RR #129 - Five Factor Investing with ETFs

[Music] this is the rational reminder podcast a weekly reality check on sensible investing and financial decision making for canadians we are hosted by me benjamin felix and cameron passmore so this is our last us what we call our us episode of 2020 we're back next week with our year in review episode and then we're skipping the new year's eve week so you get two weeks to listen to the the best of 2020 show which i think would turn out to be a great great episode hopefully you'll enjoy it and then we're back on january 7th with a phenomenal special guest and we got guests lined up right through i think through april now we have amazing lineup coming up uh one thing i wanted to highlight for everyone who happens to be a peloton writer i set up a hashtag last week rational reminder on peloton which is actually really cool i didn't know how well these hashtags work but when you go on a a ride that other rational reminder people have been on before it shows up in the in the the race standings and and it's all live standings where they were at the point that you're out on that current ride so actually uh our mutual friend mike in london he was on there as a rational minor and a ride i did on the weekend and i had to ride pretty hard to make sure i beat him even though he did the ride a few days earlier so it's it's really cool so love to see uh more of our listeners on the uh the peloton hashtag at rational reminder i also want to give a shout out for some reviews some really nice reviews that people left online jason meyerson who was really stoked to find out they were ottawa based he lives here in town jg98765 and also strathyon day i know you always laugh at you so i presume these people know who they are i just want to give a shout out and say we appreciate them uh community board updates you wanted to share uh yeah we're closing in on a thousand users in the in the community which is pretty neat and as i've mentioned before the discussion that's going on in there is is great it's a lot of really intelligent discussion uh yeah it's uh i've been continually impressed with how that community is is developing so i think it's a it's a really good resource and a really good place for people to to share ideas and ask and ask questions about podcast episodes but also otherwise i mean i would say most of the discussion is not surrounding podcast episodes it's also where we would prefer people to discuss the podcast episodes just to keep it all in one place to make it easier for us to answer and participate but most of the discussion over there is is related to the podcast content but not necessarily about like it's not in the threads that we post for the podcast episode so lots of people are asking great questions and lots of people are providing great answers and nuanced discussion points and for those who are watching this on youtube you'll notice ben has his new common sense investing csi hoodie on which i think we're gonna offer for sale in the merch shop i don't know if there's enough demand if anyone's interested drop us a note if there's enough demand we'll go and get a uh some stock in the new csi hoodie and we still have free socks from that listener who was very kind to give us a deal on some custom rash reminder socks quickly i want to give you uh because i sometimes think you enjoy getting some tips for netflix have you seen this show we are the champions uh as usual i've seen it i haven't watched it i've seen that it exists haven't you oh so we started watching the weekend it's hilarious it's like eight eight or nine maybe 30 minute episodes and it's all these crazy competitions that go on around the world like this cheese rolling race in the farmlands of england there's this hot pepper eating contest in the southern us this weekend we watched one on on frog jumping like there's families that have been frog jumping for like six generations or sorry six decades three generations another one we watched was dog dancing they're unbelievably passionate people into these completely wacky competitions and they document a bunch of people competing another one was yo-yo there's this massive yo-yo competition that goes on every year and it's very well done it's short it's funny highly recommended we are the champions on netflix cool should we uh should we go to the episode people will know from the title because i'm sure i'll put it in there but in this episode we introduce finally the new model etf portfolios so hopefully uh hopefully they meet everyone's presumably high expectations anticipation is palpable so with that let's go at episode 129 welcome to episode 129 of the rational reminder podcast it sure is so this week we'll kick it off with a book that i just finished and it's a book that's been popping up everywhere in my twitter feed so i figured well maybe it's some sort of message to me that i should be reading it so it's called almanac of naval ravicant so naval is an indian american entrepreneur investor and he's actually the co-founder of angel list and he's invested in i think over 200 early-stage companies such as uber foursquare and twitter i did not know a lot about naval beforehand but this book is not a book about him and this is what's pretty cool it's actually a collection of his thoughts and philosophies that he's put out on twitter over the past decade and in uh podcast interviews but what is really cool to me is that it was actually assembled by a guy named eric jorgensen who's a product strategist at zarly anyways eric was so taken by all these things that naval has put out there that he decided to assemble it into something as he described something more permanent because he felt that the the thinking of naval was so good they deserved to be put into a durable long-term format or a book and on top of that eric went and put this out for free so you can actually download the pdf and it's all kinds of different formats i actually bought it on my kindle and but you can download it for free at navalmenac.com that's a n a n-a-v-a-l-m-a-n-a-c k dot com and it's all there for free and i i really really enjoyed it he it's an assembly so you can see uh eric posts all kinds of different tweets that he's given that he links in quotes from different podcasts so it answers all kinds of questions that were posted of all like how important is luck is there value in networking what is your definition of retirement what is happiness and a lot of it is around happiness and wealth it's also full of what i thought were interesting quotes and thoughts here's some examples for you so in any situation in life you always have three options you can change it you can accept it or you can leave it here's another one to make an original contribution you have to be irrationally obsessed with something here's a good one for us science is the study of the truth it actually changes the world um he defines the modern struggle as lone individuals summoning inhuman willpower fasting meditation and exercising up against armies of scientists and statisticians weaponizing abundant food screens and medicine into junk food clickbait news endless games and addictive drugs i i i can't say enough about it i actually got it for my kids for christmas so we'll see if james listens to this before it actually gets posted um before christmas uh but i i really enjoy i liked how it was laid out it's a very fast read it's an interesting read and you can kind of just pick it up at any point and just you know dive in so there's your book recommendation for the week cool in other news there's a tweet last week from nate garassy so this is more question to you uh just based on some of the feedback we've been getting on the community board so nate tarasi posted last week that table stakes for major brokerage firms within the next few years will be fractional share ownership direct indexing cryptocurrency custody of cryptocurrency custody cryptocurrency easy custody of cryptocurrency exactly so i just thought it's a neat um link going back to our interview with with josh and brian you know i think three weeks ago or so just about the drive towards kind of personal biases and personal desires and portfolio versus the evidence or as josh called it the orthodoxy i thought it was neat how nate drastic is now saying that exactly what they were arguing that the ability to do kind of what feels right for you is going to be easier in the brokerage world i think if we define table stakes is what you need to be able to sell more stuff and increase margins than for sure fractional shares i think are important regardless direct indexing though that's i mean from a practical perspective from the end investors perspective i don't think it's particularly useful especially after costs because we know it's going to cost a lot more to have a direct index portfolio than it is to have a cap weighted etf portfolio and that's before you start factoring in you know factor tilts into your direct index portfolio right but if you want to make money as a brokerage then yeah of course you need to have that yeah cryptocustody same same kind of thing like it's that stuff's not going away no another data point i wouldn't mind your feedback on was a the percentage of s p 500 stocks with a dividend yield greater than the 10-year us treasury yield currently it's 63 percent which is the highest by far in this table it goes back to 1990 the average ratio is just under 20 percent any thoughts on that uh thoughts from what perspective what do you think is driving i think i said the the the low level of the 10-year treasury do you think it's i guess we don't know what's really going on behind the scenes is it the fact that a lot of dividend paying companies might be in the smaller mid cap range which have not had the kind of rally i don't know i mean prices are this is yield right yeah yeah so prices are high stock prices are high yields are low um us companies are paying and when they're comparing this to 1990 us u.s companies have been paying less and less in dividends so i mean all those things working together yep and the last story for you um article in bloomberg.com called crashing a 5.2 trillion dollar party debut etf issuers hit a record so there's been 14 new issues of etfs this year this is not etfs this is companies issuing etfs was 10 last year in 2019 so we have 14 so far this year and make the argument the article that it's based on new rules for active funds that made the launches easier is one of the reasons behind this so it also referenced the most dramatic new entry being dimensional fund advisors which recently converted six of its tax-managed mutual funds into etfs and just by doing that it launched them into 11th place overall in the etf landscape with something in the low 20 billion dollar range of etf assets now by comparison the largest participant or the largest company in the etf market space is blackrock at 1.8 trillion dollars vanguard at 1.1 trillion and state street comes in at number three at 700 billion etfs have taken at a record 90 billion dollars in november which they say is an unheard of 5 billion a day pace and year-to-date flows are now up to 427 billion dollars which is about 35 billion away from an annual record so it's just been huge in the etf market space unreal now you want to talk about uh tony shea the zappos founder who passed away november 27th of complications from smoke inhalation from a home fire a week before that ah the only thing that jumped out to me is as interesting in that story was the fact that he died intestate he died without a without a will and i i just kind of heard this in passing i think they uh one of the podcasts i listened to i can't remember which one they aired a uh uh old episode where they'd had him on might have been freakonomics or planet money or something um so i kind of i just took a quick read of the story and and that jumped out at me is pretty interesting i mean this this ultra wealthy guy who's been very successful in in business and he passes away unexpectedly without a without a will i mean exactly in in most cases or i don't know if that's true in a lot of cases people die without expecting to die um i don't have time to get everything in order so it just speaks to the importance of getting all that stuff taken care of yeah he had a net worth over 840 million u.s dollars it's amazing to think about that with that level of wealth you could still not have all the proper planning in uh in place and being in business you think of all the lawyers that would have been around his situation for years and it was never done maybe he didn't want to do it like who knows what the actual full backstory is but i just i i found it very interesting that that that's how it happened for him so the family has asked the judge to name his father and brother as special administrators of the estate but the bottom line is that stuff happens and you should always have a will in place so shall we jump into the feature topic this week yeah let's do it so this week we're um we're gonna combine not not because the content spans both uh planning and portfolio management just because we have a bigger topic for the portfolio management piece so we're going to skip i guess that's a better way to say we're not going to combine them we're just going to skip the financial planning topic but i think people will appreciate the portfolio topic that we have lined up so it's it's really a it's about the new model portfolios which people will be excited to to hear um but i i also thought it would be good to run through the main topic talking points associated with the the paper that we're going to put out at the same time as the model portfolio so kind of just the thinking behind the thinking behind all of it um which also ends up serving as a pretty good refresher of all of the main concepts behind index investing and stuff like that well that's the best part about it to me is that it's all in one spot all the rationale the papers the story behind the the reasons for this portfolio construction yeah so index investing which is kind of table stakes when you enter this world of evidence based investing index funds are i think pretty well understood and they are they are sensible as investments if markets are efficient so i think people hear that term i don't know if everybody knows exactly what it uh what it means as as eugene fama stated it so i'm going to read a quote from the paper where he introduced the concept of market efficiency so famous said this is in 1970. in general terms the ideal is and keep in mind he said this is the ideal he's not saying markets are efficient which fam has never actually argued so back to the quote in general terms the ideal is a market in which prices provide accurate signals for resource allocation that is a market in which firms can make production investment decisions and investors can choose among securities that represent ownership of firms activities under the assumption that security prices at any time fully reflect all available information a market in which prices always fully reflect available information is called efficient now fom also says that real markets can't be can't be perfectly efficient in the theoretical sense they can only approach perfect efficiency but this this hypothesis and this model became as many people know the framework for much of the empirical research that's been done in finance since then now from the investors perspective and fama said this explicitly in the quote that we just read uh if the market is efficient then prices stock prices bond prices whatever you want security prices they contain information about the expected returns of a security at a point in time and then the other thing that follows from that is that prices will change based on new information which cannot be predicted obviously just by nature of being new information so given those criteria or constraints whatever you want to call them in an efficient market the only way to earn extra returns is by taking more risk because security prices move randomly you can't outsmart the market all the all the kind of main talking points that people might be familiar with now if you can get access returns without taking on extra risk that's no one and we'll talk more about this soon that's known as alpha so a traditional active manager their their goal is to combine picking the right stocks at the right time and timing the market as a whole in an effort to generate risk adjusted excess risk adjusted returns known as as alpha now we also know that empirically active management is not done so well um the spiva reports are all often cited as evidence of that uh they're not my favorite source just because of the way that they construct the data um did you know they use series a funds at least for the canadian report yeah we talked about that didn't we yeah i think so so you've got an extra one percent commission built into the fund returns and you're comparing it to an index with no fees so it's not really a fair comparison well did you not reach out to them to mention that i did and they said that they would think about addressing it in a future report i never followed up so i don't know how if they did anything with that but i don't think it would change the distribution too too much like you'd still have most active funds under performing but anyway fortunately there are a couple of papers that were the journal of finance that addressed the same topic like the failure of active fundament fund management so those carhartt 1997 fama french 2010 uh documented the the failure of active fund managers to consistently beat the market which supports the idea that markets are efficient because if security prices move randomly no manager should be able to consistently beat the market now there are some managers like jim simons who we've talked about in and buffett for a period of time although he's trailed the market for about 20 years now but there are investors who are outliers and you can argue that's evidence of market inefficiency but it's still the same question how do you identify them ahead of their own performance correct like what signals would you have used and can they maintain it and as we've said with jim simons for example they've capped that fund forever at ten billion dollars of assets and every year they flush out all the gains to keep it at ten billion dollars and you can't buy into it so yeah you can't find it anyway there's no point talking about what's clear fast as said last year yeah right aqr will take their money take your money but jim simons won't uh so at this point where we've talked through so far markets are efficient uh theoretically and and the empirical failure of active management is is evidence supporting that therefore index funds make sense nice and easy we could stop here and many people do which is perfectly fine and there's been a lot of really interesting discussion in the rational reminder community discussion page about about that exact question like should you actually factor tilt your portfolio should you try and get exposure to the other risks in the market now i'm getting ahead of myself so since the introduction of the efficient market hypothesis the the field the study of asset pricing has become this this massive uh this this massive field of study and there have been many systematic risks identified that seem to affect the way the market prices assets so we said earlier that that the the market should reflect the riskiness of an asset the market price should have should reflect the riskiness of an asset but we didn't specify what risk specifically it's reflecting now that that exact question has not necessarily been answered definitively but there are some pretty strong theories and models showing which types of risk the market does include in prices now why is this relevant to an investor it's relevant because the market risk factor which is what you get by owning a market capitalization weighted index fund that's only one of multiple risks that currently there are really strong theories and really strong supporting evidence suggesting that there are multiple sources of of expected returns now expected returns is another loaded word which we're going to talk more about in a in a second um but the to keep with where we've gotten so far there are other types of risk that the market systematically includes in stock prices now having exposure just one of those so if you just have exposure to the market risk that's delivering one source of expected returns it's giving you one risk keeping in mind in this context taking these risks these systematic risks is actually a good thing it's not a scary risk it's a risk that you're taking exactly with the expectation of a positive long-term uh return but you can access more than just one risk and this becomes quite interesting from the perspective of portfolio management for for a lot of different reasons which we're going to talk about a lot of them there was a paper in the journal portfolio management a while ago and i don't remember the i think it's called the death of diversification has been greatly exaggerated and they argued in that paper that well correlations across geographic regions in the stock market have increased over time as the world's become more globalized and all that kind of stuff the independent risks the independent systematic risks that we're going to talk more about they have not increased in correlation so that papers that i'm talking about they actually argue that factor diversification so getting exposure to more than just one risk is more important at this point than geographic diversification which is a pretty interesting argument uh so what we're going to talk about and what we included in the model portfolios that were that we're addressing here are five systematic risk factors uh that are included in the fom-a-friend factor model so this is eugene fama and ken french pretty pretty big deals in the empirical and theoretical finance space and they have an asset pricing model that includes five risk factors the market being one of them but also for four others so we're going to talk through what those are now i mentioned expected returns being a loaded word and it but it's an important concept so when you when you buy a stock this is theory when you buy a stock theoretically what you're buying is a right to a company's future profits now this part can get confusing for a lot of people because where'd the returns come from um expected returns the returns that you expect to receive come from how much of a discount you apply to those expected future profits for a riskier asset you'd apply a bigger discount you're paying less for the same amount of future profits if those future profits are riskier now that discount that discount rate the price you're paying is your expected return right so a firm can be really profitable and not produce very good returns if you pay a lot for those profits and we see that with growth stocks and we've talked about that quite extensively in past podcast episodes and on the on the common sense invest in youtube channel so it's really what you pay for the for the asset that dictates your uh expected return and that that concept that discount rate concept is what ties asset prices to expected returns now i mentioned asset pricing models i kind of just made a reference to the fact that we're talking about one of them that pham and french have have come up with and all asset asset pricing models are doing is trying to figure out uh trying to figure out which risks are relevant to the pricing of stocks so in this case we're we're using one and there's no there's no single correct model i think it starts with deciding what framework you want to use to think about markets and from that we'll stem the type of model that you want to apply to to looking at um portfolio returns and stock returns uh we're using the one that fom and french have have developed which which lines up with the way that we tend to think about markets in general but it is kind of crazy to think about too that you could just say well no i believe markets work this way and therefore you would use a completely different factor model which would completely change your portfolio construction and there's no way to prove which model is the right one and that's actually one of the things fun has written about in his past papers this idea of the uh the joint hypothesis problem uh which basically says that that a a test of market efficiency using an asset pricing model is jointly a test of market efficiency and a test of the asset pricing model now that's tricky because you can prove as we're going to talk about in a moment you can prove that the market is inefficient using an asset pricing model you can show based on the risks in my asset pricing model the market is not pricing securities properly boom market inefficiency but someone else can say well no your model is wrong and nobody can prove nobody can prove what's right so it's called the joint hypothesis problem and this is a real a real issue so because of that you can't prove market efficiency with an asset pricing model no matter how good the the model is um but it does start to get pretty interesting when a model like the farm front five factor model explains the vast majority of return differences between two portfolios like it still can't be proof of market efficiency but it starts to get to a point where it's like there's not a whole lot of return differences that can be that are left unexplained anyway so the the original the original risk factor and this is a i guess a bit of a quick history lesson on on asset pricing models but the very first risk factor was the market the the equity risk premium um market beta as it's as it's known and the first time that expected returns were related to risk to market risk was through the capital asset pricing model so this is classic classic finance sort of 101 capital asset pricing model now uh a cap weighted index fund total market index fund should have a market bid of one always and if we took a portfolio that was fifty percent market and fifty percent cash it should have a beta of point five um if if two portfolios and this is my comment a minute ago about comparing explaining differences and returns if two portfolios have the same market beta but have differences in returns through a cap m lens that difference in returns might be portfolio manager skill or it might be related to some as yet unidentified factor correct yeah hadn't been identified yet and that ties back to the joint hypothesis uh problem now a portfolio that we mentioned this earlier with alpha a portfolio that delivers higher returns so in that those two portfolios that we were comparing a second ago if one of them has higher returns given its market beta that's great for the investor that's an excess risk adjusted return so you're getting extra returns without taking on additional risk now the cap m so that was in the 60 early 60s i think when cap m came out uh by 1972 fisher black had come out in a pit with a paper uh showing some some flaws and then rolf bonds in 1981 came up with uh his paper on the relationship between return and market value of common stock so this is the first time that someone published data showing that small stocks from a cap m perspective had persistent alpha these stocks were beating the market without taking on extra risk as measured by the risk of the market as a whole and then in 1985 there was another paper that documented the same thing for value stocks and there the title of their paper was actually persuasive evidence of market and efficiency it was pretty interesting to look at how they wanted to title their paper but then fama and french speaking to the joint hypothesis problem they came out in 1992 with a paper that said okay so we've got small stocks with these persistent alphas we've got value stocks with these persistent alphas maybe we just need to account for the risk of those types of stocks in our asset pricing model so they came out with their their now fairly famous three factor model where they said we we think asset prices reflect the risk of the market but also the risk of company size where small stocks are riskier than big stocks and also the risk of relative price where cheap stocks are riskier than uh more expensive stocks value stocks are riskier than gross stocks and when they put those independent risks into a model together a lot of those anomalies went away which i guess is obviously built they built a model to make the anomalies go away um but the interesting part from a from a portfolio evaluation perspective is that the ability of the model went from about 65 or so with the cap m um in terms of ability of spl explaining differences and returns to about 90 with the three-factor model so all of a sudden the explanatory power of the model becomes extremely strong one of one of the really interesting things to think about with a three factor model is that there was a sort of loose concept that it was related to risk but there was no real model to say why that's true at the time again kind of makes sense small stocks would be riskier yeah it kind of makes sense value stocks are risky but there was no uh sort of all-encompassing evaluation framework to say how those things related or should relate um to each other so then later research 2013 2004 and 2013 people came out with papers showing anomalies in the three factor model so now we've gone from the the small in value being anomalies for cap m and the three factor model solving it and then investment so companies that grow their assets aggressively tended to have lower returns than companies that grew them more conservatively and then companies with more robust profitability tended to outperform companies with uh weaker profitability and those alphas in the three factor model were persistent so again we have this asset pricing problem and fom in french more recently in 2015 i think came out with a new paper where they introduced their five factor as a pricing model the thing that i love about the five factor model if you can love a model is that it's it's rooted in valuation theory so i mentioned with the three factor model it was more of an empirical model where we had these empirical observations when you incorporate them into an asset pricing model it makes a lot of anomalies go away cool but with a five factor model they took the the theoretical valuation framework of the uh dividend uh dividend discount model yep where a company's value is theoretically the present value of its expected future dividends discounted at whatever discount rate they took that concept applied the theory of dividend irrelevance from miller madigani and when you transform the dividend discount model to include dividend irrelevance and we talked about this on a recent uh a recent episode but basically if dividends are irrelevant the dividend discount model turns into profitability minus investment in place of dividends otherwise the equation stays stays the same but that ties together all of the elements that go into the five factor model so the cool thing about that is now we have this empirical evidence that there these anomalies exist so you've got low price stocks you've got more profitable stocks and you've got stocks that grow their assets aggressively those are all independently uh discovered empirical observations but then you've got this unifying theory that ties them all together to sort of justify their use together in a in a model which i think is is pretty pretty cool and that's one of the tricky things with multi-factor asset pricing models is that nobody nobody tells you nobody has the answer for which factors you should include in the model and i guess i alluded to that earlier when we're talking about you know how do you pick a model well that's yeah the cool thing about this one is that it starts with the sort of rational evaluation framework and then plugs in or spits out i guess the factors that would make sense to include based on that now this this model has a few predictions which we've kind of already talked about but the model predicts and keeping in mind the empirical data are one thing but the model predicts that the same thing that we observe empirically the model predicts that cheaper stocks will perform more expensive stocks again we see that empirically more profitable stocks will perform less profitable stocks and then stocks that invest conservatively will beat stocks that invest aggressively uh the next challenge was measuring those things so we we and this is this came before the five factor model i should have said it first i guess um but measuring profitability investment because it's not current profitability you have to measure it's future profitability because we're discounting future profits nobody really knew how to measure that but novi marks in 2012 and uh there's another paper in 2013 that showed how those things could be measured with reasonable reliability to actually be used in a in an asset pricing model so all that culminates in in the five-factor asset pricing model that we're now talking about how do you build a portfolio based on on that we know these five systematic risks are important to asset pricing therefore to expected returns so what can we do as investors to uh to take advantage of that which is the the question at hand i guess now company size is a really interesting one in all of these models and you may notice that it didn't show up in the well i guess we didn't show the actual equation but in the dividend discount model there's no uh there's no variable for company size so it doesn't directly show up in that framework which is interesting because fom and french still included it in their in their five factor as a pricing model um and we'll talk more about this as we go through but small caps on their own and actually people listen to podcasts notice already because we've talked about it a bunch of times small caps on their own have not had a statistically significant premium which is pretty fascinating and even you can even push that further where bonds in 1981 the data set that he used to to come up with the original size premium if you go back and run his analysis again now because the crisp database that he used is always getting better they're always improving the data series and tyler shumway i don't remember what year he wrote the paper but he he did a paper correcting for the delisting bias in the crisp database and i can't remember the exact details but basically it made small caps look worse and so if you go and rerun the bonds research with the shumway corrections which are now included in the crisp data you no longer get a statistically significant premium so it's kind of like it's never really existed on its own but that on its own is important um so as we've talked on the podcast a few times uh all of the other factors are significantly stronger both economically and statistically in small caps uh there's a paper that we talked about in a recent episode by blitz and hanauer i think his journal of portfolio management the paper was in and they showed they showed this by comparing [Music] by running regressions on the academic factor portfolios which consist of 50 small caps and 50 large caps running regressions on those portfolios with a market capitalization weighted factor portfolio and they found statistically significant alphas which is another way of showing that the the the risk factors are much stronger in in small caps and this is a theme that comes up a few times in these discussions if i'm a french they address it in their paper too they mentioned that even though size doesn't show up in the valuation framework empirically it's so strong that it has to be included in in the model now the other big one is momentum that doesn't show up in in the theoretical evaluation framework so again we know empirically that stocks that have been doing well tend to continue doing well for a bit uh that was from jegadesh and titman in 1993 and that's that has continued to be true empirically um what do you do with that is an important question if you buy like in our old model portfolios we had iusv and ijs which are just value funds targeting value now what's the problem with targeting value from the perspective of momentum the problem is when a stock crosses the threshold and goes from being not a value stock to being a value stock it's going to have negative price momentum and momentum is a well-documented empirical factor so that means you're you're betting against momentum by buying stocks when they become value stocks that's a problem from an expected returns perspective or maybe not from an expected returns perspective i don't know what you'd call that it's the problem from an empirical finance perspective i guess you don't want to be short momentum um so the products that we're talking about in our new model portfolios they actually account for that by uh delaying trades based on momentum uh delaying or accelerating i guess which i think is important so it's almost a it's almost a six six factor model i guess if we're including that in a way okay so why do we care about all this in the first place the premiums have been pretty big which makes them kind of hard to to ignore and there's lots of extra thinking and hassle that goes into this so it's important to know that what what the premiums are so we're gonna we're gonna go through that now we're talking about factor premiums i think one of the other and little little known facts that's important to consider is that the academic long long short portfolios and we mentioned this briefly with the blitz and hanauer research the academic factor portfolios are based on 50 percent small cap 50 weight to small caps and 50 weight to large caps so the value premium as an example is um the cheap the cheapest small caps plus the cheapest large caps minus the most expensive small caps plus the most expensive large caps now that's that's the best way to construct the factor portfolios for the purpose of asset pricing so to use them in a regression model to see what's driving differences and returns in portfolios that's the best way to construct the factors but from a you know looking at looking at how stuff is done and saying is it worthwhile to pursue this that's a little bit less relevant just because you're looking at a portfolio that's overweight significantly overweight small cap stocks which not all portfolios are for example the model portfolio we're talking about here today has about 30 percent in small caps the academic factor portfolios have about 50 percent in small caps and the market has about 10 so you're talking about the value premium like market wide value premium that's 10 in small caps the academic value premium is 50 in small caps and we've talked about how factor of returns are stronger in small caps so that overweighting arguably makes the factor premiums look better than they would actually be in a in a portfolio that's not heavily overweight small caps sticking with me here i'm with you keep going i don't want to break up your train of thought uh okay so for for the us premiums i document in in the paper um the value weighted and the academic premiums because ken french has data on both and then for international and emerging markets i just did the academic factor returns because i didn't have the the capitalization weighted but if we just go through quickly uh so for the valuated portfolio for size we have 1.58 premium so small stocks beat large stocks this is the 30 of the cheapest stocks minus the 30 um or smaller sorry minus the 30 biggest stocks from 1963 to june 2020 uh the small portfolio beat the large portfolio by 1.58 percent per year on average which is a lot just to be clear that's the value weighted portfolio not the evaluated correct value weighted value weighted yes uh then for for value so for the the cheap stocks minus the expensive stocks in the value weighted portfolio it beat uh value beat growth by one point nine nine percent and then for profitability it was a two point five nine percent premium and for investment one point nine two now in terms of statistical significance small the small cap premium was not statistically significant over that time period and interestingly neither was the value premium from a from a value-weighted portfolio perspective now if we go to the academic premiums again for the u.s so small minus big but the value weighted was 1.58 premium if we go to the academic factor so weighted 50 small 50 large that premium increases to 2.04 interesting uh and then for value it went from 1.99 to 2.68 profitability it increases from 2.59 to 2.8 and for investment the premium increases from 1.92 to 2.93 by switching to the to the academic factors now i mentioned that our model portfolio has about 30 in small caps so it's not like one of these is right and one of them is wrong i think in our case with a 30 weight in small caps it's going to be somewhere in between like what is the premium you expect right um yeah so if we look at the developed xus i'm just going to rip through these a little more quickly so uh small stocks be bits big stocks by 0.81 percent value b growth by 3.01 high profitability below profitability by 4.30 percent and conservative investment beat aggressive investment by 1.34 and for emerging markets it's similar i don't think we need to keep going through it but the main takeaway here the main point is that in all of these major markets that we're talking about i mean it's basically the whole the whole global market the factor premiums have been economically large for the most part they've been statistically significant so i mean i guess why would you ignore them in in portfolio construction i don't know that's exactly what marlena lee told us when she was on last january is why would you ignore information that's out there to be had yeah so i i took a couple of examples just like how do we actually apply this to portfolios and it's important to point out too that these regression models in the in the factor premiums um dimensional for example is not actually using five-factor regression models to build portfolios they obviously know about that um but it's not one of the things that they're actually using practically to build portfolios and and we didn't either we didn't rely explicitly on that it was one of the few criteria that we looked at when we were building this this model portfolio um and it's also worth noting that the intention behind this model portfolio is to look somewhat similar to the portfolios that we use for our clients we use dimensional mutual funds which aren't available to the public except for through firms like ours so this model portfolio is designed to look somewhat similar to that in terms of regression coefficients but also in terms of characteristics which you can argue are more more important than regression um [Music] analysis so one of the things that i want to look at is let's let's take an index that we know has factor loading so i took the dimensional u.s core equity index and compared its returns to just a us total market index so from 1975 to june 2020 the dimensional u.s core index returned 13.52 with a standard deviation of 15.43 whereas the us market delivered 12.12 with a standard deviation of 15.41 so we see right there from a standard deviation perspective we're getting higher returns with any extra risk pretty cool now if you're an active manager before multi-factor asset pricing models exist you can show this and say you know look i'm generating i'm generating alpha but as as we would expect with five factor regression we can see that all of those return all of that excess return is being explained by excess exposure compared to the market to small stocks value stocks highly profitable stocks and to a lesser extent in this case um stocks that invest conservatively that's the key takeaway there's also a reason right so we've just taken this you know this hypothetical active manager that could charge 2 and 20 or whatever and we've now said well actually you can do that systematically with with an index which is the same kind of thing that the um aqr paper that showed that buffett's alpha can be explained by uh by systematic factors they took a similar approach and said well here's a set of systematic factors that we know drive stock returns if you account for those in warren buffett's historical success his alpha actually becomes statistically insignificant so it's the exact same kind of thing which i think is pretty pretty fascinating now i also looked at dividend growth investing because that's another case where uh people often believe that there's a superiority uh but the the question that we can look at with the asset pricing model is are are dividends special in the sense that they're generating alpha or do they just have the dividend stocks just have extra exposure to the the common risks that we're talking about so for this one i looked at vig the vanguard dividend appreciation etf from june 2006 to june 2020 and it had almost the identical return to the market and actually i looked at this in april people know i've been working on this paper for a while and between april and june uh this port the vig went from beating the us market over the full time period to trailing it by three basis points annualized oh no way just because dividend stocks got smoked in the in the downturn and have recovered more slowly but even still vig had very similar returns off by three basis points with substantially lower standard deviation so again we have this question of our dividend stocks superior well if we plug it into the asset pricing model the farmer friend five factor model the model explains 94.8 percent of the monthly variation in returns so basically all of it and the fund does have excess exposure to uh more profitable companies and companies that invest conservatively and i mentioned earlier the the relationship between the dividend growth the dividend discount model and the five factor model and just how they're related theoretically and we kind of see that here where if a stock if if a group of stocks have high dividends that are growing we would probably expect them to be highly profitable and we would probably expect them to be investing conservatively yeah and this is exactly what we see what we see with this uh with this analysis so another way of saying all of that is that the excess risk adjusted returns of dividing growth stocks over this time period are pretty well fully explained by their five factor risk exposures um these standard deviations a lot lower than expected [Music] maybe the 12.5 versus the 14.7 is there anything in that information it should all be captured by the all the variation in returns is being captured by the uh by the factors by the model here so i don't think so i mean the the annualized alpha on this fund is statistically insignificant so i guess we can just say it's zero economically it was negative zero point four eight percent annualized but the t stats only point five five so it's really statistically it's it's zero um so yeah i i don't i don't think so i think it's the model's doing quite a good job of explaining explaining the returns here which for a dividend investor is problematic this is a bit of a digression but if you're if you're a dividend investor enjoying the better risk adjusted returns of dividend stocks if you're really just getting a repackaging of systematic risk factors that exist in stocks that don't pay dividends or that don't grow their dividends or whatever stocks that don't meet the criteria of a dividend investor you could be missing out on diversification which can be detrimental but the bigger one i think is if we look at these companies specifically in vig this etf also has negative exposure to the size premium so it's it's larger than the market and it has negative exposure to the value premium now because this thing's targeting dividends those those risk exposures could change over time if the characteristics of dividend stocks as a whole change over time but at a point in time at this point in time or at least from 2006 until until now you had on average negative exposure to value and to size so if someone looks at that and says well i like dividend stocks you can also look at it and say well you're just getting a sub-optimal mix of for a potentially sub-optimal mix of factors you could address that by targeting the factors directly instead of bingo right uh okay so all that's fine we've talked about the full period uh premiums which is which is important i think the persistence is also important we've looked at these long periods where factors have been positive over the full time period but if you're living through being a factor investor as we're doing now with with the value tilt you you may have periods where the factor underperforms so one of the other things i want to look at in the paper is how often does that happen uh i'll go through this fairly quickly but over over 10 year periods some of these that are fascinating over 10-year periods uh the u.s market premium so that's the u.s market minus one month u.s treasury bills has been positive 80 percent of the time since 63. since 1963 so 57 years and then small small stocks have beaten big stocks 71.5 percent of the time these are rolling 10 years right rolling 10-year periods yet so overlapping 10-year periods with a one-month step value stocks have beaten gross stocks 86 percent of the time which is kind of staggering so that's in in more of the 10-year periods value stocks beat gross stocks than the market beat t-bills and everyone it's a given to invest in the market for most people right so you're basically saying if you believe in the market you should believe in these other factors also from this perspective of rolling 10-year periods yes they've been more reliable than the market exactly statistically it's a bit more debatable like statistically the market premium has been more reliable than value for example actually it's been statistically more reliable than any of the other premiums but over rolling 10-year periods it's a little bit a little bit different so it's more if you're thinking about could you stick with the factor would you stick with a factor i think that's where these data are really interesting um for the profitability premium 85.6 percent of the time and for the investment premium 98 of the time which is kind of staggering over 20 years all premiums in this data from 1963 to 2020. all premiums except for small cap were positive 100 of the time over 20-year periods it's not that many non-overlapping periods so i don't know how much insight you can draw from that data but still kind of interesting um for developed international excluding u.s 10-year premiums i don't have 20-year just because it's would only be one non-overlapping sample uh 10-year premiums market 87.5 percent of the time beat t-bills um small caps 86 percent of the time value 90.87 profitability 100 of the time and uh conservative minus aggressive investment 92 percent of the time i'm gonna skip over emerging markets sorry emerging markets you can you can read it in the paper though if you're if you're listening similar it's similar across the board yeah now the other thing that came out of uh doing this paper that was really interesting was looking at the the how the factors behave relative to each other over time somebody did a post in the raster minor community about this recently where they posted some really interesting charts that they generated with some some code uh and those were kind of neat to look at i had a chart i actually still have a chart in the paper just showing the 10-year rolling premiums all together on a single chart and you can see how they behave differently but the other thing that raymond our our director of research suggested that i had when he was reading the paper was the correlation matrix matrices for all the different factors and i'm not going to try and explain them because it's just a bunch of numbers but it's in the paper and it's it's actually unbelievable it's you know low for the most part or negative actually most of the time negative uh correlation across the factors like if we just pick one as a pick one as an example um you take well take the market that's a that's an easy one so the market correlation coefficients for u.s stocks between 1963 and june 2020. the market has been has had a correlation of 0.29 with small caps or with an s and b premium sorry negative 0.22 with the value premium negative 0.21 with the profitability premium and negative 0.38 with the investment premium and plain english that means it means the premiums perform or show up at different times than uh then market market returns as a whole so again we're talking about why would you want to do this additional expected returns are a major reason but this this low to negative correlation of the other alternative i guess whatever you want to call them the other risk premiums with the market risk premium from a diversification perspective i think becomes pretty pretty compelling and hard to ignore and we're going to talk about a couple sort of anecdotal examples of that in a second and then i have that data in here for developed and emerging markets as well similar again but you can take a look at that in the in the paper so it's a reasonable to expect a smoother ride to a higher return which is exactly what dimensional always says they say that that this increases the reliability of your outcome and we're going to speak to a couple of examples so um [Music] we talked about the rolling 10-year periods and we talked with the correlation so we've kind of already covered this conceptually but i i i it's really just interesting to show a couple of these extreme examples i guess [Music] so there's the last decade in the us which a lot of people know about so for the 10 years from the 10 years ending july 2009 now over that full period uh the u.s market index the crisp 110 index lost an annualized 0.91 0.19 percent pretty bad um trailed t-bills which returned 2.95 over the period so your risk your risk premium was was brutal but over that same time period uh u.s small value stocks measured by the pharma french u.s value index returned 9.51 pretty pretty significant difference there yep and the phantom french u.s value research index returned 3.78 not not as exciting but still a lot better than losing 0.19 and then the u.s high profitability research index returned 2.09 so you can see right there where that that's a period where the market did quite poorly over a 10-year period over a fairly long period of time [Music] and small cap being the biggest outperform there delivered a substantial premium i also looked at this in aggregate and i guess this shows up in the correlation data too but this is another way to look at it so i looked at the 111 10-year periods ending between june 19th july 1973 and june 2020 where the market premium was negative so 111 10-year periods where the u.s market had a negative premium yep over those same periods uh small minus big high minus low value uh and profitability uh investment conservative minus aggressive we're all positive which is kind of those all 111 instances of the market premium being negative smb hml and cma were all positive wow rmw was negative and 53 of the 100 profitability was negative in 53 of the 111 periods pretty crazy right yeah so again we see that diversification angle for why an investor may want to uh may want to do this so here's another one the single worst time to retire in u.s stock market history the available history was december 1968 from then until january 1984. the u.s market actually gained 7.26 percent per year but trailed t bills and barely kept pace with inflation so you had about a four basis point annualized return from december 1968 until january 1984 in in real terms so when you run like the four percent rule analysis that's always the time period where it where it breaks now over that same time period small value returned 15.8 percent annualized and this is an smb that's not small minus big that is the pharma fringe u.s small value index right the long only index not small minus big and the value index returned 13.46 so again we see an instance and i'm totally cherry-picking data but it lines up with the with a broader sample so i don't feel bad about it um and then the last one that i'll talk about is japan so july 1990 to december 2019 which is a staggeringly long time for a negative or a non-existent um risk premium for a great one it's it's it's crazy um so the the fama french japan market index returned 2.36 percent annualized over that full period uh which trailed us treasury bills one month u.s driver bills which returned 2.63 percent it's for 29 years it's crazy to think about it really is um now over that same time period the japan high profitability index uh was actually not a whole lot better 2.27 percent actually a little worse than the than the market but the dimensional japan small cap value index and the pharma french japan value index delivered annualized returns to 5.43 and 7.96 percent respectively so again uh we see another instance of these indexes representing exposure to the non-market factors delivering meaningful outperformance at times when the market didn't do so well so the benefit of factor diversification 100 it just speaks to the reliability piece where yes you can have long times where stocks don't pay off or the stock market doesn't pay off but there can still be other risk premiums over those periods of time that do pay off so what do we do with all this information uh i can hear the listeners asking that now we uh we use dimensionals products as we've mentioned uh and there as far as we can tell um from the ongoing pretty extensive due diligence that we that we do they're they're doing a great job i guess is the easiest way to say it um the challenge the challenge practically for people who are not our clients is that their products aren't available you can't just go and buy them although that's changing a bit they've released some etfs not not quite a full suite of products like you couldn't recreate our client portfolios with dimensionals etfs yet it seems sensible they would get there soon but i i have no idea if they will last time we made a model portfolio we used the we used the three factor model as the basis for the for the portfolio so we basically just ignored not not completely we we somewhat ignored um profitability and investment in the construction we didn't use products that targeted those factors directly is probably the best way to say it ijs for example they do have a financial viability screen which interestingly results in a profitability exposure but we didn't pick products that explicitly targeted all five factors because at the time they didn't exist at least not in a format that we thought was sensible from the perspective of costs and diversification but now avantus so dimensions launch etfs avantus is another company from some people that actually left dimensional which is also launched etfs and avantus has i mean the very very similar approach to dimensional um like you'd be splitting hairs to explain the the differences in execution although they might they may not agree i'm sure they'd both argue that the differences are larger maybe they wouldn't i don't know but for the purposes of for practical purposes they're very very close in terms of their risk the risks that they're delivering in their in their products now the nice thing about what avantas has launched is that they have a couple of small value etfs now dimensional has only launched core etfs which are like a lightly tilted total market exposure with ivantas they have a couple of products that give you pretty targeted pretty extreme exposure to the smallest and cheapest companies that exist in the market so that's valuable to us because one of the things a couple of things that we're worried about in this portfolio construction process are withholding taxes which can be problematic for canadian investors when you're using u.s listed etfs costs currency conversion costs u.s estate tax all these additional complications that start to be introduced when you're using us listed etfs so because they have these more extreme small cap value tilted portfolios uh we felt like it gave us an opportunity to use a mix of i guess similar to what we did last time a mix of canadian list etfs where you don't have to worry about currency conversion uh or the extra layer for holding tax um but you can still with a relatively small percentage of the portfolio you can still target a meaningful amount of factor exposure now given the choice we would prefer and i want to be clear about this we would prefer to have a more diversified factor portfolio like dimensional with dimensionals portfolios you're tilting toward the factors across the full spectrum of market capitalizations so you've got your large value your mid cap value your small value whereas with this model that we're introducing here you're getting all of your factor exposure in small caps it's an interesting trade-off because we know the premiums are stronger in small caps which kind of allows us to do this but at the same time it reduces the diversification that you're using to capture the premiums but overall we we thought as people know we've been working on this for a while we thought a lot about the different tradeoffs involved and this is this is what we decided makes makes the most sense uh at least for now so the the etfs that we're using for the factor exposure are um the advantage us small cap value etf and the uh avantus international small cap value etf so we're getting small cap value exposure in u.s and international markets excluding emerging markets there aren't a lot of great etfs that really target small value avantus does have a product but it's kind of like the dimensional products more of a lightly lightly tilted total market etf um and in the paper there's a bunch of analysis of with regression and historical characteristics and stuff like that of return characteristics of those etfs i won't dive into it now you can read the paper if you want to see more about that uh so the actual model we uh it ended up being six etfs for the etf for the equity portion so if you want fixed income it'll be another etf or two depending on how you do that but not not too complicated i mean the same as the previous one six six etfs um so here it is everybody ready so we did uh 30 in xic so you've still got a home bias which we think makes sense and we've talked about that pretty extensively on the podcast in the past 30 vun now this is an important change actually in our previous model portfolio we had xuu uh one of the things that's come up with pwl's research team recently is that the way that blackrock has decided or ishares has decided to execute on xuu is by using three underlying etfs so it owns three us us listed etfs of small cap mid cap and large cap stocks that sounds fine right if you can if you can pull it off if you can pull it off efficiently but it's actually had pretty significant tracking error relative to its benchmark so this is something that was flagged this year by our by our research team and yeah basically it just hasn't been super impressive execution by by eyeshares which shows up like you can go and look at the i didn't pull it up to to talk about right now but you can just go to the uh go to the eyeshares website and the and the pretty meaningful tracking error shows up i'm just gonna i'm gonna look it up here so that the one year tracking error ending november 2020 xuu returned 14.12 its benchmark returned 15.42 like it's it's pretty it's pretty serious pretty serious so anyway uh in in speaking with our research team the suggestion was even though vun has a higher mer execu is at seven basis points the u.n is at 16. their suggestion was just based on the continued uh concerns about execution of market exposure based on the way they've decided to construct that fund and what's been happening recently then it makes more sense to go with vun so i i thought that was pretty sensible so that's a notable change from from last year so 30 x i see 30 vun 10 av uv that's us small cap value 16 xef that's just international core six percent av dv so that's in total 16 of the portfolio is in small cap value and eight percent in xcc for emerging markets one of the things i like about this setup is that with vuen you can flip out vtf for vti and an rrsp to eliminate withholding tax if you want to go that route and likewise for xcf you can switch to iemg in taxable accounts with xef because it's canadian listed and hold securities directly you're not going to get hit with the extra layer of withholding tax that you would get from using a us-listed etf yep and that was one of the reasons we decided to go with this overall structure uh fees end up being very close to a cap weighted benchmark so you get about 14 basis points of total management fees for the factory tilts versus 11. incredible for the market cap incredible pretty pretty cool and then if we look at the historical return characteristics for the tilted model versus the benchmark which is basically just the same portfolio with the small cap and value stripped out that's the benchmark but still using etfs over 20 years the factor tilts delivered us 5.78 percent and the benchmark delivered four point nine six percent it's the difference between turning ten thousand dollars into thirty thousand eight hundred over twenty years versus twenty six thousand three hundred over the same period one year return is basically the same standard deviation was a little bit higher for the factory tilted model but we got some extra returns in exchange for it uh so that's that's basically it uh hopefully be able to post the pdf that shows the model portfolios like we've had in the past uh by by the time this episode is released but uh that's it the paper as well do you think we'll be posted or is that going to come out probably not by thursday it's it's with our it's with our marketing team now to get cleaned up and uh make all the charts look nice and all that kind of stuff so uh they did say by the end of this year it'll be realistic to have the full paper available but i think that the model portfolio is pdf i just need to plug in the updated numbers with the new and the new holdings i guess but we already have that document created well i can hear the collective cheers of many listeners because this has been a very common common request on all the different chat boards yeah i hope it's useful and i hope it doesn't throw like honestly the biggest well the factor exposure is a big change from last time like people that were holding ijs and iusv now we're looking at um we're looking at switching that up to be more concentrated in small cap value but also giving international small cap value exposure that's a pretty meaningful change um the u.s equity like that's a bigger holding 30 of the portfolio and changing from xcu to the un that's another big one that you know if there was an embedded tax liability to make that change would i do it i don't know that's a tough call that's a tough call and vun's got a bit of a higher fee than xcu as well so it's not necessarily obvious given the choice to pick one now um we don't know if i shares is going to clean up the implementation of xuu so the un may be a better a better call for now but overall i mean like i said before i think it's a relatively straightforward portfolio to implement we didn't make it too too crazy it's obviously a lot harder than just buying xeqt or something like that but if you're willing to put in the time for the extra whatever whatever you expect 50 basis points or something who knows then uh yeah great nice work so as you mentioned we're skipping the planning topic this week we'll have another topic for planning in the new year and we'll go quickly to the bad advice of the week just a short one this week who came joel passed this article along to us and we sent off a nice zip up hoodie rational minor hoodie to to joel's that offer's still out there if you happen to come across a good idea for bad advice that we just sent it through to to ben or i however you like twitter email whatever works for you anyways this is an article that came from the website seeking alpha that was published on november 9th 2020 called the vanguard total international stock etf right idea wrong implementation oops okay so the article goes on to say investors have multiple reasons to seek exposure outside of u.s equities and out of control pandemic high unemployment high debt and slow economic growth okay so far so good meantime other regions specifically china and asia pacific have superior near-term potential in my opinion uh-oh here come the opinions so it goes on to say well a total international stock etf sounds like a good idea the total part of the description means too much diversification that drags down performance like what are you talking about so as a result the author offers investors two superior alternatives that focus more on specifically on china and the asia pacific region so i do not subscribe to seeking alpha to get the whole article but the notion of choosing regions especially after listening to your whole talk about factors does not make a lot of empirical empirical or theoretical sense to me and certainly not based on near-term potential i mean it's absurd right i mean that's not the point of this kind of etf right you'd be far better enough to understand all the stuff that you just went through for 40 odd minutes or so about what factors to use to get higher expected returns from a theoretical empirical standpoint and try to pick what region then to go and slam an international stock etf to me is is nuts yeah it is nuts there was a little discussion in the rational minor community recently about this idea of reducing exposure to the us yeah i don't know i mean it's it's kind of tricky because and bond etfs have the same problem but if you're uh if you're a market cap weighted equity etf investor and this is something that i've honestly been a little bit concerned about we haven't talked about it on the podcast much but if you're if your total market you're getting always exposure to the most expensive more exposure to the most expensive stuff in the market and increasingly so as it gets more expensive so i don't know like having that constant overweight to small cap and value uh just seems to be a whole lot more sensible to me and rebalancing out of large growth into small cap value as it as it increases as opposed to rebalancing you know into it um seems seems sensible but keep buying cheaper assets that's what you're doing but there's also international diversification too right like one of the things that i didn't talk about when i went through those examples of extended periods of market underperformance is an internationally diversified investor in the u.s last decade actually did fine an internationally diversified investor from the japan 29 year period of underperformance likewise they did fine so you know international diversification is worth something too um so i think that's important for people to take away is that well i guess this article you're talking about was about a total total world fund but if you're globally diversified in market beta i mean that's pretty good still as a starting point we're talking about improving the expected outcome a bit but i don't want to scare people into thinking everybody needs factors or you're going to you know suffer terrible stock returns i don't think that's i think that's true i think there's room for improvement which is what we're trying to do with this model but no need to predict which areas of the world are going to be near-term winners yeah to speak to your bad advice article for sure not and we we did uh an episode a while ago on the difference between economic success and stock market success and in that episode we talked about how economically successful or or expected to be successful countries often actually have worse stock returns it's just like value value investing like the the least gdp growth leads to the highest stock market returns which is super counter-intuitive but it's an empirical reality anyways joel thanks for sending the article along love getting articles and people anything else to add no i think that's good great thanks for listening you

Channel: The Rational Reminder Podcast

Views: 62,695

Keywords: ben felix, pwl capital, rational reminder podcast, investing, finance podcast, wealth management podcast

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Length: 79min 10sec (4750 seconds)

Published: Thu Dec 17 2020