“New Age” Analysis – Equity and Fixed Income Research Synergies

First webinar that I'm— that my company's doing, and it's going to focus on how fixed income investors can use equity valuation tools for better bond outperformance. This is what everybody wants. Okay, and this is the first in a series of Viola Risk webinars showcasing our alliances with first-class research providers that enhance our Viola Risk research. Iola Risk Advisors specializes in stakeholder stack analysis, which is a holistic enterprise-wide risk management and capital structure investment views methodology. We focus on debt investors, equity investors, counterparty risk managers, and regulatory and systemic risk authorities. Even if you're just doing debt or regulatory or risk, you really have to understand how the other major stakeholders can influence your valuations and your exposures. Uh, just a little background on David Trainer and myself. David and I met at Credit Suisse about 18 years ago when we were both in the equity research department. Uh, one of David's roles was to introduce and implement economic value-added models across the entire analyst industry sectors. He also covered specialty finance and banks as a first-call EPS estimate analyst. After Credit Suisse, he started his own firm, New Constructs, which concentrates on economic earnings, equity valuation. Now I'm just gonna give you a little format of the talk. I'm gonna hand it over to David to talk about his approach to equity valuation, and then he's gonna hand it back to me where I'll tell everybody how I use his tools in my workflow as a stakeholder, staff, debt, equity, counterparty, regulatory risk exposure analyst. So David, take it away.

Thanks very much, David Hendler. It's great to be with you. I'm very happy to be meeting all of you all. One little housekeeping note, feel free to log questions in at any time. We're going to try to leave a bunch of time for Q&A because we want this to be about what interests you most. And David and I have had plenty of time to hear ourselves talk, so we'd like to hear from you as much as you're willing to share. So yeah, David and I have been working together for a long time. We share, I think, a uniquely analytically rigorous approach to research. I think it's good to see that kind of approach coming back into favor after most of the last, I don't know, 15 to 20 years. You know, I don't think that there's been as much analytical rigor for a lot of reasons. You know, David and I had a front row seat to the tech bubble. We saw how that affected research and the way people invested. I don't think there's been a lot of change. in analytical rigor or improvement since the bottom fell out there during the tech bubble. As quick background on, uh, on what— on me and what we do, you know, I, I got— I started New Constructs back in 2002. We were a hedge fund for most of the last 10 years. We've sort of refocused on research more recently because we've got some really unique technology that we believe is right in sync with where the investment management business is going with respect to more of a focus on data analytics. This change is best represented by the major announcement by BlackRock recently to replace humans with machines. And I think another data point that, that shows how quickly the industry is moving in that direction is the recent news from AllianceBernstein shutting down most of their active management business. But in terms of background that's relevant, I started out as an auditor and an executive compensation consultant. And as an executive compensation consultant, my job was to go to boards of directors and say, hey, whatever you do, don't pay executives based on accounting earnings because you can grow accounting earnings while running the business into the ground. And that's when Credit Suisse— shortly after that, Credit Suisse hired me to take that concept and scale it globally. And in that role, I became a bit of an expert in some old-fashioned skills, model building in particular, but even more so, reading annual reports, especially the footnotes. And as I mentioned at the beginning, as the tech bubble came along, reading annual reports and footnotes really quickly went out of style. 2 other key people at the firm is my COO, who's really helped me build this technology from the ground up, Lehman Eticola. And then our, our technology capabilities are, are kind of across the country. We go to where we find talent with respect to machine learning and natural language processing because That's pretty hard to find. So New Constructs, putting it simply, the problem we're trying to solve is, is, is on this slide. This guy who has time to read and do the diligence that we all know we should do on our fixed income or equity investments. And specifically, I'm talking about reading Ks and Qs. That's 4 times a year, on average, 200+ pages. Some of these Ks are 2,000 pages. And I started New Constructs to make this process more efficient. And the first thing I did was create an application that combined the filing, a database, and some simple parsing tools. And I had 2 very simple goals. I wanted to make the parsing process a lot more efficient so I could keep smart people around long enough to justify training them. Because I can tell you, when I was on Wall Street, it was really hard to recruit people to come work for my project when I was competing with Frank Quattrone. Come work with David Trainer and learn how to read annual reports like Warren Buffett, or go work with Frank Quattrone and make $1 million next week on that IPO. I didn't compete so well on that front, uh, and so I knew technology needed to play a role in going through these filings, not just because it was boring and difficult, but because machines are better at a lot of these mundane tasks. So I built this application back in 2003. It may have been one of the first ever machine learning tools. And since then, we've pumped over 120,000 filings through that. And the machine remembers every parsing action that the expert takes. So the analysts using this machine, this program, are all trained by me personally. They're experts in accounting and finance. And the best part is that the machine is tracking everything they parse. So over time, we're able to parse more and more things automatically, which means My smarter analysts spend less time in filings and more time advancing models, studying accounting rules and accounting rule changes. The deliverable? Type in a ticker and get an answer. You don't have time to read 100 Ks and Qs every year? We're doing that work for you. It's our goal to give our clients the fiduciary-level service that they expect. And if you think the problem's getting better, you know, I would, I would tend to disagree. Disclosure trends are not your friend. I know because I sit on the Investor Advisory Committee for the Financial Accounting Standards Board, and we've got more rule changes, accounting rule changes coming out in the next few years than have happened in the last 15. I was a— I was very much involved in the new rules regarding loan loss reserves and the fact that those are going to have to now be, you know, lifetime loss reserves, and I can tell you there's some issues there. I was very outspoken with FASB around how they address those issues, and we could probably have a whole other call on that front, but it's going to change models a big deal, not just in the year that these accounting thing— accounting changes take place, but in retrofitting historical models to keep them apples to apples so you can really understand trends. Another major takeaway is that there's just a lot more disclosures that are coming, coming along. I helped rewrite the or write the rule on bringing off-balance sheet debt back on balance sheet. It's an issue for banks and retail companies in particular. There's quite a bit of off-balance sheet debt, more than you might expect, and we've been converting that off-balance sheet debt back to balance sheet debt for a long time. So our models will remain apples to apples where other firms will not. And just a second here in terms of, you know, who we work with. We have insurance company clients, we have Major partnerships with firms like Thomson Reuters and Ernst Young, where with Thomson Reuters we're going straight into the wirehouse firms on 170,000 Thomson One desktops. We work with Ernst Young on high-level C-suite strategic consulting, helping companies focus on what matters most to investors, how to align that with compensation and investor relations messaging. Some of our clients include some of the largest, most sophisticated hedge funds, quant shops, regular portfolio managers. My original clients when I launched my business in 2003 were the global head of research at Fidelity and senior portfolio managers at Janus and TIAA-CREF. And my core product has always been a very sophisticated model, one that provided my clients all the diligence they needed in terms of going through all the filings, and then the model robust enough to deal with all the different accounting anomalies and irregularities from company to company, to sector to sector, to region of the world. When I first started at Credit Suisse, people didn't believe you could do EVA or economic earnings for banks. Even the people who founded EVA, the Stern Stewart folks, said it couldn't be done for financial companies. And I thought that this ran counter to the overall goal with respect to EVA, and that's to me always been to put everybody on the same playing field, an economic playing field, as opposed to an accounting playing field. And economic is general. It's, um, it applies to everything. And the idea is that every business, no matter what kind of activity it engages in, can be measured by how much cash flow it generates relative to how much capital has gone into it over its life. These are generic concepts that apply to every business in every sector around the world, and that's what I believe that New Constructs strives hardest to be the best in the world at. So return on invested capital, yeah, it's different for banks. It's different than the other calculations, the primary difference being that interest expense is treated like cost of goods sold. for financial services businesses. Whereas in the industrial model, interest expense is treated as non-operating because it's a financing expense and return on invested capital is supposed to be unlevered. Well, that doesn't work for banks. You need to look at interest expense again as a cost of goods sold because cash is effectively your inventory. In addition, the other key adjustments you're going to see from New constructs is that your numerator or your operating profit after tax is also cleaned up for unusual items from the footnotes in the MD&A. We do that work better than anybody else in the world, in my opinion, and we're expecting to publish a white paper with a Big 4 accounting firm proving that point with some very specific case studies. And our balance sheet is made whole. That's better too. We're taking into account acquisitions, Write-offs. Again, so we can get the best sense of how much capital has been put into the business and make sure that the numerator and denominator for return on invested capital is as apples to apples for all companies in all sectors around the world as possible. And if you wonder if return on invested capital matters, we would say yes, it does. When we do analysis on how much return on invested capital explains valuation, For all REIT— all non-REIT financials with a $5 billion or more market cap, you can see here in this analysis it's a 66% correlation. And I've done this work for, I don't know, around a dozen CFOs or investor relations officers with some of our partnerships in the compensation and investor relations consulting area. And we consistently see correlations upwards of 67%, even 90%.

Wow.

And I think at the end of the day, this is intuitive, right? The market's going to assign value to those companies that create the most value relative to the capital put into them. The key is just to make sure you measure that in a high-integrity and a consistent way. That's pretty much all I have now. I'll be happy to take questions at the end, and I'm going to go ahead and hand it over— hand it back over to David Hendler.

Okay, uh, I would like to show everybody how I use, uh, New Constructs economic earnings tools in my research workflow and how could it help you as well, and then maybe some of your colleagues in other industry groups in fixed income. So first off, uh, this is the collaborative initiatives I've been using for the last 2 or 3 years. You see New Constructs. These are, you know, New Constructs is our equity valuation expert and economic value added, economic earnings, discounted cash flow analysis of earnings. Upper right is another major collaborator, NYU Volatility Lab. They're the only academic or other institution that is regularly updating a systemic capital shortfall analysis. They call it S-Risk. Every Friday, they update their algorithm calculating that for severely adverse stock market decline of 40%. They say banks should be prepared for that at all times. Can do sensitivity to 20% or 10% or 5%, and, and the numbers are pretty large as well. We also collaborate with the National University of Singapore's Risk Management Institute, which generates credit default swap level spreads globally for about 35,000 companies. You know, a lot of companies don't— do not have liquid or active CDS markets. So for regional banks, I could get a 1 to 5 year term CDS curve based on their methodology, as well as other foreign banks and other smaller financial entities globally. Then there's New Oak. They are an investment boutique, advisory boutique focusing on structured finance valuation. They've been doing a lot of work lately in municipal bonds, especially Puerto Rico valuations ever since Puerto Rico filed. They've been doing it for a long time, but as you know, Puerto Rico filed for bankruptcy. Last week. And VantageScore is a, uh, it's a consortium of the 3 major credit bureaus on consumer risk. And, uh, they do a lot of white papers and monthly and weekly assessments of where the direction is going in consumer risk. And then lastly, as everybody is in fixed income, pretty much we're beholden to Bloomberg. We use Bloomberg data and analytics. And, you know, over the course of the year, we're going to be participating in some of their Bloomberg conferences because they're making a big initiative in trying to get more independent securities providers on their platform. Okay, next slide, please. Okay, this is showing you a summary of how I use Dave's Um, new construct factors in my workflow. So, um, this is the global systemic banks, most of them, and their economic earning outputs. You got North American in the top block, mostly US big banks, brokers, and the big 2 big Canadians. Then below, that's the European systemics, so Deutsche Bank, the Swiss, the British, the French, the Spanish. And below that is Asia, Australia. You got 3— the 3 big Japanese banks. You have Australia now. NYU does cover the China banks, but we're not going to talk about them now. They are amongst the most systemic banks in the world, but that's like another conference call. Anyhow, um, you can see, you know, in the column headers, basically, uh, new construct output. So you got return on invested capital, you got economic margin to the right— that's return on invested capital, ROIC, less the weighted average cost of capital, WACC. Then you have— so that's like your basic profitability of your business. for these banks. And you have the free cash flow yield, which is new constructs free cash flow divided by enterprise value as they calculate it. And then the next 2 columns are really more equity valuation metrics, price to economic book value. So economic book value is an adjustment along the new construct methodologies. And then GAAP is a A term or length of time assessment of how fast the economic drivers of a company reach what the stock price is saying in the marketplace. And it's on a net present value basis. So it's a lot of what new constructs does is very bond math-like, which a lot of us on the call can relate to. So, and then the far right column Is net operating profit after tax running trailing 12 months, so through the first quarter of '17. And, you know, this shows you what companies, uh, more of a cash basis are making versus the accounting basis, right? Overstate things in a lot of cases, possibly understate things. So you can see just looking, you know, browsing down the far right column how US banks are making a lot of money, especially as compared to Europe. JP Morgan and Wells Fargo, they're making $20 to $26, $27 billion on net operating profit after tax. The next level of banks that are turning around more still are B of A and Citi, $15 to $17 billion. You got your 2 pure brokers, $7 to $8 billion, and then the Canadian banks are in the same range. Then you look at the European banks, and it's just awful. Let me tell you something, Deutsche Bank through the end of the year was only making about $500 million. They had a better experience Um, in the first quarter, you know, they're basically, they're, you know, firing a lot of people, you know, and harvesting the balance sheet, Dave likes to say. Um, but it's a lot less than the other major trading banks that a lot of you trade with and have counterparty, uh, exposures to, or you're a regulator and, you know, they have a big bank in New York, Deutsche Bank, and one going on there. UBS is making a little money. Credit Suisse is awful. I mean, minus $1 billion adjusted. I think it's a little better than their accounting earnings. And then you just go down the line. Barclays, $1.5 billion. HSBC is doing well because they have a monopoly position in Hong Kong and parts of China. The French banks are making a lot of money, but can I tell you something? Nobody understands why, because if you look at their slide decks for earnings and their annual reports, a lot of the businesses they are in are just low margin and not that attractive. So, why are they making so much money? We think it is a lot of activity in equity derivatives and other exotic derivatives. They do not talk about it in a straightforward manner. They do not allow disclosure, if at all. And it presents risks that, you know, are difficult to manage at times. A couple of banks have dropped out of or restructuring their equity derivatives markets because of what happened last August and September with the vol spiking from 11 to 20 on the VIX, 22, and then dipping off to where it is now, back to 11, 10, 9. And some desks were not ready for that. Commerzbank dropped out. Credit Suisse's head of equity derivatives resigned in October, both supposedly resigned, and we didn't really hear about it until March. And they're looking to redo that business. Santander, BBVA making some good money, and then Japanese have been making some good money too. You look at their ROICs on the far left, US banks are mid-single digits to high single digits. Canadian banks a little bit higher for RBC, maybe because of their monopoly position in Canada. You look at the Europeans, it's just pitiful. I mean, that's the thing. Why are bondholders buying all this AT1 and subordinated debt or even senior unsecured of these banks? Yes, they're cheap to US banks. No question about it. Even on a rating agency risk-adjusted basis, But if they can't generate positive margins, and in my estimation, there's no reason to believe they're going to do it anytime soon, even though they go around the world calling all you guys, their IRs, their CFOs, maybe even the CEO, saying, we're going to be better next year. We heard that from Citi years ago for 5, 6 years. Now, we're finally seeing it getting better. You think these European banks, Are ever going to get better when the US banks are so far in the lead? Look at the ROICs. Look at the no-pat trailing 12 months. Look at the FCF yield, the free cash flow yield. What does that really mean? It means that this is cash flow for shareholder payouts. I know bondholders don't like that, but it does happen, dividends and share buybacks, and it's cash flow for liability management. Do they have enough cash to do a tender offer, to early buy back bonds, or do a call? Now, Deutsche Bank looks really strong, but that's because they are harvesting their balance sheet. They're basically throwing out people out the windows in Frankfurt, and New York, and London so that they can have a better ability to make their bond payments. Oh, okay, for us bondholders, But that's the way you want them to be doing things? Come on. Even Barclays is, you know, similar in that respect. Credit Suisse, um, very high free cash flow yields because they're harvesting the income statement and the balance sheet because they don't have good strategics and they don't have, uh, good profitability in their businesses. All right, let's go to the next slide.

Dave.

Okay, so now we're gonna combine, uh, 2 approaches with our collaborators, uh, new constructs, the economic earnings type of figures, and then what is NYU saying, and then how do we use it together to get a better feel for systemic risk. So, um, Again, you got the same lineup of North American, European, Asia, Australia, big companies, big banks. And then on the far left is towards the end of April's systemic capital shortfall for all those banks. You can see, you know, JPMorgan Chase, the biggest trading bank in the world, the biggest counterparty in the world, has about a $40 billion capital shortfall. What does that mean? The markets plummet 40% over a 6-month timeframe. This is the NYU assumptions for the calculation. How much capital would they need to get back to an 8% common equity Tier 1? So it's $40 billion according to their calculations. We may have another call with them on how they do this, but basically They look at stock price volatility, stock price correlations, option price volatility correlations, other Greeks, CDS, and then they factor in some fundamentals. They come up with these numbers. The guy who runs it, Rob Engle, he's a Nobel Prize Economics 2003. They've been generating this data for the last 3 or 4 years. You see, Bank of America leads the US banks with a $69 billion shortfall. That's bad in a way. And then the other banks go forward, and then you get into Europe. Europe's even bigger than the US. So, they have bigger, largely bigger for the top 5 systemic shortfalls, and they have horrendous profitability metrics. as measured by, um, new constructs. So you can see Deutsche Bank, despite raising $8 billion of equity, they still need $78 billion to be bulletproof. You know, as I said, this is what NYU wants to see. Guess what? A lot of the regulators want to see a lot of this, especially when you start looking at this CHOICE Act. It's coming up through— that was Voted positively by the House Finance, it's going to the House. It's basically the alternative to Dodd-Frank. Deutsche Bank's scary. Look at Barclays, $59 billion. Only Bank of America in the US is ahead of it. Look at these French banks. They're doing so well on earnings. Look at the far right column again, economic earnings, but oh my, BNP, $91 billion shortfall. Why? I've been trying to figure that out. I asked different people. Nobody knows really. They're just like, I don't know. SocGen, $66 billion, and Credit Suisse higher than UBS, even though they're much smaller, $30 billion. Okay, let's take new constructs, scrubbed, high-quality, NOPAT earnings, economic earnings. See that on the far right? You divide it into the shortfall to see how many years Is it going to take for this bank to organically build their capital to fortress levels, very strong levels? You can see the US banks and Canada, it's kind of low. We consider 1 to 2 years very good, adequate for such a brutal situation as a 40% market meltdown. In the US, B of A and Citi are a bit higher. They're turning around. These numbers have been getting better as they've been generating more TTM NOPAT. Let's look at the Europeans. This explains a lot of my negative bearish views on a lot of the European banks. They just don't make money, and they're not going to make money anytime soon unless they just fire people. That's not a good way to make money. You want to grow the top line. You don't want to destroy your human costs and make everybody demoralized in a lot of these companies. Everybody knows these stories. You look at DB and it's like close to 30 years to come back from a bad market experience, the DAX going down. And then you look at Credit Suisse, it's -28.3%. Really, It's minus because they have negative earnings. That's even worse. And then you look at Barclays, a lot of counterparties and regulatory authorities and bond investors say, well, Barclays is a lot better than the other banks. Hello, it doesn't look that way. 38 years, they lead the European bank group. The French are like 8 to 10 years, so a lot weaker than what their Earnings would say, and then the Spanish banks. Santander is a bit better than BBVA. You look at the Japanese banks, Mizuho, which has been doing a lot of debt underwriting in the U.S. and trading 224 years. Oh boy, it's a long time. I don't think I'll be around for that. Anyhow, so this is how I'm using. Hardcore, rigorous equity valuation tools from new constructs, high-quality data, rub data, and inputs to get a sense of what's really going on, not what Moody's and S&P is saying. You all know they drive through the rearview mirror, and it's too late for you guys to get out of harm's way and bond price deterioration or be nimble enough to pick up after the fallout and buy the better-performing franchises before everybody else does. Okay, and you know, the Street doesn't provide the sell-side fixed income research the way they used to. They're not interested in it anymore. And we think of the independent providers out there, we have a unique way of looking at things with the stakeholder stack. The holistic method using New Constructs data, using NYU's data to get better bond outperformance. Now I'm going to just go through this because we're, you know, about 30 or so minutes into the presentation. Some, uh, buy, sells. I'm avoiding holds, um, for a couple of sectors or so. So in U.S. big bank land, listen, you know, spreads have tightened. year to date, mostly because there has been issuance, but the demand by the investor side is even that much bigger. What is interesting compared to like a year ago is whereas Wells Fargo was one of the cheapest banks, I mean, the most expensive banks across 3s, 5s, 10s, 30s, now they are like the cheapest bank. We all know why. It's the sales practice snafu that started out as like a little cut. Now it's infecting maybe the whole corpus of Wells Fargo. They're having a big investor meeting on Thursday. They're going to hopefully calm everybody down. But it looks like the equity guys are getting even more concerned because they bought into this cross-sell, never questioned it. And now that's not a driver for profit. Profitability the way it was. Step back, Dave Hendler had Viola Risk. Still a quality company. This is a way to get involved in Wells Fargo at a you know sales price, having a sale. Yes, we got to monitor the situation, but the you know the mortgage banking, small business banking, a lot of community banking is still solid despite. the transgressions. This is a big buy, in my opinion. And new constructs too, let's say they make a lot of money and they got a 0.3 breakeven. That's like the best out there for systemic risk. The other 2 big buys across credit curve are Goldman Sachs, Morgan Stanley. Goldman, I guess, stubbed its toe in the first quarter with some maybe commodity trading losses. There's been a question about how good is their trading. Blankfein, the CEO, has been talking about how volatility is low in the market, and this has to change, and that has to change with Dodd-Frank. Need the Volcker Rule rescinded. So, there's a feeling that maybe Goldman's not quite as robust as it used to be. I don't believe that. I think they— first of all, trading profitability and revenues is not a high equity valuation business. It's too unpredictable. You basically want to have the capability, you want to have the risk management to make sure you don't get out of control on the risk-taking. Goldman has the best out there. They have the best investment bank M&A. That's what's highly valued. That's good for bondholders too. We think Goldman's attractive. Morgan Stanley has been doing incrementally better, although it still trades cheap. The rich banks are the ones that don't issue as much, like Bank of New York and State Street, JP Morgan. They're doing really well. So, they're pretty much trading rich in comparison to the others, as well as US Bank. They do very well. Same basic recommendation. On the preferred side, I would say Morgan Stanley, Bank of America, Wells Fargo are cheap. So Wells Fargo is kind of a new name on that front based on what I was saying before. The more rich names, I would say, is better. Top performer, JP Morgan, Goldman Sachs, Citi as well is a little bit rich. You know, we have all the more details on this on the website per company. Pretty soon we'll be rolling out a one-stop shopping site for bond picks coming out next week or two, probably. You know, you get to regional banks, we didn't spend a lot of time on them, but for the 5-year, you know, I think on a risk-adjusted basis, SunTrust, BB&T, US Bank, PNC. So some of your better quality banks as rated by the agencies, plus SunTrust, which is kind of middle quality. You know, we find them more attractive than Regions, even though it's more spread. In some situations, the risk is higher. Regions, Citizens Financial, you know, they're kind of a bank name that's issued more lately. As they spun out and IPO'd out of RBS, Royal Bank of Scotland. And then KeyCorp looks rich in the 10-year. US Bank looks attractive, Comerica, if you can find it, because they don't issue that much. But BNC 10-years, we'd rather own US Bank for similar spreads. But BNC looks attractive in the 5-year. For specialty finance, we like Capital One, hybrid banks, specialty finance card players, so to speak. We like Capital One and 5s and 10s versus American Express and Discover. Wrapping it up with the European banks, we have been saying for a while to sell Across the capital stack. So debt and equity. Deutsche Bank and more in the last few months, Credit Suisse. Deutsche Bank, okay, they raised $8 billion. They got a new major shareholder from China, HNA. Look, you know, I know they go around talking to all you guys saying we're going to be better, we got it going now. They're not. Look at these economic earnings, the prospects. Look at the league tables. They're nowhere to be seen. Sometimes they pop up a little better, but that's because they have a one-off deal that's not repeatable. Credit Suisse, you know, is basically— has a CEO that's got to go. There's no following for him and his company. Ford has been around from Brady Dugan, the last CEO, and even before that. To TJTM. They gotta go. They just have not positioned this firm properly, and the only way they generate some earnings is by firing people. They're going to get rid of like 5,000 to 10,000 people. I mean, the morale there is horrendous. How are they going to do a good job focusing on their trading and DCM jobs? Um, sell across the stack even if things have tightened at times. You know, those are just, you know, temporary technicals, I would say. And you got to sell on the tightening. You need a lot wider spreads before I'm getting interested in these 2 companies. Uh, select buys, you got to like be a little cautious. I mean, I would say you got to be a lot cautious. Maybe caution, maybe you want to trade the technicals on headlines and issuance. Yes, I have concerns. Not as bad as DB and Credit Suisse. We think they will play out in terms of Level 3 risk assets, Barclays, and housing authority loans that are really doing poorly. They don't talk about it much. And then with the equity derivatives and exotic derivatives at BNP SocGen, you know, they have been managing the risk well or getting through it, but they really need to talk about it to investors, regulators, and counterparty risk managers, because it's, it's not always easy to be delta risk neutral on these types of equity volatility books. And then, you know, we would stick with some of the quality— buy HSBC. Um, you got this monopoly in Hong Kong, doing better in the league tables. A lot of investors want a European Underwriter and HSBC is one of the ones they're comfortable with, as well as Barclays. I know we didn't talk about Brexit, but we don't think Brexit's gonna affect the league tables. It's basically a corporate relocation, trading desk floor, trading sales floor relocation, a little bit of expense add to the EPS situation. Santander, BBVA are our other buys. In Europe. So now, you know, coming up on 45 minutes, I think we're gonna open it up to Q&A. Email in your questions to Dave Trainer and myself, Dave Endler, and we'll spend 10 minutes or so on questions. Hey, David Trainer.

Yeah, I was gonna say there's, um, a place where people can, if you haven't already, type in questions. But we've gotten, um, several good questions here that, that, uh, I'll share with the group, but keep them coming in. The first one is with respect— I think this one's for you, David Hendler. I guess maybe the question's asking, you know, explain again why fixed income analysts should care much about equity analysis, equity earnings, like economic earnings. And is the free cash flow And I can answer this question. Free cash flow that we measure is for all stakeholders, but David is a fixed income expert. Maybe you want to speak specifically to that question. You know, why do we care?

Well, look, look, I've been doing this since 1983, '84. I learned CAMEL analysis that all credit analysts learn, um, from the regulatory perspective, from ADHD, for Um, you know, balance sheet credit analysis is basically what fixed income analysis has historically been for financials, especially banks. It was good in 1980, it was good in 1990s, maybe. It was not good at all in the 2000s. You know, why do we care about charge-offs right now? Yeah, you monitor it, but it doesn't mean the bank is strong because they're just negligent. Okay, you know, my feeling is the millennials are going to be the worst credit card users of all time once their moms and dads don't pay the bill for them anymore and they got to do it. Sometime that's going to happen. Okay. So focusing on these old ratios, I call it old age analysis, is not going to help you outperform. Okay, it's not— now, can you outperform based on views of technicals, uh, supply risk, uh, possible headlines on litigation and other things that are hard to quantify, the size of the loss and settlement and the timing? Yeah, you could do that. But if you want to do a fundamental analysis, you got to look at economic earnings, and that's the new age way of doing it. And Dave's got— David at New Constructs has a really good mousetrap. And, you know, basically my view is the credit crowd has to grow up already and move on to the new age analysis. Yeah, the rating agencies, that's how they're focused, got the blinders on it. But we all know that they hold it to the A category for too long, and then it goes to BBB. Bonds leak out a little bit, and then they get pummeled as the single-A-only buyers bail out for the BBBs. Same thing for the BBB. They hold on too long, and then it goes to BB, and it's even worse outcome. You got to get ahead of that and not just say, oh, everybody was wrong. lemming, you know, type of analysis. So everybody thought what Moody's said, you know, all this trying to guess what goes on in Moody's and S&P's, you know, investor committee meetings, it's, it's like ridiculous, okay? Because it's like trying to analyze, you know, entrails analysis when you're hunting. I mean, come on, they don't know, you know, they're doing it their way, but when they pull the trigger is is sometimes political because they got big exposures in their subscriptions to all these big banks, million to 2 million to 3 million, maybe 5 million subscriptions at stake. And the rating could really piss off some of these guys paying them. And like, but it's happening. Lions Bank just cut out, I believe, uh, S&P because the rating is too low, and they substituted it with Kroll. Who's really watching Kroll? Come on. So, you know, you got, you got, you gotta— we have to mature is a better way to say it, enhance our toolkit and start looking at this stuff the way equity does, but use it for our debt holder counterparty risk and regulatory purposes. And this is, you know, new constructs as an easy way for us to understand what equity is looking at and using it for the fixed income.

And, you know, I would add my marketing that we've seen a real convergence in general across the hedge fund, mutual fund, wealth manager space, even advisors, you know, back to sort of the basics. You know, we've sort of had the— over the last 15 to 20 years with interest rates going down, what I would call the E-Trade baby boom, the huge influx of unsophisticated investors or amateur investors in the market. You know, a lot of these sort of short-term superficial tools have been effective, but we're seeing that coming to an end. And we're, you know, we're seeing white papers and studies by consultants pointing out how the underlying organizational structure of investment management firms are changing. We saw what happened with BlackRock, you know, getting rid of discretionary human managers. Same is true again with AllianceBernstein. This whole idea of investment managers sort of an intuitive capability can just figure stuff out. People don't buy it because it largely hasn't worked. And in the equity space, active management has woefully underperformed before fees. And it's driving a real sort of shift back to analytics. It's a numbers game at the end of the day.

Yeah.

And we believe machines are better at numbers. And we're seeing that changing. The world is changing on that front. And I think David Hendler has been on the leading edge of pointing that out to you, that it's— look, it's not going to be as easy as it once was. It's time to start paying attention to fundamentals. And getting good research on fundamentals is not that easy. Can't just pull it all off of a Bloomberg. You can't just pull it all off of an S&P report. You got to have somebody going through and doing the diligence and the footnotes and the MD&A if you really want to do fundamental research right. And I think one of the things that David Hendler told me early on, he's like, listen, my perspective on this is as long as it's accessible to our clients, why would you overlook it? Why put yourself at a disadvantage when you could be at an advantage?

Right.

when it comes to understanding fundamentals when we make it as easy to access as New Constructs does. And on that front, I thought maybe I'll jump in and do a quick kind of show you how easy it is to access New Constructs just real fast. We're a website just like anybody else. So if you wanted to get our rating or our report on Deutsche Bank or Credit Suisse, You type in a ticker, you get an answer. Again, this is all at newconstructs.com. If you want to download a report, click another button, right? And we'll give you details on what we see in quality of earnings, what we see with respect to valuation, history of return on capital versus cost of capital, accounting earnings versus economic earnings, and then details in the appendices behind where all this data comes from. Institutional clients get access to our models, and our models are auditable back to the original financial statements. So, and we're the only firm in the world that I know of that even tries to do that, and that is to link the models directly to the Ks and the Qs. And so we've got not just more data but higher quality data on that front. With that, I'll get to the next question. I think we kind of already answered that. A few of these. Here's one: How does forward? How how is new constructs like bond math? That's a great question. So when I when I grew up in the business, you know, my mentor had a had a slide where he basically said, "Look, you know, the value of a bond is a function of." The coupon payment, the risk to that coupon payment, and the maturity date. And he said the analogous drivers for those 3 things for stocks are cash flow— coupon payment is like cash flow— risk is like the weighted average cost of capital, and maturity date is like competitive advantage period. And, and I thought, okay. Um, he said, well, the big difference is that for bonds Those drivers are contractual. You know the coupon payment, you know the maturity date. Risk is an unknown, that's interest rates. But you pretty much on any given day, you know what interest rates are, so that's why people can calculate the value of a bond on a daily basis. For the stock, you don't— nothing's contractual. But what you can do is work backwards from the stock price and figure out what kind of cash flow, risk, and maturity date is implied. By the stock price. And that's what our models do. And so when you're— when we're looking at valuation for new constructs, this growth appreciation period is the market's implied number of years of profit growth baked into the stock price. And so our approach to valuation, again, is very different from traditional sell-side. I'm not trying to pretend like I'm the expert, the oracle of XYZ stock. That's what Mr. Market does. And what I try to do is help my clients identify when Mr. Market is most euphoric and most depressed. When expectations for future cash flows are way too high or way too low. When it's somewhere in between, you know, we're kind of like neutral. We don't really play in that. We're not pretending that we can— we have a better crystal ball. But we do like to say that our focus on quantifying the expectations baked into stock prices is unique, uh, and, and very transparent. So like one of our models, for example, uh, if you want to go in and create your own forecast for a particular company and look at the implications on cash flows, we could do that. So for example, let's say that we think margins for Credit Suisse are going to jump up to the highest level in the last few years, get up to 10%. We can call this an optimistic scenario, save that off, and then we can quantify what kind of equity market value and cash flows are going to be generated by the business if the company can achieve this optimistic scenario. And on our decision page, you'll see that we've now plotted 2 lines, one for the default scenario that's primarily based on first-call consensus— that's the blue line here— and then the This optimistic scenario based on a much, much higher margin, you see, has much higher implied cash flows. And then, as I mentioned before, everything's auditable back to the original filing. So if you wanted to see all of our income statement adjustments, things we're pulling out of cash— of operating earnings, you know, for example, here we've got, you know, asset write-downs hidden in operating earnings, $31 million. This is on page 283.

Okay.

You can see you just click there and you get an immediate detail on that adjustment we're making. Same is true for balance sheet. So for example, operating leases are on page 333, right? We saved you quite a bit of time taking you straight to that. I'll pause there and we'll get to some more questions. I don't want to monopolize too much time. So David Hendler, I think this is more for you. What makes you think that now is a good time to focus on this stuff versus others? Obviously, New Constructs has been around for a while and you've been around for a while. Why now? Why do you really think it matters?

Well, you know, first of all, I spent, I guess, 4 years on the buy side in my early years, years on the sell side at 5 big bond trading and underwriting shops, did mostly debt, then equity. And then I was, you know, one of the early-stage builders at Credit Suisse. I ran US financials. I was the global coordinator for the overall global financials product. And, uh, I basically decided I wanted to do my own thing. So that's been the last 3 years. So now I could do it the way David Hendler wants to do it, not within, you know, some other major management team's construct. So, you know, these are things I've been thinking about for many years. Um, I think with my own company, I'm able to showcase it. And that's why it's now versus before. But I also think, you know, look, we're in this age of data overload and, you know, a lot of— now you got fintech. I was just in Silicon Valley the other day, you know, there's something— We got to figure out besides the hype and the, you know, salesmanship of Wall Street, they're very good at that. I I worked with them for many years. What's real out there? I'm trying to give an assessment, a view of what is— what you really need to know, what is real. It has to be economic-oriented, economic earnings, economic performance, not camouflaged accounting performance or the way the CFOs companies arbitrage loopholes in accounting to make their results look better for— look at Wells Fargo and the cross-selling. Why didn't all these equity analysts who followed them all these years and debt analysts and rating agency analysts, why didn't anybody question this religion on cross-sell? It was like, well, Wells had goodwill with the community. through. They didn't get crushed in the credit crisis. They weren't a big capital markets bank, but now you have a major differentiating event. Now, could I have caught that that easily? Probably not. But we always pretty much felt that Wells was rich, even for what we could see. So, that's You shouldn't own the bonds back then. Now I think you should be owning the bonds. There's some hair on it. Yeah, there's some controversy, but we think with our toolset, you know, utilizing new constructs, NYUV Lab, the way Dave Hemmer looks at things, um, that it's time to get more involved in Wells. Maybe it'll get a little bit cheaper because they do have T-LAC debt to do, but I think they said in their last call it's More like $5 to $10 billion versus $20 to $30 billion a year ago. So, you know, yeah, there's always going to be some technicals, some headlines you don't even know they're going to happen. But I think the more you stick to economic earnings, you have a better gauge of what's really something you should be concerned about and what's like a Noise, and it'll get through it. Yeah, you could day trade it. Yeah, you could hedge fund it. But if you're like mostly out there longer-term investors or intermediate-term, you know, negative economic earnings trends is so much worse than, you know, temporary blip on some litigation or some, you know, view on Dodd-Frank choice now. And All these other temporal issues. Next question. We got to wrap up soon.

Yeah, I would say just to add one little thing to that, that the way I think you've put it, David, that I thought was great some of our other meetings, you can look at these equity earnings as sort of the heat shield, um, protecting the debt. And if you know that that heat shield is burning up quickly or is very thin, you're better off positioning yourself to be prepared for the additional risk implied by the thin heat shield than not. Uh, and, you know, I, you know, another great example I think is, you know, my partnership with Scottrade. My first meeting with senior leadership there, I said, look, I don't even know if you guys want to, you know, are interested in new constructs. I did this meeting, you know, because of a friend, um, and, and because I know most of your clients only focused on, you know, technicals and short term. They said, no, no, we, we think it's a good idea to to start providing higher quality research to our, our clients. And so we're interested in diversifying a little bit around just pushing them the technical information. I said, well, that's— I think that's great news because look, even if you are focused on whatever you're focused on today and you have methodology that's, that's been working, it still behooves even, you know, the day trader technical analysis analyst at Scottrade to screen his technical ideas through our fundamental due diligence. And have the best of both worlds, especially since we make it available so inexpensively and, and make it so easy to access. Why not have an additional layer of protection and intelligence when making investment decisions? And, um, you know, and we were off to the races with Scottrade. We had 5,000 people sign up in a month, uh, with zero promotion on that platform. And now we're looking forward to working with TD Ameritrade and having, you know, being on it in front of 10 million investors and a variety of other partnerships. Thomson Reuters is on 170,000 advisor desktops and working directly with corporations. You know, at the end of the day, if you're not focused on returns on invested capital as an executive, you know, What does that mean to us as investors focused on EBITDA, non-GAAP EBITDA? Anyway, that's— I'm getting off on another tangent here, but I think the time has come for more rigorous analytical tools, and I'm proud to be working with David Hendler to help bring that to more fixed income investors.

Okay, that sounds like a good way to wrap it up. Thank you for your time. Out there. And if you want to talk to Dave Trainer at New Constructs, I could, you know, give you an introduction. If there's equity colleagues of yours who want to, you know, explore this as well for their purposes or other sectors, you know, energy, technology, telecom, utilities that want to look at New Constructs for their analysis for, you know, surveillance, you know, we can set that up as well through Dave. All right, thanks for your time and speak to you soon.

Thank you.