop up and buy in the panic.

1:13:35 And there's a There was a guy named Wally Deemer, who was an old-time trader,

1:13:39 who had some great quotes, and he turned them into a little book.

1:13:43 And he But his greatest quote of all is,

1:13:45 "When the time comes to buy, you won't want to." So,

1:13:50 this this idea that upheaval creates

1:13:54 opportunity is logically correct, but not realistic,

1:14:01 because most people's psychological impediments prevent

1:14:05 them from taking advantage of the upheaval.

1:14:08 You see?

1:14:09 Maybe you mix active plus AI together to try and take emotion out of it.

1:14:13 Well, that that could work.

1:14:16 That could work.

1:14:17 If If Claude could call you or send you a message which says,

1:14:23 "This is one of those opportunities we talked about.

1:14:25 Don't be stupid.

1:14:27 Get your ass in gear and buy something.

1:14:29 Don't hide in your in your in your in your hole."

1:14:34 That could That could be a good thing.

1:14:36 Yes.

1:14:37 But But I still think that [snorts] I still think, Nikhil,

1:14:42 that when you get into areas which are

1:14:45 not connected with what I would call mechanically.

1:14:50 Where where where physical laws are not everything.

1:14:54 Mhm.

1:14:56 That means that human psychology plays a role in developments.

1:15:02 And that tells me that people who are superior

1:15:06 at dealing with human psychology can get an advantage.

1:15:13 And I think that includes investing.

1:15:16 Exactly.

1:15:16 But not everybody.

1:15:17 It always comes back to not everybody.

1:15:19 And you know, there's a there's a phrase in in our world.

1:15:23 A friend of mine in England used it as the title for a book,

1:15:26 simple but not easy.

1:15:28 Mhm.

1:15:28 Our job is simple.

1:15:30 We got to find the best managers,

1:15:32 the best companies, the best ideas, the best products.

1:15:34 My son is a venture capitalist and does a great job.

1:15:37 He finds the best founders.

1:15:39 The task is easy.

1:15:40 I just said it to you in 10 seconds.

1:15:42 Mhm.

1:15:43 It's just not easy.

1:15:44 Because what makes you superior at finding founders?

1:15:48 What makes the better founders available to you rather than somebody else?

1:15:54 Uh and Cha- Charlie Munger once said to me,

1:15:57 putting together simple but not easy.

1:16:02 Charlie, when I finished my first book, The Most Important Thing,

1:16:05 I had lunch with Charlie and as I got up to leave,

1:16:08 he said, "Just remember, none of this is easy.

1:16:11 Anybody who thinks it's easy is stupid." That was one of the great things

1:16:15 anybody ever said to me cuz Charlie said it in his typically brusque way.

1:16:19 But it it can't be easy to be smarter and more

1:16:27 disciplined than all the other smart people who are trying.

1:16:31 Mhm.

1:16:32 That's what the efficient market hypothesis says.

1:16:35 They I've never seen it written down that way, but all these smart,

1:16:39 highly motivated, educated, numerate, computer literate,

1:16:44 interwired people are trying to get rich.

1:16:50 So, where is the $10 bill nobody has picked up right now?

1:16:54 Well, I think it's in it's it's around AI.

1:17:00 It but but everybody's excited about AI.

1:17:03 So, if if your excitement level, and by that I mean your insight level,

1:17:11 is average, you don't have a an edge.

1:17:15 Your perform and you get involved in AI, your performance will be average.

1:17:20 You will go along with the tide if it works,

1:17:25 you'll be schmeissed if it doesn't work.

1:17:29 Superior It all comes down You you boil down our conversation to this point.

1:17:36 It all and the things Charlie said and and and so forth.

1:17:39 It all comes down to superior insight.

1:17:42 And not You know, we have an author in America,

1:17:47 a guy named Garrison Keillor, and he wrote a book called Lake Wobegon.

1:17:51 And Lake Wobegon was a fictional community in uh I think uh Wisconsin,

1:17:58 if I'm not mistaken.

1:17:59 And he said in Lake in Lake Wobegon, all the children are above average.

1:18:06 Well, we know that there is no place where

1:18:09 all the children or all the investors are above average.

1:18:13 So, I think my my own vision of the world, which is not a scientific vision,

1:18:22 is that in fields where human nature is involved and the future

1:18:29 is unpredictable and things don't operate according to mechanical rules,

1:18:34 there is still a place for superior insight,

1:18:40 but you will not have success without superior insight.

1:18:47 I would most of my investing is in India.

1:18:51 I'm 13 39 years old now.

1:18:54 I know you've deployed a certain amount of capital,

1:18:57 I think 4 billion to India recently, but you haven't written a memo about it.

1:19:02 My assumption is India is growing at say 7% or 6%.

1:19:09 It will continue to do so for a period of time.

1:19:12 GDP per capita will go up, so consumer will do well, energy will do well.

1:19:19 Energy consumption goes up as GDP per capita goes up, maybe above $5,000.

1:19:26 Would I be okay in just staying allocated

1:19:29 to equity say 80% for the next 20-30 years?

1:19:34 And if so, is there a sector that you like?

1:19:38 Well, I I I've been cautioning you about things I don't know much about.

1:19:44 Here I can be more uh more uh emphatic.

1:19:48 I don't have any idea what the right sec what the best sector in India is.

1:19:54 Right.

1:19:54 Uh I will not uh hold myself out

1:19:56 as as knowing anything about the Indian stock market.

1:20:00 Okay.

1:20:01 I read that during COVID you lived with your son Andrew in a house.

1:20:09 Yes.

1:20:08 I'm sure Andrew has learned so much from you.

1:20:12 Is there one thing that you learned from Andrew?

1:20:14 Oh, I've learned so much because uh and this is how we started the conversation.

1:20:18 You said to me, "How do you stay sharp?" Yeah.

1:20:20 And and uh you know, uh speaking with young people.

1:20:25 If you stay If you speak If I speak to my contemporaries,

1:20:29 how am I I'm going to learn anything?

1:20:31 Mhm.

1:20:31 Speaking with young people is how you learn.

1:20:35 And the They they know stuff you don't know because

1:20:39 they are still learning and they learn more recently and hopefully

1:20:43 you have something you can give them in exchange which is

1:20:45 experience that they don't have cuz they haven't lived 80 years.

1:20:49 Uh but Andrew was essentially your age.

1:20:52 Mhm.

1:20:52 Uh and I wrote a memo after that experience

1:20:56 uh three generations living under one roof Mhm.

1:21:00 was of great value and I wrote a memo called something of value.

1:21:05 And the other reason I chose that title is

1:21:06 cuz we mostly talked about something called value investing.

1:21:10 Uh [snorts] but I get so much from him and he pushes

1:21:15 me to see things that I don't wouldn't otherwise see.

1:21:20 And he's also intolerant of of my not uh staying sharp and moving ahead.

1:21:29 You know, how how do you How do you keep moving ahead at 80?

1:21:31 That's really the question.

1:21:33 But I I don't think it's impossible.

1:21:36 But a great example,

1:21:39 I mean the the example that immediately comes to mind uh and I think it's

1:21:43 a it's a great one is that he observed and I wrote in the memo,

1:21:47 the memo was something of value January of '21 as I recall.

1:21:55 He pointed out it was almost

1:21:57 revelatory readily available quantitative information about

1:22:03 the present cannot hold the key to success because everybody has it.

1:22:11 Success in investing is doing better than others.

1:22:14 So in investing is a is a funny field because it's really

1:22:18 easy to be average and it's really hard to be above average.

1:22:22 But readily available quantitative information about the present is not going

1:22:26 to make you above average for the simple reason that everybody has it.

1:22:30 And and I talk in the memo about that one

1:22:32 of the reasons Buffett was able to steal a march on everybody

1:22:36 else and become Buffett is because nobody he he he

1:22:41 sorted it out and he worked it when nobody else did.

1:22:46 And you know, when I was starting off in this business in the research world,

1:22:51 think about your process.

1:22:53 Let's say I said you know, I went into a store today.

1:22:56 I bought a product.

1:22:57 I like the product.

1:22:58 I think maybe that company has a future.

1:23:00 I'd like to learn about it.

1:23:01 How would you get information?

1:23:04 Think about what you would do if you had

1:23:06 that experience this morning here in New York City.

1:23:11 What did we do then?

1:23:14 You know we did then?

1:23:17 We wrote a letter to the company and asked it for a copy of the annual report.

1:23:24 It took a week for them to get that letter.

1:23:28 They put it at the bottom of the pile and they took the letter

1:23:31 off the top of the pile and they sent that person an annual report.

1:23:35 It took a week or two to get down to my letter.

1:23:41 And then they took an annual report, put it in an envelope, addressed it to me,

1:23:44 put a stamp on, put it in the mailbox and it took a week for it to get to me.

1:23:49 Now, I exaggerate.

1:23:50 But the point is it took a month to get

1:23:54 an annual report so that I could start studying the company.

1:23:57 There was no online.

1:23:59 There was no Wiki or whatever source you might use.

1:24:04 Uh the only alternative was there were there were books

1:24:07 called Moody's manuals and they were each book was this thick.

1:24:12 No, this thick.

1:24:14 Take it off the shelf.

1:24:15 It had a paper called onion skin,

1:24:17 the thinnest of paper and it had tiny print tiny print.

1:24:21 you needed glasses, and it it they had the financials,

1:24:26 the current financials on every company.

1:24:29 Not much narrative, nothing no discussion of the future,

1:24:33 but just the financials of every company.

1:24:36 That's all you could get until the year annual report came in the mail.

1:24:40 Then you maybe you could start figuring out the business and its potential.

1:24:44 So, uh you could if you were Buffett and if you sat in your office

1:24:50 in Omaha and read the Moody's manual when

1:24:53 nobody else was willing cuz it was stultifying, you could get an advantage.

1:24:58 Is that what he did?

1:25:00 I think well, that's an that's my that's my illustration of what he did.

1:25:04 Maybe he did more.

1:25:05 I don't know.

1:25:07 But I'm no one to pay you a compliment, Howard, but if I could Yes.

1:25:12 I think Compliments are always good.

1:25:15 I think the nimbleness and the willingness you have to change

1:25:20 at 80 is by far the most impressive thing about you.

1:25:27 And when I speak to really successful people,

1:25:30 I think this trait over all others kind of makes them who they are.

1:25:36 Well, I I appreciate that comment.

1:25:38 I hope it's true.

1:25:40 Uh but it makes sense, doesn't it?

1:25:42 Because the ability to change your mind and change your thinking and learn

1:25:48 new things is an is is an example or a component of superior insight,

1:25:56 which is what you have to be.

1:25:57 This is a competitive game.

1:25:59 Uh it's like golf.

1:26:01 You say, "Today I shot 74." Mhm.

1:26:05 I tell you I shot 74.

1:26:06 Mhm.

1:26:07 You have no idea if I won or lost.

1:26:09 Mhm.

1:26:10 The only thing that matters is what did everybody else shoot?

1:26:13 Right?

1:26:13 If I tell you, "Last year I made 13% in my stock portfolio.

1:26:18 Is that good or bad?

1:26:19 Well, it's pretty good.

1:26:20 The average return on the S&P is 10.

1:26:22 But, of course, the S&P was up 18 last year.

1:26:25 So, it's 13 stank.

1:26:27 So, this is a competitive game.

1:26:31 You don't have to It's not a matter of being right or wrong.

1:26:34 It's a matter of being more right than the other person or less wrong.

1:26:38 Are you able to change because you've been able to consciously remove ego?

1:26:44 Uh Well, I think that helps because ego, if you have too much and the wrong ego,

1:26:54 would probably, I would imagine, tend to make somebody say,

1:27:00 "I've always done it this way.

1:27:01 It's worked in the past.

1:27:03 I'm an enormous success.

1:27:04 You know, I'm worth this much money.

1:27:06 So, why should I change my approach?" But, you have to keep changing.

1:27:11 Uh innovate or die.

1:27:14 What could What could trigger it?

1:27:16 Like, if we were to advise people watching this, if you were

1:27:19 to How can they trigger the realization that they need to constantly change?

1:27:25 Well, you know, it's a funny thing.

1:27:26 This has been a theme for me for the last 9 months.

1:27:30 I say this every time I get a question like yours, Nikhil.

1:27:34 The The really hard questions are the ones that start with the word how.

1:27:40 How can I learn the need to evolve and grow?

1:27:47 How can I learn to see things better, more clearly than other people?

1:27:54 How can I learn to be a credit analyst

1:27:57 who better understands the default probability than anybody else?

1:28:04 How can I become a what I call a second-level thinker?

1:28:10 Understanding things at a higher level and better than other people.

1:28:15 And all the hows, I can't tell you.

1:28:19 How How can I remain sharp at 80?

1:28:21 I can't tell you.

1:28:23 I can tell you what you have to do.

1:28:28 You have to do all the things that I

1:28:29 mentioned in order to be a superior investor.

1:28:33 I just can't tell you how to do it.

1:28:36 And in my first book,

1:28:37 uh it's it's funny when when when I said when I had the idea for the first book,

1:28:42 which is called The Most Important Thing.

1:28:43 It has 21 chapters.

1:28:44 Each chapter says, "The most important thing is" and then it's

1:28:47 a different thing cuz there are so many things that are important.

1:28:50 And I told Columbia about the book and they wanted to publish the book,

1:28:53 Columbia University.

1:28:54 And so they said, "Give us a sample chapter." And I

1:28:58 wrote out a chapter called said it's a Each chapter says,

1:29:01 "The most important thing is" and this one says,

1:29:03 "Second-level thinking." And I wrote the chapter about second-level.

1:29:06 I had never really thought about it before.

1:29:09 It just kind of struck me and I wrote it down.

1:29:13 Um uh and and what it says is it it's pretty simple.

1:29:19 If you think the same as everybody else, you'll act the same as everybody else.

1:29:22 If If you act the same as everybody else,

1:29:24 your investments will perform the same as everybody else.

1:29:27 So, to perform better, you have to deviate from the herd.

1:29:31 Seems clear.

1:29:33 Do you think How do you do it?

1:29:35 How do you do it?

1:29:36 And uh I said in the book, asking how to how to become I I

1:29:44 can tell you the importance of second-level thinking,

1:29:47 but asking me how to become a second-level thinker is like in basketball we say,

1:29:53 "You can't coach height." All the coaching

1:29:56 in the world will not make your team taller.

1:29:59 So, can you I can tell you that you must

1:30:03 become a second-level thinker to be successful as an investor.

1:30:06 I just can't tell you how.

1:30:10 If I were to draw a extrapolation,

1:30:13 that second level thinking is also contrarian thinking in a way.

1:30:19 Mhm.

1:30:18 Do you think AIs which are predictive

1:30:21 in nature can be modeled to be contradictory tomorrow?

1:30:27 I But that's the challenge, you see.

1:30:30 Because second level thinking or contrarian thinking

1:30:33 is not just different from the herd.

1:30:37 Mhm.

1:30:37 That's not enough.

1:30:38 Mhm.

1:30:39 It has to be different from the herd and better.

1:30:42 So, you can say you could I I I don't know how how to program AI,

1:30:48 but I assume you can say to Claude, Mhm.

1:30:52 every answer you give me on every

1:30:54 company has to be different from the consensus.

1:30:57 Or the opposite of consensus?

1:30:59 Or well, the opposite is is pretty categorical.

1:31:02 But let's say has to deviate from the consensus.

1:31:05 Mhm.

1:31:05 I don't want to and no consensus thinking is welcome here.

1:31:08 Mhm.

1:31:09 You can say that.

1:31:10 You can you can make it be different.

1:31:13 Can you make it be better?

1:31:15 Mhm.

1:31:16 If if it cuz you see, this is the catch.

1:31:21 Because the people you compete against

1:31:24 in the investment arena are also intelligent,

1:31:30 educated, literate, computer able, highly motivated.

1:31:39 They're pretty good.

1:31:41 Mhm.

1:31:43 Much of the time, they're as close to right as you can get.

1:31:50 So, if you believe the consensus is as close to right as most people can get,

1:31:55 then if you tell Claude, I only want non-consensus thinking,

1:32:01 then it has a high probability of being wrong.

1:32:05 That's not a good thing.

1:32:07 In a way, AI in investing could work if everyone in investing uses AI.

1:32:16 No, I don't think so.

1:32:18 Because if if if everybody uses AI, and let's assume everybody's AI is the same.

1:32:26 Mhm.

1:32:26 Let's assume different.

1:32:27 Well, are they?

1:32:28 That's the question.

1:32:30 Mhm.

1:32:30 If if if, you know, if That So,

1:32:35 that's that maybe that's what my partner Bruce Karsh,

1:32:38 the the recovered lawyer, would call a gating question.

1:32:42 Mhm.

1:32:43 Are some AI models smarter than others?

1:32:47 Since they all have super IQs, Mhm.

1:32:50 computing power, Mhm.

1:32:51 and they all are trained on the same history, Mhm.

1:32:55 are some smarter than others?

1:32:57 I don't know.

1:32:59 I need somebody to tell me.

1:33:02 [snorts] But if if they're all the if they're all equally smart,

1:33:06 and you say to that This is an interesting thing.

1:33:13 So, they're all equally smart.

1:33:15 You say everyone says to all of them, write out a process Mhm.

1:33:22 that will produce investment success.

1:33:24 Mhm.

1:33:26 Theoretically, they all write the same one Mhm.

1:33:28 because they are all equally smart and have the same training.

1:33:31 Mhm.

1:33:33 And if they all follow it perfectly, they all produce the same result.

1:33:38 So, nobody there's So, there's no superiority.

1:33:42 But then everybody makes 10%.

1:33:44 Nobody makes 8 or 12.

1:33:45 Right.

1:33:46 But then but then what what do you get paid for making a 10%?

1:33:51 But AI doesn't need to be paid.

1:33:53 Yeah, but who employs AI?

1:33:56 Mhm.

1:33:57 That person wants to get paid.

1:33:59 Nobody's doing Nobody's employing AI for fun.

1:34:02 Right?

1:34:03 They're employing AI cuz they want to get rich.

1:34:06 And getting rich in investing comes from superiority, not from average ness.

1:34:14 How do you get superiority?

1:34:16 I don't want to ask you this question, but But you will.

1:34:20 You can choose not to answer it.

1:34:21 Yes.

1:34:22 Do you think the world is going to socialism and AI is triggering that?

1:34:28 I don't I don't consider myself a futurist.

1:34:32 I don't engage in that kind of That's

1:34:35 That kind of thinking is what we call blue sky.

1:34:38 And I am partial to what Albert Einstein said on the subject.

1:34:44 He said something like, "I don't think about the future.

1:34:46 It'll come soon enough." But do I think about the past?

1:34:52 I think about the past to learn from it.

1:34:54 And I I try to I try to I'm I'm great on these quotes

1:35:00 and my favorite on this subject is from Mark Twain, who supposedly,

1:35:04 but I think didn't really say it, supposedly said, "History does not repeat,

1:35:09 but it does rhyme." There are certain themes

1:35:12 that that rhyme from instance to instance in history.

1:35:17 And um they mostly have to do with human nature.

1:35:28 And I think human nature doesn't change.

1:35:32 Incredibly slowly.

1:35:33 I mean, when we talk about fight or flight,

1:35:36 people are still talking about the the the the the Stone

1:35:41 Age man and the and the watering hole, right?

1:35:44 Well, that was millions of years ago.

1:35:47 These things are still relevant.

1:35:48 So So, the point is that that uh uh I think I think you can learn from history.

1:35:55 Mhm.

1:35:56 And what you what you mostly learn are the lessons of human nature.

1:36:01 Mark Twain said that.

1:36:03 And Napoleon said history is written by the winners of tomorrow.

1:36:07 So, we don't even know how accurate the history we have access to really is.

1:36:11 Well, except except for we have the numbers.

1:36:15 Financially.

1:36:15 Yes, financially.

1:36:16 When you have numerical history, it's probably not that subjective.

1:36:22 But maybe not the psychology that led to the numbers.

1:36:24 Right.

1:36:25 Right.

1:36:26 Well, I mean, I just read Andrew Ross Sorkin's new book 1929.

1:36:31 It's a great book.

1:36:31 Yeah, I liked it.

1:36:32 I have a memo coming out this week talking about private credit.

1:36:35 Mhm.

1:36:35 Uh and I refer to it in that in the What's happening with private credit?

1:36:40 Let me just finish this thought, okay?

1:36:42 Uh so, you know, he explains the events that wrote that led

1:36:47 up to the Great Crash rather vividly and gives you a picture.

1:36:52 Uh And and I think there's a lot to be learned from that and I

1:36:55 tried to convey some of the lessons of 1929 in this new memo,

1:37:02 which is coming out in 2026.

1:37:05 Um I hope that the history that Andrew

1:37:09 describes is the real history because if not,

1:37:13 the lessons on will not be that valid.

1:37:16 That's all I can say.

1:37:18 Any last last words, Howard, to our audience?

1:37:21 Any piece of advice?

1:37:24 Well, I I what I what I always say to people about investing,

1:37:27 Nikhil, is that investing is a puzzle.

1:37:35 Challenging puzzle.

1:37:36 Investing I define as positioning your capital

1:37:40 to take advantage from of future developments.

1:37:44 But I also say that future developments can't be predicted Mhm.

1:37:48 accurately.

1:37:49 So, it you need superior insight to get it more right than most people.

1:37:59 But you're not going to get it right all the time.

1:38:02 If you have to be right all the time,

1:38:03 if there's something in your makeup that that says you're

1:38:07 going to be unhappy if you're not right all the time, don't become an investor.

1:38:11 Uh Taleb in his book Fooled by Randomness

1:38:15 uh talks about the difference between investing and dentistry.

1:38:18 He says if you go to dental school and you learn how

1:38:20 to fill a cavity and you fill the cavity that way every time,

1:38:23 you'll be successful every time.

1:38:25 So, if you have to be successful every time, become a dentist.

1:38:29 Or or an engineer.

1:38:31 Uh civil engineer, you say I want to build a bridge from here to there,

1:38:35 he does his calculations, how much steel, how much concrete.

1:38:38 Every time the bridge stands.

1:38:42 But but but it's not that interesting in my opinion.

1:38:47 And so, investing deals with this fascinating puzzle that you're trying to solve

1:38:55 to a better degree than others even

1:38:58 though there are no laws that work absolutely.

1:39:02 Fascinating.

1:39:04 And I love it.

1:39:05 Um it's still a puzzle.

1:39:06 It's still a puzzle I'm trying to uh peel like the onion.

1:39:11 Um but you're never done.

1:39:13 And that makes it interesting.

1:39:15 Uh and and and and so, that's the kind of person who should be engaged in it.

1:39:23 It's interesting that you resonate with Taleb because I

1:39:27 somehow when I read your stuff and his stuff,

1:39:31 I find you guys on the opposite ends of the spectrum.

1:39:34 I think Taleb when he he ran his fund he was

1:39:39 buying way out of the money call options and put options,

1:39:42 hoping for black swan events.

1:39:46 Mhm.

1:39:45 And you in a way are doing the opposite

1:39:49 of that, wherein you're buying debt in distress,

1:39:53 hoping that the percentage of things being black

1:39:56 swans are lower than what the market perceives.

1:39:59 Right.

1:39:59 I I I In that sense, I think we are different.

1:40:03 Uh I mean, I said earlier, I believe in putting together a portfolio that would

1:40:08 do well in the main portion of the probability distribution.

1:40:14 Mhm.

1:40:15 He's advocating protection that can be bought cheaply

1:40:20 because it only deals with the tail event, which rarely happens,

1:40:25 so people underestimate the value

1:40:27 of the of the of the uh of the uh tail protection.

1:40:32 Uh but [snorts] uh so, you can buy you can cheaply buy

1:40:40 protection against something that's unlikely to happen,

1:40:42 which in theory is a good thing, but since it happens so rarely,

1:40:47 uh that the value of that uh

1:40:51 underpriced tail protection doesn't become apparent very often.

1:40:55 Even he uh compares in the book, as I recall,

1:41:00 I only read it 20 2 years ago or something like that.

1:41:03 Mhm.

1:41:03 Uh I've read all his books.

1:41:05 I love him.

1:41:05 Yeah.

1:41:06 But he even he says that investing is like Russian roulette.

1:41:14 But rather than having a bullet in the six chambers,

1:41:19 there are 100 chambers in the gun.

1:41:21 So, the bullet rarely goes off.

1:41:23 Mhm.

1:41:24 And I I I don't think you can I mean, so,

1:41:28 you could spend 1% of your money to buy tail protection every year,

1:41:33 uh but I think it's I think if it's that's going to be your whole existence,

1:41:38 it's going to be a dull existence because

1:41:40 the because the the explosion will happen so infrequently.

1:41:45 And he also said that even COVID was not an explosion.

1:41:49 He said it's not a black swan event.

1:41:51 So if COVID wasn't, the question is what is?

1:41:55 Well, it's Yes, I mean um you know, obviously COVID was not the first pandemic,

1:42:04 but it it was I I would say it was

1:42:06 the first pandemic of the modern era and it was

1:42:09 the first pandemic that that was that encountered the digital

1:42:13 economy and many many and globalization many many other things.

1:42:19 So it it was kind of unique or certainly

1:42:23 innovative in a lot of ways that and and um I I I would guess we could find we

1:42:30 could say some people dealt with it better and worse,

1:42:33 which is to me the definition of what makes something interesting,

1:42:37 the ability to deal with it better or worse.

1:42:41 Thank you, Howard, for taking the time today.

1:42:43 This was incredibly [music] interesting and I

1:42:47 feel like I'm learning so much from you.

1:42:48 Well, and I I have learned from speaking with you and I've enjoyed

1:42:52 it and your your your questions were in many cases novel and provocative.

1:42:59 Thank you.

1:43:00 Thank you for doing this.

1:43:01 Cheers.

1:43:14 Mhm.