Chapter 1: What is the significance of the DMS dataset in financial history?
This is the Rational Reminder Podcast, a weekly reality check on sensible investing and financial decision-making from two Canadians. We're hosted by me, Benjamin Felix, Chief Investment Officer, and Brayden Warwick, Financial Planning Product Architect at PWL Capital. Welcome to episode 408.
I love the conversation that we just had, Brayden, and it's an episode that I have wanted to do for a long time. Professor Elroy Dimpson is a busy man.
Chapter 2: Why is it essential to understand financial history for future investing?
I was on another podcast in the UK and that person, Damien, is the Damien Talks Money podcast, has a relationship with Elroy. And so he made an introduction, which finally got the connection made. We would have done this one sooner if we could have. I guess is the point of my long preamble, but I'm super excited that we got to talk to Elroy Dimpson.
He is a professor of finance and research director at Cambridge Judge Business School and bi-fellow of Gonville and Caius College, Cambridge. He is also emeritus professor of finance at London Business School.
Chapter 3: What biases affect historical stock market data and returns?
Listeners will likely know his name, Elroy Dimson, which is the D in the DMS data, which we've talked about many times because we use it a lot in our own research at PWL. We also did an episode, I can't remember the episode number, but we did an episode a while ago, something like lessons from a hundred years of stock returns or something, where we went through a bunch of their past reports.
They do something called the Global Investment Returns Yearbook, that they've been publishing for many, many years now. Right now, it's sponsored by UBS. Formerly, it was sponsored by Credit Suisse, but it's this just incredible book that they publish annually that details stock bond and bill returns for a whole bunch of countries all around the world.
They also publish indices, which we, PWL, subscribe to. We purchase them every year, purchase a license to use them. In their yearbooks, in the Global Investment Return yearbooks, they Also, and he mentioned this during the conversation, they also do a couple of essays where they take a topic and they use their historical data to analyze it.
So an example would be, what is the historical relationship between economic growth in a country and its stock returns or industry growth and stock returns? But they've got tons of these different essays over the many, many years that they've been doing this. And it's a wealth of incredible analysis and information.
Chapter 4: How did the Triumph of the Optimists change our understanding of equity risk premium?
They've also got a very famous book called Triumph of the Optimists, which we also discussed. That book was the culmination of their work using historical data to reconstruct indexes for a whole bunch of different countries. And we talked about this during the conversation too. It really changed our knowledge of what is the equity risk premium?
How much should you expect in stock returns relative to bond returns, which prior to their work had been heavily influenced by the US historical record, which we all know has been
Chapter 5: Why might economic growth not lead to higher stock returns?
incredible, exceptional. And so their expansion to international markets really gave us more knowledge about what it might be reasonable to expect as an equity risk premium going forward, which was great. We're super fortunate and grateful to be able to talk to Elroy. We talked for about 90 minutes. Braden, any comments? What'd you think of the conversation?
Chapter 6: How does global diversification impact risk and returns?
Well, I think he was just so cool from my perspective as someone who's used the DMS data for years now. I use it all the time to just hear the origin story about why he decided to collect the data and all that went into it over the course of time. And then it just really brought the data to life to me to hear his perspective on it. Yeah, it was just such a cool conversation.
Really a pleasure to talk to Elroy.
He's got his academic experience, but he's also done lots of interesting investment committee work, including with Norway's Sovereign Wealth Fund. It's the biggest single investor in the world. And he helps to form their whole setup and investment policies and all that kind of stuff. He's not just an academic, he's got real world experience dealing with people.
And he talks about some of those types of issues during our conversation, people in committees and just making like real investment decisions. An incredible wealth of wisdom that comes from both tons of time with the data and doing analysis, but also tons of time working with real humans, trying to make investment decisions based on the data and other inputs.
That's a good introduction for Professor Elroy Dimson. Let's go ahead to our conversation. Elroy Dempson, welcome to the Rational Reminder Podcast.
Thank you for having me. It's a very pleasant afternoon here, but other people who are tuning in will be all over the world. Weather may be different where you are.
It's actually a very nice day where I am as well, so that's good. Real quick, Elroy, super excited to be talking to you on the podcast. This is something that I've wanted to do for, we've been running the podcast for eight years now. You're someone that I've always wanted to have on. Super excited that we're talking to you.
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Chapter 7: What is the expected equity risk premium moving forward?
Well, I hope it's exciting for everyone.
That's good. To start with the first question here, can you talk to us about why it's important to study financial market history when thinking about the future?
It's extremely difficult to think about the future without knowing where you've come from. It's an integral part of a journey. If you don't know where the journey started, you can't start thinking about where you're going to end up.
So what was the process like to assemble the data for your 2002 book, Triumph of the Optimists?
That's an interesting story because when Paul Marshall, Mike Staunton and I, we all did our PhDs at London Business School. Early on in our academic lives, textbooks all made very heavy use of American data and a little bit of British and a tiny bit of Canadian data. But basically, if you had what then was a standard textbook of Bailey and Myers, which now has another couple of co-authors,
you would see some indications to what returns you might expect, but there was very little choice other than to recite what had happened in the United States. And so there was heavy reliance on the long-term data which had come out of the University of Chicago.
Paul Marsh and I had done a bit on looking at the long-term for the UK, and there'd been one or two snippets of not very satisfactory research on the UK. But that was about it, and even Canada didn't really play a part. We, at that time, distributed our research. We began at the very end of 1999. We distributed it through a firm which sort of changed hands a bit.
We have not changed sponsors much, except when there's been a corporate event amongst the sponsors. It became clear there was a demand to go beyond the American and British data that we had. And we were moving into a period of internationalization. Money was kind of free at the end of 1999, expecting 2000 to come along.
And the global head was our own knowledge of the research that others were doing and a practitioner who was thinking globally. And we liked that idea. We worked through the run-up to New Year 2000 on producing a book which was privately published. First, we had a number of countries. But as we reached the end of 1999, we found that it was creeping up towards 10.
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Chapter 8: How should investors remain optimistic in uncertain markets?
Actually, you have a birthday. You are one year old when you're into your next year birthday. So birthdays actually are calculated differently. And so people pointed this out. And by that time, we discovered data for lots of other countries. And the suggestion was, well, we should have Millennium Book 2 for the real millennium. And the real millennium was once there were 1,000 years behind us.
And we were in the 1,001th or 2,001th year. So the story was one of evolution. And that was a big success. Millennium Book 2 then was an idea that Princeton University Press thought would be something worth bringing to people.
And the book that you know, Triumph of the Optimists, a fiercely expensive book, which was produced by us, building on something which we had already done in a private publication. And so a few people around have got the original Millennium Book and Millennium Book 2. It pops up on eBay from time to time. The little beginning was once we were into the current century,
And we've had 25 years of running with it. It's been an amazing journey.
When you're assembling the data, like when you say you got to 10 countries and you keep adding countries, what are you actually doing? Where is the data coming from?
Our data set is primarily a compilation of data. So let me go backwards in time. What would we like now? Nowadays, we have high quality indices. And so if you start a particular period, we'll go back where there's a good quality capital gains index with an income series. Nobody would dream of telling you what the return is on treasury bills excluding income because it's a dollar.
The value every year is dollar, dollar, dollar, dollar, dollar. For equities, people would manage without income, and that's really strange. So we wanted data which cut us a longer period. We presented our data. I can tell you a bit about our very detailed data in a moment. Once we'd got that first book done, there was so much interest in it.
We were presenting it all over the place to academics and practitioners. And every so often, we'd be in a large room. Question time comes along and somebody would say, you know, I've been collecting data like this for my country. It never occurred to me that anybody would be interested. And so we grabbed.
By the time we had our first 10 countries, we had accumulated some long-term return series, but that rapidly went up after that. We used data which has often been assembled by other people in more recent decades commercially before that academics who are doing this job. They've been kind to us and we've been kind to them. We credit their work in great detail.
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