For the first part of today’s discussion, we are joined by Don Coletti from The Central Bank of Canada. He is here to talk about their upcoming recommendation for a monetary policy framework for the next five years which is incorporating public feedback into its development through the survey, Lets Talk Inflation. From there, we touch on some favorite books, Starbucks’s stored value card liabilities, the benefits of keeping inheritance in a separate account, new standards for financial planners and advisors proposed by the FSRA, and why SoftBank did not pile into call options and cause the rally in tech as the previous headlines suggested. Heading into the meat of the episode next, Ben shares some findings from a model he built inspired by a program written by one of this show’s listeners that tests historical safe withdrawal rates for factor loaded portfolios. Ben gets into a series of papers that speak to the diversification benefit of adding factors in this section too. He wraps up the discussion with a spanner in the works though, which looks at this question through the lens of time-series momentum rather than cross-sectional momentum. Here, he considers trend following as another type of diversification that has shown favorable impacts on portfolio returns in the data that exists. As usual, we wrap up with our bad advice of the week, hearing Cameron relate the bizarre ‘findings’ of a Forbes article claiming that active management beats passive investing in the face of piles of data to the contrary!

Key Points From This Episode:

• Updates: An upcoming guest, great reviews of this show, and the brilliant discussions thread. [0:00:23.0]

• Introducing Don Coletti to talk about The Bank of Canada’s outreach programme. [0:04:52.0]

• Alternative approaches to monetary policy the Bank of Canada is considering. [0:07:19.0]

• Thoughts on the US Federal Reserve’s change to average inflation targeting. [0:11:43.0]

• How open the Bank of Canada is to making a change. [0:13:14.0]

• Why the Bank of Canada is placing more emphasis on engaging with the public as part of their renewal. [0:14:35.0]

• Why questions about large scale asset purchases and forward guidance were included in the survey. [0:17:00.0]

• The response rate so far to the Bank of Canada’s Let’s Talk Inflation survey. [0:18:59.0]

• Favourite books and series, and Starbucks’s stored value card liabilities. [0:21:50.0]

• The benefits of keeping inheritance in a separate account. [0:26:24.0]

• Standards for financial planners and advisors the FSRA is proposing. [0:28:20.0]

• Why SoftBank was not piling into call options and responsible for the rally in tech. [0:31:43.0]

• Ben’s remodelling of a listener’s code that tests historical safe withdrawal rates for factor loaded portfolios. [0:34:40.0]

• Safe withdrawal rates for different stock indexes according to Ben’s model. [0:37:15.0]

• A paper looking at the interaction between factors historically and the results this produced. [0:47:52.0]

• Findings of a paper looking at the five factors through business cycles. [0:56:57.0]

• Papers exploring whether a factor can be cheap and therefore have a higher extended premium. [1:00:41.0]

• The shadow time-series momentum casts on this; the impact of trend following on safe withdrawal rates. [1:02:46.0]

• Bad advice of the week: Active management beats the stock market. [1:15:51.0]

Read the Transcript:

Ben Felix: This is the Rational Reminder Podcast or weekly reality check on sensible investing and financial decision making for Canadians. We're hosted by me, Benjamin Felix, and Cameron Passmore.

Cameron Passmore: Welcome to 117. I know we've had a few listeners ask about, or the ability to see your first 3D printed items. Where are you at with that?

Ben Felix: So I called them and it's shipping, I think they said, this week. The company that makes these things, they ship them in batches. So I guess my batch is slated to ship this week, but the kids and I've picked out the items that we're going to print. So hopefully we'll have something to show off by maybe next week.

Cameron Passmore: Or the next time it's us. Yeah. Awesome. Cool. Interesting. I'm doing this Peloton challenge every day this month of September, to do 30 minutes and burn up to 400 kilojoules, which for me is a pretty good clip. It's tough enough for me. So I just kind of threw it out on Twitter and have a few listeners actually going to join me for the rest of this month. And maybe we'll do a different challenge every month. Might be kind of fun to build up our community. Upcoming guests, we have Annie Duke joining us. She's the author of Thinking in Bets and also has a new book coming out called How to Decide. So I highly recommend to everyone to pick up a copy of her first book Thinking in Bets because our interview with her will come out just after her book, How to Decide, comes out. So take a look at that, download it.

Also, you might want to check out our friend Ted Seides interview on capital allocators with Annie. Fabulous interview. Also, I want to throw a greeting out to some of our YouTube commenters. So Ronaldo and Malta, Khalid, Windowpane 1000, Enrique, Spirit of the law, Peter [inaudible ], John Claude and a ton of others. It's been a lot of engagement on YouTube, which I get a kick out of and it was great.

Ben Felix: Oh, it is. It is great. It makes it doing a lot more fun than it would be if there was nobody engaging. And as you'll hear in this episode, it actually gives us some pretty cool ideas to talk about and investigate.

Cameron Passmore: It's really fun having Mark Hebner on last week. He had a blast engaging with people on YouTube as well. He had a real good time. So he's going to be having a bunch of your videos, I believe, on his website at indexfundifa.com.

Ben Felix: Yeah. I wanted to post links to some of the videos, which is cool.

Cameron Passmore: The other thing that acts of kindness that people do, I'm amazed at how kind the reviews are and thoughtful the people are putting on the podcast.

Ben Felix: Yeah, it's great.

Cameron Passmore: I want to give a sincere thank you to [inaudible ] mojo, Lee M_Sask, Zalupe228exe , Pauly , Birdieinthesky63, AnasticiaMD, Hammer6969420, and Zalupe228 again.

Ben Felix: I get a kick out of you reading the names of the people that review stuff.

Cameron Passmore: These people know who they are. I just think is worst sounding out because it's amazing. These aren't just great podcasts thanking you. They're putting down thoughtful as you know comments is awesome.

Ben Felix: Yeah, you're right. But hearing you say Hammer6969420's.

Cameron Passmore: Anyways, also worth mentioning too, we get a lot of comments now and I wish I had more time to invest in responding to everybody, so sometimes we just can't keep up.

Ben Felix: I think that's been the case for a while, but one of the awesome things about the discussion section on the rational reminder site, which as a side note, we will eventually improve with some sort of form or something. It's just investigating what to use is time consuming and we haven't had time to do that. But the discussion section, I feel like I keep repeating the same thing, but it's unbelievable the discussions that are going on in there, like highly informed, very friendly discussions on a pretty niche topic. Like how many people really want to go and get into a detailed discussion about the theoretical and empirical backed investing? But apparently there are a lot of people that want to talk about this and it's really cool to see. So even though we're not answering, there are some users in there that are answering people's questions, which is great.

Cameron Passmore: It's also really cool to hear from the many advisors that listen to this podcast.

Ben Felix: Yeah.

Cameron Passmore: There's a lot of people on LinkedIn that are pinging me quite often and I love to hear from people. I love talking shop with people in the business.

Ben Felix: All right, while we have a ... Oh shoot, I was going to mention the length. Oh, lights out. I said it. We have a bit of a long episode, so we're going to get to it.

Cameron Passmore: It doesn't matter. We kick it off with a interesting interview with someone from the bank of Canada, which we talk about once we get going. Is there anything else to add?

Ben Felix: No, let's go.

Cameron Passmore: All right, enjoy it.

Ben Felix: Welcome to episode 117 of the Rational Reminder Podcast. Today, we don't have a guest in the traditional sense, but we were joined by someone from the Bank of Canada for a segment of our episode. Now, they're doing some public outreach that they don't usually do or haven't done in the past at least. And they talk a little bit about that in our conversation with them. We thought it was pretty cool. We're actually the first podcast ever that the Bank of Canada has done outreach through. So it's pretty cool. They're trying to engage with the public. And again, in our conversation, they talked about why they think that's important. But yeah, so we thought it was pretty cool to be the first ever Bank of Canada official conversation through the podcast medium.

Cameron Passmore: You have to hand it to them for a very conservative organization, obviously, to do an outreach like that with us was a lot of fun and really interesting to coordinate.

Ben Felix: Yeah. It's part of a campaign that they're doing. They've got a survey called the Let's Talk Inflation survey. And as part of this public outreach, they're trying to do for their policy decisions, they want Canadians to take this survey. So we'll put a link in the show notes so that people can take it. I took the survey. It takes about 10 minutes. The questions are, I mean, pretty technical. I think that the average Canadian would have a pretty blank stare looking at the questions. Our listeners may be less so, but anyway, yeah, I think it's worth checking out the survey. So we were joined to talk about the survey, I guess, but also just a more general discussion about what the Bank of Canada is trying to accomplish with their public outreach.

Ben Felix: We are joined by Don Coletti. He was appointed advisor to the governor of the Bank of Canada in 2013. Don's responsible for financial system issues, including vulnerabilities, reforms, and market dynamics and their implications for financial stability and monetary policy, Clearly, well educated on the topics of central banks and how they interact with financial markets and with ultimately Canadians.

Cameron Passmore: I agree. Before that, he joined the bank in 2000 and he was at the Department of Finance for a couple of years before that. And a lot of economic pedigree that he has for sure.

Ben Felix: Yeah. So we'll jump into the conversation that we had with him. And then we'll continue on with our normal episode after that. Don Coletti welcome to the Rational Reminder Podcast.

Don Coletti: Thank you very much for having me today.

Ben Felix: So the Bank of Canada's current approach to monetary policy is to adjust interest rates to target a 2% inflation, but the bank's considering some alternatives. Can you talk a little bit about the alternative approaches to monetary policy that the Bank of Canada is considering?

Don Coletti: Sure. Well, let me start by saying that the approach that we ultimately take for monetary policy over the next five years will have real implications for people in their everyday lives. Our ability to stabilize the purchasing power of money makes it easier for Canadians to plan personal finances and business investments. Our ability to smooth swings and economic activity helps minimize job losses and financial stress for Canadians during economic downturns. Targeting 2% inflation has served Canadians very well for over 25 years. Nonetheless, every five years the bank and the federal government renew our agreement or the monetary policy framework and ahead of each renewal, the bank looks at how we might improve its approach. This time around there are some new challenges, probably the most important is the global low interest rate environment. Now, with that backdrop in mind, I would put the alternatives to the current framework into four main buckets.

The first option is to raise the inflation target. The idea is that raising the inflation target will increase the nominal interest rate, giving the bank, the room to lower rates again when needed. The bank researchers find that the cost of higher inflation would be significant and they would be felt by everyone, even more so by people living on fixed or lower incomes. Also, the bank's credibility could be undermined if people thought it was a slippery slope to an even higher inflation targets down the road. The second option would be to target the aggregate price level. Unlike inflation targeting, targeting the level of prices means that the central bank would promise to make up for all the inflation misses along the way. That means that if inflation wants to go below 2% for a period, the bank would allow inflation to run above 2% for a while to make up for it.

By moving around inflation and inflation expectations in this way, central banks could get more bang for their buck, spatially when faced by the lower bound on policy interest rates. But the benefits of this approach depend heavily on everybody believing that over time the central bank would be able to deliver on its promise of making up for all past misses. Now, our work studying how can you use respond to price level targeting in a laboratory suggests that this may be difficult to achieve. Now, this bucket also includes a mild or makeup strategy called average inflation targeting. You can think of average inflation targeting as lying somewhere in between inflation targeting and price level targeting. Now instead of promising to make up for all past misses of the inflation target, hours inflation targeting only makes up for some of the misses, say for example, the last two or three years.

So a third option that we are considering is to add full employment to the bank's current inflation objective. This is known in our business as having a dual mandate, the fed and the reserve bank in New Zealand have dual mandates. What the Bank of Canada already considers a range of labor market indicators when setting policy and when a trade off between stabilizing inflation unemployment does arise we consider both. Nonetheless, there might still be some benefits from incorporating an explicit full employment objective into the bank's mandate.

The fourth and final option would be to target the nominal gross domestic product. Now that's the economic output valued at market prices. Nominal GDP targeting has received renewed attention recently because it could help reduce the chances of running into the lower bound and interest rates. It may also help promote financial stability, but it too has its drawbacks. So the bank has been doing our comprehensive side-by-side assessment of these and other frameworks to see if any are better. We do this work using different economic models, including the terms of trade economic model or totem, which is the bank's main policy analysis model. So we call this work our horse race. We assess the different policy frameworks by their capacity to do three things, to meet their stated objectives, to support the wellbeing of Canadians, and to serve Canadians well in both good and bad times.

Ben Felix: Very interesting. You mentioned average inflation targeting, which the federal reserve in the US has changed too. They've made that change. What do you think about that move from them?

Don Coletti: Yeah, so we've looked carefully at the federal reserve strategy review with great interest. Similar reviews are going on in many countries around the world and researchers and central banks and academia from all around the world are in frequent contact, sharing their insights and the lessons learned. Governor Macklem said last week that the bank is hardened to see the fed and other jurisdictions adopt elements of our long standing framework review and renewal process. For example, the fed is now moved to a five year review of their framework, something that we've been doing for a long time. The fed also said that it would likely aim to achieve inflation marly above 2% for some time after periods of low inflation. So that is a very specific type of average inflation targeting. As I indicated earlier, we are looking at average inflation targeting and other options within the context of our own review for Canada. What I can tell you so far is that our worst suggests that average inflation targeting has some benefits over the alternatives, including inflation targeting in certain circumstances, but so far there's no regime that absolutely dominates in all circumstances.

Ben Felix: Wow. Now, the current approach, like we mentioned at the beginning is, has been around for 25 years. How open do you think the Bank of Canada is to actually making a change?

Don Coletti: Yeah, there's no question that our current monetary policy framework has proven thus far to be the best option for keeping low, stable, and predictable inflation. It's also done very well in terms of stabilizing output and employment in the face of large adverse shocks to the economy, but no system is perfect and that's why the bank is always looking at how it might improve its approach of these efforts crystallize every five years as part of the renewal of the agreement on Canada's monetary policy framework. Now it's important to keep in mind that frameworks don't get set in a vacuum. And this time around there are some new challenges. Probably the most important of these new challenges is the globally interest rate environment.

When global interest rates are low, there's less room for the bank to cut interest rates to support economic activity and inflation. Persistently low interest rates may also encourage households and investors to take on excessive risk. This can leave the economy exposed to boom bust financial cycles. The low interest rate environment is one of the reasons why we thought it would be a good time to do a comprehensive horse race amongst the contenders. We will want to make sure that we're always doing the best possible for Canadians

Ben Felix: Don, can you talk about why the bank is placing more emphasis now on engaging with the public as part of a renewal?

Don Coletti: Yeah, that's a great question. Traditionally, the bank has largely engaged with academic industry and government stakeholders while providing regular updates to the broader public via media and speeches. But in order to gather a wider diversity of views, enhance transparency, and encourage dialogue, we have expanded our consultations during this renewal cycle to include more direct engagement with the public. Now, this process has been going on for a couple of years now well ahead of our renewal in 2021. And this engagement is really important to us for three reasons. First, it improves our capacity to make better policy decisions. Second, it also enhances our illegitimacy as a public institution. Now, the bank's actions affect the lives of Canadians in an important way, and Canadians have the right to understand why we do the things we do. We also believe that the more Canadians are aware of and understand the work that we do at the Bank of Canada, the more effective our policies will be.

In fact, last month, Governor Macklem spoke about the imperative for central banks to engage the public directly when he addressed the world's central bankers at the annual symposium in Jackson Hole, Wyoming. Now, there are other elements to this broader initiative to engage the public than just the engagement we're doing around the inflation target renewal. Let me tell you about one of them that's near and dear to me personally, and it's called The Economy Plain and Simple. So it's a publication that we introduced in September of 2018. The idea behind it is right there and it's title. So we get our economists, and researchers, and communications professionals to write short, quick reads with engaging visuals about the economic subjects that matter to Canadians in the simplest way possible. The subjects that we used to write about are often subjects and topics that are submitted to us by our readers. They ask us to write topics in different areas and when possible, we're happy to oblige. Now, this document is proven to be very popular. I would encourage your listeners to give it a shot. You can find it very easily on the bank's website.

Ben Felix: Yeah. I've checked out that content than it is. It does a really good job taking what are pretty complex topics and presenting them in really easily digestible bites kind of like you're saying.

Don Coletti: Great. I appreciate that.

Ben Felix: Yeah, it is really great. This survey that you've released as part of this consultation with the public, I've taken the survey too. It was really interesting to go through and our listeners definitely should check it out. We'll put a link in the notes for the show. The survey is asking Canadians on their thoughts on some of the actions. One of the things that the survey is asking you about is your thoughts on some of the actions that the bank's taken in response to the COVID-19 pandemic, including large scale asset purchases, which we've talked about on this podcast, and forward guidance. Why were those questions important to include on this survey?

Don Coletti: Yeah, as I said earlier, the process for an enhanced public engagement started off long before 2020. It always included a review of our policy toolkit and interactions between monetary, fiscal, and macroprudential policies. Now, that extended policy toolkit includes large scale asset purchases and forward guidance amongst other tools. Of course, through the experience of COVID-19, we've implemented some of these policies in real time, making it easier for people to put them into context and to provide feedback. As you know, we've committed to hold interest rates that are effective and lower bound until economic slots is absorbed so that the 2% inflation target is sustainably achieved. And we've also engaged in QE or our large scale asset purchases for the first time. We are now pursuing at least $5 billion per week of government of Canada bonds to help keep interest rates low across the yield curve.

The monetary policy works better when people understand it. Without public understanding and support for independent central bank, we lose the public trust and that's core to our mission. Asking for people's inputs to our actions gives us that direct line of sight into their understanding. Moreover, our governor has said many times in recent months that central bank need to spend more efforts speaking to and listening to the citizens we served. The public has a right to understand what we're doing and we need to be held accountable for our actions.

Ben Felix: Don, can you talk about the response rate that you've had so far for the Let's Talk Inflation survey? And also, I'm sure you've got some anecdotes that you can probably share.

Don Coletti: Sure. I'd love to. So we're very pleased the response of our rates so far. So thousands of people across Canada are completing the survey and we see particularly high interest from Quebec. We've had a pretty good mix of responses from all demographic groups, but we really love to see more women, more young people, and more low income Canadians participate. One thing that we've learned so far is that perceives inflation in Canada is generally above the actual CPI inflation rate, although it's still pretty close to 2% target. The other thing I'd like to share with you is that when we asked respondents if higher more volatile prices were acceptable in exchange for a stronger economy or higher wages, most were not in favor. In fact, most respondents feel that the bank's current inflation targeting framework or a dual mandate, which includes targeting employment as well, would best serve Canadians.

So to all Canadians out there, I really hope you'll take 10 minutes to go on the Bank of Canada website, click on Let's Talk Inflation, and fill out the survey. It will be available until October 1st. We want to hear from you. We want to know more about how price changes and the ups and downs of the economy affect you. We also want to know about how you're making your key economic and financial decisions. Now, our plan is to consolidate all the feedback and input in [inaudible 00:20:29] report, which we will publish on our website in early 2021. We will then use what we learned from you to help us prepare our recommendation for a monetary policy framework to the minister of finance.

Ben Felix: That's great. Well, Don, will you, we really appreciate you coming on the podcast to talk about this and we appreciate the bank as well being willing to use a medium like a podcast, which I don't think the Bank of Canada tends to engage in. So yeah, we really appreciate it. Thank you.

Don Coletti: Great. Thank you for having me and happy to have a chance to get the word out there to Canadians, and to encourage people to participate in the survey, and have a say in how we're setting up a monetary policy over the next five years. Thank you.

Cameron Passmore: Thanks Don very much.

Ben Felix: So we hope that you enjoyed that as much as we did. It was clearly a buttoned down interview, which you might expect from an organization like the Bank of Canada or any central bank for that matter. But definitely some really interesting information in there.

Cameron Passmore: I guess we shouldn't expect any breaking market moving news on a interview like that.

Ben Felix: No. I know I'm repeating myself, it was pretty cool to have someone like that from an organization like that on our podcast.

Cameron Passmore: I agree. So carry on with the regularly scheduled programming.

Ben Felix: Let's go.

Cameron Passmore: All right. So quickly, the book of the week this week is a book recommended by our mutual friend, Aiden. And the book is called, Who is Michael Ovitz? I'm not really a big Hollywood guy. I knew a little bit about him, but Michael Ovitz, it's basically a story about a guy who was a kid loving the movie industry. And it seems like as soon as he started working at a very young age, he was driven to get into the movie business and ended up becoming an extremely powerful agent in Hollywood and founder of the venerable agency, Creative Artists Agency, CAA.

And it's a great story. He really did create a revolution in Hollywood. And what I found interesting is that he didn't just represent talent, but he also had this ability to have a vision for an idea or a story and pull it together with both the actors, the writers of the script, and the studios to pull it off. And it's really fascinating how so many of these big be it movies or TV series weren't all ... I had a vision that it was more a manufactured thing, like they knew the story that had to be told and how to do it, but it's really not. It's really highly creative how the whole thing comes together right down to there's seven major studios and this is kind of a for all the Netflix and Amazon Prime, et cetera that are creating content at a different era. But it's really interesting how different studios have different economic models for how the movies are made, how they choose different actors, and how the deals actually come together.

So we go into great detail about pulling a number of deals off. I mean, completely unexpected things like how successful Shogun was. Michael Crichton's Jurassic Park is one of their ideas. Rain Man. They thought Rain Man was going to be a complete flop. He was also deeply involved in a lot of the big production companies that were taken over by other companies, so he was very involved in when Sony took over Columbia Pictures. And then later in the book, he gets into how he got involved in Silicon Valley with a number of the big names, and one of them we've talked about a few weeks ago with Peter [Teal 00:23:59], and many others. So he got into the investment game as well on the other end. So bottom line, it's a fun read. If you're into Hollywood at all, you'll really enjoy it. It's a story of risk taking and family dynamics. I enjoyed it very much.

Ben Felix: Cool. That dovetails with the book that I mentioned recently, The Master Switch, about information empires. They talk in that book the story of Hollywood and how it used to be the opposite of how you described it, closed and non-creative and regimented. And it wasn't until those empires, I guess, those information empires that were controlling the movie industry started to be dismantled, which I think came from regulation if I remember correctly from the book. That was a good book. I think last time I mentioned that I was just starting to read it. I finished reading it now. Definitely worthwhile.

Cameron Passmore: So I've downloaded it. It's in the queue. I just need more time in the day apparently.

Ben Felix: I'll be curious to hear your summary. Your book summary is always good.

Cameron Passmore: Speaking of content, I know you said a while ago, you liked Animal Kingdom. You kind of get hooked on watching Animal Kingdom. So we introduced another one, similar vein called Kingdom. It's just as crazy, outrageous, horrifying as animal kingdom, but it's got to do in the industry of MMA, mixed martial arts. Yeah, it is as crazy as Animal Kingdom. We're about six or seven episodes into that. Anyways, in other news, I just loved the father's story that our friend Barry Reynolds posted on the weekend was really interesting. Did you know that Starbucks has $1.6 billion, billion in stored value card liabilities. These are like gift cards or money on your Starbucks app. Unbelievable amount of basically interest free debt. And every year Starbucks recognizes a portion of those liabilities that they assume will be completely lost and that's known as breakage. So get this, Starbucks recognized the amount as profit and in 2018 Starbucks recognized $155 million in breakage, which is about 10% of all these stored value balances. Doesn't it blow your mind?

Ben Felix: People just flushing money down the toilet. That's crazy.

Cameron Passmore: I know around our house, my kids have a number of these gift cards sitting in their bedrooms just waiting to be spent, but they've been sitting there for who knows how long.

Ben Felix: I wonder if I have any gift cards. I don't think I do.

Cameron Passmore: I don't think I do. I doubt you would. Next item. So two weeks ago we went through, you and I, the list of nudges that Dr. Daniel Crosby wrote about, and one of the nudges was the benefits of keeping an inheritance in a separate account. The argument at the time that I was making was keeping it separate doesn't necessarily make sense. It may not necessarily be rational, but it can perhaps make you a better investor.

So a listener kindly posted that actually keeping it separate in an inheritance situation does make sense because it is a way to ensure that it does not get included in any division of assets should you go through a relationship breakup. So I completely agree. I wasn't specifically talking about the inheritance necessarily. It was more about the notion of keeping money in separate buckets. So the listener is absolutely correct, and grateful to get that input and feedback.

Ben Felix: Yeah, for sure. So from a family law perspective, it can make a lot of sense to keep assets separate, because like you said, they then get ... inheritances get excluded from division of assets, but if they have been kept separate, it's just a lot clearer. I think if they're commingled or used toward purchasing a matrimonial home, then they may not be included in the division.

Cameron Passmore: So do you want to quickly go over the news on planning designations?

Ben Felix: Sure. I just want to say real quick though that that comment is one of many. The discussion that goes on in the Rational Reminder discussion page and on the episode comment sections, but more so in the general discussion, some of it, it's really, really good.

Cameron Passmore: Yes.

Ben Felix: We will talk in our planning topic about a little bit about some of it was inspired by one of those posts, but somebody wrote a program in Java to test historical safe withdrawal rates for factor loaded portfolios. And it's like, "What?" And they posted their code on a Github so people could see it. Anyway, a bit of a digression there. Yes. Let's talk about the title regulation.

Cameron Passmore: So this a new development. So the financial Services Regulatory Authority of Ontario who was responsible for supervising and regulating a broad range of financial service sectors, including autohome life, health insurance, pensions, credit unions, mortgage brokers, et cetera. So they have set proposed standards for planners and advisors. I know we mentioned this a couple of weeks ago. We thought it would be worth digging into a bit more. So the Global Mail had an article earlier this year that highlighted that Ontario had Passed the Financial Professionals Title protection Act, which requires anyone who wants to use a title of financial advisor or financial planner to obtain appropriate credentials from recognized professional bodies and remain in good standing.

So to that end, there is a proposal from the FSRA that reps who want to call themselves financial planners will need to have higher credentials than those who want to be called a financial advisor. So that credentialing bodies will be required to demonstrate to the FSRA how their designation aligns with the education requirements in the proposed rule. It's also interesting to note that there will be no grandfathering for existing planners and advisors, and some existing designations may not meet the new standards. They mentioned the life licensed qualification program may not, meaning if this is the case those that hold only that designation will not be able to call themselves planners or advisors.

Ben Felix: Which it makes sense. I've done the LLQP program. I wouldn't call it a designation. It's the Life Insurance Licensed Qualifying Program. You need it to sell insurance. It's not overly challenging. I mean, you need to know about insurance to write the exam. You do not need to know about financial planning to write and pass the exam. So, I mean, that's just sensible. I think one of the most telling outcomes of this whole process is going to be when they go through that review to determine if designations aligned with education requirements proposing the rule, what are they going to approve? Because an example is advocatus, which is, I guess, a financial advisor association. They've just come up with their own credential.

I can't remember what it's called, but presumably it's not going to be as rigorous. I'm making an assumption here. Maybe it will be, but I'm going to assume that it's not going to be as rigorous as the CFP program, which is fairly rigorous. So where's the bar? I think that's going to be the most telling thing. One of the outcomes of this could be that new credentialing bodies come out with credentials that meet the bare minimum of the regulations. And then you're going to have a whole bunch of different titles out there that aren't going to mean very much.

Cameron Passmore: But so many people now are not credentialed.

Ben Felix: That's true. Something's better than nothing. That's a fair point.

Cameron Passmore: Currently, there's no Canada wide legislation on standards other than inside Quebec, which has its own set of rules.

Ben Felix: Yeah. I mean, that's an issue with Canadian securities regulation, more broadly speaking. Financial planning, I guess, you could argue is different from securities regulation. It is different. I think more and more financial planning regulation in Canada is a good thing.

Cameron Passmore: We agree. You wanted to talk about SoftBank?

Ben Felix: Yeah. It's been in the news a bunch a few weeks ago. I had somebody email about it. I thought we'd mentioned it quickly. It came out as this big story that SoftBank was piling into call options on tech stocks and making these huge bets, and that they were responsible for the rally and tackling all this stuff. I'm glad we didn't talk about it when all of that was happening because more information came out later. I don't know how definitive any of this is because I don't think, at least not from what I can find, that SoftBank has come out and explained exactly what they were doing. We do know that they have a public securities arm that they've created, but you can never know exactly what's going on by looking at transaction records or anything like that because not everything's public. A lot of it can be done over the counter.

So the information that's come out since that initial news broke from the Financial Times is that they were actually deploying call spreads, which means that they were both buying and selling calls, which is actually a pretty conservative thing to do. It's a way to participate in some of the upside while limiting downside, which is not nearly as crazy as you know, people were saying that they have this massive leveraged exposure of $50 billion with their $4 billion of call options, which might be true if they were only buying calls. But if they were buying and selling calls entering into call spreads, it actually wasn't that crazy of a thing.

Cameron Passmore: Interesting. That was the story though, the 50 million [crosstalk].

Ben Felix: Yeah, yeah. Well, that's why I'm saying I'm glad we didn't cover it because there were news articles that came out like the week after saying, "Ah, this is actually probably more likely what's what's going on." And then the other piece of that is that if they were doing the call spreads as opposed to the calls, they wouldn't have been moving the price as much. They wouldn't have been responsible for the tech rally if that's what they were doing. The thing that I read that was explaining this though, was also saying that one of the more likely causes of the rally, and you can never pinpoint exactly what the cause of a rally is, but one of the things might've been the short term option activity from retail traders. Apparently, retail option activity has been massive through platforms like Robinhood, is one that people talk about the most, but short term options require the market makers to hedge against the option exposure. So they purchase the underlying securities, which can increase stock prices.

The thing I was reading was saying there was about $4 billion of option activity from SoftBank, but there was about 40 billion over the same time period from retail traders, like people sitting at home on their Robinhood accounts. Always more to it than there appears to be when a story like that breaks. It did seem when I read that at first like, "Geez, SoftBank's crazy." But it seems like they're still crazy, but maybe not as crazy as it appeared.

Cameron Passmore: It's one of the big meat of the episode today where you've merged kind of the investment and planning topic into one combined topic this week.

Ben Felix: Yeah. So this is the part that was inspired by one of the people commenting in the Rational Reminder discussions named Samuel. You can see his comments in there and the link to his code if you want to take a look at it. I'm not exactly fluent in Java, so I didn't necessarily review his code. But the idea behind the analysis that he was doing is what inspired this. I've recreated something similar to his model using Visual Basic in Excel so that we could run our own analysis.

Cameron Passmore: So what's the big picture? Where are you going with this?

Ben Felix: Yeah. So it's all about withdrawal rates. Samuel was asking, I've heard Ben rubbish the 4% rule on YouTube and on the podcast, but what about with factors? And it's true. Anytime that we've talked about the 4% rule not making sense has always been considering the market portfolio. So I mean, it was right of Samuel to be questioning whether or not there's more to it if we start to include factors, which is exactly what he was trying to do in his model. So I wanted to address it in as much detail as I could, particularly because the people who are listening to this podcast are well aware of factor investing the idea that there's more than just the market risk premium that drives stock returns, and they may even have factor tilted portfolios. So the idea of safe withdrawal rates with the factor tilted portfolio is particularly relevant to our audience. So we modeled it.

Ben Felix: And one of the things that Samuel found, so I wasn't able to recreate this part of his code, and I don't really fully understand how it works in his model, but he was able to back test the optimal mix of factor loadings for safe withdrawal rates. So I used his findings as a guide to input into the model that I built. My model didn't optimize for it the way that his did.

Cameron Passmore: Oh, that's interesting. He had an optimizer to get to the sweet spot for factor loading.

Ben Felix: Yes, he could find the maximum safe withdrawal rate by changing the factor loadings for the portfolio using Fama and French data, going back to 1926 or whatever the Ken French dataset starts.

Cameron Passmore: Interesting.

Ben Felix: And it was interesting. It was really interesting. It ended up being something around, loading on market beta, 0.5 on size and a one loading on value. And we'll talk a little bit more about the practical implications of building portfolios like that in a minute, but first I want to talk through safe withdrawal rates for different indexes, just different stock indexes. So not an optimal back-tested portfolio. So I use 50 year safe withdrawal rates. So 50 year time period and found the amount that you could have withdrawn in the worst period to not run out of money, same as the 4% rule.

Cameron Passmore: What do you mean by that worst period?

Ben Felix: So what percentage of the portfolio in the first year-

Cameron Passmore: So 50 years ago.

Ben Felix: Yep. What percentage of the portfolio could you have withdrawn 50 years ago and then adjusted that dollar amount for inflation monthly thereafter, I used monthly inflation, such that you wouldn't have run into money in the worst 50 year period.

Cameron Passmore: Also, it's not just the last 50 years, just looking at 1970 to now.

Ben Felix: No, from all the rolling monthly 50 year periods what was the amount that you could have spent. Actually, I had a 1% failure threat threshold. So this is the amount that you could have spent in the first year such that only 1% of the 50 year periods resulted in failure, resulted in running out of money.

Cameron Passmore: So all the 50 year periods going back to the late '20s, and then moving it ahead all the 50 year periods.

Ben Felix: Moving forward monthly. Yeah.

Cameron Passmore: Got you. Okay.

Ben Felix: So then the safe withdrawal rate is that amount that you could have spent in the first month. Well, I guess the safe withdrawal rate is the amount you could have spent in the first year, but I was doing the modeling monthly.

Cameron Passmore: Sorry, just to be clear so that everyone gets it, so it's the dollar amount on that first month, and then that dollar mountain increases with inflation. You're not doing the safe withdrawal rate each month. It's a dollar amount of the first month and that carries on with inflation through the subsequent 50 years.

Ben Felix: Correct. Correct. So the first monthly withdrawal is based on the safe withdrawal rate and then adjusted for inflation thereafter.

Cameron Passmore: Cool.

Ben Felix: The research on this usually looks at US market, just US equities. So I did look at that. So for the Fama/French US Total Market Index, which is like VTI, like the Vanguard Total US Market Index, and the safe withdrawal rate there was 3.1%. S&P 500 was 3.35, which is interesting, but higher. Fama/French US Growth Index, so a market wide growth, 2.8,5% safe withdrawal rate. And I won't go through all of them because-

Cameron Passmore: [crosstalk].

Ben Felix: Yep. A lot of them are around 3%, but I'll go through the ones that are not 3%. US small cap, so just small cap universe, 3.4% safe withdrawal rate, small cap growth, 1.9% safe withdrawal rate, also interesting. And we know that the risk adjusted returns of small sap growth tend to be pretty awful. So that's no surprise. Small cap value, now, this one's interesting because we talk about the sequence of return risk and how volatility is bad in the withdrawal phase. And that's true, but even though that's true, the US small value research index had a 3.6% safe withdrawal rate, the highest of all of the indexes that I looked at. And that in terms of factor or characteristics or factor exposures is pretty close to something like IJS or AVUV, the amount of small value.

Cameron Passmore: So that's 100% of the portfolio in the US small value.

Ben Felix: Correct. Which would be horrifying, horrifying to live through I'm sure.

Cameron Passmore: Well, there must've been some rough periods in that.

Ben Felix: I don't have that data up in this screen that I'm looking at here, but I did run the maximum drawdown for all of these portfolios and small value did not have the worst maximum drawdown. I think it was actually large value that had the worst. And the worst drawdowns all happened in great depression era and they were all around 88%, but small value did not have the worst of the index that I tested, which is interesting. But the returns would have been the most volatile though, but it got to the highest safe withdrawal rate if you could stick with a strategy, which most people probably wouldn't have, and if you could access a small value portfolio, which again, you wouldn't have been able to throw at these time periods.

Cameron Passmore: Strategy is only as good as your ability to stick with it.

Ben Felix: Yeah. Yeah. We'll touch more on that too as we go through this topic. The Fama/French US Value Research Index and market wide value, 3.3% safe withdrawal rate. And this is for 50 year periods. I just want to point that out because the original 4% rule analysis that people might be familiar with was based on a 30 year withdrawal period. So if we went back and looked at S&P 500 for 30 years, it would have a 4% safe withdrawal rate. For 50 years, it's 3.35, which is the analysis we're talking about now. Microcaps were 3%, which I was actually kind of surprised by. I thought they'd do a little better. And then I looked at the dimensional US Vector Equity Index, which is an index that represents the factor exposure that the Vector Equity Funds have. And it was 3.35. Vector's kind of like a ... not quite small cap value, concentrated portfolio. It's more of a market portfolio, heavily tilted towards small cap and value. So the best one was small value like I mentioned, which on its own was a pretty interesting finding.

Ben Felix: For 30 year periods, I also wanted to mention that William Bengen the guy who created the 4% rule he's since updated his model to be 4.5% based on the inclusion of small cap value stocks. I didn't go and look at exactly what allocation small cap value stocks he was talking about, or if it was all small cap value with bonds. I didn't dig into that, but I do know that he's updated the number to 4.5% for a 30 year period using US stock data, which as we've talked about on the podcast in the past, doesn't make a whole lot of sense to do.

Cameron Passmore: And that's a recent update?

Ben Felix: Somewhat recent. It was actually on a Reddit. He did a Reddit AMA, which is kind of interesting. And in there, he said that he's changed his spending rule. I mentioned that the characteristics of the US small value research index are pretty close to something like IJS or AVUV. IJS is the iShares small cap value. I think it's the S&P 600 small cap value index.

Cameron Passmore: That's right.

Ben Felix: And the three factor coefficients. And I'm only talking about three factor because five factor data doesn't start until 1963 for profitability and investment. So three factors is what goes back really, really far. So this portfolio has an SMB coefficient. So that's the exposure to changes in the small minus big premium of 0.93, which is pretty big. And it has an HML coefficient. So that's exposure to the high minus low value minus growth coefficient of 0.78. So that means that if value stocks minus growth stocks, whatever that premium is, positive or negative, this index would capture 0.78, 78% of that variation in returns.

And likewise, if we just use market beta as a simple example, if you're investing in a traditional market cap weighted index fund, it should have a market beta of one. So it's factor exposure to the changes in the market risk premium, which is the market over one month treasury bills. If you've got a market beta out of one, you're going to capture 100% of that variation. So that's what all these factor regression coefficients are, how much of the variation in the premium would you expect to capture or would this allocation historically have captured?

Now, it's interesting to see that the SMB loading, the small minus big coefficient, on the US small value research index is 0.93, because to get a coefficient of one, you should technically be long all of the small stocks and short all of the big stocks. This portfolio isn't short anything. It's a long only index portfolio. So why does it have such a high regression coefficient? It's because it's concentrated in the smallest, cheapest stocks. I'm guessing cheap stocks tend to be smaller, so you get a really high loading. It's like in a past episode, we talked about how you can get higher factor loadings by being more concentrated in a position. So if you go and take the smallest stocks, not the smallest half, but the smallest like 10% say, your SMB loading is going to be high. So I think that's why this has such a high loading without being actually short anything. Now concentration has other trade offs, but we're going to leave that alone for now.

So like I mentioned before, in Samuel's model using Java, he found something around a 0.5 market beta, 0.5 size and one. So full long short exposure to the value premium gave the highest withdrawal rate in this data sample. And it gave a safe withdrawal rate of 5.5%, which is pretty staggering when you consider 3.6 was the highest with just the small cap value portfolio. So a huge increase in safe withdrawal rate, but this portfolio is short the market, or I guess you could just be ... No, yeah, it's got to be short the market, not full exposure to the size, not full long short exposure to the size premium, but full long short exposure to the value premium. So that could come from high concentration and the cheapest stocks. I don't know how you get to exactly. You'd have to short the market a bit to get there, which I think from a practical perspective is probably not realistic for most people.

And it was pretty sensitive to those loadings. Like I tried doing higher weights on market beta and higher weights on size, like something that you could probably more realistically get with a long only portfolio and the safe withdrawal rate fell off a cliff pretty quickly. So I think this is sort of theoretically interesting practically, and maybe not super useful, but there are practical implications I think that are important to talk through.

Cameron Passmore: This is so fascinating.

Ben Felix: Yeah. And you think about why does that portfolio that's long the value premium, which means long value and short growth, and short the market and only 0.5 exposure to size, why does that do well? Or why did it do well over the sample period? So then you start getting into how do the factors interact with each other? Like when the market is doing something, how does value tend to be doing and how does size tend to be doing?

Cameron Passmore: So I'm wondering, is this something to do with the smoothness of returns? Because smoothness in growth of dollars going on as well.

Ben Felix: Yeah, both of those things are happening. There are some interesting papers that try to quantify sequence risk and they've tried to make up some measures about how you look at that. And volatility is a big piece of, obviously, sequence risk, although doesn't necessarily dictate it. But there was a paper that I found in the Journal of Portfolio Management and the paper's called a Wealth Management Perspective on Factor Premia and the Value of Downside Protection by Louis Scott and Stefano Cavaglia. So they were basically looking at the interaction between factors. They tested an investment in the global equity portfolio, so like a market cap weighted index fund and then compared that to an investment in the market, so a normal index fund with an overlay in either, so an access exposure to either the size premium, the value premium, the quality premium, or the momentum premium.

So market with excess exposure to one of those. And then they also tested market with excess exposure to all of those in equal weights. And they said they did equal weights to avoid the kind of data mining that Samuel ran into by finding that ex post optimal factor exposure. So there the purpose of this paper was basically to see how would we expect those ... or how have those interactions historically looked? And what can we learn from that? Instead of just using historical data, they used what they call circular block bootstraps, which I had not heard about before, but they select a month at random and then sample a 12 month period starting with that randomly selected month. And then there's a good reason for using this approach as opposed to a normal bootstrap. It's because it preserves the auto regressive structure present in the market and factors, to try to preserve the relationship between the factors.

If you did a bootstrap where you're randomly selecting every single month, then any relationship between them would disappear. So they used this model to run a bunch of simulations with data from 1990 to 2012, which was a bit of a short data sample, but we'll talk about some other research that has longer time series to analyze. So I mentioned the interaction between the factors being important. They observed that size is a procyclical factor, so it tends to move with the market. And I thought this was an interesting finding because relates directly to a paper that Cliff Asness wrote, but also comments that Cliff made when he was on our podcast in episode 93, about small caps just being higher beta stocks. So this finding supports that, which I mean, no surprise. So small caps, they tend to move with the market, but with a higher beta.

In this dataset, they did say that that relationship was weak. It was present, but it was weak. And then quality and momentum, they said are countercyclical. Value appears to be weekly countercyclical, but the variation did not appear to be significant. So those are all interesting and important points. One of the other papers that we'll talk about in a second, they found value to be more countercyclical, not just weekly. So all of that though speaks to the diversification benefit of adding factors. And that's really what this paper that we're talking about right now, it's what it's all about. From a wealth management perspective, can you build a better portfolio using factors? So we'll talk a little bit about their results.

They simulated 20 year periods. And they found that the distribution of outcomes, which is really what we care about, was improved pretty much across the board by adding any of the factors. And it was definitely improved by adding all of the factors. They found that the median value of a $1 investment in the equity portfolio, in the market portfolio, rises from $4.15 over 20 years. So that's the median value of a regular market cap weighted index fund investment. It gives you $14. It goes up to $4.86 when you add small caps, $9.97 when you add value, $16.13 when you add momentum, $8.96 for quality, and $9.10 cents for the equal weighted multifactor portfolio. So the median result improves, which is important. And we also care about the shape of the distribution and how the factor exposure affects that. So the fifth percentile, the worst 5% of the outcomes was improved in all cases, except for the case of adding just small caps, which again makes sense with the procyclical nature of small caps that we're talking about before.

But if you look at the fifth percentile, so just the market in the fifth percentile of outcomes from their simulations, you had $1.06 left. So over 20 years, you basically break even. Adding small caps brought that up to $1.09. Marginally better, but not really and probably not for the amount of additional volatility that you're taking on. But for all of the other factors, so market plus value, the fifth percentile was $2.27 cents, market plus momentum, $2.65, market plus quality, $3.62, and then the market plus all factors combined left you with $2.68 cents in the fifth percentile of outcomes. So I thought that was a pretty important finding. It's giving you that by reducing the left tail of the distribution of outcomes, which is obviously attractive when we're talking about building portfolios.

This one was really useful from a practical perspective, they asked, "What if the factor premiums in the future are lower than they've been in the past?" Which is something that we've been living through, whether this continues at this magnitude or not, who knows. Hopefully it doesn't. But just theoretically, once the factors have been discovered, and documented, and published, and everybody's piling into them, or maybe they are, we would maybe expect smaller premiums. So they cut the historical factor premiums by 50%. And they obviously found that the median wealth over 20 years was reduced, which obviously you'd expect because we're cutting the premium by 50%, but the fifth percentile of outcomes were still a lot better with the factor tilts. So even if the magnitude of the premiums isn't huge, the diversification benefit of adding them to the portfolio was still very meaningful except for small caps again.

So then they looked at drawdown statistics. So what was the worst peak to trough a drawdown over the 20 year simulated periods? And no surprise again, they find that the factor loaded portfolios in both the 50% haircut case and the normal premium case, the drawdowns were significantly improved across the board, which was, again, one of the potential benefits of adding the factor exposure. I didn't really see that too much when I ran my simulations that I was talking about a second ago on the safe withdrawal rates. I mean, the quality was the biggest reduction, adding quality, which is like adding profitability. And I didn't have that in my simulation because, like I mentioned before, the Fama and French data, going back to 1927 doesn't have quality.

The multi-factor though in this simulation, the multifactor portfolio had a very favorable drawdown. I mean, market in this case was 93% was the worst drawdown and market plus the multifactor additions was a 79% drawdown, was still a pain for sure, but not nearly as bad. And I pulled a couple of quotes from their concluding remarks in their paper that I thought were important. So they said, "Our result, which favors a portfolio of factor premia overlay remains unchanged. As previously suggested the benefit of factor premia is not in their mean returns, but rather in their ability to mitigate adverse conditions as for instance, captured by drawdown statistics during the 20 year wealth accumulation journey."

And they also said, "We believe that the main contribution of his article is to provide fairly robust orders of magnitude statistics that highlight the diversification value of factor premia in a multi period portfolio construction problem. This diversification value is over and above the conventional expected return benefits that have been expounded in the smart beta literature." Important findings. In very simple terms, there's a diversification benefit to factors over and above and separate from the higher expected return benefit that we often get stuck talking about.

Cameron Passmore: Yeah, it's about protection more so than returns.

Ben Felix: Right. Which is counter-intuitive when we talk about the premiums being risk premiums, you're taking more risk by adding factors. But I think one of the things that we mentioned sometimes, maybe not enough, but what this research is highlighting is that the factors perform ... they're all risks, they're all independent risks, but in absolute terms, by adding factors together, you're not necessarily taking more risk. This literature is suggesting that you're taking less risk because you're adding independent risks together.

Cameron Passmore: Because you're isolating them, then laying them back together in this recipe.

Ben Felix: Yeah, exactly. And they're going to behave differently. Okay. So then I want to talk about another paper that looked at a longer data series, but it looked at the Fama-French five factors through business cycles. So this one we may have mentioned in the podcast before. I've definitely mentioned it in a YouTube video and in the past, but it's a 2017 paper titled Fama-French Factors in Business Cycles, pretty creative title, by Arnav Sheth and Tee Lim. And they looked at the market size value momentum, investment, and profitability factors across business cycles. They broke the business cycle into four stages, recession, early stage recovery, late stage recovery, and very late stage recovery. They examined how each of the factors performed through those different segments of the economic cycle.

They also threw in, although I don't think I'd talk about it in this segment here, but they also looked at how the factors perform following yield curves in versions. That they looked at 10 US recessions, which is the data that we're going to talk about designated by the National Bureau of Economic Research, going back to 1953. And they examined the cumulative factor returns for the 10 months following the start of each recession and 10 months is relevant because that's the median length of historical US recessions, of course. So they found the best performing factors in a recession on average where the investment factor, which had an average cumulative 10 month premium of 18.3%, pretty good, during recessions. And then the value factor, which is the one that I think we're probably most interested in for this conversation, the value factor was second with an average cumulative 10 month premium of 12.5% during recessions. So there's that countercyclical nature of value showing up.

In the early and late stages of the economic cycle, the investment premium was not so good. So it was the best during the recession, but in the recovery, not so good. But the value premium was pretty good all the way right into the late stage, but then it tapers off in the late stage. So again, we see this diversification benefit, this low correlation between the various factors, which becomes increasingly important as we're talking about stuff like safe withdrawal rates.

There's another paper that I'm not going to dig into the details, but it's just worth mentioning their finding. So there's a paper from 2012 by Jared Kizer and Antti Ilmanen titled The Death of Diversification Has Been Greatly Exaggerated. And they found, this as a quote from the concluding remarks of their paper, factor diversification has been more effective than asset class diversification in general and in particular during crises. Okay. So that's the interaction between factors, not just how does adding any factor, but how does adding factors affect withdrawal rates? I guess we could have looked at something like building a portfolio of markets, small value and value or something like that, and test the withdrawal rates on that. I didn't do that. Maybe that's a further research problem.

The other thing that I wanted to mention, because this came up, I think in that same comment thread on the Rational Reminder discussion, was the idea of value spreads. And again, it ties back to one of the ways that we've tried to discredit the 4% rule. I don't mean discredit like we're trying to be mean to them. It's just, I don't think it's right. But one of the reasons for that is that throughout the periods that the 4% rule was originally tested, market prices were relatively low, relative to earnings. Like if we use the Shiller or CAPE earnings measure. Prices have tended to be lower throughout those periods. Now, they're really high, particularly for US stocks. But the question is, does that extend to factors? Can a factor be cheap and therefore have a higher expected premium?

So there are a couple of papers that I found on this. There was one from AQR that was really easy to digest. So I'm going to mention that one. As far as I know, AQR actually created the idea of the value spread. So if you look at the long and the short side of a factor, you can compare the valuation of them. And if the valuation spread is bigger, you may be able to expect a higher premium in the future. So they use the value spread in the paper that I'm talking about to try and model it out. They found a modestly positive relationship, in their words, for the value factor and weak correlations for the momentum and low beta factors. And those are the only ones they looked at. So there's a bit of a relationship. And the other paper that I didn't dig as much into had a very similar finding where there is some information in value spreads about feature premiums. So if value spreads are wide like they are now, you might expect a higher premium in the future.

Cameron Passmore: And therefore a higher withdrawal rate.

Ben Felix: Yes. Would I bet on that? I don't know. It would be irrational for me not to, I guess. But one thing that they did find, and this is very similar to the ... and AQR has done really good work on the Shiller or CAPE ratio too. When the market's cheap, you can expect higher returns, but you can't use it as a timing signal. They found the same thing with the value spread. When the value spread is wide, you can expect higher premiums, but you can't use it to time value. So I thought I was done this topic there, but there's a whole body of empirical evidence on this other thing. I apologize to all of our listeners because this is going to send some people down a whole other rabbit hole that they may not have gone down yet. And maybe they shouldn't even go down. Maybe I shouldn't even talk about this. It seems like it's the dark side.

Cameron Passmore: So that's your disclaimer?

Ben Felix: But I feel like I've got to talk about it. I don't think [inaudible 01:02:44].

Cameron Passmore: Let it out. Let it out.

Ben Felix: It wouldn't be intellectually honest to talk about this subject without mentioning the empirical evidence on this thing. So the thing I'm talking about is trend to following, which is also known as time series momentum. Cross-sectional momentum, which is the one that we were talking about previously when we mentioned the momentum factor and momentum UMD, minus down, in the Ken French language is the best performing stocks over some time period, say the previous 12 months, minus the worst performing stocks. Up minus down, best performers minus worst performers. That's cross-sectional momentum. Time series momentum is comparing an asset's value to its average value over the previous whatever time period, 10 months, 12 months, whatever you want to call it. Time series momentum is used or can be used as a market timing strategy where ... well, yeah, it can be used as a signal to get into or out of the market based on how an asset is trending relative to its own history.

So time series momentum, because you're comparing it to its own time series as opposed to cross-sectional momentum where you're comparing it to all other asset returns. Now, the reason that this is empirically interesting, is it in the historical data trend following has, I mean, really undeniably good characteristics. It increases withdrawal rates meaningfully. There are different papers that look at this in different ways, but we're talking about like 50% increases, sometimes more in safe withdrawal rates by following a trend following strategy. I find this intellectually really challenging because that's market timing and it is, but you can do this systematically. I'm not saying people should do it, but you can do trend following systematically based on rules. There are lots of different models out there, a lot of them surprise, surprise are sold on a subscription basis to get access to the signals. But a lot of them are not. A lot of them you can just do yourself.

Cameron Passmore: Does it make any theoretical sense to you?

Ben Felix: Yeah, so it does. This is part of the challenge I guess. It clashes with the traditional thinking of you can't time the market and all that kind of stuff, but the way that it makes theoretical sense. The theoretical basis for the whole trend following strategy is rooted in behavioral finance.

Cameron Passmore: Who says behavioral, not risk based.

Ben Felix: It is absolutely not and it's explicitly not risk based. So we mentioned when I was talking about adding other additional risk factors to the portfolio, one of the benefits and one of the things that you want from a safe withdrawal rate perspective, is to reduce the left tail of the distribution and trend using a trend following strategy does that really well, like arguably at least as well as, leave it at that, other factors. So it's like another level of diversification. Now, there are tons of papers out there looking at how trend can improve safe withdrawal rates and how just portfolio characteristics in general, tons. Most of the papers are in practitioner literature. A lot of them are in the Journal of Portfolio Management, which is mostly practitioner literature. I mean, it's somewhat academic. It is a peer review journal. So it's not like it's garbage or anything like that.

In the Journal of Finance, which is sort of the premia academic theoretically consistent journal that exists, I searched for trend in the Journal of Finance database and there was one article in the history of the Journal of Finance. And this was one of the other things that I find challenging about getting behind trend is where's the deep theoretical discussion. Now, I'm not done with this topic. It's a huge topic, and there's a lot to digest, and a lot of really smart people that talk about it, which is another reason that it's hard to ignore. But we'll talk a little bit about some of the challenges that I see with it in a second.

So there's a paper in the Financial Analyst Journal, which is again, more practitioner literature than it is an academic journal. But I pulled a quote from this paper, which I thought it captures the whole concept well. So they say diversifying across asset classes should nudge portfolio returns in the desired direction with improved risk return, trade off, and possibly a lower maximum loss, which we've just seen. And you can kind of see why this ties in so well with this topic, but an even more powerful technique according to this paper, this author, can be applied to individual asset classes to dramatic effect. Trend following whereby one invest in an asset when it is in an uptrend defined as a current value above some measure of recent past average and switches to cash when the current value is below such an average. So I guess I've kind of already described that. But again, to reiterate, this is market timing. It's rules based market timing, but it can't be ignored because it's so strong in the data.

Now, where I see the biggest theoretical challenge, and I think this is an empirical challenge too, I'll explain why in a second, is that persistence, because this is a purely behavior based phenomenon it should be traded away. Now, there are reasons why it wouldn't be, and I'll mention those in a second, but it should be. If enough people know about this, if everyone's doing trend, it's gone.

Cameron Passmore: You're basically buying high, selling higher in real simple terms on a relative basis?

Ben Felix: If it's on an uptrend, you're staying invested and if it's on a downtrend and you're going to cash.

Cameron Passmore: I wonder which side of that is the most ... So many interesting questions, which side is more valuable, getting up before it sinks further or getting in as it rises higher?

Ben Felix: So I found out one paper that discusses trend in a long, short sense. I didn't dig into it, but they were talking about using futures contracts and you can be long and short. And they said most of the value came from the long side.

Cameron Passmore: So buying high, selling higher.

Ben Felix: Yeah, I guess so. So there's a paper of AQR. AQR is one of the firms and the people from AQR or some of the people that have done some of the most prolific work on this topic, but they looked at this and they explained the theory behind why it works. So I'm going to quote them for a second. "A large body of research is showing that price trends exist in part due to longstanding behavioral biases exhibited by investors such as anchoring and herding as well as the trading activity of non profit seeking participants such as central banks and corporate hedging programs. For instance, when central banks intervene to reduce currency and interest rate volatility, they slow down the rate at which information is incorporated into prices, thus creating trends."

So interesting reasons. Now, that theoretical challenge of should this persist? I think that the theoretical challenge is augmented by the empirical experience of trend since it became extremely popular. So trend using futures contracts became pretty popular I think in the '80s and '90s. Cameron, you probably can speak to that better than I can. I don't know if you remember seeing products like that.

Cameron Passmore: No, I do not.

Ben Felix: Okay. So there's CTAs. A lot of them were like two and 20 type hedge funds that were doing this stuff and the numbers I think looked pretty good. So the strategy started to become more and more popular. And then in 2008, trend following did really well. Actually I think in 2000 as well and in 2008. In both of those instances, trend following did really well, like mitigated the losses big time, which is what it's designed to do. Since then though, since it killed it in 2008, it's become increasingly popular. And now there are all sorts of ETFs and mutual funds and anybody can access, all sorts. I mean, I did a search in Morningstar Direct to speak to some of the data, but there were, I don't know, probably, I don't know, more than 20 trend following ETFs and mutual funds.

So again, it speaks to that question of persistence. If there are billions of dollars pouring into these types of ETFs, would we expect the favorable characteristics from the past to persist? I don't know. And then you look at the data, and we probably don't have enough data. I probably shouldn't even be commenting on this. And by the way, just so everyone knows, I know that if we were having this conversation about the value premium, I can be bashing it for the same reasons as what I'm about to say because value is done horribly for the last 10 or so years too.

But in this recent COVID related downturn, which from a signal timing perspective would be a pretty tricky one to get right, but all the trend ETFs that I looked at in Morningstar Direct, they, for the most part did a little better than like VTI than the just abroad US market index, which dropped about 30%. All of these trend ETFs did a little better. Some of them did a fair amount better, but most of them did a little better, like minus 25, that kind of thing. But since then, if you look from February until now, all of these trend following ETFs are still getting smoked, still double digit negative returns over the time period whereas market's back up.

Cameron Passmore: Because the signals wouldn't have been fast enough to take advantage of the rapid rebound?

Ben Felix: I guess, but this is one incident and it's different, who knows? I don't think that that data point, isn't enough to say, "Hey, this thing doesn't work anymore." But from the perspective of making portfolio allocation decisions, the proliferation of ETFs that are investing in this from a persistence perspective makes me nervous like for value or profitability or investment or whatever, there's at least partially a theoretical risk based explanation for why they exist. And at least some of the historical premia is explained by risk, then at least some of the premium should persist in the future. I think that has to be true.

With trend following, there's no real risk based explanation. And then the other, this is the big one, is even if we say like, "We can assume with the value." If the value premium goes away, it doesn't mean you're going to get negative returns for the rest of your life. It just means you might not get a premium. You're still going to get stock returns and value is going to do better than growth over some time periods in the future. It has to. If there's no premium, it just means you're not going to get a consistently positive premium over the longterm. With trend you're introducing higher costs, unless you're doing it yourself, which you can do just by trading ETFs. But if you're buying a trend following fund, the fees are higher than a normal ETF.

There are some tax implications, although the ETF structure can mitigate some of that. The tax implications will be worse if you're trading on your own, unless you're in a registered account, I guess. And then transaction costs in terms of spreads when you're trading. Those also obviously eat into returns, especially if you're doing this with any degree of frequency. So, I mean, in short, you're adding a bunch of costs and if it doesn't persist, it's troublesome. But at the same time, the empirical data, and it's not just in stocks, like the research on trend following extends to anything you can think of, currencies, commodities, futures contracts, anything.

Cameron Passmore: How does trend following link back to the original question, which is any sense of how it impacts safe withdrawal rates?

Ben Felix: It's huge. Yes, it's huge. I don't have the numbers to say that it takes the 4% rule to 8% or something like that. I think some of the papers might have tried to quantify that, but a 50% increase in safe withdrawal rates using trend following in the historical data would not be unreasonable. I think that's on the low end. I'd have to go back and look. So that's how it relates to this is that using trend falling in the data historically, it's had a phenomenal impact on results. One of the other reasons I wanted to cover this is that I had some people after we had Michael Kitces on talking about sequence of returns risk, some people were sending me stuff on trend and, "Hey, what do you think about trend and how this impacts sequence of returns?"

And it improves it in the data. I mean, it's tricky, right? You can go and look at it in iShares, iShare has had value in growth funds for US small, mid and large caps in, I think, June of 2000. So you can go back and look, okay, value ETFs have actually outperformed over the time period when the value premium was positive, which it has been from 2000 until now, just not more recently. But as far as I know, there's no live data like that on trend. Maybe there is. Maybe someone can show it to me. But if it's one hedge fund, I'm not interested. If there's a proper dataset of live trend following funds, I'd be curious to see it.

Cameron Passmore: It's interesting you mentioned the community that's been developing around this. It is so much fun and it's so interesting to engage with people that are part of this community, and this kind of leads to the next story. So the bad advice the week is turning out to be a very popular topic on Twitter. So this next one came from our friend, Troy in Saskatoon, beautiful Saskatoon, and who by the way, has already received his Rational Reminder hoodie. And I, by the way, just got a couple of cases in today of new hoodies. Anyways, it's an article that was in Forbes, entitled Stock Market: Goodbye Passive Indexing, Hello Active Stock Picking. So queue the booze.

Anyways, the article started with, "The coronavirus has produced a stock pickers market, therefore now is a time to pursue superior returns from stock picking and actively managed funds and ... " Get this, Ben. "This new environment could last as a long time for two reasons. Number one, the preponderance of stock investing is currently in index funds and a number of coronavirus negative effects on industries are expected to last a long time. This will cause many stocks to lag while producing opportunities for others to become new leaders." But get this, this is what blows me away. They then display a chart showing the difference in returns for the second quarter and part of the third quarter.

Yes, like 18 weeks and how two active funds, the Vanguard Explorer Fund, which is one of their active portfolios, and the Fidelity Contra Fund outperformed in that 18 week period. And to quote, "Think of those differences not academically, but in dollars and cents." "In only four months, 100K in the Fidelity Fund would have grown by ... So a hundred thousand in that fidelity fund would have grown by $8,503 more than the S&P 500 ETF. And the Vanguard Fund would have grown by more than $16,000 more than the S&P 500 ETF!" And here's a quote that I can just hear you saying one day, "Nothing says compelling and exciting like multi thousands of dollars in added returns."

Ben Felix: That's a terrible line. I'm also self-conscious now because I just did, in the segment on trend following, the exact same thing that this guy did in comparing the active ETFs to the index. I literally just did the same thing over the same time period. Did I give bad advice? Was that bad advice?

Cameron Passmore: Unless you did it over 18 weeks or not. Well, two reasons they're often cited, there really is only one reason. They go on to say that indexing might benefit, which is lower fees. However, you get what you pay for because missing from index fund management, our skilled analysts and portfolio managers, the necessary ingredient for successful active stock picking. The other benefit is "the belief that active managers can not beat the market." However, that can become a drawback because active managers can and do beat the market.

Moreover, when active is the favorite approach, their performance can be large. Incredible, incredible to me. The good news they go on to say is that passive's become so entrenched. Think of it as a mindset bubble, Ben. The budgeting move back to active can produce a dramatic extended period of superior performance for active managers. So the bottom line, now, yes now, is the time to get active. The mindset that the belief that an index fund is a wise equity investment is broadly held. However, that mindset is inaccurate. There are times when active management easily beats the stock market, and it appears we are entering such a period thanks to the coronavirus shakeup.

Ben Felix: That statement was based on the performance of two funds?

Cameron Passmore: For 18 weeks.

Ben Felix: Right. Okay.

Cameron Passmore: But that was exciting. It was exciting. Therefore, with the large majority of investors focused on index fund investing, now is an excellent opportunity for actively managed funds to shine. Moreover, once the passive to active cycle gets in gear, the money flow themselves will produce even better actively managed results and excitement.

Ben Felix: I want to get my popcorn. That sounds pretty exciting.

Cameron Passmore: It does sound exciting.

Ben Felix: I really don't understand stuff like that where it's looking such a vast amount of data in the face and saying, "No, no, no, no, no, no, trust me, we can do this. Look at these two funds at least in the trend following." Whether we want to use it in portfolios or not, at least with that, there is a massive amount of data, at least. I don't understand how you can sit there and say, "Look at this active fund that did well." Despite the many, many years of underperformance and all of the theoretical justification for why that should persist.

Cameron Passmore: That's why I always wonder what is the true motivation other than business. I get the business side of it. What's your motivation to want to stand in the face of this mountain of peer reviewed academic evidence where you just don't know.

Ben Felix: Maybe you just don't know.

Cameron Passmore: There you go. Compelling and exciting. Multi thousands of dollars in added returns are compelling and exciting.

Ben Felix: That kills me. Think about it in dollar terms. You could have had an extra $2,000 if you had invested in [crosstalk 01:20:39].

Cameron Passmore: In those 19 weeks.

Ben Felix: Anything else?

Cameron Passmore: No, I think that's good.

Ben Felix: As always thanks for listening.

Books From Today’s Episode:

Thinking in Bets — https://amzn.to/34bBhA7

How to Decide — https://amzn.to/2RXKW7n

Who Is Michael Ovitz? — https://amzn.to/3ctKOpH

The Master Switch — https://amzn.to/3h8CRXO

Links From Today’s Episode:

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Don Coletti — https://www.bankofcanada.ca/profile/donald-coletti/

'The Economy, Plain and Simple' — https://www.bankofcanada.ca/publications/the-economy-plain-and-simple/

'The BIG list of behavioral nudges' — https://blog.brinkercapital.com/the-big-list-of-behavioral-nudges/

'Will Ontario’s new law protect financial planning in name only or in substance too?' — https://www.theglobeandmail.com/investing/article-will-ontarios-new-law-protect-financial-planning-in-name-only-or-in/

'A Wealth Management Perspective on Factor Premia and the Value of Downside Protection' — https://www.researchgate.net/publication/316481345_A_Wealth_Management_Perspective_on_Factor_Premia_and_the_Value_of_Downside_Protection

'Fama-French Factors in Business Cycles’'— https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3082577

'Stock Market: Goodbye Passive Indexing, Hello Active Stock Picking' — https://www.forbes.com/sites/johntobey/2020/08/02/stock-market-goodbye-passive-indexing-hello-active-stock-picking/#6f656b6824de

'The Death of Diversification Has Been Greatly Exaggerated' — https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2998754