Trading and investing can be a very emotional game. If you’ve ever had a single dollar of your own hard earned money in the markets, you know exactly what I mean. This leads to the next logical question, “what can be done to remove the emotion?” There is certainly no perfect system to do it, but one way is to get so focused on the numbers and data, you almost forget to have emotion. In this episode I welcome back fellow member Sean who is all about the data. To his credit though, he admits that even with a massive deep dive into the data, there can still be hiccups that arise. I enjoyed this talk and I’m sure you will too. Sean had no problems talking about his hiccups and (most importantly) what he learned from them. Let’s get to it.
Clay: This is the Stock Trading Reality Podcast episode 273.
Announcer: This is the Stock Trading Reality Podcast, where you get to see the realistic side of a trader’s journey. Get inspired and stay motivated by every day normal people who are currently on their journey to trading success. This is your host, his mind was blown after staying at the Marine Base, Clay Trader.
Clay: I mean, I guess I don’t know why I’m so surprised. It was a military base, but in my mind, I guess I had the old Westerns where you have the planes and then you have a fort, seeing out on the planes, and it’s got the basic four walls. Do you know what I mean? Anyways, military bases, I mean, I’ve only been on one, so I have a sample size of one, which that’s a pun that will make more sense here in just a second, but my mind was just blown by it.
Clay: I mean, there’s grocery stores. We ate at Panda Express for lunch. You have all these Marines walking around in their uniforms. I mean, it’s literally a city. It’s a little city surrounded by fences and Marines with guns, and people, they’re prepared to kill you with their bare hands. It’s good Marine stuff, but the best part, I think the best part was no taxes, no sales taxes.
Clay: So, if you’re looking to buy a big screen TV, a computer, anything of higher price, you know what? Find somebody that is a Marine or, really, I guess any military person and be like, “Hey, can you invite me on the base so I can make a purchase?”
Clay: So, as soon as I heard that, no sales tax, I was like, “So, where’s the car dealership?” Unfortunately, there are no car dealership. So, you can’t quite go that far. See, they’re one step ahead of me. Just when I think I’m going to get the system to work for me, “No, Clay. There’s no car dealerships on the base,” but I was very impressed.
Clay: I mean, not to mention, it’s pretty cool when you’re just walking along and my brother-in-law who I went out there with to see our friend, he’s a judge out there. He’s worked his way up through the system, started off as a JAG, a lawyer, and now he’s a judge, which is crazy, but we’re out there hiking. There’s cobra helicopters flying over and ospreys. I mean, I thought I was in a movie. I want to start rolling around on the ground and army crawling, but it was awesome.
Clay: So, I mean, if you live on a military base, for us mere mortals out in the real world that aren’t, I mean, I think it’s pretty sweet. When I came back, I was telling Nate who I work with, who’s the producer of the show, “Man, the military base had this, and then we had Panda Express.”
Clay: So, let me put it this way. I’ll end on this point. If you ever get a chance to check out a military base, this was Camp Pendleton that I was at out in San Diego area. Really, any military base, I would say definitely check it out. It’s a crazy experience.
Clay: Now, earlier, I had mentioned, yes, my military base experience is a sample size of one, but sample size, that’s a term from statistics, and our guest today is all about statistics and numbers and making decisions not based on emotions, but are driven by straight up data. He’s been on the podcast before. He is Sean, his name, and he’s very spoken. It was a great time. We talked about lots of data.
Clay: Let me put it this way. I don’t want to offer up too much of a spoiler, but he tried something, it didn’t work out, but he doesn’t hide the fact. He just went with it. He shared lessons learned, and then we talked about quite a bit of other things. At the core, the underlying dynamic here is think back to a couple of episodes ago, The Power of Do, if you listened to that episode.
Clay: When you just get out there and do stuff, when you get out there and do stuff with a plan, and are just aware of what’s going on, I mean, there are so many learning lessons and you can walk away just so much better than where you started off. Even if it doesn’t quite work out and it’s a failure, that’s okay.
Clay: Don’t let a failure be just the total failure where you walk away saying, “I don’t even know what happened. What did I learn or did I even learn the right things?” So, just like I said, keep those components in mind as we go through it because, yeah, there’s number talk in all of that, but just from a practical, not even trading perspective, really, just a practical life perspective, there’s definitely some great nuggets of wisdom and experience that play out throughout the conversation. So, with that being said, let’s hear about Sean and his current journey.
Clay: Sean, welcome back to the show.
Sean: Great to be here, Clay. Thanks for the invite.
Clay: Now, before I got recording, there’s just something about … I was looking at the calendar and I saw Sean. I was like, “Okay. That name. All right. Whatever.” Then I looked at the name again. I thought, “What? What? What is going on? Why is that name just nagging at me?”
Clay: I do apologize. I feel stupid about it if I’m being honest, but you’ve been on the show before, and I apparently had forgotten, but there was a nagging something like, “Why does that name look so familiar?” I honestly felt stupid when you … because we get started, a little behind the scenes here.
Clay: I always ask people, “Hey, have you listened to past episodes?”
Clay: Most people say, “Yeah.”
Clay: Then I say, “Okay. Well, you now understand how this goes.”
Clay: Then Sean says, “Well, yeah. I’ve actually been on the podcast before.”
Clay: I’m thinking, “Oh, okay.”
Clay: Well, that makes me feel better that I’m not going crazy by seeing the name. So, Sean, I do apologize.
Sean: No worries.
Clay: Okay. Well, thank you for not making me feel like a total moron. All right. Well, you’ve been on. We were just talking just very briefly. It sounds like you’re just going to shoot straight. You’re not going to try to paint any pretty pictures. I’m excited just because that’s the whole idea of this is The Stock Trading Reality Podcast. We’re going to hear some good solid reality, and you’re very clearly a bright guy given your software engineer. So, in no means am I worried for your wellbeing about your future prospects or anything like that.
Clay: Like I said, you gave me a very cliff notes version of things. I look forward to digging into it. I guess I’ll let you pick up from wherever you think it makes the most sense.
Clay: Maybe give people a little recap of the last time you’re on, if you can nutshell that, and then help build some context for listeners.
Sean: For sure. So, I think the last time I was on it was February of 2019. The episode was pretty much around data, making decisions based on data. Long story short, before I started to pick up options trading, I’ve been using my own algorithm for stock investing, and it’s been very successful. I’ve been doing for about four years on the side, of course, with software engineering, which has been my primary career for about 15 years or so.
Sean: I’m like, “You know what? I want to see if I can apply the same type of algorithm to options trading.”
Sean: So, I started getting into different courses and I let you know at that time that, hey, I’ve tried other courses, but they were not as in-depth as your education. I really liked your courses, and thought they provide a lot more details. So, anyway, to bring everybody up to speed, I did apply the algorithms, if you will, to options trading, and I started out with paper trading, and I was profitable on paper, but then I set a limit like, “Okay. So, let’s see if I can actually do this and become profitable.”
Sean: I fortunately have other streams of income, so I compartmentalized different buckets of revenue, if you will, and say, “Okay. I’m going to set aside 5,000. I’m going to see if I can do this with options trading,” and through the duration of four months, I ended up losing. It wasn’t the full 5,000, but it was about 4,500.
Sean: I’m like, “Well, you learned a lot, but you’ve proven, Sean, that you’re not as good at this as you thought you would be.”
Sean: So, it was a great learning experience, but I figured we can go from here and just unpack the details of lessons learned and see where it goes from there.
Clay: That’s perfect, yeah, because I definitely want to … I mean, yeah, I guess I agree with the saying, “You learn more in the loss than you in the wins,” sometimes, but at this part, you’re a very analytical person, and you love spreadsheets, right?
Sean: This is correct.
Clay: Okay. It’s coming back to me. I’m like, “Okay. Yeah, yeah. Okay. Yes.” I did run a search while you’re talking. I couldn’t remember exactly what I named the podcast, but it’s all starting to come back to me very vaguely. You were the very, I want to say the name of the podcast was Making Decisions Based on Data or something like that, but-
Sean: Yes. That’s right.
Clay: Okay. So, all right. Good. Now, the light bulb is coming back on for me. So, I guess what … I’ll let you maybe … My main question is what exactly, what data were you searching for and how is this data being applied to the options or maybe this is going to be one of the lessons learned that you can share, but, I mean, that’s what I’m looking at or wondering right now is how exactly, what data were you collecting, and then how is it being applied to what you’re attempting to do? Like I said, if that would take us off on a tangent that doesn’t work, then I’ll let you take it from where we think it makes most sense.
Sean: Yeah. So, I’ll start at a high level, and then we’ll go a little deeper. So, just to build a quick comparison here, when you have historical data within the world of stock investing, you can use that to your advantage and you can calculate a trajectory of a stock. It’s not going to be the trajectory overnight like what is going to be tomorrow or the next 30 days. It’s going to give you a longer horizon like we’re talking out six months to several years.
Sean: You can make a lot of money that way within the stock market, but, again, it’s a longer term horizon. So, I thought, “Okay. Maybe I can tighten up this algorithm and apply it to options trading and try to forecast a trajectory over the next 30 days or less. That’s really hard to do because the volatility of stocks, especially over the last summer, there’s a little bit of activity with the trade war and a certain president that likes to send tweets out left and right. You can’t judge where things are going.
Sean: So, anyway, as I jump into this Excel sheet now, what I would do is I would look at variables like the current IV. You have your own term for this, but I think we touched on it briefly, is the IV magnet. You may recall that a little bit, but that’s where things are going. I also like to look at three-month high, one-month high, just to see if there’s any trends, and I can run it through an Excel sheet and see where things are going.
Sean: Long story short, on that short of a time horizon, you just cannot and you really have to rely on charts. Again, I was never good at reading the charts to make a profit in options, but that’s pretty much where I arrived after my analysis of even trying, let’s say, single calls, bullet point credits, and iron condors. The data variables I had applied to each strategy, you could find the most boring stock that’s not really going anywhere, and even an iron condor wasn’t profitable.
Sean: So, I feel like in this world, correct me if I’m wrong, in options trading, in short-term horizon, you have to pay closer attention to charts as opposed to leveraging data. That’s where I arrived at least.
Clay: I mean, in short-term, what were timeframes were you-
Sean: 30 days or less.
Clay: 30 days or less? Okay. I thought that’s … Okay. Yeah. Exactly, because I mean to your point, all it takes is within a sample size of that small for the price of just potentially bleep upper, jump something, and you could get not even a single outlier, but I mean a couple can really start to throw stuff off if it’s only 30 days. I mean, a couple of bleeps, obviously, over a huge amount of time, I realized I was speaking to the choir. You understand statistics just fine.
Clay: Yes. So, I would agree with that conclusion. I’m glad you bring that point up because there are some people that they make it seem like charts don’t matter at all, and it’s all, everything is data-driven. You just look at the statistics. I’m not saying those people are wrong at all, but I do think that there’s always that fine line where it’s just like I could never sit here and say, “Listen, all you need is a chart, and you don’t need to do anything else. Look at a chart.”
Clay: I mean, there’s extremes in both directions, and I mean, I would agree that our chart is the holy grail. No, but it is solely data under the premise of 30 days like you were talking. Is that going to be the holy grail either? It doesn’t sound like it because like you said, there’s just too many little variables I can cap in and then threw off the data. So, I mean, it sounds like that’s pretty much what you were experiencing then.
Sean: That’s correct. If I were to really break it down and easier terms to understand for the audience, anybody listening, I would say it’s probably the 80/20 rule, 20% data. You want to pay attention to some of those variables I listed before. Your bid ask spread, of course, you’re looking at those elements, and your current IV and some of those data points, but the 80%, I really feel like, and this is my assumption is if you want to get good at options trading and short-term stock trading, it’s charts. It’s got to be charts.
Sean: Again, going back to the algorithm I wrote for stock investing, it is sound, and I’ve proven it, and even back tested it for 20 years all the way through the dot come, bust into the recession. Works perfect, but short term, it doesn’t work that way. It’s a whole different game.
Clay: Short term, are you talking about just for stock options? Are you talking about even for stocks that algorithm?
Sean: Stock options and stock trading. Anything I would say if you’re in by short term, I would say short term to me is probably 90 days or less. So, if you’re running an options trade, and I tried a lot of different options trading within 30 days, but even looking at 90 days, you really can’t predict it because the volatility is just … It all goes back to reading charts. That’s what I feel like.
Clay: Yeah. No. You’re absolutely right because, I mean, at the end of the day, if you’re trading in a shorter term timeframe, and as obvious as this may seem, I mean, you got to know what direction the price is going to go within a relatively short amount of time. To Sean’s point, to which I fully agree, a chart, holy grail, absolutely not, but is it worthwhile? Is it a valuable tool to use to help you answer the question? In the next X amount of time, 30 days or 90 days, what do I think the price is likely to do? Well, I mean, a chart can definitely be very beneficial in that.
Clay: So, my question, though, and I’m curious. So, the algorithm that works, it sounds like, I mean, you’ve back tested it for the past 20 years through the dot come bubble and all-
Clay: Yeah, recession and all that. How much of that has to do with the market just tends to go up overtime anyways? I mean, is that playing a big role in it or I mean, do you know what I’m saying?
Sean: You mean like is it calculating volatility or we’ve been a short term?
Clay: I guess if I’m putting together a photo school here, Sean, don’t judge me. I don’t understand coding. I don’t understand. I’m not a software engineer, but if I’m writing a program, and this program is looking over an immense amount of years, and over that immense amount of years, the market has trends it up, which the market just historically does ever since there was some tracking back in 1990, whenever that was. I mean, the market does go upwards. There’s some massive dips, there’s some nastiness that occurs along the way, but overall, the trend is up.
Clay: So, if a computer program is based on huge amounts of data and over that huge amount of data there’s an overall uptrend, I mean, is it almost like a self-fulfilling prophecy within the algorithm itself or like I said, I may be totally misunderstanding, but does any of that make sense to a professional like yourself?
Sean: Some of that does. I can go into a little detail here on how it works. With the stock markets investing, you’re looking past, for instance, while we’re recording, everybody’s in the middle of this COVID-19 issue, and this has caused a lot of volatility with the stock market, and a lot of stocks have fallen, but what it does is this algorithm past all this. It looks at the intrinsic value of a stock. We all know what the market price of a stock, for example, let’s say PayPal. PayPal is just shy of, I think, 120 today. That’s the market price, but that’s not the actual intrinsic value.
Sean: The price looks at that stock’s value, and where it’s going to most likely land within the next one to 10 years. So, it’s really a buy and hold strategy. So, your time investment is very minimal, but it finds stocks at having very high probability of going high. So, when you invest in those stocks, you’re not making what a financial planning gives you, which is 6% a year. We’re talking big percentages like 15%, 20%, 25% up to 50% return per year, which that’s higher than a lot of hedge funds, let alone financial planners.
Clay: So, what is intrinsic value? I mean, how is that being defined? How is that being calculated or what are the primers for that within the algorithm itself?
Sean: Yeah. So, some of the variables that go into that trajectory is the growth rates, and you’re looking at different growth rates, including your revenue growth rate, your EPS, earnings per share growth rate, equity growth rate, your ability to keep debts at a minimum. So, it’s factoring all those variables in.
Sean: Full disclosure here, even though this is something I put together, I’m a research guy first. So, I give all the credits to guys like Benjamin Graham and Warren Buffett, and Charlie Monger. These guys use these same algorithms. I’ve just taken them and put a little more rigor around them, and just made my own understanding out of it, but it’s really inspired off guys who have gone there and done it before me. So, it’s not like I’ve reinvented something completely new here.
Sean: There’s guys that I work at hedge funds and they don’t allow any of this out to the public. I mean, this is their own strategy. They keep it internal. They do this, and they provide the service, but they don’t tell their clients what the actual algorithm is. I’m a self-directed investor. I don’t have a hedge fund, and I’m not a financial planner as we speak. So, I do this because this is a lot more profitable than working with a financial adviser or wealth adviser.
Sean: The self-directed adviser market out there is probably like a lot of the people who listen to your podcast. They do it yourself, right? They’re not going through somebody. They options trade on their own or they stock invest on their own.
Clay: No. You’re absolutely right. So, going back to the options that you tried, so were you trying to tie some of the options value to the company growth rates and the debt and all that sort of stuff or was the option stuff just strictly data-driven based off price action, for example, over the past 30 days, and that was the number you’re using? I mean, what was the … Let me ask it this way. What was the difference between what you have set up for stocks and then what this options algorithm was? I mean, what were the minor tweaks? Was it just the timeframes or was there other bits of data that were tweaked?
Sean: It’s different data. It is looking at that, the price changes over the last 30 to 90 days. When you’re looking in Thinkorswim, you can see a lot of this. Using that to apply the same methods, but the data is completely different. So, it’s really doing a lot of [inaudible 00:21:29] error which is really how it works when you’re writing something like this, and just determining, “Okay. Does this work? Does this work?”
Sean: I was starting to, and this is when we talked last, you brought up a great point. I was like, “Wow! I’m really consistent here. 80% of the time I’m profitable.”
Sean: You were like, “Yeah, but this is beginning of 2019 and everything is going up.”
Sean: I was running single [inaudible 00:21:58] and bull put credits at that point. So, really, most stocks at that point, yes, you’re right, but we hit some turbulence through the summer, and the algorithm was shot. It couldn’t do anything there. That’s when I knew that, “Okay.”
Sean: I pulled as much as I could from those different price points you can see within Thinkorswim and applied them to this algorithm within Excel, and still, there’s no way you could use just data alone, so I had to pivot and start using charts and even through the volatility, even the chart reading, I was like, “This is Greek to me.” I just could not find something probable within 30 days or less.
Clay: Yeah. I mean, that’s right. I thank you for bringing that up because you’re right. It’s a situation where, I mean, if you’re not careful, data can be very deceiving, depending on the environment that you’re in. As you disclosed the environment you’re in was very much so just not … I mean, it was accurate, it was a real environment, but it wasn’t a real environment in the sense of, “Well, this is not how things normally are.”
Clay: So, that may not seem like it makes sense, but it does make sense, is it? You’re getting data, but is it actually, I mean, is it the most accurate of data based on circumstances? I’m glad I was right at least about something. I made that up. If I told you, “Well, right now, the markets are basically going straight up,” but you’re absolutely right. It’s just little things like that, little nuggets. That’s so true. I get it all the time.
Clay: People, “Hey, I’m paper trading. I’m back testing this, and I’m doing this, that, and the other.”
Clay: What they’re doing works, and you’re sometimes, “You’re just a hater.”
Clay: It’s like, “No. I’m not a hater. You need to consider these other variables.”
Clay: So, this is why I’m really enjoying this, Sean, because you’re just flat out saying, “Yeah, these other variables exist and they can throw a monkey wrench into things,” and like you said … What word did you use? Turbulence? When some turbulence hit, yeah. Sounds like turbulence can tear up a computer code pretty quick.
Sean: Yeah. Totally. At the end of day, it’s really fun to get in to the data and see what you can do with it to try to provide value. So, at the end of the day, even though options trading isn’t something I really do anymore, but understanding options and really the training that you’ve provided has been invaluable because it’s like a compliment to stock investing. You have more a stronger grasp around the stock markets and the different ways that it works, and how stocks can be profitable for companies and individuals.
Sean: So, you get a bigger picture of things. So, even though I don’t really use it to directly make a profit indirectly, I feel like it’s helped just because the understanding of all the different strategies as you go through on your site that are available to generate your own revenue. There’s some guys that do it and are extremely profitable. As we both know, there’s a lot of bet on that.
Clay: In fact, most are not, I mean, if you’re just really being brutally honest about it. That’s why just a question. How much have you really dug in to charts? I mean, you clearly know what they are. I mean, are you just somebody that’s, “No, I just want to stick with pure data. I don’t want to worry about …” No. I mean, charts are data, but there is a visual component to it. Whereas it seems like you don’t want any visual components at all. You’re just, “I want numbers and numbers alone.”
Clay: I mean, how much effort, how much really time or what have you have you put in to technical analysis and the use of charts to make decisions?
Sean: Yeah. That’s the magic question, which I figured you would ask, which is I spent about one month on charts, which I know is not enough, but it was enough for me to, as I wait my time investments of learning charts against my profitability with stock investing, that’s when I made the decision, “Okay. I bet I could get good at charts if I really invest in some time.” I’m talking six months to a year, just trial and error paper test, a really big time investment for me at this point.
Sean: I decided, “You know what? I’m going to pause that. I respect what options are, but I’m going to stick to what I’m good at.” That’s essentially what I did.
Clay: Got you. So, it was a matter of you need to … You mentioned, and it does makes more sense given that you mentioned earlier on that you have multiple streams of income. So, you’re a person, and I understand I’m the same way. When you have multiple streams of income and when you have multiple things going on, you do have to take that calculation of, “Is the time that I believe … Is X worth what I think could come with Y?” In your case, that does make sense. You just thought, “You know what?” Because I do agree with you.
Clay: One month, yeah, you’re not going to become technical training expert in one of month of charts, but I do also understand the respect, your angle of, the time commitment is just not worth it. I mean, do you ever see giving charts another go or trying to do more technical training? Because I look at it as, I mean, if you could understand the charts and really truly figure out what’s going on and then build an algorithm around that, I mean, who knows, maybe there is something out there where 30 days or 90 days or less it could potentially work out or I mean, do you ever foresee that happening or you just got way too much other stuff going on?
Sean: I do. As I mentioned earlier, I’ve been in software engineering for about 15 years. I’ve worked for probably bigger businesses the last 10 years, one of those including GE. I’m fortunate, especially right now, to be very busy with work, but I have an exit strategy here to go off on my own. When that happens, my free time could free up a lot, which means, yes, I can dive in to the education with charts. So, I’m looking forward to that day, and that will happen. It’s just a matter of time at this point.
Clay: No. I love that you got exit strategy things. You got stuff going on, and that’s what I like to hear. So, bringing back to … because the lessons learned did … How long and I apologize if I missed this part, but how long did the experiment go on before? I know you said you didn’t lose all 5,000, but it’s how you waved the white flag. I apologize if this is a miss, but how long did that go on?
Sean: No. We didn’t talk about that. So, I started learning options. This was just before we spoke, which was February of 2019. So, let’s just say January 1st. I probably focused on the algorithms, trial and error probably for about four or five months, and then I went another … Let’s say it’s five months just so we can arrive at the six-month mark. So, then I did another 30 days after the five months, and that 30 days were focused on charts. So, it was really a six-month trial, and during that timeframe is when I lost the 4,500.
Sean: That’s when I said, “You know what?” I’ve heard on your podcast, and I’ve heard it on other podcasts, where people, “Well, all right. I can make up. I can make up this 4,500.” I’ve heard stories of people going into hundreds of thousands of dollars of debt through options trading, and they just keep telling themselves, “I can do this. I can get out. I can just make this up. I’m just there,” right?
Clay: Yeah. Exactly. Just one more. Just one more.
Sean: Yeah. “This is the next one.” I’m not that kind of guy. I don’t take those kind of risks. You can probably tell already, very calculated on my decision making. So, I knew I set that limit. When you lose that, it’s like going to the casino. You’ve got 100 bucks. When I lose my 100 bucks, I’m out, right? We know how many people follow that strategy, right?
Clay: Exactly. No. Exactly. I think this is why … Well, first off, your great point on why the stock market is not the same as the casino. Can it be treated as a casino? Absolutely, but just because it can be doesn’t mean it actually is, but what spread on this thought is it’s like gambling. You want to stop, but then all of a sudden you keep going. Yeah, there’s so many parallels between gambling and the market when it comes to emotions. Yeah.
Clay: To your point, I don’t want to be one of these people that, “Okay. I’m going to have it soon,” and then boom. “Okay. No, no, no. I’m going to have it soon.” Well, no, that’s the same as the gambler is going to say sitting at the table. It’s, “Okay. This next round, this next, next.” At some point-
Sean: You make it all up.
Clay: Yeah. Exactly, and, “Okay. Double or nothing.” It can be a vicious cycle. Here, Sean is in … This is why, Sean, correct me if I’m wrong, but I’m pretty sure there’s nothing you could do with the slot machine to give yourself any advantage. Could you?
Sean: Yeah. No. There’s no technical historical data that’s going to show that within the next 10 tries that’s when you’re going to make money. No. There’s nothing like that.
Clay: Okay, which is why you’ve heard of professional investors, which is why you’ve heard of professional traders, which is why you have not heard of a professional slot machine player because there … At least, Sean, we got to be honest, though, as far as where where? I mean, maybe there is somebody out there that has some system and they are a professional slot machine player, and they’re not just telling the world, but as far as where where, that’s just not how the real world works, but that’s a great point about emotion and gambling are the same thing.
Clay: So, it sounds like it was just straight up your 5,000 reached a point. I guess this is what I’m asking is it never did quite … You didn’t lose all 5,000. So, was there some glaring issue that you were just like, “It’s flat out not working,” or was that just a matter of 100 bucks left and you’re like, “Okay. Fine.” I mean, was there something that even gave you a warning sign sooner than just simply the $5,000 being gone?
Sean: It wasn’t like a definitive point. It was like going back to that opportunity cost we discussed earlier like, “Hey, focus on what’s working and do that.” I was like, “You know what? I could just keep going down this path without additional education and get more of the same.”
Sean: So, that’s why I just paused like, “Hey, let’s focus on what your time is available to focus on,” right? So, day job, number one. Second to that would be stock investing, and just keep it simple.
Sean: So, I used this as a learning activity, and I’ve done this before because I’ve invested in private tech startups. It’s the same thing. It could be 5,000, it could be 10,000, and you learn a lot through that process, and you just apply it forward, and that’s really what I look at. This is just business investment.
Sean: I was running all the revenue through an LLC, so it’s all right off, right? So, that worked out in my favor, but you look at those variables. If you’re going to be spending the money, even if you lose the money, you can still come out win. So, it’s a win-win scenario at the end of the day.
Sean: I look at any other venture I invest in, it’s the same thing like, “Okay. So, if I make money, great.” It’s a win, but if you don’t, what else do you win on and education should be one of those things.
Clay: I mean, I do agree, and I don’t know. Maybe I’ve just become so jaded and cynical being around since 2013. Like you said, everything you said is valid. The problem is I … It goes back to what we were just talking about about gambling is I feel like that’s also one of the almost get out of jail cards that people uses. So, they lose a bunch of money, then they’re like, “Well, you know what? Those are learning experience. So, I mean, that was actually money well-spent.
Clay: Now, for you, I fully believe because you are so data-driven that you are learning. The data is telling you things, and you’re making progress, but some people, most people I feel like when they get to that stage, they’re just using, “Well, that was good. I learned. So, that wasn’t really a lost of money. I gained some knowledge. Well, let me go gain some more knowledge,” and then they throw more money in the market and things spin out of control that much more.
Clay: So, would you agree? That seems like a slippery slope maybe for some people if they, again, I fully believe you, but, I mean, I can see that being a problem for others where they’re just like, “I don’t think you learned.” Let me rephrase this way.
Sean: What did they learn?
Clay: Yeah. Exactly. To your point, it goes, when you told what your conclusions were, I was like, “Yeah. No. That does make good sense.” Yeah. A chart is definitely going to be much more important in near term timeframes. That’s definitely true, but some people will be like, “Well, I took a big loss.”
Clay: “Well, what did you learn?”
Sean: What did you learn technically? Great, you learned a lesson not to lose money, but with what I said earlier, what I learned were all the different options strategies, so bear call credits, and single calls, bear put credits, iron condors. In the world of stock investing, you don’t need to know any of that. It’s good to be aware of it, but I had no idea. So, that education was huge.
Sean: Then the one strategy that overlaps are covered calls. That is the one that I’m not running any right now, but in the world of stock investing, you can make additional profit there looking at stocks longer term. It’s a great strategy. Now, I would have never known about that without going into the homework of options trading.
Clay: You read my mind because that’s where I was headed was covered call is I think so, it seems like it could be a viable thing, whatever you want to call it in your algorithm because I always look at it as you’re basically creating the dividend for yourself. So, the easiest way from a lit way, a covered call. Wait, what? Just look at it as some stocks paid dividend, but in certain situations with covered calls, I just view it as you’re creating a dividend all on your own.
Clay: Now, there’s some risk that come along with it in terms of you could actually lose the stock that you’re investing, but we won’t go down those rabbit holes. Like you said, I guess you answered the question in a form, but it sounds like you do have some interest in pursuing that a little bit more. Did I understand that right?
Sean: I do, yeah, yeah. At the end of day, yup.
Clay: I guess in what ways and I realized you probably don’t have this all planned out right now, but maybe just surface deep, just shoot in the breeze, do you have any macro ideas about what bits of data you would think that would matter to figure out just how the algorithm would work within a covered call scenario?
Sean: You know what? I haven’t thought about that. I would have to look at charts. It would be great to overlay a software to look at the different changes on the chart maybe between from day-to-day or hour-to-hour and see what the … You see trends when you look at data. You could probably tell I like talking about data here. I use it everyday, essentially, but you can see a different story to anything, to business, to the weather. That’s what weathermen uses. They use trends.
Sean: So, it’s like the same thing is there’s some thing you can do, and it will be a fun experimentation to see what those trends are, but I have no idea at this point. It would be in time investments. I have to consider that.
Clay: Yeah. Just off the top of my head, I feel like if somehow you could figure out the average growth in … So, let’s just say you’re doing a covered call that expires in, I’m just making this up, 60 days. So, if somehow you could look at what’s the average growth over the previous 60 days, and maybe factor in like a flood tractor because … Let me take a step back.
Clay: For listeners, the idea behind covered call is if a stock actually goes up to a certain price, then, yes, you make money. So, that’s good, but from an investment standpoint, which is what Sean is talking about, you would actually lose the stock out of your portfolio. So, you still make money on it, but the catch-22 is you lose money. Whereas if it doesn’t go up to a certain price, you still keep the stock, but you also make money from this, we’ll just call it a dividend right now.
Clay: So, that’s why I’m thinking if you could somehow project how far you think it could go, then maybe that could help figure out what strike price or what have you that you could sell to get the premium at. So, I don’t know. That’s where my mind goes immediately is just looking at, to your point, trends and almost over X amount or the previous X amount of days as what’s the average volatility banner or what have you, but you know this world a whole lot better than I do. So, I’m probably just throwing egg on my face right now, but not the first time, won’t be the last.
Sean: You have a good point there is maybe focus on just one strategy first. That would be the leading strategy in my mind would be covered calls and see if there’s an algorithm that could just, you could win significantly more with that than lose. I think that would be possible because that’s one of the easier options trading strategies. Of course, I don’t think you could overlay that same algorithm, if you will, over an iron condor or bull put credit. That would be a whole different project on its own, I feel like.
Clay: To your point, to me, I feel like those other things are … It’s just a hard … It seems to your opportunity cost, I don’t know, is it really worth this, that, and the other when you could just do a covered call and just keep on creating more dividends for yourself?
Clay: You know what I mean? From a risk perspective, the biggest risk with a covered call is you make money. Now, the downside risk is you lose your stock. So, that is a risk, but if you are losing your stock, and I’m not talking to you, Sean, I’m more so talking to the listeners, but as a covered call, that just means you don’t have your stock anymore, but in order for that to happen, that means the price has gone up quite a bit away into your favor and that you collect the difference and you’re still walking away with cash in the hand.
Clay: Whereas a covered or an iron condor, yes, those things have defined risk, but sometimes the risk is a big old monetary loss, and there’s a lot of things you have to weigh. Whereas from a covered call perspective, I mean, when the biggest risk is, “Okay. I just lost my stock, and I can always go and buy it again at a reasonable level,” and then they just start the whole sequence over again, I don’t know. I feel like there’s worse situations out there. I mean-
Sean: 100% agree.
Clay: Okay. Yeah. So, I guess I’m just agreeing with you that, yeah, maybe just focus on one strategy such as covered calls because that does seem to be just a very streamline way to go about it.
Clay: So, this is good stuff. Some people were like, “What are these guys …” Listen. Well, actually, do you watch Shark Tank?
Sean: I do, yeah.
Clay: Okay. You made the comment about, “Well, I’m data driven and all this sort of stuff,” but I’m thinking more people need to be data driven. In fact, I’ve read Kevin O’Leary’s book who maybe you’re not familiar, vaguely familiar, The Mean One, for your listeners out there, the guy that sits in the middle and he’s-
Sean: Mr. Wonderful.
Clay: I’ve read his book and he’s like .. From what my understanding, I know Mark Cuban feels the same way, but as soon as the entrepreneur reveals that they don’t really know their numbers like, “See you. Peace out. Bye.”
Clay: Yeah. Exactly. Dunzo, and because you’re right, and I love what you said. Numbers tell us story. They absolutely do, and I’m very visual, and that’s a technical chart is at the end of the day. I mean, candlesticks, they’re just made by numbers. Now, of course, you sprinkle in some colors and shapes and stuff like that, but that is just data. That’s a way for me to see the number.
Clay: Sean, he’s absolutely right. That’s why numbers are powerful. Kids, stay in school, okay? Listen in Math class because if there’s anything that matters in life, whether or not you want to hear it, it’s Match class, okay? Because numbers do tell a story, and that’s … I absolutely agree.
Clay: Now, before I forget this, we ran it, but I don’t want to forget. When did all this actually start for you? Not the options, but just in general. I guess I’m not asking you to give me your age, but can you give me your age in a roundabout way? I mean, how long have you been in the software engineering world and grinding and hustling with all this stuff?
Sean: Yeah. So, I graduated in 2006. I’m 37 right now. So, I started in-
Clay: So, we’re like the same age. Where did you graduate from? Well, are you think about high school or college?
Clay: In 2006?
Clay: Yeah. All right. Nice. Same here. Same here.
Sean: Yup. So, long story short, I went to work for a company, and it was an ad agency for a year, learned that business model. For those listeners out there, the most lucrative service within an ad agency is software engineering. So, ThinkApps, and websites, and all that kind of good stuff. So, I’m like, “You know what? I’m going to go start a firm like this on my own.”
Sean: Did that for four years. I grew that business through the recession, but it was the most unlucrative, most painful business model one can think of. You’re dealing with a lot of emotions, with clients, and fixed price projects and scope creep. At the end of the day, I didn’t make a lot of money through those years.
Sean: After those years, that’s when I made the transition to serving bigger business with software engineering, project management, really just to be specific on my skillset, but understanding the code and what it does.
Sean: So, I essentially had been doing that since about 2010. So, that’s 10 years now, but in parallel to having a day job, it’s been the investment in private businesses and tech startups, and I did that until 2015, and I never really had that 10x ROI for anybody out there that knows in the tech business world, tech businesses can sell for a very high multiple.
Sean: Whereas a service business, to give you the numbers here, so service business can sell for about 1x or 2x revenue or EBITDAs to be more specific, but let’s say you’ve got a service business you slave away your entire life, and it makes a million dollars a year, and then somebody wants to buy it from you, the best offer you’re going to get is about a million dollars, which is a punch in the face, especially since you’ve been spending your whole life on it.
Sean: Whereas in the tech world, you bring a business to a million dollars in revenue approximately, again, EBITDA is the number you’ll sell on, but they’re going to take a multiple of both 10x. It can be lower, it can be higher. That’s why these tech entrepreneurs out there just make a killing. It’s crazy.
Sean: So, anyway, never really experienced that. I made some money in tech. So, in 2015, I’m like, “You know what? I’m just not making those big returns. I’m going to start looking at the public market.” Since I was using a lot of data in my career anyway, that’s when I decided, “You know what? We’re going to use data because we know the big guys out there like Warren Buffett, Ray Dalio, David Tepper, list goes on, they’re not making billions with luck. They’re not guessing. They’re not using emotions, which means they’re using logic, which means they’re using Math.”
Sean: So, I spent the first year researching what these guys do, and I’m talking every book you can get your hands on. I would take those books, write down the formulas, and test them. Within a year, I was making pretty good money in the stock market, and then I’ve just been refining this algorithm since 2015 and 2016 to today. So, it’s rock solid.
Sean: Again, with stock investing, you’re not looking for short-term gain, you’re looking at longer term horizon, but compound interest is a whole different game when you use that to your favor instead of retiring in 30 years, which is the 6% I alluded to earlier. You can retire in 10 years or less.
Sean: So, that’s the pathway I’m on now is just focus on leveraging compound interest in my favor. So, that’s … I don’t know if that took three minutes or whatever it was, but that’s the story of my career so far.
Clay: No. That’s very interesting. I’m just sitting here and listening. I always believe there’s a great value in listening to how people go about their thing. In fact, I guess I don’t know where this is going to irrelative to the … I just interviewed another guest, and his episode was just The Power of Do, meaning, sometimes you just got to go out there and do something, right? Just do something and pay attention, and you can learn lots of lessons like we were talking about earlier. That’s what you do. You’re just getting out there and doing.
Clay: So, I would assume that right now your algorithm is, and I’m not saying that this means there’s any flaws with it, I’m just saying that right now probably, like everybody else, it’s probably experiencing a rough path right now given the markets have pulled back quite a bit.
Sean: Surprisingly, no. Here’s the thing. Yes, my stocks that I’ve invested in they all took, like everybody took a hit, especially over the last month, but some of the stocks are actually already at all-time highs right now as we speak, which is crazy because there’s guys on CNBC complaining that this is so painful right now, and I’m looking around like, “What?” Some of the stocks this algorithm has picked are already at all-time highs again, which is really exciting.
Clay: Are you able to give at least just one stock or is this all classified information?
Sean: I’ll give you the stock, Okta. Here. O-K-T-A, Okta.
Clay: Oh, yeah. Aren’t they an energy company or something like that?
Sean: No. It’s all SSO multifactor authentication. It’s essentially cybersecurity-related. They’ve been amazing. So, yeah.
Clay: Yeah, I know. I’m looking at their chart right now. Yeah. They pulled back with the market, but, yeah, they’ve already gone back over their highs. Yeah. Awesome. Good stuff.
Sean: Correct. Yup.
Clay: So, the principal being stocks, this will help, boy, the ones that have taken more of a hit because I’m not saying this to what you’re proclaiming, but I would assume I does pick stocks every now and then that don’t go straight up or anything like that, right? I mean, it’s not like-
Sean: You got to be really patient. Since we’re on the story of stocks here, I will say this. It’s 90% of the stocks are making you money within the first year, and over three years, it’s even higher than that. Here’s a stick for you.
Sean: So, I’m not a big fan of wrestling, but WWE has an incredible balance sheet and my algorithm has rated them very high. Well, over the last year, they have really fallen a lot. Are you looking at their charts right now?
Clay: I am. I see over the past year, yeah, they started 2019, give or take at right about, we’ll call it 80 bucks. Yup. Now, they went as low as right around, we’ll call it 30 bucks, but they recovered a little bit as of right now.
Sean: Yup. So, what’s happening here is, and it’s not fundamentals-related, it’s not the economics of the business. It’s personnel. Not only that, there was a legal issue there, but the CEO has left. So, it’s a lot of things that data can’t control, but at the end of the day, and this is one thing I’ve learned from those that have gone before me is these stocks, they’re fundamentals. They usually end up winning at the end of the day.
Sean: So, guess what? Earnings report happened yesterday, and their EPS, earnings per share, was targeted at 26 cents and it went up by 41 cents, which is huge, almost double. So, they, if you’re looking at the chart right now, 20% increase today.
Sean: There’s even hedge funds out there have been talking about for the last few months that this may be a really hot buy. Well, when I buy a stock and it falls, I do not sell. That’s guaranteed way to lose money. So, you just hold. You hold and you wait because this timeline is 10 years or less.
Sean: So, I see that today is a big turning point for WWE. I think new management coming in, they’ve got, again, their balance sheet hasn’t changed a whole lot. Their revenue is almost doubled from last year to this year. I don’t know how, if it’s toys or video games or what, but they’ve got something figured out. The reason I like that stock not only because the algorithm passes it, it’s pretty much a monopoly. How many competitive companies do WWE in the world of wrestling are there, right? I can’t think of any.
Clay: I was going to say I disagree with you when you say pretty much. I’m pretty sure it is a monopoly. I don’t know of … I mean, yeah, there are some other things out there, but, yeah, you’re absolutely right. For argument’s sake, it is a monopoly. I mean, you’re absolutely right.
Clay: So, all right. Well, so you mentioned, before I forget, the 10-year number you don’t sell a stock. So, are you saying that you’ll give a stock 10 years to recover or you just will never sell and if something goes to zero, then it goes to zero?
Sean: There’s a gray area there. There are some reasons why you want to sell early. Algorithm, I’ll let you know now, what it does is it calculates if a stock is on sale or overpriced. If it’s continuing to stay on sale, I’ll hold, but as soon as it moves to overpriced, which means the market price is no longer at a discount under the intrinsic value, when it turns that corner, which what impacts that turning would be the revenues, the debts, the growth rates, everything factored in, when those start to turn, that’s when you sell because it’s more than likely not going to continue climb. It’s going to continue to fall.
Sean: Through back testing through the years, there are a few stocks that definitive moments in time that they did turn those corners. Harley Davidson was one of those. It was a great stock I think through the ’90s and early 2000s. I could be wrong in my exact dates here, but they turned, and it’s just been a thud since. It’s unfortunate because it’s a great brand, but is it a good investment anymore? No.
Clay: Yeah. No. I’m just looking at the chart right now of HOG. What a great ticker symbol, though, HOG.
Clay: Yeah. Well, I mean, it definitely boomed. I guess everything that go after the dot com, but, yeah, you’re right. Since 2014, it’s really just been, you’re right, just drifting on down. So, I guess at the heart of that question was there is protocols in place where you will sell at a certain time.
Clay: Okay. All right because you almost meant to sound like, “Look. If you sell, that’s a guaranteed way to make money. So, I’m just not selling.” Now that you’ve clarified, there is definitely a protocol in place, and it does make sense is, “Okay. No. It’s still considered on sale. It’s still considered on sale, but there does reach that point where this thing is just flat out not considered a good deal anymore. It’s just a bad stock.”
Clay: What I love the most, you’re not saying, “Well, it just keeps going down. Stupid stock. This is a bad stock.”
Clay: What are you talking about? That’s pure emotions. Says who it’s a bad stock already?
Sean: It is.
Clay: You gave through all the very … Well, I don’t know about all the variables, but plenty of variables to show that, “Well, when X, Y, and Z interact in this way, and then this behaves in this manner, all right. Yeah. It’s just no longer … It’s time to cut it loose.” So, have you had to cut many stocks loose over the time period of your investing?
Sean: Yeah. Actually, before this whole COVID-19 thing kicked off, I did sell Disney. I did sell Nike. There were a few that they’re waffling on that line between on sale and overpriced. Nike, I think, will do okay. I think Disney is going to really take a hit because of parks haven’t had a whole lot of traffic for traffic. I’m pretty sure they haven’t during this whole quarantine. So, there’s some businesses like that.
Clay: Now, I don’t mean to be rude, but let me cut you off there. Okay. So, you think that Disney, and I’m not saying you’re wrong, but does any of that actually … So, let me do it this way. Let’s just say that tomorrow, hypothetically speaking, your algorithm spits out, “Disney, buy.” Are you buying or are you saying, “Well, but I think that traffic is going to be … Put traffic is going to be dropping here.” So, I mean, are you buying tomorrow if there’s a flash or if your algorithm spits out Disney and tells you that it’s now a good deal?
Sean: In most cases, yes. I’ll give you a little context here. This algorithm I wrote, it does about 90% of the work for you. So, it cuts through all the clutter, gets the data, and most cases, you’re going to make money on it. Like I said, 9% of the time you’re making money.
Sean: In investing, have you ever heard of the four Ms? Otherwise, I can define those real quick.
Clay: Yeah, maybe. Maybe I’ve heard of them but just not … I’ll just say no, I haven’t heard of them. No.
Sean: Okay. So, the four Ms, they’re broken down into one quantitative and three qualitative. Quantitative is the math, qualitative is understanding the business. So, they go like this. The first M is margin of safety, which is pretty much what my algorithm is. It determines that intrinsic value of where the stock is going. So, it does all the hard work for you. You don’t have to do any mathematics, which is great.
Sean: The other four Ms include the meaning, the motes, and the management. So, the meaning in the business is like, “Do you know the business?” Anybody listening out there, you should only invest in businesses you know. Warren Buffett preaches this all day. For me, personally, I don’t know pharmaceutical businesses, so I don’t invest in them. So, meaning is one.
Sean: Mote is another. I referred to WWE earlier. Do they have competition? Right? So, you want to understand if there’s competitors.
Clay: I had definitely heard of mote. That’s another Buffett or at least unless Buffett got it from somebody else. Yup.
Sean: Yup. Exactly. Most people can figure out the meaning of the business and the mote pretty quickly, right? Everybody out there has interests and hobbies and whatnot. You should lean in that direction to businesses in that arena because you’ll know the businesses like you’ll know the products and how it works, and sale cycles, and stuff like that.
Sean: With mote, you can figure that out, too. You do a Google search. You can see how many competitors they have. Then the last one is management. This one can be fun because you want to a CEO that’s like … This is meant in the best way, but you want a CEO that’s boring. You don’t want a CEO jumping on twitter, writing up comments with politics.
Clay: Elon Musk would highly disagree with you.
Sean: I was going to arrive there. I like Elon, but when he went on Joe Rogan, we all remember what happened there that [crosstalk 00:59:31]
Clay: Here’s my theory on things. Elon Musk is not CEO, he’s not in management. He is the P. T. Barnum of our day and age. The dude is a straight up marketing sales genius. He knows exactly what he is doing, but, yeah. He’s brilliant, right? I mean, he’s just on-
Sean: He is, totally.
Clay: It’s just crazy. Yeah. Go ahead.
Sean: Another point there on management, and this can take anybody 30 seconds to figure out, especially if you’re a good judge of character, but you look at their quarterly reports and annual reports, and they’re usually a few pages long. You can get a few paragraphs in. If there’s any issues and they’re pointing fingers at things outside such as factors outside the business or maybe personnel issues or anything that’s not themself, that’s a red flag. You want somebody with good integrity that’s owning it like, “Hey, I made this bad call. Here’s what I learned. Here’s what I’m going to do differently.”
Sean: You hear that language, okay. You’ve got yourself a good CEO, but we all know there’s guys out there that they can do no wrong, right?
Clay: It’s the currency. It’s foreign currencies that are causing all these issues. Yeah. I feel like that’s a favorite one is such and such predicts because of, what is it, currency challenges or exchange rate, however they word it, but it’s like, “Okay. Well, I don’t know,” but there’s always a wiggle room within all those areas.
Clay: So, I guess it’s, I mean, at the end of the day, you do have to put in some of your own feelings into this process. Is that a fair statement?
Sean: In stock investing, yes. You could just use the algorithm and go invest, and like I said, you’re going to make money most of the time, but you should go a step further, and just look at that, the meeting, the mote, and the management. If all check out, you’ve got yourself a really good investment.
Clay: I think, you know what? Looking up at the time, people are going to think we actually had this scripted out, but we both set an hour, and it’s basically an hour, and I think that’s a great way to end things off. Well, Sean, you got to keep in touch.
Sean: For sure.
Clay: I promise now, Sean, we’ll try to do this maybe a year from now, but now, I guess I probably shouldn’t promise because who knows? I’m a bozo, so maybe I’ll be like, “Sean, have you listened to past episodes?”
Clay: “Well, Clay, I’ve actually been on twice, you moron.”
Clay: I’d love to have you back.
Sean: For sure.
Clay: I do want to just, well, A, publicly thank you for volunteering to come on here. You make my life very easy. So, I appreciate that and B, for not trying to come on here and make it sound like you’re some options guru now that has some holy grail magical, mystical robotic system. No. You’re quite the opposite, actually. “No, man. I tried. Didn’t work out. Here’s what I learned.” So, thank you for just being candid and I appreciate that.
Sean: For sure. Yeah. Hopefully, the audience can learn a little bit from what I learned, and apply it to their own life.
Clay: That is awesome, man. Well, will you come back at some point?
Clay: Excellent. Excellent. Sean, well, I really appreciate it. Yeah, man, just keep on … I mean, you don’t need any encouragement. You’re already a beast mode, but keep on beast moding. I guess that’s just the best way to put it. So, thank you again.
Sean: For sure. Yeah. Thanks, Clay. Appreciate it.
Clay: All right. Now, for you listeners out there, before you go, final few things. If you’re listening on iTunes or any other podcast players, then if you could subscribe, that would be very beneficial not only to you because you’ll all know when new stuff comes out, but to us, but what would be most beneficial and what I would really appreciate is if you could leave a comment, especially on iTunes. Your written review goes a long way. If you’re listening at claytrader.com, in the show notes page, there’s a live chat box right there, so feel free to reach out, comments, questions, suggestions. We’d love to hear from, oh, and I say here from people of the podcast.
Clay: So, keep that stuff in mind. Thank you again to all of you as listeners. Thank you, Sean, and we will see you all back next week.