On the latest episode of the Schaeffer's Market Mashup podcast, Patrick is joined by author, analyst, and options trader extraordinaire Don Fishback to discuss his work on options valuation and probability over the years. Don shares how contrarianism fueled his probability models (8:53), how they can apply to current events like the Reddit craze (15:50), and their role in options valuation (24:02). And between all of those gems, there are stories about founder and CEO Bernie Schaeffer, some horse-racing talk, and much more!
Transcript of Schaeffer's Market Mashup Podcast: March 12, 2021
Patrick: Ladies and gentlemen, welcome back to the Schaeffer's Market Mash up as promised I have a very, very special guest with me today. Author, analyst, world renowned options, expert, Don Fishback is here. His website is a gym in the investing world and he's here to chat about options valuation in probability, Don, how is Lexington, Kentucky treating you right about now?
Don Fishback: Right about now it's perfect. The weather's great, the trees are budding, had a lot of rain and a lot of snow and ice about a week and a half ago, but it's all warm. March came in like a line and it's a little bit like a lamb right now.
Patrick: Wonderful, you know, I bet you Keeneland looks beautiful right now.
Don Fishback: Keeneland. That is, yes the racetrack is gorgeous. The animals are beautiful I don't know if you know the setting that we're in on the back road of Keeneland. And so like I've got, I'm surrounded by large thoroughbred operations.
Patrick: That's amazing.
Don Fishback: You know, the woman across the street from me, she owns, she's the widow of Jesse Jackson who owned Kendall Jackson wines. And there's a horse that she's got Rachel Alexandra's in the paddock right across the street from us. And Barbara, she bought Rachel for $32 million and she's got another horse over there Curlin. She paid; they paid 48 million for that one. So there's, you know, it's a beautiful setting and it, Keeneland is gorgeous. I don't know if you know this, but Bernie was a big racing, horse racing fan. I don't know if he's still in it, but we even had a service back in the late 1980s called the morning option live, which was, you know, based off of the morning live, you would get for the odds and we call it the morning option live. So, you know, he was really into race horses back then.
Patrick: Wow. No, I did not know that that's...
Don Fishback: Bernie and I go way back.
Patrick: Yeah, well that's a perfect transition.
Don Fishback: He's a great guy.
Patrick: You know, we'll get to Bernie here in a second, but to start, let's run through you and your history because you've been everywhere and all over the place. Take me back to how you got started.
Don Fishback: Yeah. I got started as a broker back in 1984 as a commodities broker. And I did that for a while but I was what I learned was that the brokerage business, at least at the time, the brokerage business was more in the sales and the analysis. And I always wanted to figure out how stuff operated. And instead of doing the sales, I was more interested in the analysis and I was fortunate enough that Bernie and his partner at the time Bob were back at 19, it was shortly after the stock market crash in 1987. They wanted to get into the commodity options business. And I wanted to get out of the sales and into the analysis. And it just so happened that one thing led to another and we got together in March of 1988 and I had the good fortune of being by Bernie's side for five years.
And it was just a wonderful, it was a wonderful experience. I learned a lot and then we, the nice thing is Bernie and I had a similar view of the way the markets function when we, when I started there. So it wasn't like I was having to relearn things. He was very skeptical about consensus opinion and he was very much in the, he had a very contrary opinion street. And because I had lived my life as a broker and I saw what the research departments at the brokerage firms were pushing out. I developed a contrary opinion street too so it naturally worked together and I think we both, he learned a lot while I was there and I learned a huge amount while I was with him. I mean, he's just a great mentor. I mean, just a spectacular mentor.
Patrick: Good to hear. I know that I was attracted to the contrarian philosophy as a writer. That's a fascinating way to explain and unpack a narrative I think. When I found that this theme was throughout the website, I was like, yeah, I would love to write about this stuff, it sounds fascinating. And so I know you moved in on your own to 1993. Talk about what, how that got started and where it's at right now.
Don Fishback: Well, I got, I ended up going out on my own in 1993. And one of the things, while I was working with Bernie, I remember vividly that he and I would have these conversations about the option pricing models, especially the black Shoals. And I remembered how, I remember vividly how frustrated he would get when he talked about the unrealistic assumptions that the models made, just so they would work. In fact that, you know, one of the co-creators of black scholes Fisher Black himself is, I mean, if there's a direct quote, he says the black Shoals formula is still around, even though it depends on these 10 unrealistic assumptions. Well, one of those unrealistic assumptions is the way that, the way you assume that prices move in such a way that the returns of financial assets can be represented by a normal distribution.
And that was, I mean, would drive Bernie nuts, because, you know, I mean, part of it is you have to understand there has to be this balance between put-call parody. Otherwise you get risk-free trades, but the other, one of the side effects of that is that it means you can assume that there's no trend. And so for instance, like the stock market has this persistent, you know, you go back to 1984 and the stock market has had this persistent drift higher except for maybe between 2000 and 2010, there was a little bit of back and forth. But generally speaking, the stock market has this trend higher and Black Scholes says ignore that that leads to inaccurate predictions of options, returns of that, you know, that this is what used to drive him nuts, pretty nuts.
So basically I wanted to get involved in the probability side. And in 1996 I created a program that captured some of the inconsistencies between theory and reality, and that method has been duplicated by a few others. You and I were emailing back and forth and I asked you about definitive. And if you had the icon, and if you, I don't know if you got a chance to see the historical return analysis they have, but those things they help, but they come up with their own set of limitations. So I basically, for the next two decades, I continue to work on a solution. And the big key, the big key was that technological improvements in data storage and processing power have allowed me to create a model free method that delivers a probability distribution that does not have these unrealistic one size fits all assumptions. And we can do, we can just model probability and valuation without the limitations of some of those other methods. So that's what I do.
Patrick: You know, I don't think you're giving yourself enough credit by saying, you know, things became easier when you had technology. It sounds like no one, you were obsessed with solving this puzzle and these probability models became your modus operandi. What insight did you have that was then aided by technology and allowing you to develop these tools. But what was your line of thinking like as these technologies were becoming more readily available?
Don Fishback: Oh, that's a really interesting, okay. There was an article that I read a couple of things. One, I, created some probability tools that were based on the standard bell curve, which is, you know, which itself is a part of the black Shultz option pricing formula. I mean, that's an inherent part of the option pricing formula. And in 1993, I developed a software program that chartered the bell curve. And then in 1996 I created a probability code, I call it the probability com. You'll see this in TD Ameritrade, Fidelity’s got it, E-Trade has it.
So a lot of these companies have these probability codes and the problem is it's just kind of like what I was telling you about would drive Bernie and me nuts is that you get some really nuts calculation results from some of these things. And so it was finding these flaws and I'll give you a perfect example of it, GameStop. This is from; this is from yesterday GameStop closed at $246 and 98 cents. You know, the bell curve is for those people that don't know it is a, it's just a way to measure probability. And it's the area under the bell curve is probability. So if the x-axis was going to be your standard deviations and then the area under the bell curve is going to be the probability.
So between plus and minus one standard deviation is about two thirds. When you can go, you can, plus minus two standard deviations is about 95% is the area under the bell curve. And if you get a little bit further out, you can get where the interior probability is about 98%, which means the two edges at the end, the tails would be 1% on one side and 1% on the other. Well, if you use the math in GameStop where you say, what's the volatility? And I don't know if your listeners know this, but volatility is standard deviation.
Patrick: Yes.
Don Fishback: If you use the volatility of the July expiration options, you find that the 1% boundary on the top end is $6,909. Now that means that the game stop options, at the money options are assigning a 1% chance. The game stock will be above 6,909 on July 16th. Now, is that possible? Well, here's what has to happen? It's 6,909 game stop would have to have a, we have a market cap that exceeds that of every company in the U S except for apple, Microsoft, Amazon, Facebook, and Google. So GameStop’s market cap would be higher than Tesla, higher than JP Morgan, higher than Procter and gamble, higher than Disney, Home Depot, Netflix, and Berkshire. It would, you don't have to ask this is it realistic in the next four months that the market cap of game stop will exceed the capitalization of all, but five of these us companies?
And that's what I mean, it's an unrealistic probability to come out of these calculators that are based on a one size fits all formula. And it's an example, it's a current example of what had Bernie and me scratching our heads back in the 1980s. So those flaws, I began to pursue a solution shortly after opening up my own shop. And one of the, Larry McMillan was a huge influence in that. I mean, I was reading his option strategists newsletter when he did that. And he would talk about, he would put a break even, he would come up with a trade and say break even.
And he'd say let's say the stock was at 20. And he would say, okay, the breakeven on this price is 15, was 25% below, right? So how many times in the last five years did the stock move down 25% in 30 days? And he would count it and so that was an influential part of it. And then I read an article in Wired Magazine and it was titled The Data Deluge. And it was about how the difference between Google and Yahoo and how Yahoo and Google had already started.
This was early days of Google was you could always tell; already tell that it was starting to overtake Yahoo and the other info seeking some of the other search engines at the time. And it was the guy; he was the head of development that he was talking about how instead of us trying to predict, create a model that predicted how, what people are going to want. We're just going to measure what they actually linked to. And so we're going to measure it instead of modeling and I said, I liked that idea. So that was, you know, which kind of got along with Larry's thing he didn't say it, what was the probability is signed by the volatility that the stock was going to drop 25% in 30 days, he measured. How many times did it drop 25% in 30 days? And that was the probability. I figured if Larry McMillan is measuring things, instead of modeling it and if Google is measuring things, instead of modeling it, that's a pretty good idea. So I'm going to do that. So that's what led to the development in 1996, where I, my first version where I started modeling, measuring probabilities than modeling.
Patrick: Now I want to fast forward, because lots of things happen since 1996 of course you think dot com 2008, and now we're in the pandemic. How are these probability models correlated to scheduled and unscheduled events like we've had in the, you know, in the past 20 years and what are some more recent examples of how that's changed really in the last decade?
Don Fishback: That's a really good point. And so the problem, if you look at a bell curve, you'll see that it's bunched up at the top. And then as you get further towards either end, it gets smoother and smoother and lower and lower. And so if you say, okay, the probability is the area near the bell curve. Well, if you go very far out in either end that area under those ends is tiny, tiny, tiny.
Patrick: Yes.
Don Fishback: So it's extremely small. So that's where you get this concept of bat tails is what it's called, or as Caleb would say, the black Swan where you get these aberration it seems like a five standard deviation genetical once every 5,000 years. And yet, we're seeing five standard deviation moves in game stop.
Patrick: Exactly.
Don Fishback: Day after day, right? Well, how can something that's supposed to happen every 5,000 years happened back to back? And it's not just that you look at the bond market, the 30 year bond is down. I think it's down my 25% year to date so, or it's down 25% from its peak, at least that those kinds of moves, and then 2008, you were getting seven standard deviation moves in like three days in a row.
Patrick: Yeah.
Don Fishback: Well, that's fine. That shouldn't happen. It's like, so you had, I mean, you think 5,000 years that's longer than civilization. So these things should happen once in civilized humanity's existence, when they're happening, they've already happened a few times this year.
Patrick: It's not like we were in some special time, you know, nothing has changed. So the way we model these things and measure them has to change.
Don Fishback: Yes, that's right. When you start using real world behavior, you start to see where the models break down and you can, the advantage that the real world probabilities give you in which the valuations are based on those real world probabilities you take into consideration those fat tails. So you don't say a seven standard deviation event should happen once in the history of civilization. You say, how many times did it happen? Well we've gotten the seven standard deviation move 30 times in the last 20 years, then take that into consideration.
Patrick: And I think that's so much easier for a retail investor to wrap their head around. Is it not?
Don Fishback: Yes. It is because the formulas have certain advantages and they have, they had their time. What we do is not hard, but it's very data intensive. I mean, we're talking about petabytes of data and that is something that you could not have done. I mean, terabytes of data would have been impossible for anybody to have done back in the 1970s.
Patrick: Yeah, impossible to conceptualize really.
Don Fishback: Yeah, it is. And so, but now that the technology has caught up and surpassed it, I mean, we built our, to do this stuff we build our own computers. And we use a video game cards from Nvidia, because they are really good at crunching numbers, well, you know, cards like that, they're $150 now and $500. They didn't even exist 10 years ago.
Patrick: And it makes you wonder what are we about to embark on in the next 10 years?
Don Fishback: I don't even want, I don't know, I don't know. Well, it's just, it is, I think it's going to be really interesting, but I will say this. I don't think there's some things that will change. I mean, the notion of risk and reward and probability, you know people say, well, why does probability matter [unclear 20:32] you’re so hooked up on probability. The reason I am is because probability determines the risk and reward of a trade. I mean, if you have a trade where the probability is 80%, and then you're going to have a certain risk and reward profile to that trade. If you have an 80% chance of profit, then you have a 20% chance of loss, then that you need to get a certain return based on the risk in order to have what we call fair odds. So probability is crucial to determining I mean, I'll give you a classic example.
We use one of the things we use to determine probability and what we're looking at versus what we measure. I'll give you like SLV which is silver, that thing got really popular here lately because the Reddit folks started thinking silver is going to be one of these things. And so SLV options, I mean, if you look at the open interest to some of these SLV options it's in like the top five of all options. So it's just out of nowhere, this SLVs coming out of nowhere. Well, you could look at the option prices and determine what the probability people are assigning it. And I'll give you an example so SLV, it was at, this was for Monday, the price was 2332. So you could look at the March 19th options and I think that expired and look at the 25 call and the 25, 25-50 call. The risk is the 5 cents.
The profit potential is the difference in strikes minus the net debit, which is 45 cents. And the breakeven is the strike of the call you're buying plus the net debit of 5 cents. So you're breaking this 25 on five, well your risk is 5 cents and your profit potential is 45 cents. When you look at that and just with some real simple math, you can see that, that price implies a probability of 10%. It's a, there's a price implied probability of being above 2505 and expiration of 10% chance of that. And you can do, we can go through some examples, but anyway, that's, we look at those prices. We get what people are expecting through the prices, the price implied probabilities. And then we look at where that stuff is, might be off where the implied probabilities of prices are vastly different than the measured probabilities.
Patrick: I think that's so important, especially when you consider the recent two months of the Reddit crowd, where it looks like they're just throwing darts blindly out there, and you can't do that. You can't just pick the next game stop, right?
Don Fishback: Yes, well, alright. So I actually got two things to say about that. First off, in most circumstances, generally speaking, you can't just throw darts. They used to have a Wall Street dartboard contest where you had to compete against a dart board. Bernie was a participant in that and actually did real well where he would, you know, it would be him and some other advisors that would have to pick a stock. And then the wall street journal’s take, they take like four advisors and then they take four darts and throw it at the you know wall street journal, hanging up on a dart board and they pick these stocks. And he actually did really; he did really good at those competitions. I remember that.
Patrick: Wow that sounds fun.
Don Fishback: I had forgotten about that. But the dark board now, the dark board actually beat most advisors. That was the other sad part which you know you're talking about contrary opinion. That'll reinforce that, but generally speaking, you cannot throw darts and expect to come out whole. You tend to, it's better to have some kind of systematic method. And that's what our value and probability does. It gives you a systematic method where you look for inefficiencies, where there might be some mispricing, just like Warren Buffett does with his value investing.
He looks for inefficiencies where he can buy something cheap and, so which is becoming harder and harder to do on the, because so many other people are doing what he does. But I did want to mention something you know, you talked about GameStop. There's one thing that you can do with options that will help you spot the game, potential game stop opportunity. And it's where you use; for those that don't know what put call parody is it's the time value of a similar strike call put they had to be equal. So if the stock is at 50, this is assuming no dividends stocks at 50. If the 50 call is priced at four, then the 50 put has to be priced at four, it has to be otherwise there's some [unclear 26:15]. I get, I'm actually doing a webinar on this, we did one before but we're going to do a repeat. It's really interactive where we ask people a lot of questions on like clearing and, you know, brokers get margin calls.
What's the risk in a short sale things along those lines, I'll put something in the slide deck so that people can download the slide deck. And maybe if they want to go to this and register for the webinar they can, but you can use, it's called the negative. It's called the applied borrow rate. And you can look at option prices and get an idea of the short selling intensity live.
Patrick: ohhhh.
Don Fishback: You get it live. So you're not, you know, most people have to wait until the short sales figures come out monthly.
Patrick: It takes a while.
Don Fishback: It takes a while. This is something that you can get live any day. And it's really interesting.
Patrick: And again, it just lends to say that, you know, you always have to have that nuanced look at things and I can draw a connecting thread to you and Bernie, the dynamic duo back in the late eighties, you know the contrarian philosophy to start. And then you ran with your obsession, the good obsession. You were obsessed with figuring out how this puzzle into the probability that there is such, to me it seems like a straight line between the contrarianism and finding value, you know, through probability.
Don Fishback: And the reason that happened is you, I think you're right on with the contrarian part, Bernie and I never, we always had a deep skepticism of consensus opinion. You know, he was a big believer in that, I think its Humphrey. Is it Humphrey O’Neill the Art of contrary opinion? Probably both, we both were like that. We both had this skepticism of the consensus view. He used that in a way to make directional picks on options based on his view of the stock. And I used it in a different way than I was going to look for those, how of solve the puzzle of the unrealistic assumptions in the option models. But it's, you know, it's a similar, driven by a similar point of view that we, neither one of us believed in the consensus at the time.
Patrick: On the note of Bernie here, as we're starting to wrap up, I have a source that I will not confirm that there is a picture. That there is a picture out there circulating of you 2, I think maybe in the late eighties, do you care to comment on that? Or do you want a representative with you? I haven't seen it. I just know there's some crazy picture out there.
Don Fishback: Okay, you know, Bernie and I we were the only newsletter people that would go to these options industry conferences that they would have. And as both of us were horse racing fans, they happened to have these stupid things on the exact rogue. It was Derby day; they would have it on fricking Derby the first weekend in May. And it was, it would drive us nuts, but we would go to these things. Yeah, there's a picture of the 2 of us back, think it's like, it might be like 1991 or something like that. I can't remember what, we did. We went to Florida, they were always in Florida and he would go play tennis and I would go, I would hang out by the pool with my wife. And I don't know if Kathy came along with this or not. So yeah, that was, yeah I've got a picture. I'll put, I can put that in the handout.
Patrick: Yeah. That would be really the clincher right there. But yeah, that's just funny that they would do that on Derby.
Don Fishback: I have a lot of very fond memories of Bernie. Like I said, he was a great, great mentor. I have a lot of very fun memories of Kate. Sometimes she would come over, you know, Kathy would bring Katie over to the office and Bernie would get busy. And I ended up playing on the floor with Katie, keep her occupied while he was doing whatever he needed to do.
Patrick: That's great.
Don Fishback: And it was a lot of fun. It's, it is remarkable to see her in the position that she's in now.
Patrick: She's outstanding. We love her here and that's not just podcast talk here that's coming from me, myself. You know, we couldn't be happier that she's in charge and I'm so glad we were able to link up here. Anything else you want to close with and just, yeah, I'm going to give you the floor.
Don Fishback: Yeah, if anybody, we've got a special website set up for anybody that wants to tune in to our webinar it's going to be next week. It's going to be on the implied bar rate and it's got the catchiest title you'd ever want. It's like how to use risk-free trades to spot the next game Stop.
Patrick: That's, people are going to flock to that.
Don Fishback: Well, because what we're going to do is we're going to use the basic principles of a risk-free options trade called the conversion reversal. And when you look at certain factors with the conversion reversal, which is a risk-free, when there's certain factors present, it signals that the conditions are right for a major short squeeze. So we'll, we will get into that and it's about an hour. I can tell you, it's a repeat that we did it live once and we're going to do it live again. When I started, we did it, it took about an hour, but you're going to learn about risk-free options trades, when they exist, when they don't. What's one of the factors that's going, that determines whether it exists and is the thing that highly shorted stocks like GameStop rallying like that was a short squeeze. Was that, is that unusual for 2020, 2021? Or was that different than previously? So we'll get into all of that and it's going to be a really good webinar.
Patrick: Great.
Don Fishback: So people can tune in.
Patrick: That's exciting stuff.
Don Fishback: Everyone is going to get the slide deck.
Patrick: Yeah, the slide deck is...
Don Fishback: We did get into all of the, everything, but I've got slides that talk about a lot of this. And when I talked about how you can use option prices to predict probability and probability to predict option prices, you would get into some real simple examples in the slide deck. So you know it explain a lot of what we talked about.
Patrick: Wonderful, so be sure to check that out and keep a lookout on our site for when we plug that and then check out Don site as well. Otherwise, I mean, Don Fishback it's great to have you on. Looking forward to maybe linking up again, maybe in the summer, we can keep up the discussion, but couldn't thank you enough for taking the time.
Don Fishback: Excellent.
Patrick: Alright. Go Cat's Don.
Don Fishback: Okay, we'll see you there.
Patrick: Alright, take care.