WAYNE HIMELSEIN: It became clear to me that while there are many exposures in asset classes, volatility is what everybody's invested in at the end of the day.

There's nothing like experience and being a trader and doing it discretionarily for many years. That understanding that led me to build the logic around the phase shift was because of my experiences as a trader versus if you read the textbooks, volatility is mean reverting. Well, not always.

To me, '08, at the end of the day, was a short vol trade gone wrong. Therefore, my position is, don't worry about what's going to happen, just be long vol.

MIKE GREEN: Mike Green for Real Vision. I'm here in Los Angeles, we're going to sit down with a friend of mine, Wayne Himelsein, who runs Logica. Like me, Wayne is very focused on the idea of how to generate positive profitability from long volatility in this environment. He's taken a really systematic approach to how to deconstruct a profitable trading strategy around a long volatility approach. It's very unique and I really look forward to getting some insight from Wayne in terms of how he's looking at the world, how he's thinking about how he can positively protect his clients' portfolios without running too much of a carry cost.

Mike Green. I'm here in Los Angeles, with Wayne Himelsein of Logica. Logica is a hedge fund that is focused primarily on-- at least as I think about it, tail risk dynamics. Mostly, where you and I have bonded in the past is talking about the underlying dynamic of buying volatility. Not truly tail risk, but trading volatility. Can you briefly just described to me what Logica does and what your primary focuses as a strategy? I know you have a background that I'd like to get into right after you give me that.

WAYNE HIMELSEIN: Yeah, rather than a hedge fund, I think it could be that but we're more of a cost and R&D shop. Logica was started with the focus of building strategies with quantitative thesis or mathematical thesis. It was my background, and that led to a couple of strategies and market neutral portfolio and long only portfolio. Then one of them, as you mentioned, is the volatility portfolio volatility trading. We-- I'd say got into that very quickly because the other side of every other strategy is negative skew and volatility being the risk.

In building a bunch of strategies over, not just when I started Logica, but in my prior life in being a quant for 15, 20 years before Logica was started, it was the clear realization that whatever strategy was built, had, at the end of the day, exposure to volatility. That was the shared pain of everyone. It became clear to me that while there are many exposures in asset classes, volatility is what everybody's invested in at the end of the day. Therefore, we got really dedicated and focused on building a strategy to take advantage of volatility, both-- in the beginning, it was a hedge to the other stuff we were doing.

We had a market neutral portfolio, and we knew that it could consistently pump out a certain return profile, but it had negative skew. I had this positive output, but my risk, again, was volatility. Therefore, building the vol strategy next to that meant that the two together could be a more stable portfolio. In doing that, I realized that the real beauty wasn't the other stuff, it was the volatility itself, or managing around volatility, because that's what, at the end of the day, everybody needs. That's the grand exposure that we all live with.

MIKE GREEN: Well, you've created a way that you're able to profitably trade from a long vol position, which is similar to many of the arguments that I've made around what I think are the appropriate strategies going forward. Real Vision viewers have heard this over and over again. Have these opportunities always existed in the market, do you think, to trade from a profitable standpoint to be long volatility, or do you think this is somewhat a temporal feature of a market in which people are increasingly, not just implicitly being short vol.

Buying equities or building a skyscraper, doing any form of investment has a short vol component to it. You're anticipating that the future looks an awful lot like the past and didn't have a discontinuous break associated with it. Historically, tail funds, or funds that have traded long volatility have experienced negative continuous returns, so they've had negative results. That's not been your experience with Logica.

WAYNE HIMELSEIN: Right. Yes. The question being is, is it temporary, or is it a sign of the times or if it was possible?

MIKE GREEN: It can be skill or it can be skill in the right environment.

WAYNE HIMELSEIN: Absolutely. Could be or both. I'd say my-- let me separate it, it might be a better environment in-- to your point, there's more short vol exposure these days than there ever has been so in the drive for yield, everyone's getting short vol, and more and more so. In the buy the dip market of the last 10 years, why not get short vol every time S&P drops, short some out of the moneys and capture that IV crush. Sure, that's been something that investors have been rewarded with over the last many years so they continue doing it and the amounts are getting larger. I agree with that.

That said, I don't believe particularly that that's the benefit that we have. Our skill set and my background is a trader. I started my career in the mid-90s as a prop trader, I learned my trading skill. My first model I built was a trading model. I still run it today. I still benefit from that that trading know-how.

For me, the ability to trade long vol was to really infuse the trading skill on top of volatility. You think of it as a thought experiment. If one is a trader-- and what does it mean to be a trader? I'll just use a very simple terminology, it means that you're pretty good at buy low, sell high. That's the skill. You could trade anything.

If you give a trader and you tell a trader, you can only trade tech stocks. If you told me that, what would I do? I'd bring up some charts, I'd look at Google and Netflix and I'd start seeing their levels and their price volume, behavior and characteristics, and from my experience, I figured out some good points to buy or sell and stop losses, et cetera. A trader can trade.

I took that same construct and just said, well, what if I constrain myself and I only could trade volatility, I could only trade long options? I'm not allowed to trade any stocks or indices, I can only trade S&P puts. Where would I buy and where would I sell? How would I do that? That was the original thinking, which said that if you have trading alpha, why not do that on long vol products or long vol instruments?

With that, began the research. Soon over time, we realized that we could make more money be long volatility more of the time, by scalping by trading to keep that position profitable. I hope that makes sense, or that answers your question.

MIKE GREEN: It does. And it also speaks, I think, to the particular situation that we're in, where I would argue that the retreating liquidity conditions in the market, whether that's a function of passive penetration, i.e. a higher propensity for stocks to move with positive correlation on any form of extreme move, which creates positive convexity to the vol surface now created both melt-ups and meltdowns.

People tend to focus way too much on the meltdown dynamic, but under those conditions, it exists in both directions. One of the unique things that we're seeing is a very significant rise in realized correlations, both up moves and down moves. That type of environment actually goes very well with that, because what you're really doing is you're trading gamma. You're not really trading volatility.

WAYNE HIMELSEIN: Now, we're scalping gamma.

MIKE GREEN: How do you think about that in a world in which more and more strategies are effectively selling gamma? The underlying dynamic of I want to sell weekly variants or weekly puts is that they have a negative expected return and if I do it more and more and more times, probability leans in my favor. That's the traditional approach to it, certainly looking at the historical databases, but it doesn't seem to be borne out in today's markets.

We're seeing more and more dynamics in which realized volatility-- we're certainly seeing this now, where the realized variants or realized volatility premium is failing to deliver. Does that affect the way that you think about pushing your positions or as you think about analyzing-- the fact that there are more and more people on the other side of it, does it change the way you think about the trading style, or are you primarily using the historical tools, and then modifying it with your trading instincts?

WAYNE HIMELSEIN: I think I haven't thought about that so much. What I can say instinctively, is that all that could do really is improve our ability to trade. Why would I say that? Sounds good. But besides for that is, at the end of the day, when people, when the masses are getting short, they have to cover and everybody's got their risk controls and their stop losses at some point. When there's that squeeze, there's going to be that further push up. As a trader, you like that.

You'd like the melt-ups, and meltdowns, you like that, because there's bigger bands to trade. If anything to me, as to your point, people are selling the shorter dated paper to get their portfolio looking Vega neutral, but at the same time, it's not because one little move and it's all out of whack. They're synthetically creating the safety for themselves, which is not really there. They're doing that to hedge probably some other larger portfolio that it's facing off to.

I know that at the end of the day, all that positioning is going to have to be rejiggered when something really bad happens. That means I'll have more trading opportunities. That's in my mind, I haven't seen that play out. I've seen it a little bit, bigger moves, but trading is betting on a mean reversionary process. There are swings or undulations in markets and in this case, in volatility and so the bigger those swings are, the more gamma you can scalp during the swing. I'm going to like that.

MIKE GREEN: Well, I'm also going to push back a little bit because while you come from a very quantitative space, your trading is largely discretionary in nature. You're not slavishly devoted to 3% decline, therefore I buy or 3% up move, therefore I sell. Am I correct in that?

WAYNE HIMELSEIN: It's a mix. You're right, it's discretionary, but my discretion is very systematic. I don't know what it means to be fully discretionary. My discretionary approach has a rule, always has rule. I think if we talk simply about a trade, getting into any trade, whether it's an option or an equity or an index, before I get in, I know where my stop, where my level is, I know where potentially a profit target or trailing stop, I have that all in my head. It's a rule based discretion.

Yes, sometimes you get into position and it moves in a certain direction and I had a feel for where it would go but there's so much more volume in a move than you expected that now you're going to give it more space. The discretion is, I'll say a bending of rules, is in itself, just another rule that if you get in and this and this takes place, then you have a new rule set. What I've done in the vol trading approach, over these many years, over the last 4 or 5 years, what we've done as a firm is build those rules, that discretion, into a systematic approach.

At this point, therefore, it's not discretionary. What we're doing is we're trading it, we're following this system, which originated from a trading instinct. Then when we see things in the market, I'm in the markets every day, and I'm watching this thing trade, and I'm thinking, what would I do here? Does our model, our system now align with the decision I would have made given that we've programmed it into a structure?

When I see that it does, I'm like okay, that's exactly what I would do. My rule set is working the way I would trade it. When I see that it's not or something different, then we go back to the R&D table and we bring up the mathematics and we start looking at why is this not exactly what I feel like I would do? We do some more testing and that might be a tweak that's infused into a later iteration of the model. It's not a change that will happen that day. I won't discretionarily say, oh, you know what, let's buy a few more puts today.

I just I don't do that because we have a system. What I'll do is go back to the R&D desk and say, why did that not align with what I might have done personally? Then we have a new version that might come out 6 months later if that thinking was correct or not.

MIKE GREEN: This is one of the things that appeals to me about this type of approach. Is the marrying of human intuition and experience, the trading dynamic with a formalized or systematic model--

WAYNE HIMELSEIN: Yes. I love that, that's a good summary.

MIKE GREEN: --so very few people that are developing quantitative models have the trading experience, simply because they haven't been in the industry long enough to actually ask that question. What would I be doing if I was fully discretionary? How does that disagree with what the model is putting out? It tends to be-- this is one of the problems that I have with empirical finance-- tends to be very focused on what are the outcomes. There are any number of times where rigorously repeating the same algorithm, doing the same thing, selling puts on a 10% drawdown will offer a positive payout, in particular, because the data set that exists historically is generic in terms of anthropomorphic in terms of its nature, it wouldn't exist-- anthropocentric, I'm sorry, in terms of its nature wouldn't exist if the big one had come. The markets had crashed and you had the--

WAYNE HIMELSEIN: Yeah, works 'til it doesn't.

MIKE GREEN: Right, it works until it doesn't. That ability to actually combine the two strikes me as different certainly than what I'm seeing from most of the quantitative approaches.

WAYNE HIMELSEIN: Yeah. I very much agree with that. I see that a lot of quants come out of financial engineering school, and they're right away into the programming and they haven't traded a day in their life, but they've learned the models and they learnt the programming. In fact, where Logica's offices are, we're very close to UCLA and we have a deal with them. The MFE program, Master's in Financial Engineering, we get a couple of their grad students or one at a time over a few months and work with them.

It's very funny for me, because they come in and they have all this knowledge, it's of course academic, and they know how to program and they've learnt the empiricism, and they believe that the models play out and, oftentimes they do, but sometimes they don't. In fact, there's an occasion I had where I got into a high level-- not high level, intense is the word, debate with one of the students.

He was in my office and he was saying that-- I asked him to do a research project and he said, well, that's not going to work. That's not what the models said. I said, well, I know it works, because I trade it. Like just I'm asking you to go and-- no, that's not what-- you can't-- because I was looking for convex behavior in equities and he said, well, equities aren't convex. No, some are and you can model that acceleration.

MIKE GREEN: He must have missed the running in video.

WAYNE HIMELSEIN: He missed quite a few runs, particularly in ETFs, but the point was that his understanding was that that wasn't possible from the academic world. We got into a big fight so much so that he started talking aggressively to me and I said, I just can't, I can't work with you and leave my office. It was unpleasant, but it highlighted to me the danger of schooling-- and of course, schooling is incredible. I very much believe in education, but there's nothing like experience and being a trader and doing it discretionarily for many years.

So yes, marrying those two makes all the difference. I trust empiricism. I'm a big scientific thinker, very analytical, I look at observed data, but I know in my heart that it's not stationary. They can't be. Volatility is a good example. It tends to be mean reverting, but sometimes it pops right out. I know this and I categorize this behavior mathematically, I understood that, okay, we can rely on a mean reversionary process, but once in a while, it's going to be mean expansionary. We have to come up with a flag or something that tells us when it's moving from one regime to another, we call this internally a phase shift.

That understanding that led me to build the logic around the phase shift was because of my experience as a trader versus if you read the textbooks, volatility is mean reverting. Well, not always. So yes, exactly, that experience, or exactly, as you said, it's what I've dealt with over the years, and why I love being a trader on top of doing the math.

MIKE GREEN: Well, it's really interesting,