Inside the Hidden Cycles That Rule Markets and Life

what we both cover. But it seems like markets have been kind of quiet lately. Don't you think, Oh my god, tell me about it. Um there. There's only so many times we can write about falling volatility and range bound markets and like new highs and stocks. It's really really frustrating as someone whose job it is to actually write about these things. Right, we have we have a call every day that we're on and we chat about the themes and the markets, and we're like, all right, what's

the theme today? And every day it's like, uh, low volatility again, when our rates going to move and break out in a certain direction. It's getting a little repetitive. Yes, why are you reminding me of the futility of art challs. It'll change eventually, you know. Right now we seem to be in this mode where there's no volatility in almost any asset class. But it's always good to be reminded that,

you know, things change. There's you go through periods where things are very quiet and then things are crazy, and then when things are crazy, it feels like things will never be quiet again. But you know, things go in cycles. One can only hope. I guess the key thing here is the timing, right, Like, how do we know when things are going to change? That is always that's always the trick. And if you knew the timing then you would you would do very well in the markets. But nice,

So why are we talking about this? So today we have a guest I'm very excited to talk about. He is a long time veteran of the markets, lots of experience in trading hedge funds. He's seen lots of these different cycles over time. Uh, And in fact, he's also devoted some of his research specifically to studying market cycles and the patterns that repeat over and over again and

figuring out how to time them. And um, you know, I think, uh, it's sort of the perfect the perfect guests to sort of figure out where we are and what could be where we could go next. I'm yeah, this sounds great, and he'll be able to tell us when markets are going to get exciting again, right hopefully, hopefully, hopefully we'll be able to get him to tell us to the day when markets will get excited again. But we'll see if that happens. Our guest is Peter Borish.

He's a strategist at the Quad Group. He I've had him on the TV show a couple of times, one of my favorite guests, and so I was really excited about the chance to talk longer with him and to get to know a little bit more about his background, which is extremely interesting. So I'll bring him in now. Peter, thank you very much for joining us. Well, it's a pleasure.

It's really an honor when you talk about how uninspiring and how uninteresting the markets are, that you can have a guest that can join right in incredibly uninspiring and uninteresting. Now it's just the opposite. We were bringing you in because we hope that you'll remind us that just because it feels a little quiet right now, uh, it won't stay this way forever. So just the it's just the opposite. But um, before we get into it, tell us a

little bit about your background. You've been a you're I think you're a legitimate veteran in this industry at this point, and so tell us how you got into trading and markets and sort of your your path through. Well, first of all, thank you. It's really fun to be here. And I do very much like to go greater and in depth and and and bring some substance to these issues which are complicated. I sort of bring everything back

to Michigan. I'm a big Michigan guy. I went there for undergraduate in graduate school, and I was very fortunate to get a job at the New York Fed at the real recession, which is in two i finished graduate school. My career arc has been one of pure luck. I started at the New York Fed, as I said, in two that is the summer that SMP Future started, and

I was in research. And then I went down and people didn't understand these new futures markets, and they created a futures and options group right outside the desk where

they traded foreign exchange. And then three years later I was recruited by this young guy from Memphis, coming off the floor of the Cotton Exchange, who was starting something at the time which people didn't really know about called a hedge fund, by the name of Paul Tutor Jones, and I was sort of his first research professional at Tutor Investment Corporation, and we were lucky to apply what I would say the discipline and methodology of futures markets

as financial futures around the world were being developed. So the SMP Crude Royal started in eighty five, the Japanese futures came on in in the later eighties, and then you had the European futures markets in the early nineties, and that's when it became very much a twenty four hour world, not just in foreign exchange of course, but now in all the markets, and with the advent of stock indecks, futures, treasury futures, UH trading in the inner

actions among them. So give us some insight to what trading was alike then and how the rules of future markets futures markets kind of differed from other types of markets. Well, the thing about futures markets, which are everything is a mirror.

It's what's a blessing can be accurse, but in futures markets because they have this performance margin that you put up, so there's an embedded uh more leverage in terms of trading those markets relative to equity markets, So your risk management has to be far more sophisticated because of if there's volatility in one of those markets, then uh you

can lose money much more quickly. The success and every trading business is about worrying about risk, not about the reward so much, because it's if you can limit your risk, if you can stay in trade for another day, then you have the opportunity to be successful. We're always talking about that. We're interested in people that want to make money, not wanting to be right, and making money means limiting your losses. So that approach that most of the future traders.

So if you think of Paul Jones, if you think of Louis Bacon, if you think of of Bruce Covener, even George Sorrows, all of these people started and we're more active in the futures markets, and the sophistication of those risk management tools then could be applied to other markets as they came online. So it's a certain discipline that those guys had in terms of not losing, not being carried on at a stretcher, being able to survive to the next day. That really sort of made them

the cream of the crop. Yes, we always talk about and and I sit down with all our traders now that it's discipline before vision. You know when we talk in your introduction, you were saying, well, the markets kind of boring, and I think this is gonna happen, and I think that's gonna happen. And I try to distinguish very much between research and a discipline approach to markets versus gossip. I'm a Mets fan. We can gossip about baseball.

The season just started their one and oh if I project that out, they're gonna go a hundred and sixty two and zero, And you would say, wait a second, that's kind of ridiculous, that's not gonna happen. Well, Amazon's up today, it was up yesterday. I guess it's gonna be up every day. We also know that's ridiculous. So the logic of I know I'm going to be right, this is what's going to happen. No, you are wrong, the market is right. That's where risk management and discipline

comes into play. You started working for Paul Tutor Jones. I think it's and two years later was the famous crash of October or about two years later. And not only did Paul Tutor did that? Did your fund do extraordinarily well in that crash? And having called it right, I believe, uh, Paul himself credited the work that you did for helping the fund be on the right side

and anticipate that crash. So tell us a little bit about specifically the research you were doing for him and how you were able to anticipate what, you know, considered one of the most pivotal market events in financial history. Sure, I want to back up one second. Served fortunately that what we thought was going to happen economically as a result of the crash, in terms of you know, deflationary

pressures and things did not happen. Uh. So that was very much a positive because we thought that the economy would contract far more than it did. But it goes into the cycles where we were is that we were looking at data and cycles, and back then their computing power was expensive, ATA was expensive, trading was expensive. And one of the great things that one has to give credit to Paul and the other people at Tutor was

the investment in all of those things. We were early users of data computing power, and so we put this together and and and I build a model, and we were looking at early days. You know today you pull up your Bloomberg, you can pull correlations up on anything, a cross correlations, inverted matrices that back then it was very difficult. We were doing that. We saw this pattern which was incredible in terms of where we were both.

We started with the economic thought of technology innovation and what was happening back in the early eighties relative to what was happening with the innovation and technology in the twenties, and then the markets were tracking that very much. And when we first started this, the projection was sort of it would go into early UH and then the data and the patterns indicated that the market was likely to break.

One of the things about it was with the advent of these derivative markets and futures markets that there's some embedded misunderstanding. One can argue that to a certain extent with some of these new volatility products. It's a little bit like anybody that has a five year old. You think you could talk to them, you think they're rational, but they're not fully rational, and as markets develop and people think they understand them, they don't always do that.

So that was part of the UH embedded sort of market UH construction. The way that it worked in the terms portfolio insurance and the assumption that there was always going to be liquidity that led to even more acceleration to the downside. So we were very, very fortunate, UH. And all credit has to go to UH Paul and the execution team at TUTOR, because even if I was right and I gave the exact low and the exact high,

nothing goes in a straight line. And he's a far better trader than I will ever be, so he would make far more money. And UH we were fortunate as a fund to benefit from that. And I think that benefit of the entire industry in understanding the importance of both risk management and understanding that these markets have a place where they can be used for hedging. Peter, give us some more insight into this idea of cycles, because um,

you know, I started researching this. UH. Joe basically gave me some homework and told me to go read some articles. So I've been learning about Martin Arms Armstrong and Edward Dewey and thinking about Fibonacci sequences and things like that. It kind of has a long history, right, Yes, I am a a a firm believer in in in cycles. Nothing works exactly, of course, but it goes back to the nature of us as human beings, which is fear

versus greed, complacency versus uncertainty. And I look at where we are right now, and and this is something I talked about in Bloomberg Markets right after the election, that if you're a student of history, so you can't be a student of markets without being a student history. And there's always these long waves that appear to be obvious after the fact. So by the way that I'm one of the greatest traders of yesterday, I can tell you exactly what happened. So after the fact, my batting average

is amazing. It's that pesky uncertain future that makes this business much more difficult. So what am I referring to? So, oh, well, the advent of of you know, Apple, Amazon, and the obstitution effect. So if you line them all up, one of the questions have they created more wealth than they've destroyed in terms of stores, in terms of other uh markets, Whether it's best Buy or BlackBerry in terms of Apple,

in terms of the retail stores that you're seeing. Now, these are long waves and this is a cycle that's taking place so in Bloomberg markets. To me, the broader cycle that we're seeing in one of the most famous ones historically are the Chndrati of wave and the schoom Painter. Schum Painter is a famous economist that talked about this creative destruction. And where we are if you think about it,

is the Berlin Wall went up. Ironically, it started its construction August thirteen, UH Ninette below in the stock market, by the way, was August thirteen of Fibonacci, twenty one years later. So if we talk at eighty two, excuse me sixty two, and then you move forward twenty seven years. UH. Ronald Reagan's most famous line was Gorbatov, tear down this wall. The wall came down, uh November nine, twenty seven years after that, November nine, ninety two thousand and sixteen, UH,

President Trump is elected. Now, if you look at history, we haven't seen too many economies that have grown uh by building walls and and looking inward. I like to say, how the Great Wall of China work out, so we're here potentially at the end of another long cycle. It completes from sixty two to eighty nine to sixteen contralty

of fifty four years. Now, that just keeps something very deep in the back of your mind, because that has nothing to do with trading some p futures today, where you know, if there are twenty three sixty do I think they're going to before I think they're going to But in terms of the Ralph Laurent announcement in the UH, the pay less hues closing more stores, and you're seeing that and you're saying, Okay, the deflationary pressures continue to build up. We talked about a DP this morning and

being strong. Where are all these retail workers going to go? Where's the marginal consumption going to be? From what we've seen in this last cycle, which has not been addressed at a policy perspective nor per se in the markets, which is the things that you don't need have gone down in price, the things that you do need have gone up. So what do you need, education, healthcare? What you don't need? I can skip a good meal, and I can get an iPad, I can get an iPhone

because for a few hundred dollars, that's the difference. The things that you don't need have really gone down the quality of life, whether it's a fifty five inch television or not. So that's what the dichotomy, and that's what's leading some of these deflationary pressures, and you're seeing that through lower real wage growth and the bond markets telling you that as well. So just to wrap up, because there are a lot of important ideas there, one thing

that really stuck out to me was this idea. You know, as you said it, from the construction of the Berlin Wall through the election of Donald Trump Key, events have happened, as it turns out, on interesting annual or interesting intervals. You mentioned the Fibonacci sequence, which is of course a well known sequence that also appears in nature. You see

it in flowers and stuff. So the idea being that these various events in history have a sort of deep natural rhythm to them, and that it's sort of not an accident that they appear at these certain intervals. Well, think about us as as human beings. We we go through cycles and things take place at at also that

natural rhythm. Uh, But it's really a build up of of time, and that the innovation takes place over a cycle, so that we were always planting the seeds today for the next substitute, and and and it's it's funny so you think of, well, thirteen years old right on. I'm Jewish, so you have a bar mitzvah when you look at twenty one, which is a year, you know, Huh, they're both Fibonacci numbers as well. It's kind of it's I don't know why it's there. That's not I'm not smart

enough to figure that out. But I just try to sit back and be an observer, which is why I said before, Uh, if you want to be uh student of market, you have to be a student of history. But you also have to be a student of people because of the behavior. If we go back to the markets for one moment, the one thing that was missing to sort of indicate a potential inflection point or top before the election was sentiment. And now sentiment is off

the charts. Everybody is particularly bullish. That to me is a little bit of a contrary signal. The market hasn't gone anywhere. We talked about uh, you know after the election, when I was on uh that likely five percent move to one thousand in the dow around March expiration. That some of the largest turning points have taken place in March, and that's what we've seen. And we haven't taken out

those highs yet. From March one, we've been meandering the nastic Has you had that divergence between the nasty A in the SMP back at the two thousand high uh, and everybody talked about how you know, sort of under President Obama there was all this uncertainty. There was an uncertainty. They laid out a path, there was a route. You may not have liked it, but you kind of knew

with Dodd Frankin. Now the uncertainty is even wider. So it's likely that what's happened previously is unlikely to continue. And we make this mistake all the time as participants in the marketplaces. I said earlier is trying to, you know, draw one line and assume that it's going to be a linear UH movement, which is why I said the Mets will be undefeated this year, which will be great.

I want to take a quick break for a word from our sponsor, but knowledge to work and grow your business with c i T from transportation to healthcare to manufacturing. C i T offers commercial lending, the seeing and treasury management services for small and middle market businesses. Learn more at c i T dot com Put knowledge to work. And we're back with Peter Borsch of the Quad Group. We've been talking about markets and history and cycles. Um

I wanna. Tracy in her last question to you talked about some of the early people who worked on who started seeing cycles and markets and economics. You mentioned Edward Dewey. Who was he? And uh, what did what did he learned in his work and what have you learned from studying his work? So Edward Dewey was actually worked for the US government and was one of the early people

that innovated and collected government data. His passion was cycles, and he started this foundation called the Foundation for the Study of Cycles. I served on so when I was at tutor again, we would scour the world for data literally because you couldn't download it there. There wasn't the internet.

I mean I flew to Zurich to collect, you know, foreign exchange data, and got around and turned around the next day, and and and and came back and we would hire summer interns to punch in all that data in spreadsheets. Dewey was doing all this by hand. How I met Tom Demark if you talk about another data person. He was in Wisconsin and he had by far and away the cleanest data. He had these to mark chart books that he would put out which were better than

Value Lyne and others. And we needed clean data. And that's how we met. And we would try to gather every book that we could that went over history and collected data both from the original source, whether it was doubt owns and in their library or people like Edward Dewey or Martin Armstrong and others that were, you know, passionate about clean data. What were some of the most interesting um sort of cycles or data sets that you

can remember either collecting or studying over the years. Well, the most important one in terms of doing the model was getting the UH open high low and clothes, which was unusual at that time for the Dow Jones. And there was also Saturday sessions, so we needed to have all that. You couldn't make all these assumptions. We wanted

to go to the pure source. At the same time, when of SMP futures started trading and even then understanding the SMP cash index versus the futures index, and we would look for movements in and in fair value as well. That was an early thing people doing index arbitrage because that was a sentiment indicator to a certain extent. When people were selling futures and they went to a discount, then that probably was an indication of too much negativity out there. Uh And so that was another area of

data that we would collect. But we also did things which related to economic fundamental data which is relevant even to today. So the unemployment number comes out on Friday, that's the number that the market sees. But if you go back and you look at your database and you say, what's the unemployment for uh March that comes out this Friday in April, the number you pull off the database is the revised number. That's not the number that the

market saw. We would have to go back and we would work with people that did newsletters and things like that. We wanted to see. We wanted three numbers. We wanted the number of what the expected number was, what the actual number that the market saw, and then finally what the revisions. So we needed that all that data you keep expanding the size of your database. So we then had to invest in smarter uh technology people to build

those databases. It took a serious investment. But that's where people often make a lot of mistakes that they just download data from the internet and they go, oh, I'm going to run a model on this. No, it's completely irrelevant. Joe was telling me before we went on the air about the ADP number. The number that the market saw last month was just revised down by fifty thou Well,

that is what a revision. That's enormous, And if you're building your model on something that's different than the market first saw, you're likely to have mistakes. So you really have to roll up your sleeves and get into the weeds on this stuff. It's it's not easy. It takes a tremendous amount of investment, which is one reason why today the quantitative firms that are successful get bigger because they can invest in the time, the data, the cost

that's involved in building a really outstanding model. I find this really fascinating because obviously, to some extent, we take for granted the ability to just pull up data, even revised data. It's not that hard to find, but the idea of really having to do legwork to get it all. And in your case, you know, talking about going back to the early days of the Dow Jones and figuring

out those quotes when they had the Saturday session. What did that tell you when you when you say it's you found this data, you had some of the best data anywhere. Then you had to actually do something with it, because it's not enough to just have it. So what were the kind of things that looking back at that old Dow data and finding Saturday numbers and high low and clothes that other people hadn't seen. What were the kind of insights that enabled you to look at that

and then profit in present day markets? Well there, So there's one other thing I want to add. And when it comes to data, because when you look at the high low close of the Dow, and if you took the high low close of the thirty components of the Dow, they would not be the same. So we went a

step further. There was a theoretical high and the actual high because the theoretical high H means that the high print for each of the individual components doesn't happen at the same time that the actual high for the doubt Jones index takes place. So we thought, originally we could just get the thirty components and create our own Dow index. It's a price weighted index. You you you, you know, you get the divisor and and build it. No, that

didn't work. So there were mistakes there. Each point along the way. You have to realize that you're likely to make a mistake one of the things that you will apply models and you think, okay, I'm ready to do it. And no, today, when I'm looking at models, I've never seen a bad simulated model. Nobody ever comes to me and says, you know, Pete, this is the worst model you ever saw. It's got a minus three sharp ratio. You should invest in it because it can only get better. No,

because there's what I call this creeping intellectual cheating. It's not that you intend to cheat, but because you don't fully understand because you haven't made those mistakes yet, that things are over optimized. And and where that's where experience comes into place. So when you ask about these things, yeah, that's where having a person that's implementing the model, like a great trader like Paul Jones and the team around

him you have to pick it apart. And so I would think that I would have a great answer, and sometimes I'd work, you know, on shorter term stuff all weekend and I'm like all excited about this the market open, it's in the trash can, and I'm like, wow, I could have had a much more fun weekend and staying in the office all we again working. So that's that's part of it too, is realizing it's a very humble business that you think you're smart, but you're really not

that smart. So all those little different subtle things with the data, as you just talked about putting us in open high low clothes trying to do that. So the question that we had to do and talk to dal Jones and go back is is was it the actual high was it a theoretical high? Because those are two different things. We'll talk to us about how best to use models or cycles because a lot of these underscore modern finance, right, like there are models everywhere, there are

all these quantitative funds. Um technical analysis is really popular, but people always levy a bunch of criticisms at those things. You know they can be wrong or history doesn't always repeat itself. This time is different, So how do you actually apply those things? So a model or cycle, it's literally it's a map. You pull up Google Maps and

you're gonna go and you're going a look. But until they've perfected self driving cars, you still need to be behind the wheel because there is likely to be a pothole or there's likely that the weather is gonna change and a bridge is gonna be out, and therefore you have to uh change your route. You kind of the map and the model tells you here's where I think we're going from A to B, but it's not a specific uh timing of that aspect. That's where your risk

management comes into play. And that's where you probe and you probe and you probe. And so let's say I'm super negative here, I'm like, Okay, I'm gonna sell, but if we make new highs, I'm going to get out because then my thesis is wrong. So if I risk a little bit, if I'm wrong ten times in a row, but then when i'm right, I can make it all back. That's how you want to trade. Unfortunately, most people participate in the market and it's upside down because they think

they're right. So they're like Okay, well we just made new highs. It's just a little bit, it's no big deal. Or I'm going to get out, or the market shortcovering in front of the unemployment number we talked about earlier on Friday, so I'll wait. Then you lose your discipline.

It's all about maintaining your discipline and your process and what the cycles can say and where the roadmap is, both whether it's a an economic cycle or whether you think it's a fundamental cycle, or whether you think it's a political cycle. It's when they come together. When I sit with our traders and portfolio managers, the best approach is when both the fundamentals and the technicals are coming together.

So we can argue now that the fundamentals are disconnected, but they can go for a longer period of time. What the technicals say is get out of the way, because this is it's not telling you that it's breaking down. When they come together, that's where you do it. A great trader, and I've been fortunate to be around some

of the best, that's when they push it. My favorite line is by Stanley Drucker Miller, which always says you have to earn the right to trade big and when you're there and that's when you put on the big position, when the things line up, not when you think you know more than the market, because you never do. You'r there's one of you and there's millions of people participating in the market. Something I've always been curious about. You know, you talked about these long term cycles and things that

go on many years. You also see and I think you kind of alluded to it, but you also see these very short term ones. And you see charts that are literally are intra day and that someone will annotate and that will have five waves of a cycle within the course of a day or the course of a week. Do you see this sort of like fractal nature of cycles.

So we talked about Fibonacci sequences starting in the early sixties, But do you find value in finding those same patterns and the span of a few hours or a day or a week. Well, so when you talk about five waves, that you talk about, uh, the Elliott wave and the motion again, that's a great way to have a discipline to approach the market and look for potential inflection points.

In today's world with the speed of technology, what I call man versus machine and shorter run trading, that's not a space that we can compete in at quad group and in long run trading, you basically become it's difficult to outperform the index. Why do you want to pay me two percent to be long Google? There's lots of other ways markets work. So whether it's an et F for directly or through yourself. Where we try to be is that combination of man and machine one week to

three months what I call an earning cycle. And yes, these things are all applicable for that, particularly when you think about an earning cycle and in a market movement. Now on the way down, this is where nothing goes straight down or straight up. But if you think about some of the retail stocks, and if you look at Macy's and then it went down and oh someone's gonna buy it, or there's an act and then there's a pop, they tend to go back down because you know what

are they always say, the trend is your friend. Human nature is we want to be smart. I've learned long ago that I'm not, so I try to stay with the trend and I'm not smart enough to pick the bottom or pick the top. But that's where if you're trying to do that something like the Elliott wave where you have disciplined or what we talked about before, where if I think the market is topping and I'm gonna sell it, then I need to have a risk management tool that's going to take me out so I don't

get buried. Okay, one more question. I know you just said that you don't want to try to pick the top or the bottom, So I'm going to rephrase this slightly. When do you think markets are going to get more interesting? I think we're in the process of them getting more interesting. So we worked out this game plan, as we said at the end of the year, and I've spoken about and I just mentioned about how we thought that that would go five percent from the election, it would get

to twenty one by March expiration. We're here and we've been in this trading range. When you do something ahead of time, when you do it intellectually and unemotionally, then when you get to the point where you have to implement it, you can think about a thousand reasons why it's not gonna work out. We try to maintain our discipline and say the thesis when I created it on emotionally is going to work out until the market tells me I'm wrong. So right now I think we're at

that inflection point. I think we're rolling over and until the market tells me I'm wrong, And that would be you know, the Dow making new highs uh closing above the high, and the SMPS closing above March one high, which could easily happen by the way between now and and Friday afternoon, assuming the unemployment is very strong. But again, I look at the bond market, I look at dollar yen, I look at the commodity markets, and if I recommend for all your listeners to look at the be calm.

I'm a big fan of the commodity index and what that's been telling us that there's underlying weakness. I think that is a perfect note to wrap up the conversation, starting from your early work at the New York Fed too, where we are exactly today in the markets. Peter Boris really appreciate you coming on, fascinating conversation with pleasure. Thank you very much. So trades see, are you are you optimistic now that perhaps our morning market conversations will soon

start to get a little bit more interesting. I mean, I don't want a big sell off, like I don't want people to lose money, but something other than low volatility and range bound markets would be very, very welcome. I mean, I have to say, we do this a lot on odd lots, right, We talk about past history because we think it tells us something about the present.

So I am into the cycle idea. I'm not sure I'm totally into, you know, the notion that Fibonacci sequences hold like the secret to nature and you know, the inner workings of markets. But I feel like there might be something there maybe well, you know, as you say, we talk all the time on the podcast about historical episodes in markets, and so it intrigues me these this idea of taking it to the next level and to say, Okay, we acknowledge that at least to some extent, history repeats

or rhymes or whatever. So is it plausible to quantify those repetitions as opposed to just saying that history repeats and leaving it at that. Can you take it to the next level and say, okay, well, let's let's actually put some rigor behind this and see if history can provide real guides to right now Yeah, that's a really

good way of putting it. Um. The other thing that interested me was the idea of the importance of data, I guess, and the notion of you know, flying to Zurich to get a data set that maybe not many other people have. And that's something that we've talked about previously on the show. How proprietary data seems to becoming more and more important in the market, right, Yeah, we've talked about it, and I think a number of different ways on the show. I think we've talked about satellites

and the attempts to get faster real time data. We've talked about the bond market and how difficult it is to really get clean sort of real time data on what's going on there. And I think it's always sort of worth reminding that in this current age, we take the existence of data for granted, like it's oxygen or water, but that even still, you know, I think we actually have a hope we're trying to get another episode in

the future. There's still important economic data points that people look at all the time, where people have to call up operators on the phone or message him and say, hey, what's the price of this today? Like It doesn't just appear on a blinking screen. It really takes legwork to get it right. Okay, well, don't give our future episodes, but we will do more on this. Well, this has been another episode of the Odd Lots podcast. I'm Joe Wisn'thal. You can follow me on Twitter at the Stalwart and

I'm Tracy Alloway. I'm on Twitter at Tracy Halloway and Peters on Twitter too. He should tweet more, but he's at p Borish. Thanks for listening. Put knowledge to work and grow your business with c i T. From transportation to healthcare to manufacturing. C i T offers commercial lending, leasing, and treasury management services for small and middle market businesses. Learn more at c i T dot com. Put Knowledge to Work