Line Your Own Pockets

Michael: 00:00

Hello, everyone. Welcome to another episode of Line Your Own Pockets. This is one that comes from a user question, and we actually picked it as Dave's, like, giving me, you know, ideas. We're going through our doc of what we could talk about. Like, we haven't fought in a while.

Michael: 00:14

So let's pick this one just because we've been agreeing too much. We've seen the comments. The audience seems to like a little spirited back and forth. And at least initially, I know there's gonna be some disagreement on this whether or not we, you know, hug and make up after, we'll we'll figure that out. But, yeah.

Michael: 00:34

So why don't you kinda talk about the question you got, and we'll go from there.

Dave: 00:39

Alright. Yeah. This question is from Helena, and she asked very simple question. Should you include delisted stocks in your backtesting database? Yes.

Dave: 00:50

So I think you're I can tell you're gonna have the wrong opinion about this.

Michael: 00:55

Oh, okay. Alright.

Dave: 00:57

Why don't you, what's your take, Michael?

Michael: 01:00

So, yes. And I'll give my reasons why yes, and then you can say what are your wrong opinion, and you can give your reasons why you're incorrect. But the main reason being that you have a lot of things that can happen to stocks from buyouts to mergers to bankruptcies. And the bankruptcy side of thing is to me is is one of the biggest because especially if you grab a mean reversion setup, and it's something that is, you know, you're gonna buy, you're gonna hold it for a week on stocks that are absolutely getting killed, and you run that same exact system through a database that has delisted stocks and a database that doesn't, you are getting two wildly different results because you're not gonna have your Bed Bath and Beyond, which just a funny story, still to this day, you can go on Twitter. You can type in b b b y q in the little search box, and there are still to these days wackos that think that this thing's gonna come back, and they're gonna be make tons of money even though it's been bankrupt for, like, three years of as of recording this.

Michael: 02:08

But there's just tons of names that have just gone to zero overnight. Regional bank crisis of I think it was 2023, 2024, where there's regional banks were just dropping kinda left and right, very quickly can just completely change a backtest from this is something that's amazing and I should definitely trade to, oh, man, I go bankrupt periodically if I trade this thing.

Dave: 02:32

Yeah. So I have the different opinion. I think

Michael: 02:38

The wrong opinion.

Dave: 02:39

This is a classic classic case of premature optimization. Now you might think, okay.

Michael: 02:50

Wait. Hold

Dave: 02:50

on. Why would you not

Michael: 02:51

You need we need a t shirt that just says premature optimization. Yeah. And we could yeah. Okay. So I'll note that.

Michael: 03:02

We'll do that. That's hilarious.

Dave: 03:04

So I think this is I I now I know where this argument's gonna come down to. I like that you I I love your approach of running your backtests, delisted stocks and then not including them, and that's that's where the rubber meets the road. Right? For day trading, it's almost irrelevant. And, I mean, you hit the nail on the head there.

Dave: 03:32

But I think a lot of traders will come across this, like, maybe they've already started backtesting, and then for whatever reason they come across something or somebody points out that, hey, are there delisted stocks in your database? And they're like, oh my gosh, there's not. Like that, this is the worst thing that could ever happen. I need to go get those into my backtesting database. Otherwise, everything I've done is just out the window.

Dave: 04:03

And the reason I think it's premature optimization, which as we've said on this episode many times, is, is the root of all evil, is a famous quote by a computer scientist. There's a certain kind of trader that comes from a data background. Maybe they're a software engineer. They have a very technical mindset, and they require basically require perfection before they can even get started. Right?

Dave: 04:35

And I think this is a classic case of for day trading at least, requiring that level of perfection in your data is a mistake. There's other things that are have the priority that are way bigger problems. So I think a little bit of this is day traders and swing traders talking past each other.

Michael: 05:00

Could be. And and I I could definitely see you know, we could we could turn off the episode now and say, yeah, you're swing trading, you probably shouldn't. If you're if you're day trading, you shouldn't. But I can think of a couple examples off the top of my head of very specifically low float crazy penny stocks halting, k, and never coming back or not coming back for years or or longer. And depending on the strategy that the person is doing, that could be a career ender.

Michael: 05:37

So, you know, how do you take the square of the circle? Is it just, you know, the obvious solution is just, you know, don't put all your eggs in one basket. Don't leverage your whole account in a single trade, that kind of stuff. But I could see a world in which, you know, someone who doesn't know better or somebody who is just getting started ends up trading one of these things. I think there's one that's like a TCGL or QMMM.

Michael: 06:06

There's a handful of these things that just they went nuts. And then there there is a world in which you were in an intraday trade, and it just went to zero. And it's like, depending on how hard it is to get that data, which is something we should probably circle around, and I we both know two data sources that we use, and one's got them, one and one doesn't, pros and cons. But let's say all else was equal. Let's say you had to do absolutely nothing else to add those symbols in.

Michael: 06:35

They were just part of your universe already. What's the downside? You know? And just for that one in 10,000 thing that could take 30% of your capital if you end up trading if you're in a big big trade with it.

Dave: 06:50

Yeah. So I think, ideally, you would just you you would include them. But just the reality of the situation is it's just a lot easier to get the data without the delist or, you know, without the delisted stocks in there. So the way I like to think about it is, okay, I can come up with a strategy that's highly dependent on those or I can come up with one that's not highly dependent on those. So it is important to know about.

Dave: 07:23

It's important to understand.

Michael: 07:26

But how would you know? If if you don't have the data, how would you know if the system is highly dependent on them or not?

Dave: 07:32

Well, the example you gave is a a halted stock that stays halted for a long time. Well

Michael: 07:40

Forever. Yeah.

Dave: 07:41

Right. So you can have your starting universe for your strategy. You you can add rules to that universe to define it such that that is minimized. Not gonna eliminate it every, you know, all Mhmm. Every corner case that could possibly theoretically happen.

Dave: 08:05

But you can't do that anyway. So there's always gonna be something you don't know about that could happen in the future that puts you at risk. I mean, that is part of trading and that's what you have to that's sort of the underlying understanding and the underlying way that create your foundation for trading is, yeah, there's going to be some risks that you just can't control. And rather than trying to identify every single one that might happen this, in this very corner case. You're just not going to be able to think of all those.

Dave: 08:43

So I think it's a much better plan to just not worry about every single thing. Do what you, you know, control what you can, come up with a strategy that minimizes the chance of some of these things, but still just know that there could be a situation where, yeah, you get stuck in something. And the best way to do that is to just really have good risk control, good money management. You're never risking too much of your account that's gonna cause a risk too high of a risk of ruin.

Michael: 09:19

You you just made a really great case for why you should be swing trading. Just FYI, you've just inadvertently is because again, it's something else I gotta ask you too. But inadvertently, isn't all of those arguments the same arguments that people make about why they only day trade and not swing trade is that there is these variables that can happen outside the market with, you know, stocks gapping up and down and all that kind of stuff, and you can mitigate some of them. Because my philosophy when people ask me this is always, you know, there's a POET, this one stock that just like it was on a huge tear. I know a lot of people that owned it.

Michael: 10:00

Then the next day, they're like, yeah. Our biggest client just pulled out all the contracts and dropped, like, 60%. And, you know, people are asking me. It's like, okay. Why do you swing trade?

Michael: 10:08

And my argument has always kind of been the same thing is that I trade kind of small enough throughout a whole bunch of different, you know, trades and symbols at once that over the life of my career, there will probably be as many stocks that gap 30% against me as gap 2030% for me, and it all just wash and I'm controlling what I can, which is kind of the data behind it. But I feel like I should write down the other question I'm gonna ask you so I'll give you a chance to answer that. But the yeah. It's just like, isn't that the argument to why if you're sitting in cash every night, you're not utilizing your cash to the fullest potential.

Dave: 10:46

Sure. But the risk that you can control there's the real risk in trading and holding overnight is that stuff news items come out after hours and you can't trade. Those are where and those are more plentiful. And there's a very, very natural way to avoid those, and that's just don't hold overnight. So that is the default.

Dave: 11:12

I I feel way better about it. And plus you get I mean, we we don't need to go over the whole argument about why they trade and why you swing trade, but there's lots of reasons, and that's just one of them.

Michael: 11:25

I'm just every time I see an opportunity, right, I'm just I wanna keep, right, throwing pebbles at that crack I see in the armor until eventually Dave goes, listen. I got this strategy because that will be the I know the gateway will be like, man, with these twenty four hour markets, I got something that buys the close and it puts out a limit order and then, you know, captures a little bit of the post market, and that post market will become like the extended post market than the twenty fourth. Like, He's man, I just hold this thing for three days, it's a it's a better so I'll I'll get you there. But the question I did wanna ask is, okay. And this might just be a how data sources deal with these things, for example, is something like Bed Bath and Beyond, which we already picked on, went bankrupt.

Michael: 12:10

For some reason, another company, Overstock, said that's great IP, the the the defunct bankrupt company. Let's become Bed Bath and Beyond, change our ticker so that it is the Bed Bath and Beyond's old ticker and just continue going from there. So in situations like that, like mergers or or changes or whatever, do you ever worry that it's affecting the data going back where at some point in the backtest, like Bed Bath and Beyond was gonna be this one thing, and now it's gonna be a different thing. And I'm thinking of things like averages. Like, so say, you know, the average volatility of Bed Bath and Beyond the day the ticker change would have been huge because it went from a, you know, 5¢ bankrupt stock to like a real $30 company or something like that.

Michael: 12:57

And that by not incorporating these corporate actions in your dataset, periodically, again, not commonly, but periodically, you could have something where just because the name changed, the character of the security change, and you end up thinking something's a gap that's not a gap, or thinking it's a volatile move when it's not. The other example I could give here that probably make more sense is these SPACs that just always sit around $10.

Dave: 13:24

Yeah.

Michael: 13:24

And then all of a sudden, they're a real company, and then they start moving like a real company. Those type of things, it's not as big now as it was, but I remember in 2021, different data sources would deal with differently. Sometimes you would go to what the ticker is now, and it would lose all of the data going back, and sometimes it would keep it. And I always liked seeing it because as soon as the company was announced, it had a trading entity, and then the name changed, but it was just a name change, so you can that consider trading on. So by just, like, ignoring corporate actions the best you can, is there, like, any of these edge cases that you're worried about?

Dave: 14:04

Well, if I was string trading, I would be worrying about it because, I mean, think about when all those announcements come out. They come out after hours. They're not gonna Yeah. That's not gonna happen in the middle of the day.

Michael: 14:18

Yeah. But just to just to clarify my point is that, you know, a company went from, I don't know, rumble. Right? With something else beforehand and something now. So if you have any anything in your calculation that uses a daily ATR or a daily moving average or any sort of, you know, calculation of a gap or this is what yesterday's candle looks like or any of that, which I can think of tons of day trading strategies that do that, you just would either miss those, which, you know, how much money are you leaving on the table, or even worse, you could just be wildly wrong and and taking trades based off of an ATR that is not a true ATR because it's looking at, like, old junky data because it didn't include this delist, relist thing.

Dave: 15:06

Yeah. So my philosophy for handling that is I have strategies that make a lot of trades, and any particular trade is just not gonna matter that much. And that's that allows me to live with that small risk because it's really small. And, it and the data that I use to back test, yeah, it's not perfect, but the data you're using to swing trade isn't perfect either. I mean, when you do a symbol change like that, when it comes down to it, there's some subjectivity about what how you treat the day before that and after that.

Dave: 15:51

There's no I mean, you can go down the, the rabbit hole with unlimited resources to try to solve this problem algorithmically with all these corporate actions. And you're not gonna get to a perfect solution, I can guarantee you, because there's all sorts of edge cases that just make no real sense, and you can't come up with something that's sort of, continuous across days. So rather than try to solve that whole problem, I create strategies that minimize it so I just don't have to worry that much about it.

Michael: 16:25

I don't know. That could just have been a that could have been a big grant of, I'm just too lazy to worry about.

Dave: 16:33

Well, that's oh, I wouldn't lazy. Yeah. I mean, laziness is a virtue. Right? I I could could spend a whole lot of time looking at correcting some of these minute, you know, very small things, but it's not worth it because I know I can create strategies that minimize it and I just don't have to worry about it.

Dave: 16:56

So it's like, you know, it's like a fart in a hurricane. Right? You it just doesn't really matter that much for the kind of stuff I'm doing. But like like you said, though, for swing trading, it's gonna be massive because the whole point is you're holding overnight. That's where your edge is coming from.

Dave: 17:15

And and most of the time, it's on the long side. So a bankrupt company that isn't in your back test that would have matched your rules, that's a huge deal. It's gonna make a massive difference.

Michael: 17:28

Well, and

Dave: 17:29

you So in that case, I would like, my like, it would be a hair on fire emergency. Like, I would I would say that.

Michael: 17:35

I use that example for simplicity. The real killer that I've seen is actually to the short side, in which a company gets bought out, and then it generally will just get removed from old datasets, and then you don't get that. So you don't get the, you know, the company that goes bankrupt could be a big deal. But the company that gets bought out for 200% of of what it was trading at the day before, that could be just a a career ender because you're short this thing that's kind of quintupled in value. But I guess the real kind of question is, because you kinda said it yourself, if if you didn't have to do much or any extra work, you would just do it anyway.

Michael: 18:18

Yeah. Why we had someone here from IQ feed. Like, why don't they have so for anyone who's wondering, if if they're like, man, I'm in the swing trader camp, and I don't include the back tested data, now I'm scared. Yeah. What do I do?

Michael: 18:37

I always just recommend Norgate. It's what I use for my daily data. They include every company, I think, going back to, like, 1950 that used to exist, and you get all of this. So you get and if you're doing constituencies, say you're trading like S and P 500 names, it will include if you say I want to entest whatever was in the S and P five hundred twenty years ago, it knows what was removed and added the the whole time. So it keeps those going as well.

Michael: 19:08

But, yeah, why not why not IQ feed? Why can't they do the same thing?

Dave: 19:13

I think they could. In fact, I'm I'm in talks with Trent to to fix some of the data that they have to make that that part easier. Yeah. I mean, it is kinda curious that they've been around so long and have some holes in their data or, you know, at least ways they could be doing it better. There's maybe it's because they hadn't had as many competitors.

Dave: 19:43

I mean, e eSignal competed with them for a long time. Now they're sort of it seems like they're kind of out of that game. But, you know, now they've got Polygon, which I guess I'm gonna start calling massive at some point. Yeah. And not Polygon.

Michael: 20:01

It's Facebook. It's Google. It's not Alphabet. It's Google. It's it'll be Polygon.

Michael: 20:06

We'll just leave it inside the

Dave: 20:08

So Polygon has you know, they've got adjusted data, unadjusted data. They've there's some and they've got a whole bunch of data that you can get that handles all this, including delisted stocks. So, yeah, I think that's I'm hoping that that provides some competition for IQ Feed to tighten up some of the stuff they're doing.

Michael: 20:32

Mhmm. Because my my initial reaction, but then I was like, that wouldn't make any sense, was just the amount of data would be much more. Right? Because you would you would have, at some point, a company that existed for a long period of time that's just not being measured in their dataset that they just kinda drop off. So the further back you go, I would in my brain, I was like, yeah, there'd just be more and more data the further back you'd go.

Michael: 20:58

But I'm like, that's not right because for every bankrupt company, there's an IPO that comes out. So it's probably just somewhat the same or or kind of equal throughout, whether it was just a way to account for it. So when, you know, again, if you're using Norgate inside, all they do is they amend the ticker to the date of delisting. So, like, you know, there there's a real BBBY in which when they change the name, they go and they they fill all the data back for that. But then there's the BBBY that has like dash and then whatever the official day of of delisting is.

Michael: 21:36

So it just seemed like when I was looking through their data, I'm like, that's a simple, elegant kind of solution. And I was just kinda wondering, well, why doesn't everyone do that other than the fact that going back might be a little bit hard, but, like, yeah, if Norkey do can do it, why not why not everyone else?

Dave: 21:54

Yeah. One thing is you were talking that just reminded me. May maybe part of the issue is that, you know, if you're starting right now, yeah, you're not gonna have the delisted symbols. But if you started two decades ago, like I did, you've got this database that, like, you know, BBBY was in there. It stopped backfilling data.

Dave: 22:21

So I mean, the data's in there. So it's it's almost like when you're starting from scratch, it's important, but every day that goes by, it's a little bit less important.

Michael: 22:32

Yeah. You know, assuming that when you, you know, backfill, it doesn't wipe it. That would be the only thing that, you know, you'd need to go back and check is Yeah. We'll wipe it. Can you find a BBBY trade from this long ago and that it makes sure it doesn't do anything weird to the data because kinda like, I'm thinking this is kinda technical, but hopefully I can make people envision it is that if I'm running a backtest and that backtest just includes the ticker BBBY, and it, you know, buys and sells it, well, as soon as Overstock changed its ticker to that, now there's if unless it kinda happened at the same time, if you go back in time, is it now getting confused between the two identical tickers that exist?

Michael: 23:20

Right? Because this ticker was overwrote with that ticker. And it sounds like a really fringe case, but I bet you it's one of those fringe cases that happens more than you you think it would.

Dave: 23:32

Maybe. But, you know, the the strategy that would have to be vulnerable to this would be would have to have a trade on that particular day timed perfectly to be vulnerable to it. And, I mean and even I I have seen some cases where I I come across this in a back test, and then I just say, okay. I'm gonna skip this trade that day. And my data is pretty much clean.

Dave: 24:02

Now I've I've removed something from the backtest that could be there like this weird edge case. But I mean, like I said, there's there's just so many trades that there's comfort in having a lot of trades like that. If that was the only trade to backtest or there was just two or three, I don't know, like, a a small number of trades per year, it'd be a huge deal. Like, that's completely different. It's a that trade is a higher percentage of the number of trades in the backtest.

Dave: 24:34

So it'd be really important then, but there's it's a little bit of a luxury to have a lot of traits in your back test to be able to just skip over some of these things and not, you know, go down to the nth degree to to get to the bottom of the specific issue and how to handle it. Like, just skip it. What's the big deal?

Michael: 24:55

Well, and it does show that is one of the major benefits of systematic trading that we talk about versus discretionary kind of trading. You'll hear discretionary traders that say things like, oh, man. As soon as I get over maybe two, three positions at once, I get overwhelmed. And then I'm looking down at my swing trading broker, and I'm in, like, 15. I don't know what any of the companies are or what they do.

Michael: 25:19

So there's a natural benefit to being able to I guess you could just look at it as smoothing out errors, period. The more the more trades you're taking from, you know, many different systems across as opposed to I'm gonna take, you know, three, four big trades a day and hope they work out. If you're like, well, I'm gonna make fifteen, twenty trades a day. Well, then all of a sudden, that one trade goes from one third of what you're gonna do that day to one fifteenth. And then if you're up to, like, 30 trades a day, it's one thirtieth, and then it's one.

Michael: 25:51

So eventually, every individual outlier gets just buried on top of more and more instances of whatever it is you're trying to do.

Dave: 26:00

Yeah. And the real the real backstop here for me is something that every trader should be doing every day anyway, which is a daily review. I've got a reconcile process that runs my back test, compares my back test to my regular fill, the actual fills. I see, okay, what did my back test take that I didn't? Why?

Dave: 26:25

What did I take that my back test didn't? Let me dig into that and figure out why. These are important things. And then I also will run a backtest from my backtesting database, a longer term backtest. And I'll do that periodically and I'll do that comparison there too.

Dave: 26:50

And that's where these issues are going to come up. And it's not only these issues, the ones that we've identified, it's any number of other issues that you will see that will be you know, will come up in that process and you'll be able to identify. So it's like this constant backstop that is gonna if you've got a good process, it's gonna tell you what's what the issues are and where you should be looking and how big of an effect they're having. You'll see it in real time and you'll say, okay. Wow.

Dave: 27:22

This is a bigger deal than I thought because I can see it here in real time. I I could have made this trade, but I didn't, or I took this losing trade and I shouldn't have. All of a sudden you can say, okay, well, this is more the benefit of me solving this problem is worth the trade off. And that becomes crystal clear when you do that. But if you don't have that backstop, there are going to be issues that sneak through that you're not aware of.

Michael: 27:48

And we say this, I think every episode, but that's a perfect, I think, new episode to do. I think we could do a whole episode on on the importance of that reconciliation process and also in how easy it's been with AI. I could even maybe grab something from what what happened recently, but I have this thing where it wakes up every night and it runs the ammo broker and it runs real tests. So then it grabs my broker statement and compares them and writes me up a nice pretty little report that I can read every single morning, and it says, these were lined up within a margin of error. These are different.

Michael: 28:29

Here's some examples of what I think could have happened. Let's go and and take a look at them. But, yeah, it's it is just like I find there's a lot of discretionary traders out there that don't journal at all. They don't even record their data. They just think they can sit down and through like osmosis get good enough that, you know, things will will happen.

Michael: 28:48

I know so many systematic traders that just don't have, they spend the whole time and back test, and they don't have that reconciliation back. Yeah. And and they're wondering why they're underperforming or even just performing poorly, period. As opposed to, yeah, if you had just, you know, sat down and and done that, it becomes it shows glaring issues very quickly and makes them very abundant what especially if, you know, the P and L is way higher on the backtest side, which I've had it happen just by accident the other way. But when it's like, hey.

Michael: 29:23

You should have made $10, and you made one. There's no better motivation to holy shit. Where where's my $9 to sit down for a day and and dig into what happened.

Dave: 29:33

For sure. And that's you know, the back test is such an awesome reference for that exact reason.

Michael: 29:40

Mhmm.

Dave: 29:41

And that's really what separates systematic traders from discretionary traders. Think about, like like I say, you hear me say all the time, what's your path to confidence? A discretionary trader's path to confidence is way longer precisely because of this. You have a back test that you can reference every day. And instead of, you know, evaluating your performance at the end of the day and say, okay.

Dave: 30:07

Did I make money or did I lose money? That's my measure of success. The measure of success is, okay. How well did my trading follow the backtest? That's success.

Dave: 30:18

And you that's a huge confidence boost. It's a completely different mindset because you can have a day where you lose money and still feel successful about it because, okay, it matched the back test. I know what this back test does because I know it goes up into the right. It doesn't matter that I had a bad day. What matters is that I'm matching that back test closely.

Dave: 30:40

Mean, it's a it's a it's an enormous difference in mindset for traders.

Michael: 30:44

Yeah. It is. And it's funny. I actually have in this AI prompt, it has a pass fail condition, and that's the pass fail condition is how closely within, right, some margin of error did it did it make. The whole comparing yourself to whether or not you make or lose money is something that, right, I fell into when I this discretionary trade a lot.

Michael: 31:06

And I know they all do because it's, you know, it's it's how do you you look at success. Oh, I made a grand a day. That's a good day. Or, oh, I lost a couple $100 a day. It's a bad day.

Michael: 31:15

But if you don't have that, you're you're tying yourself to randomness, and you're whether or not you're achieving a random result ends up being whether or not you feel good. Whereas a systematic trader, there is a a clear kinda set in stone, these are the trades that should have taken place. And you have a bar that you can actually get to and reach. Whereas with discretionary trader, the bar you're trying to get to is just like, did I predict the coin flip well? Am am I a smart person or a bad person?

Michael: 31:49

Because did I you can never come up with a system to predict the coin flip well, but you can make sure that you're really close to your backtest. And then over time, your backtest ends up making you making you money.

Dave: 31:59

Yeah. Yeah. Like I said, I I know you know, there's there's discretionary trade people think we're, you know, crapping on discretionary traders, but but I've seen some discretionary traders that are really, really, really good, but they've been doing it a long time. And they have this intuitive sense about the market from their experience, and that experience takes a long time to develop. So for new people coming into the markets, it's just a much quicker path to success because of this way you can, the systematic way of running a back test, seeing all of a sudden what happened over the last ten years.

Dave: 32:45

That's how you get confidence in a strategy and and enough confidence to put money at risk quicker and and grow your account quicker.

Michael: 32:54

I would argue, and this is I've done it. I've done it to some discretionary traders that I know that do really well to their phase two where I'm like, you're just a systematic trader in denial. Like, you know, there there'll be people who come in and they they make a lot of money in the market, and they're like, oh, yeah. I'm purely discretionary. And then I'll ask a question about, like, you know, tell me about the day.

Michael: 33:13

It's like, okay. Well, I I first, I take a look at these charts, and then these are the indicators I use to measure, you know, my candidate that I could trade that day. And then from there, I look for this thing to occur intraday in order to take a trade based off the candidates. I'm like, that's a system. You've you you just don't you don't have the back taste of the test of data.

Michael: 33:32

Maybe there's some discretion that kinda happens on the fly. But I'm like, you're 80% of the way there. You just, for whatever reason, don't wanna take on the mantle. The the pure discretion, the people who think that eventually you can just sit down in front of a chart and guess whether it's gonna go up or down, that kind of those are the people that that come and go. So my argument to those people is that they are systematic traders anyway.

Michael: 33:58

They've just got there in the way that you said just through, you know, bleeding and trial and error and beating their head against the wall, and eventually they have a system, a series of things that they've proven to themselves work. But they all come in every day, and and the best discretionary traders are, like, insanely ritualistic. They have these are the steps of the things that I do, and then this is the output from it. And I'm like, well, again, you're just you're a systematic trader. You're just in denial for now.

Michael: 34:26

I was like, you you you can keep going and pretending that you're doing this discretionary, but it's your system.

Dave: 34:33

You know, it does it so a lot of traders, it probably sounds like splitting hairs or that they are really the same thing. But there is some it's it's a bit of a philosophical and esoteric topic, what the difference is. I think there is a difference. And, you know, we're gonna have a guest on the show. I'm not sure exactly when we have it nailed down the date, but he's a very good discretionary trader, and he's a very good systematic trader.

Dave: 35:02

So I'm very interested to talk to him, and and he and I have talked. I know there'd be some good info from that because to talk to talk about the differences because it's it's kind of rare to have somebody that's good at both. And it'll be good to hear his take on this exact topic.

Michael: 35:22

That's interesting. So that's a nice little teaser. But so we went a little off topic there. But I I think at the end of the day, what we landed on is if you are swing trading for the whether or not to include, definitely, because, you know, there's a lot more overnight things that can happen, bankruptcies and mergers and and all of that. If you're day trading, probably don't worry about it.

Michael: 35:46

Maybe we'll actually get back to this topic when the inevitable twenty four hour three sixty five markets hit because does that change things entirely? I don't know. I haven't thought that much about it. But the yeah. At the end of the day, and then whether or not your data provider can do it, whether or not it's it's an interesting whether or not your trading strategy needs it, and whether or not your data provider does it.

Michael: 36:11

So the last thing I'll just say out from the swing trading side of things, if you're not shorting and, like, say you're someone who's just buying breakouts, generally speaking, it's gonna be less of a problem because there's not many companies that go bankrupt from, like, above a two hundred day moving average at all time highs and just disappear the next day. It's more gonna be if you're mean reversion or or buying that kind of stuff. So there I think there's there is a lot of ways that you could kinda skate around it and make it a rare enough occurrence that maybe it doesn't matter very much. But if you're swing trading, just get Norgate data, and they take care of it for you. If you're day trading, maybe don't worry about it that much.

Dave: 36:49

Yeah. I think the main takeaways here for me are evaluate the cost and benefit. Don't like sweep this under the rug, but take an honest look at it and maybe it, maybe the benefit of going through the work to do this is worth it and the extra cost. If so, do it. But also don't require perfect data to be able to do anything at all.

Dave: 37:18

Like, that's also a mistake. So, yeah, I think you and I think that where I would land here is with day trading, the benefits probably not as much for swing trading. The benefits going to probably be immense. So I think just the cost benefit analysis of both is going to be different. And I think that decision point is where the difference lies here.

Michael: 37:47

Alright. So I guess we're I guess there will be a podcast next week because we we made up to the end. That wasn't

Dave: 37:52

Yeah.

Michael: 37:53

We gotta find something else to to fight about maybe a little bit harder to take a little break or something because we're so mad at each other. But so, yeah, we landed on something that makes sense. I hope that in a very rampant way. It's funny as I look up, we're like, it's probably gonna be a really short episode because we're gonna fight for a bit, and we'll find a middle ground, but we did it. So I hope that answers your questions.

Michael: 38:14

As always, we love questions. So wherever you're seeing this, right, you can comment. We always read them. We, you know, take them and add them to the doc, the ones that we like. And yeah, it's it's a great way to know what you guys wanna talk about because we're just sitting here chatting so that you guys can listen.

Michael: 38:32

But as always, I'm Michael Nauss.

Dave: 38:35

And I'm Dave Mabe. Talk to you next week on Line Your Own Pockets.