Despite the mountain of evidence against it, day trading is thriving. Today we dive into the research and explore why the practice is alive and well before answering the question — “Can too much confidence lose you money?” After touching on investing news, listener feedback, our books of the week, and our take on the ‘Ultimate Ned Debate,’ we open our discussion on day trading. In our conversation, we look at the results of numerous papers on the topic, none of which present-day trading as sound financial practice. We shed light on the reasons that people day trade, the performance differences between traders, what a day trader’s learning process looks like, stock-picking strategies, and why it’s impossible, except in outlier cases, to earn a living as a day trader. As we unpack the literature, we discuss key insights on the impact of day trading on the financial world. From one investing sin to another, we talk about how overconfidence can harm your investment performance. We balance the positives and negatives of having confidence, highlighting how too much confidence can lead to poor decision-making and a false sense of how much you know. Tune in to hear some of the latest investing news and to learn more about the pitfalls of day trading and overconfidence.

Key Points From This Episode:

• Acknowledging the 33rd anniversary of Black Monday. [0:01:08]

• How the podcast is faring against other podcasts within the investing category. [0:02:07]

• News on past and upcoming episodes and responding to listener feedback. [0:04:09]

• From technological revolutions to starting with a ‘why’, we explore the books of the week. [0:07:23]

• Top news story; Fidelity Magellan Fund is moving to an ETF format. [0:12:06]

• Weighing in on the “Ultimate Nerd Debate” on the value and risks of small-cap allocation. [0:14:45]

• Why performance doesn’t change when you invest in a fund using a different currency. [0:19:12]

• Introducing today’s portfolio and planning topics — day trading and overconfidence. [0:21:56]

• Examining the data sets and papers that assess the effectiveness of day trading. [0:23:48]

• Analyzing two competing theories that explain the behaviour of day trading. [0:25:57]

• Attributing a portion of all portfolio return losses to the effects of day trading. [0:30:39]

• Comparing the performance of the best and worst day traders. [0:33:52]

• Why it might be impossible for you to earn a living as a day trader. [0:36:58]

• Applying Michael Mauboussin’s ‘Paradox of Skill’ to day trading. [0:39:50]

• Three reasons why people still day trade, despite evidence that they make for bad investments. [0:42:38]

• Which stocks day traders trade and how they pick their stocks. [0:45:42]

• Why overconfidence can turn you into your worst enemy. [0:50:25]

• Trends in which investors develop an inflated sense of how much they know. [0:56:02]

• Hear this week’s bad advice of the week; ignore the data and only invest in excellent companies. [01:01:24]

Read the Transcript:

Cameron Passmore: All right. You've been reading a book that you've been telling me to get. It just came in today, Technological Revolutions and Financial Capital by Carlota Perez. I've not even cracked it yet, but you've been raving about it.

Ben Felix : Yeah, I've read about half of it. I listened to probably every podcast that Carlota Perez has been a guest on, which is kind of fun actually, to do that with the author while also reading the book, because you pick up all sorts of little bits and pieces that you don't just get from reading the book. The book's from 2002 as well, which makes it ... when you read it, so the premise of the book is it's a theory that ties together what has happened and the mechanism that drives or the cycle, I guess, that technological revolutions follow. She goes back to the 17 hundreds and documents the last five major technological revolutions, and she says, to be a technological revolution, it has to have a profound impact on every existing industry. So, information networks would be one. Canals, I think canals was the very first one.

Steam power, steel was one. Anyway, but it goes through that, so that piece of it, which is what's actually happening in the economy with technological revolutions and it ties right in not just to capital and innovation, but also the cultural effects, the political effects, the policy responses that inevitably come or have historically come as part of this cycle, but keeping in mind that it was written in 2002. You read through it and think about how the world looks today. One of the things late in the cycle that she documents is that there tends to be big populist surges, big wealth inequality. It's like all this stuff that ... high concentration of wealth with a few people that are running the biggest companies, that the winner take all companies of that paradigm. This has happened. It's not like she's just making stuff up. This cycle has repeated itself four times completely, and we're in some phase.

You can never pinpoint exactly where of the fifth technological revolution, but it's just unbelievable. I know I'm repeating myself, but knowing that she wrote this book in 2002 and looking at how the world looks today, it's quite something. Quite something.

Cameron Passmore: Well, I will definitely read it. Maybe we can make it a investment topic in an upcoming podcast.

Ben Felix : Yeah. Well, the reason I found this book or the path that I was following when I found this book was looking at the relationship between stock returns and technological innovation. That's what brought me here. The reason for that is that I want to do a video and a podcast episode on exactly that topic.

Cameron Passmore: Just slightly inspired by the community board, I'm guessing.

Ben Felix: Before, so you're talking about the post about the commercial for the ARKK Innovation ETF.

Cameron Passmore: Yeah.

Ben Felix: I've been getting questions about the ARKK ETFs for a few months now, and they've taken in like 8.6 billion. I think that was a tweet you sent me, in assets this year, which is, jeez, but it's a concentrated portfolio of basically the high growth glamor tech stocks. Well, not all tech. I think Tesla is in there. They're not really tech, but the high growth stocks.

Cameron Passmore: I'm sure Tesla would disagree with you, but yeah.

Ben Felix: They think they're a tech company?

Cameron Passmore: Well, I'm just surmising. I'm not representing Tesla, of course, but that'd be my guess.

Ben Felix: Yeah. I found this book and a couple of other really interesting resources on the relationship between technological innovation and stock returns.

Cameron Passmore: Cool. This past week I reread a book I read a while ago called Start With Why, Simon Sinek book. I'm sure many, many listeners have listened to it, or they've seen his popular Ted talk, how great leaders inspire action, which amazingly, is the number three highest ranked Ted Talk of all time. The premise of the book is you start with why. People buy why you do what you do more than what you actually do. The why is really the inspiration in terms why people do deal with your company, is a great read. I'm glad I reread it. Kind of went back to my bookshelf, got out of the autobiographies that I've been reading of late and took another read at that book. Quickly moving on, did you see that the Fidelity Magellan Fund is moving to an ETF format?

I thought that was kind of an interesting news piece. Magellan is the famous fidelity fund that had Peter Lynch at the helm. We talked about Peter Lynch a few weeks ago. So, he ran that fund from the late '70s and through the early '90s, and it peaked about $110 billion US and assets. Now, it's down around $20 billion. It's like the S&P 500 dramatically for the past 20 years, but they're going to be reentering as an ETF in the actively managed non-transparent format. The A&T format. Prior MER was 77 basis points, but the new fee is not yet known. I guess there must be something going on that there's more demand in the ETF format as well as the fund format, which I guess is why the repackaging it, any thoughts on that?

Ben Felix: Well, I think in the States specifically, and this is not true in Canada, unless you're holding a US listed ETF, but that comes with other implications, but in the U S because of the heartbeat trades that we've talked about off and on, on this podcast, you're really not going to get a whole lot of capital gains distributions from ETF in the States, whereas with a mutual fund, you will. It also sounds like, I pick this up, just speaking with somebody that's running an ETF company in the States that they don't have the same mechanism for the capital gains refund. I haven't looked into this in any detail at all with mutual funds in the States, whereas in Canada, we have the capital gains refund mechanism within mutual funds, which helps.

You don't get massive embedded capital gain liabilities inside of Canadian mutual funds, at least not to the same extent, but in the States, that's more of an issue, and the ETFs have the opposite, where you never ... You're unlikely to have any capital gains distributions ever. I think any high turnover strategy, like an actively managed fund, or momentum fund, or just a more concentrated high turnover portfolio in general, the ETF structure in the States just makes a ton of sense, so I'm assuming that's got something to do with why they're doing this.

Cameron Passmore: Yeah, I'm guessing a lot of people are just on a brokerage platform, in general, prefer to do their own trades in ETF. They get to know the symbol. It's easier to trade than perhaps doing a mutual fund trade.

Ben Felix: Could be.

Cameron Passmore: Anyways, pretty big name going to an ETF.

Ben Felix: Yeah. Well, that's the story of the Magellan Fund. That's the one where the returns were annualized 22% a year or something like that, but the average investor return was negative, or negative, or trailed the S&P or something like that.

Cameron Passmore: Certainly trail with the funded. The average invested worse than the funded.

Ben Felix: Like I'll bow, a lot worse though. Not just worse, like yeah, brutally worse.

Cameron Passmore: Anyways, you wanted to talk about the nerd debate that's going on.

Ben Felix: The quant is what I called it, but the ...

Cameron Passmore: Some bunch of guys on Twitter, a bunch of fintwit people call it the ultimate nerd debate or something.

Ben Felix: Oh yeah. Yeah, it's about the size factor and whether or not it's actually a factor. We've tended to side with what Cliff Asness and AQR have said, and what Cliff talked about on our podcast asked too, which is that, as a stand-alone, there was really not a size effect. If you take small caps in aggregate, their excess returns are not statistically significant and can really just be described as high beta, so you're not getting anything. But Cliff, on our podcast, he made an interesting point, that if you want more beta, but don't want to use leverage using a total small cap allocation, could be a way to get higher beta exposure. I think that probably comes with a bunch of skewness issues too, but it's a different topic.

Scientific Beta, which is an indexing firm. Now, I've seen some of their stuff. I think they did the ESG products, or Scientific Beta Indexes. That's the only time I've seen their stuff, but they wrote a paper, short paper disagreeing with this idea, that there is no so size effect. They took the angle that sure, you can say that, as a standalone, there's been no statistically reliable premium, and there has been an economically meaningful brand, but it just hasn't been statistically significant, so we maybe say it doesn't exist. But their stance is that taking that point of view and looking at the size factor in isolation does not make any sense. Why would you ever do that in the first place? It doesn't make any sense. It's actually a pretty good argument, and Fama-French have written about this too.

They show, in this Scientific Beta paper, they show all of the major asset pricing models that exist today, including the Fama-French five factor model, the Q five-factor model, Fama-French six-factor, and then there's one other six-factor model. I can't remember the name. But all of them, while they differ in some of the other factors that they include, all of them include marketing size. The point of the paper's like, clearly from an empirical perspective, the size factor has use in an asset pricing model. Then they referenced a 2015 paper that Fama and French did, where they argued that the contribution of a variable in an asset pricing model is more relevant than the return spread of that variable on its own.

Basically, if adding size to an asset pricing model increases its explanatory power, that makes it a factor or a useful factor, even if on its own, it doesn't have a big return spread or a statistically return spread.

Cameron Passmore: That is really interesting.

Ben Felix: Yeah.

Cameron Passmore: So, it's all about controlling it, or controlling the other factors when you throw in small.

Ben Felix: Yeah. We know that is, without question, empirically true. The reasons are not as clear, like the risk story for small caps, and that was part of AQR's whole paper, is that they argued that there isn't and shouldn't be a risk premium for size, but the empirical reality is all of the other factors are much stronger in small caps. They clearly have some meaning in terms of as a pricing. Yeah, that's basically it. It's kind of a non story, but it is really interesting thought exercise because this has come up in the Rational Reminder community discussion too. The question of, should you target individual factors and combine them together in a portfolio, or should you take a multi-factor perspective in building the portfolio? The multi-factor perspective is the answer, and this is one of the reasons why that's true.

If you just go for small caps, you're probably going to get a bad outcome, or at least not as good of an outcome, but if you like what Avantis is doing or what Dimensional is doing, use size as one of the things that you're waiting on, but within the size, you have to do all of the multi-factor weighting as well, otherwise you're not targeting the right stuff.

Cameron Passmore: Very interesting. Okay. Let's talk quickly about currency because this is something that comes up a lot so we just want to talk about this quickly. Often, people will settle a trade in US dollars and want to go and invest in a fund in that same currency, thinking that the performance will be different than if they converted to Canadian. This has been an age old challenge that I found to try to explain to people, the only thing you're saving by investing us dollars is the spread in what house is taking to convert you from us to Canadian or vice versa. That's the only difference. It's a very hard concept to get across to people because most people just don't get that.

Ben Felix: Yeah, there are some other little nuances in there too. If you're holding a us listed ETF that has some tax implications, we can even just forget about US listed ETFs because you can buy a Canadian listed ETF that trades in US dollars. If we compare the returns of two Canadian listed ETFs, one trading in US dollars, one trading in Canadian dollars, and they're tracking the same index, their returns in one of the currencies, so choose the currency in which you are evaluating your performance, the returns in that currency, in your, call it your base currency, are going to be the same for those two ETFs tracking the same index, but trading in a different currency. If you convert the performance back to your base currency, the returns are going to be the same, or roughly the same.

Cameron Passmore: Or a mutual fund. You could have a Canadian listed mutual fund that trades in Canadian dollars, or US dollars. The performance will be identical. The only difference ...

Ben Felix: Your Canadian dollar performance will be identical. That's the trick because you see in your account, you see your US dollar performance, which makes it feel like it might be different, but if you convert everything back to Canadian dollars ...

Cameron Passmore: Or back to the same base currency, the returns will be identical.

Ben Felix: Correct. Back to whatever base currency it is that you're calculating your performance in. Yeah, that's an important one that I agree is often missed.

Cameron Passmore: That's not to say the spreads can be meaningful, so you have to be very aware of what the spread is and make sure that you understand what that might be, because it can be a fair chunk of change convert, depending on the amount. I'm not minimizing that. But in terms of, once you get into that fund, you bring them both back to the same currency, the performance is identical.

Ben Felix: Yeah, and how you're converting to. If you're converting through your brokerage, they might charge 2% or whatever through the bank. If you're doing Norbert's Gambit, it's going to be cheaper, but you're still paying a spread. Yeah, that's a whole other maybe discussion topic. But when you do Norbert's Gambit, you're still paying the spread on the ETFs that you have to transact. People often calculate the cost of Norbert's Gambit as the trading costs, but you're crossing the spread twice to do it.

Cameron Passmore: The portfolio topic today, you wanted to talk about day trading, which also links to our planning topic of overconfidence.

Ben Felix: I think I've said this before about different topics. It's easy for us to imagine that people are over day trading, like who would ever day trade anymore? The evidence against it is so obvious, but I think there are probably still a lot of people doing it. Where there was actually a question, and this is not quite the same, but there was a question in the Rational Reminder community about technical analysis. I know that's not the same thing as day trading, but same idea, where it's like, the evidence is pretty clear that it doesn't make a whole lot of sense, but there's still people doing it and still people asking you about it, which is fine. Asking questions is good. But I thought it made sense. You know what maybe inspired me for this was the TikTok stuff that you were talking about. They're telling people, look, you can day trade, look, I'll teach you how to day trade. I thought it made sense to cover it as a topic.

Cameron Passmore: I'm sure the volume is massive on day trading now.

Ben Felix: Yeah, yeah. Right. Maybe that's what inspired me to revisit this as the whole Robinhood during the pandemic thing and the crazy trading volume and DIY stock trading accounts.

Cameron Passmore: And probably a ton of money being made. You start picking these hot stocks that have gone up with these huge returns so far this year, you can certainly see how that could lead towards overconfidence.

Ben Felix: I don't think there are a whole lot of day traders that are buying and holding though. Maybe if you bought the ARKK ETF, you've done really well. We'll address that in a different episode though. But day trading, I mean, if you ever go on the WallStreetBets subreddit, there are a lot of, it's called, within the subreddit, they call it loss porn. There's a lot of loss porn. People lose a lot of money. People make money too. I guess theoretically it nets out to zero. Maybe you hear about the wins more. Okay. There are a bunch of papers on this. How do you study day trading, is an interesting question on its own. Most of the research dug up anyway. It takes the approach of, let's get hands on the full dataset of all transactions in a market, in whatever market we can.

Most of the data come from ... not most. A got a good chunk of the data come from Taiwan. I don't know if that's a regulatory thing or I don't know what ... for whatever reason, they were able to get their hands on data for Taiwan, but the whole stock market, like all transactions that happened in Taiwan over the time period, they get their hands on that data. One of the other papers looks at a US discount broker, and same thing. Through whatever arrangement, these researchers were able to get their hands on all of the transactions for all of the clients of this discount broker. There's one other dataset that has a few papers written about it that I did not address just because I had enough already, but that one is Finnish data. Again, for whatever regulatory or whatever reason, you're able to get all of the transactions for Finland.

The methodology that these researchers take, or at least in the papers that I've found, is that they get the full dataset, and then they classify the day traders within the data based on their transaction history. So, it's unbiased sample. It's not like you're getting the people who are self declaring as day traders. They're taking the full dataset, looking at the transactions that are happening and classifying them as day traders.

Cameron Passmore: What constitutes a day trader? How fast they trade, how often their average holding period?

Ben Felix: The methodology is slightly different from paper to paper, and I didn't too much into that portion of each of the papers, but in general, they're classifying day traders as accounts that transact on the buy and sell the same security on a single day.

Cameron Passmore: Oh really? Okay, so it's daily, hence day traders.

Ben Felix: Yeah. Well, that's the idea, I think. The first one that we'll talk about is, it was in The Journal of Finance in 2000, and it's called Trading Is Hazardous to Your Wealth: The Common Stock Investment Performance of Individual Investors. This is the one that had the US discount broker data, and that was between 1991 and 1996. The premise of this paper was testing out two competing theories of day-trading like, why do day traders day trade? One of the theories is that day traders will trade when the marginal benefit of doing so exceeds the marginal cost. Right?

Cameron Passmore: Sounds rather theoretical, but fine.

Ben Felix: Yeah. But it's true. That rationally is when they should trade. I think that's some Grossman-Stiglitz Paradox stuff too. Then the other theory is that investors are overconfident and trade to their own detriment, so two very different theories. But I think this is one of the first papers, if not the first paper, to really take the data and rip it apart and ask this question. No surprise based on the title of the paper, but based on the results of their analysis, the authors conclude that individual investors are overconfident, based on the evidence that the average household earns a return close to the market before costs, which again, makes sense, so you've got 66,000 households. They get the market return before costs. They hold the market portfolio in aggregate, but they trail the market by about 1.1% annually after costs.

So, they trade to their own detriment. This was also interesting, and this is maybe time periods specific, '91 to '96. I don't know. I don't imagine people day trading small cap value stocks today. It seems like it's more focused on ... I mean, what do I know about day traders? The stuff you read about what the large cap glamor stocks. So, in this-

Cameron Passmore: What shocked me in your notes is that they do tilt towards small cap value. I just can't believe it.

Ben Felix: In this sample.

Cameron Passmore: In that sample.

Ben Felix: Again ...

Cameron Passmore: This is before the big tech run-ups. Big tech run-up was just starting after that period.

Ben Felix: Yeah. In this sample, they did find that the households had this tilt towards small cap value, and when they accounted for that additional excess risk exposure, so instead of just using a market benchmark, if they go and adjust for size relative price and market exposure, the average household trailed the risk appropriate benchmark by 3.7% annually after costs. Then this is a really interesting data point in here too. So, the average household turned over about 75% of its holdings annually and the associated costs were what explained for the poor performance, but the 20% of the households in the sample that traded the most often turning their portfolios over 200%, twice, turning over all holdings twice annually, they trailed the market by 5.5%, and they trailed a risk appropriate benchmark by 10.3% annually.

Cameron Passmore: Wow.

Ben Felix: Actually, now that I'm thinking about it, I don't know if this paper specifically classified day traders. I think they're just looking at the relationship between transaction volume and investor returns at the individual investor level. I don't think that they did break out specifically traders. Some of the other papers did. Now, this is from a theoretical efficient market perspective. This is meaningful because if the market is efficient, you shouldn't usually have an informational edge, at least not enough to exploit it consistently. If that's true, then picking stocks, day trading, actively managed funds should all trail the market, especially after costs.

Cameron Passmore: This is a different era as well. This is pre pro uses of the internet, pre all the different finance sites. It would have been large, everything subscription-based services…

Ben Felix: Newsletters and stuff.

Cameron Passmore: Newsletters, newspapers, tips from friends. Maybe that's why it was small cap value oriented. I'm just guessing, but it's a whole different time, which is ... It's hard for us to even think of that now.

Ben Felix: Yeah. The authors of this paper may conclude that their finding support, the theory that investors are overconfident and trade to their own detriment, and the interest in relationship from the perspective of day trading was that more transactions led to worse returns, which lines up with some of the later studies that we'll also talk about. Then there was a 2009 paper in the Review of Financial Studies, and this one was titled Just How Much the Individual Investors Lose by Day Trading. This is the one that I was thinking of before, where they classify day traders by their frequency or the frequency of their transactions, or the characteristics of their transactions. For this one, this is where they had all trading history of Taiwanese investors, of all investors in Taiwan from 1995 to 1999.

Taiwan being the 12th largest stock market over the time period. They found that individuals who engage in day trading, now this is a bit of a staggering data point, individuals who engage in day trading reduced the aggregate portfolio return for all individual investors by 3.8% per year.

Cameron Passmore: How?

Ben Felix: Yeah. That loss amount was attributed to trading losses, commissions, transaction taxes, and market timing losses. They also give an interesting statistic to frame those costs in a different way. Taiwanese individual investors, in aggregate, over this time period, lost about 2.2% of Taiwan's GDP to trading losses per year.

Cameron Passmore: Can you imagine?

Ben Felix: Pretty substantial. Now, this part I find fascinating, keeping in mind the time period that we're talking about here, so 1995 to 1999, in this case, they had all of the data. The last one we talked about was for just a US discount brokerage. This time it's all transactions occurring in Taiwan. They were able to look at how individuals did, but also how institutions did. They found that institutions, while individuals were losing money to trading and market timing losses, institutions were making money from the same thing. I think it kind of speaks to that age old question that anybody place in individual stock trade should ask themselves, which is, whether or not they know more than whoever is on the other side of the trade? These data suggests that individuals on average don't, and in this paper, they actually found that almost all of the losses incurred by individuals stemmed from aggressive trades.

They defined aggressive trades as limit orders with high prices, buy limit orders with high prices and sell limit orders with low prices. I think in Taiwan, you can only place a limit order on their stock market. The people who are willing to pay way above market to buy and sell way below to sell, that's where most of these losses were concentrated, and that's where institutions were making a lot of their trading profits in this sample. The authors had a good quote in there. They said that the institutional profits associated with passive trades, which is just accepting the liquidity, as opposed to going out there and trading with urgency, that the institutional profits associated with passive trades are realized quickly as institutions provide liquidity to aggressive, but apparently uninformed individual investors.

Cameron Passmore: Yeah, the price of liquidity.

Ben Felix: Yeah, exactly. There's another study, a 2012 study. This one's titled the cross-section of speculators scale evidence from day trading. This one is really interesting. Again, using Taiwanese data from 1992 to 2006 this time, the premise here was, instead of just looking at the aggregate results for day traders, let's look at the distribution of outcomes within the sample of day traders. On average, it's not so great, but how do the best day traders do and how do the worst day traders do, that kind of thing. They found that 1% of the total population of day traders in Taiwan, from 1992 to 2006, was able to reliably earn positive excess returns after costs. So, 1% of the total.

Cameron Passmore: It's crazy.

Ben Felix: Yeah. The odds are not good, and it gets worse. In the average year, in their sample, there were about 450,000 Taiwanese individuals who engaged in day trading based on this ex-post analysis of the raw data, and only between 1,000 and 4,000 of them, depending on the assumed level of trading costs, now that's between 0.22% and 0.9% of the 450,000, are inconsistent alpha after costs. That was that 1%, really breaks down to, somewhere between 0.22% and 0.9%, depending on how you model transaction costs. Now, this piece was interesting. The top 500 day traders, so that's the top 0.1% in this sample, did earn large alphas, 38 basis points per day after costs, which is pretty serious.

Cameron Passmore: But is that more than you'd expect by pure chance, do you think?

Ben Felix: It is. They looked at that in the paper too. They modeled what you would expect by chance, and that did account for some of this, but not all of it.

Cameron Passmore: So, there is some skill in that pool.

Ben Felix: It seemed so. They tried to look at, or think about, they didn't really try to analyze it, but they tried to comment on what that could be caused by. They did look at some data on that too. They looked at the number of people who were caught for insider trading over the time period and all stuff like that to see if that would account for it. Yeah, it seems like over this period, there were some traders that had reliably good information and were able to profit from it. There's hope for day traders maybe, in the 0.1%, but I do think it's important to note that this time period, between 1992 and 2006, we, being the aggregate group of investors, did not have high frequency trading yet, at least not the way that it exists today. I think, just in general, the financial institutions are bigger and assets are more concentrated in institutional hands today than they were, even back in 2006.

There was another paper, and this one we mentioned on the podcast when it came out, but this is a 2019 paper titled, Day trading For a Living, and this time they were looking at individuals in Brazil ... in the Brazilian equity futures market, sorry, who began to day trade between 2013 and 2015, and they looked at the data through the end of 2017, so they had at least two years of data. The Brazilian equity futures market is the third largest in terms of trading volume in the world, which is ... I would never have ... If you asked me what the third largest equity futures market in the world was, I wouldn't have said Brazil, but there you go. Over this period, there were 19,646 new day traders.

5.7% of those day traded only one day, 50.8% day traded between two and 50 days. I'm sorry, 50.8 traded between two and 50 days. 15.8% traded between 51 and 100 days, 13.9% between 101 and 200 days, 5.9% between 201 and 300 days, and 7.9% of the sample traded for more than 300 days. That breakdown is important in a second. Here's where it's important. They found a monotonic decrease in the probability of profit with an increasing number of trading days. Monotonic decrease, more days you traded, the worst your chances of ...

Cameron Passmore: Of course, you did.

Ben Felix: Yeah. Of the 1,551 individuals who traded for at least 300 days, 97% of them lost money, 1.1% of them earned more than minimum wage, 0.5% of them earned more a bank teller salary, and the single best trader in the sample earned 310 US dollars per day, on average, with massive volatility.

Cameron Passmore: Wow.

Ben Felix: Now, they also asked if there's learning among day traders, and we started looking at the literature on day trading. This question comes up a lot. Is there evidence of learning? If there's learning, you would expect the bad day traders to self-select out and the good ones would stay and continuously improve. These authors found no evidence of learning. Their commentary here is interesting. They said that, instead observed patterns usually found in gambling activities where the proportion of successful players also monotonically decreases with a number of rounds played. Now, this paper mentions what I was talking about a second ago, that a possible reason for their finding, diverging from the Taiwan paper that we just talked about, and I think they specifically referenced that paper, is that their traders today are now competing with the bigger institutions and the high frequency trading specialization firms.

That's maybe what's going on, or maybe the outcome in that Taiwan paper was just spurious in the first place. That concept is important, the high frequency trading and the, who are you trading against. It made me think of a concept that I believe Michael Mauboussin coined, which is the paradox of skill, and there's a paper that he wrote about this for Credit Suisse, which we can link. He used the example of Ted Williams, who was the last player in major league baseball to hit over 400 for a full season back in 1941. Now, the interesting piece is that he was obviously, Ted Williams is obviously very good back in 1941, but baseball players have gotten better over time. If you take, I don't know anything about baseball, but if you took a really good baseball player today and put him back in 1941, they'd probably blow that past record out of the water.

What's going on? This is where the paradox of skill comes in. So, Michael Mauboussin said that you have to think about the two different dimensions of skill. One of them is relative skill, and one of them is absolute skill. In terms of, to use the baseball reference again, in terms of absolute skill, today's players are much more skilled than athletes of the past, and not only more skilled, but better trained, better coached, better nutrition, bigger talent pool, just by the global population being bigger, probably access to more talent pools as more countries are becoming, or having baseball programs and athletic programs.

Cameron Passmore: Definitely.

Ben Felix: Baseball had the whole performance in enhancing drugs issue that I remember back when I was living in Boston, that was a pretty big deal, but they're all competing against each other. You don't get to take one of the juiced up, jacked up baseball players from today. Maybe they've solved those problems. I don't follow baseball at all, but if you took one to put them back in time, their relative skill in that scenario would be extreme. But then you put them back into today where everybody's doing the same stuff and everybody's on the same playing field and their relative skill is arguably, and arguably using the Ted Williams example as evidence, is lower because no one's been able to match that record since him.

The same concept can be applied to trading. Everyone wants to find an edge and everyone's pouring resources into it. It's the Grossman-Stiglitz paradox idea, where people will pour resources into finding mispricings or finding alpha. When that's happening, when the absolute level of skill is increasing, the relative level of skill is decreasing. That concept is just really, really important. There's another paper in the Review of Asset Pricing Studies. This is a 2019 paper. This one's asking, basically, okay, we understand day trading is no good. All this evidence that we just talked about, the paradox of skill, why would anybody day trade? This one suggests three different reasons for why people are still doing that. It's clearly not a rational action.

One potential reason is the day traders don't have standard risk averse preferences, so they actually like the highly skewed outcomes, the lottery like outcomes. The authors of this paper suggest that, if that is the case, they should just hold a single volatile stock because individual stock returns are extremely skewed anyway. So, if you want a highly skewed outcome, just hold a stock. You don't have to trade. You don't have to take on the transaction cost if you're looking for skewness. Just hold a concentrated portfolio. The second suggestion is the day traders may be overconfident, which is maybe obvious, and that's what some of the evidence pointed to, but also biased in the way that they learn. So, they suggest that somebody can hear all of the information that we're talking about right now, and they can see the data on day trading, but the stories of successful day traders, and this is kind of what we were talking about the beginning with the WallStreetBets example, the stories of successful date day traders probably circulate a non-representative proportions.

So that people can hear us talking about this stuff, but then you log into the WallStreetBets subreddit or wherever on the internet, and the impression can easily be had that lots of people are making money day trading, even though the data completely disagree. Then the last one, oh, you know what, and this one's really interesting, I just realized more interesting than I originally thought. I'll touch on why briefly, but this is a whole other topic. The third one is that day traders may trade for nonfinancial reasons like entertainment or a taste for gambling and a desire to impress other people, to the extent that they're willing to bear the cost of the losses. The reason that I realized this is so interesting, is because there's a paper that just came out recently looking at that skewness preference, looking at skewness basically as a factor, where people are actually more ... they have a taste for skewness.

There's evidence that people have a taste for skewness. They have a taste for lottery like outcomes, which means that the prices of those stocks get bid up higher than they should in a rational asset pricing model and end up having lower returns. You can actually go long stocks with negative skewness and short stocks with positive skewness. That's like long non lottery-like stocks and short lottery-like stocks, and there seems to be a reliable premium in there. It actually adds a bunch of explanatory power to the Fama-French five-factor model. I just realized this that, that explanation for why people might day trade, that preference for skewness actually matches up with some more recent literature on that, on people having that preference.

Okay. The last piece on this topic is really interesting question. When I found this paper, I wouldn't have even thought about this. This is the 2007 paper, but it's asking, okay, so people day trade, it's irrational, but maybe they've got a preference for it, whatever, whatever. You talk all the data about day trading, but which stocks to day traders trade, and how do they pick those stocks? It's kind of like what you were talking about earlier, Cam. How do people get the information to decide which stocks are going to day trade? This paper tried to answer that question again, by looking at a whole bunch of stock transactions, the whole unbiased sample, same as I was describing before. They found that individual investors are net buyers. Oh, they had this, it was not specific to day trading. This is just for individual investors.

Individual investors are net buyers of stocks with high trading volume. So, if something happens in the news, it was the idea here, that causes a lot of volume in a stock, individual investors end up being net buyers of those stocks. They're net buyers of stocks following extremely negative and extremely positive one day returns. So, if a stock is in the news because of extreme negative or positive returns, individual investors end up being net buyers of those stocks. Oh, and then specifically stocks that appear in the news. Those three main characteristics. They looked at high trading volume, extremely negative or positive previous day returns and stocks that appear in the news. Then they go on to explain that this is a problem.

If it is true that individual investors are choosing which stocks to buy based on attention grabbing stuff, that is majorly problematic, because it's limiting the opportunity set obviously. We know that stat on 1.3% of stocks explaining all of the net wealth creation on the market from 1990 to 2018. If you're only picking the attention grabbing stocks, that's not ideal. But then the other perspective that they took on that, they gave the analogy of a well-circulated article about a deserted vacation spot. All of the people who arrive, all of the people hoping to find this deserted vacation spot from the well-circulated article end up showing up with a whole bunch of other people who are looking for a deserted vacation spot, which is obviously not ideal.

To relate this to stock trading, they say that you may end up, if you're buying based on attention grabbing information, you may end up purchasing something that has a temporarily inflated price. I thought that was just fascinating, because it's a great question. If someone's day trading, which stocks are the day trading? In my experience, based on the conversations that I've had with people, it seems like most of the time, it's the stocks that you hear about. It's never some stock that I've never heard about.

Cameron Passmore: Well, you see those bubble charts on Twitter, right? Where stock trading is going, and then the larger the bubble gets, the price goes up. What the traders are trading. Robin had used to disclose that, right? It was so fascinating to see what they were buying. It was crazy stuff.

Ben Felix: Yeah. That was pretty much it, but it shouldn't be a surprise to our listeners, but maybe it'll help them communicate these ideas to family members or whatever that are still ... I had a YouTube comment recently, and maybe that was one of the other things that inspired me to do this, that was basically saying, my parents day trade, and it pains me like to watch them day trading. Is there anything that you can help me to help communicate to them why day trading is not a good idea, but then the data around ... or no, that wasn't data. That was just more of a theory, I guess, but why do day traders trade, and it may not even be because they're looking for profits. It could be because they are looking to gamble. They have a taste for gambling.

Cameron Passmore: Anything else to add?

Ben Felix: No, I don't think so. When investing gets that reputation of being a casino and being gambling, which it does for a lot of people in the world still, that is about day trading. Day trading is gambling, or maybe even the odds are worse than they are in gambling. I think that's ...

Cameron Passmore: To take your YouTube question like what to do with your parents who might be day trading, it's like the only thing worse than ... some would say the only thing worse than losing money day trading is actually making money day trading because that can lead to overconfidence potentially. Might become bigger trades or more frequent trades of bigger money on the line. At some point, your luck may run out. That's why we thought today the planning topic we would cover would be investor confidence. Are you your own worst enemy? Really, what we're talking about is overconfidence, which is a very biased way of looking at a situation. When you're overconfident, you misjudge your value, the opinion, beliefs, and abilities, and you have more confidence than you should, given objective parameters of the situation. I loved a quote from Daniel Kahneman, "Overconfident professionals sincerely believe they have expertise, act as experts and look like experts. You'll have to struggle to remind yourself that they may be in the grip of an illusion."

We talked about, with Annie Duke last week, we talked a lot, obviously about decision making, and how many of us don't consider the different probabilities of possible outcomes when we make decisions. Look at all the data that you just showed. A lot of people who may choose to do day trading, don't think about the probabilities of being wrong, I don't think, and the more times we're successful, that can lead to more overconfidence. I got this idea from an article in the August 4th edition of Financial Planning Review, an article from Colleen Tokar Asaad, who is in the department of finance at Baldwin Wallace University in Ohio, who asked the question, is too much confidence in your investing knowledge harmful to your investment performance?

It's a really interesting paper. They referred to a number of studies that demonstrated that higher knowledge levels are associated with good things, such as more financial planning, more regular daily financial management, greater focus in your life on retirement planning, higher stock allocation, and in general, greater wealth accumulation. More knowledge is a good thing. Lower levels of financial knowledge were associated with increased borrowing, more expensive, mortgages, and a higher level of mortgage defaults. However, the perceived level of financial knowledge influenced savings and borrowing, investments, retirement planning and credit card behavior. It's this question they're looking to ask is, how much confidence is reasonable, and how much overconfidence is detrimental? Which is a really interesting question.

They refer to the definition of overconfidence as, and quote, "A positive difference between assess confidence and observed achievement," which is a really interesting question.

Ben Felix: Yeah, it is.

Cameron Passmore: Right? This is something we hear a lot in our world, which is, and I'm quoting this from the article, "People prefer to bet in a context where they consider themselves knowledgeable or competent, rather than in a context where they feel ignorant or uninformed. This competence hypothesis may manifest itself in the investment domain, through the familiarity bias, where individuals invest in the familiar while ignoring tenets of portfolio theory. With familiarity behind each stock is a story of family business, family quarrels, legacies, and we abstract from all these stories and building our models, not because the stories are uninteresting, but because they may be too interesting and therefore distract us from the pervasive market forces that should be our principal concern. The psychological factors, such as illusion of control, competency and familiarity, help shape overconfidence." There's quotes in the paper from other authors.

But we live this all the time, right? People who might work in a certain sector feel more comfortable investing in that sector. People whose family grew up investing in real estate will have a bias towards real estate. But what is also interesting is overconfident investors are more apt to make risky choices, which can erode investor returns. They could be more likely to trade more, they could be less diversified, and more likely to have confidence in market regulations, and less likely to seek the device of an adviser, more likely to trade on margin, more likely to trade commodities, futures and options. This last one, I don't understand why, but over-confident investors are more likely to have whole life insurance.

Ben Felix: Wow.

Cameron Passmore: Okay? But some overconfidence can be beneficial because that can play a role in overcoming risk aversion, if you have greater confidence, therefore, a higher risk tolerance and also may lead to better and quicker financial decision, which is interesting to think about that. If you are overconfident, you'll end up with, I would presume, a greater allocation of stocks, be more confident when things get rough to hang on through it. Overconfidence may help explain why invest or invested returns are consistently lower than investment returns, which has long been called the performance gap.

Ben Felix: Yeah.

Cameron Passmore: Higher levels of financial knowledge is linked with more financial planning, daily financial management, more stock exposure and greater wealth accumulation. So, knowledge is important. But get this, I thought this is really interesting, and I want to go through these questions quickly, but FINRA in the US has a national financial capability study. In 2018, they surveyed 2000 respondents who held investments outside of the 401k plans. These are people who had non-registered investments outside of their company. Okay? The questions, there's 10 questions, none of which are terribly hard. I'll go through them quickly, and I'll tell you how people did on them. In general, investments that are riskier, tend to provide higher returns over time than investments with less risk. True or false. If you buy company stock, do you own part of the company, have you lent money to the company? Are you liable for the company debts, or the company will return your original investment to you with interest?

The answers. If you buy a company's bond, do you own part of the company, have you lend money to the company? Are you liable for the company's debts and you can vote on shareholder resolutions? Which answer's correct. Over the last 20 years, in the US, the best average returns have come from stocks, bonds, term deposits, money markets, precious metals, don't know. If a company files for bankruptcy, which of the following securities is most at risk of becoming virtually worthless? Preferred stock, Com stock, bonds, or don't know. So far, not terribly difficult. The past performance of an investment is a good indicator of future results, true or false? Which the following best explains why many municipal bonds pay lower yields and other government bonds. Municipal bonds at lower risk, bear demand for municipal bonds, municipal bonds can be tax-free. We don't have these in Canada.

What is the main advantage that index funds have when compared to actively managed funds? Index funds are generally less risky in the short-term, index funds generally have lower fees and expenses, or index funds are generally less likely to decline in value. Another one, number nine, you invest $500 to buy $1,000 worth of stock on margin. The value of the stock drops by 50% and you sell it, how much of your original $500 investment are you left with? 500, 250 or zero. Last one, which is the definition, best definition of selling short? Selling shares of a stock shortly after buying it, selling shares of a stock before it has reached its peak, selling shares of a stock at a loss, or selling borrowed shares of a stock. Those are the 10 questions. None of them are terribly hard. Before this, only 15% reported, self-reported lower than average knowledge level.

65% of people self-reported as higher than average, but more than half of the respondents cannot answer half of those questions accurately. Isn't that incredible?

Ben Felix: Yeah.

Cameron Passmore: The new questions on that, which was the index fund one, nearly half of respondents think that past performance is a good indicator of future results, and less than a third understand that the main advantage of index funds, or were actively managed funds, is generally lower fees and expenses. It shows you the average knowledge level is not that great, and certainly not as great as the overconfidence levels.

Ben Felix : Yeah, that is really interesting. I mentioned for the day trading research, there's the Finland dataset, and one of the papers looked at the relationship between individual investor outcomes and IQ, among a couple of other variables, and they actually did find a statistically reliable relationship where people with higher IQs use tend to have better investment outcomes, and not just from the perspective of generating alpha, but also from actively engaging in tax loss selling. There were a couple of other things.

Cameron Passmore: So, better behavior, better overall financial behavior.

Ben Felix: Yeah.

Cameron Passmore: And that's what this is saying too.

Ben Felix: Yeah, so intelligence correlates with better financial behavior, but overconfidence in intelligence leads to bad behavior.

Cameron Passmore: There's your takeaway. Interesting stuff. Something to be mindful of and to be aware of.

Ben Felix: But how do you determine if your confidence matches up with your intelligence?

Cameron Passmore: Care to take a skill testing questionnaire to find out?

Ben Felix: Yeah, jeez. We had a podcast listener that I think have an email conversation with. There's a text based conversation. I don't remember what platform, but anyway, they're taking on this role of managing their family's finances, which is great. I guess the base of the conversation was they were appreciating the podcast as a resource, but their process, I may have actually mentioned this in the past episode, their process for taking this on was to go through all of the certifications that somebody who does our job would have to do. All of the securities licenses and all of the tests that you have to take to be a portfolio manager, so they're going through that full process before taking on the family's finances. I thought that was a pretty good a test. I'm not saying that those exams are a good benchmark, but definitely better than nothing.

Cameron Passmore: Yeah. That is good. Okay, onto bad advice of the week quickly.

Ben Felix: Yeah.

Cameron Passmore: Now, remember, if you do contribute something, send us an article. We'll send you off a world famous Rational Reminder hoodie. This one came from Carla, who's an adviser in Montreal sent this article to me. So, it was an article published in French from an advisor just outside of Montreal. The title translated to English is, Do You Hate Stock Indexes Just Like I Do? Here we go again. Uh-oh, the article goes on. Find out why I hate stock indexes. They're a composition of good and bad companies. Then goes on to share his concern with the various indexes, such as the Dow Jones's price weighted index of just 30 companies. The S&P TSX is 225 companies representing only 3% of the world economy, with mainly three sectors, finance materials and energy, making up 56%. The S&P 500 being too tech focused and five companies making up a large weight.

Again, nothing new here. We agree with them on these points, and we've talked about this many, many times. What does he suggest you do is the obvious question. I'm quoting here, "Since indexes have big loopholes and are not indicative of the economy, an investor should aim to obtain returns based on his plans and not based on stock market indices." Okay, so far so good. "So, how do you do that? By investing in the right companies. Therefore, I prefer to be an excellent investment advisor who selects excellent portfolio managers who invest the wealth of my excellent clients in excellent companies, regardless of their weight in their index and all with the aim of increasing your wealth and achieving your financial dreams." Which we agree with, it is all about investing to reach your financial objectives, whatever they might be what is your purpose for your money. I just don't get how you make that leap from indexing and evidence-based investing to only investing in the right companies when the data does not suggest that, that will likely have a positive outcome.

Ben Felix: No, I love the data point that I came across recently on ... this is part of my research on technological innovation and stock returns, but the railway industry is the ultimate declining industry from 1900 until now. It went from being the majority of global stocks by capitalization in 1900 to whatever, a small percentage. I don't have the exact amount. Over that time period, railway stocks outperformed the stock market and also outperformed, I think it was vehicle manufacturers and aircraft manufacturers. So, the new transport technologies that came along later underperformed railway stocks, which were the ultimate declining industry. It just speaks to that a concept, the difference between industry growth or a company being good. It's all about estimation errors.

Unexpected stock returns come from estimation errors. Expected stock returns come from discount rates. Good companies might have low discount rates and therefore low expected returns. If they don't happen to have high unexpected returns, for some reason that you can't predict, then you're going to get a bad outcome, and you have a bad expected outcome from the good company. I've been thinking about our bad advice segment. We often talk about bad advice, but don't talk about why it was bad, so I wanted to throw that in at this time.

Books From Today’s Episode:

Technological Revolutions and Financial Capital on Amazon — https://amzn.to/3m8Xiqy

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Benjamin on Twitter — https://twitter.com/benjaminwfelix

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'How Great Leaders Inspire Action' — https://www.youtube.com/watch?v=qp0HIF3SfI4

'Trading is Hazardous to Your Wealth' — https://papers.ssrn.com/sol3/papers.cfm?abstract_id=219228

'Just How Much Do Individual Investors Lose by Trading?' — https://faculty.haas.berkeley.edu/odean/Papers%20current%20versions/JustHowMuchDoIndividualInvestorsLose_RFS_2009.pdf

'The Cross-Section of Speculator Skill: Evidence from Day Trading' — https://www.researchgate.net/publication/228289143_The_Cross-Section_of_Speculator_Skill_Evidence_from_Day_Trading

'Day Trading for a Living?' — https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3423101 

'Alpha and the Paradox of Skill' — https://research-doc.credit-suisse.com/docView?language=ENG&format=PDF&source_id=em&document_id=805456950&serialid=LsvBuE4wt3XNGE0V%2B3ec251NK9soTQqcMVQ9q2QuF2I%3D

'Is Too Much Confidence in Your Investing Knowledge Harmful to Your Investing Performance?’ ‘Investor confidence: Are you your own worst enemy?' — https://onlinelibrary.wiley.com/doi/full/10.1002/cfp2.1092

Learning Fast or Slow? — https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2535636

All That Glitters: The Effect of Attention and News on the Buying Behavior of Individual and Institutional Investors —https://pdfs.semanticscholar.org/1026/cd3db0ee888fdd505a8f1e4204cd426106ae.pdf