Associate Analyst Virtual Meeting With David Trainer

Hello everyone, this is David Trainer, CEO of New Constructs. I'm here today to talk to you about our Associate Analyst Program. Feel free to send in questions during the— in the question and answer GoToWebinar control panel. And today we are going to talk about what kind of firm New Constructs is, what our purpose as a firm is, what do our analysts do, what's the experience like, How does our work impact the business and markets? And how does our technology work? As a former auditor, executive compensation consultant, and Wall Street analyst, I can tell you most of what you see on TV or what comes out of Wall Street is very biased and incomplete. They're looking to make you sell or buy quickly over and over, and honestly, to take advantage of you. If you don't believe me, you don't have to take my word for it. There are plenty of surveys, Studies and articles published in major media outlets that speak to this. CFOs admit that they fudge their earnings and the sell-side analysts don't pick it up. Another really good article is When a Buy Is Really Not a Buy, which basically points out that sell-side ratings, investment ratings mean nothing. And for those of you familiar with the space, when 90% of the ratings are neutral or buy, or 95% are neutral or better, and 80+% are buy ratings, You got to know something's a little bit funny. A big part of the background here is that the amount of work it takes to do the real work, to understand footnotes and understand cash flows, is tough because 10-Ks are getting longer and longer. When I started in this business, they were short. Now they are super long, over 200 pages on average, and they're not exactly comic book material. If you're relying on the regulators to help you out with respect to investing, Not going to happen. I've worked directly with the SEC. Their inability to leverage technology, their desire to do things sort of the same way they've always done them, has really put them behind, behind the 8-ball. Look no further than Valeant or the Madoff scandal if you want specific examples. The Financial Accounting Standards Board is making real strides, but they're still mostly populated, that board, with ex-corporate and audit folks, and they don't really always understand accounting. They understand accounting well, they don't understand finance, and there's a big difference. The rules are changing. It's getting more and more difficult to get to the truth about companies. As long as the bad guys out there, inside the banks and inside the companies, know this, they'll have an advantage over those folks who don't do their diligence. And when it comes to doing diligence, the things we like to do for folks, it's as easy as understanding certain assumptions buried in footnotes. Like what's in the footnotes for pension plans. We like to look at the expected return on plan asset assumptions. These are assumptions that can drastically affect earnings. In fact, we've got a case study a little bit later that shows how we use finding this data point to predict a company was going to go bankrupt. The point is, there are always outliers in financial reporting. When you've been through hundreds of thousands of filings as we have, you find that there are— there's an exception to every rule. And there's nothing you can assume about what companies will do to cook the books. And in the big picture here, technology is changing investing. We're in a different world today than we were 10 years ago. When I got started in the business, there was no such thing as an E-Trade baby. There was no such thing as direct online access. When my grandfather was in the business, he had to wake up and look at the Wall Street Journal in the morning to find out what closing prices were. The world is different. Most of that has been directed toward online trading or self-directed trading. That's where most of the changes happen. It's mostly hurt client relationships. It's definitely hurt the level of rigor that's gone into research because guess what? The majority of investors out there, if they're E-Trade babies, well, they're not doing research beyond technical research. They don't care. So technology has not done much for due diligence. We make due diligence possible again. Think of it as value investing 2.0. We help our clients, whether they're institutional money managers, hedge fund managers, consultants who speak directly to CEOs, advisors, or individual investors. We help them improve their assets under management. We help them improve client trust. And think of us like the robo-analyst, somebody in there who's got the time to do the things that people don't have time to do. This is the pain point we solve. Look, machines can be better at some forms of diligence. Going through filings, have you ever done it? Maybe once or twice. Try going through 120,000 as we have, right? Try going through a few thousand that I did manually before I created the technology. It's tough, it's difficult, and often the smarter you are, the harder it is to do it. That's why we created technology. Technology to show exactly how the machine should do things. We didn't pretend to think that machines could all of a sudden figure out how to analyze filings. We created a machine learning environment in 2003, and that machine learning environment— and you can learn more about this on our technology page available from our homepage— Our machine learning environment was very simply a combination, an application that combined the filing itself in a digital form, a database, and a very simple parsing tool. And that framework allowed us to put a lot of efficiency into the parsing process. There were checklists that had to be checked off to make sure analysts looked at everything. There were easy error-catching mechanisms that could be included. Most importantly, though, in that environment, machines could track exactly what the humans were doing. and catalog the human actions into a library of human-validated instructions as to how to go through filings. And that library has grown as we've been through, as I pointed out before, and we note up here, 120,000 filings. Now the machines are parsing more than 2/3, sometimes as much as 85% of the filing forest for us. So our analysts learn faster, They do what Warren— what took Warren Buffett 25 years to do, we do in one filing season or one year or really in a matter of weeks. And the idea is that machines are better at doing this kind of work than humans. Once the machines do more of the filing parsing, humans get to do more interesting things like identify new accounting loopholes, find ways to update and improve our models. Because at the end of the day, we want to give our clients the best in technology. Who doesn't deserve the best in technology? Who doesn't deserve to be served at a fiduciary level? Who doesn't deserve to be a client where their best interests are put in front of the advisor or the manager? We all deserve that. We're making that possible at New Constructs. New Constructs is also 100% unconflicted. We don't have any ties to our clients or to our bank or to companies or the companies we cover. Morningstar is not An independent research firm. They get paid by the fund companies that use their ratings. In order to talk about your good rating on Morningstar, you have to pay Morningstar a license fee. Anyone want to guess at the distribution of ratings for funds by Morningstar? They have more positively rated funds or less? You guessed it, a lot more positive because those companies are a lot more likely to pay the Lansing the licensing fee in order to brag about the positive rating. Also, a little bit more about New Constructs. You want to know who our clients and partners are. We have some of the biggest partners and clients in the world. Thomson Reuters, we have a distribution partnership there that puts our research on 170,000 financial advisor desktops through the Thomson One Wealth Management platform. We're on Scottrade, Interactive Brokers. That's about a million almost individual investors, self-directed investors, and registered investment advisors between those 2 firms alone. Wells Fargo Advisors is a big client of ours. Ernst Young on the consulting side is a client of ours. We often publish our op-eds in MarketWatch. We're on CNBC. We're regularly in Barron's. Our work is some of the best in the business because we have the best data and some of the smartest people when it comes to accounting and finance at New Constructs. As I mentioned before, I'm a former auditor and executive compensation consultant. I was an equity analyst at Credit Suisse and a hedge fund manager. The rest of the team, the key people: Lee Manetta Kohler, he'll be your direct report for the most part. He runs the operations. He's been with us for over 10 years, and no one knows more about our technology, our models, and how things work than Lee. Rich Brashears is our CTO. He's out on the West Coast. You don't see him very often, but he's in many ways the ghost in the machine. He and his team have allowed our machine language learning platform to drastically improve our efficiency. And most of that's been done in the last 12 months, the last 9 months, because technology, fintech, just recently caught up to what we've been doing since around 2002. The first machine language platform or product that we built was produced in late 2003. And most of our work up to that point was focused about— focused on becoming a hedge fund, which we did for most of the last 10 years. And really just recently have we pivoted to focus more on research. We think it's better to sell bullets to the war than be in the war. We think the applications of our technology, our automatic parsing, our intelligence around how to navigate complex unstructured datasets, how to leverage natural language processing, Give us a big advantage in a lot of places in the investing business, corporate governance business, consulting business, and executive compensation business. So what do we offer? First of all, training. We're going to invest a lot in our analysts, and we expect a lot back. The first part of training is 2 weeks of classroom training with me. It's a no-pass/no-play deal. If you don't get a 90 or better on the cumulative final, you don't get a job. After that, there's 5 months of systems and implementation training where you get practice in applying the principles learned in the classroom training. Don't get me wrong, we're not looking to weed people out. We weed people out in our interview process. Everyone we bring in, we want to pass, and we'll do everything we can. There's not a question on the final that you won't have seen before you take the final. So while it's a no-pass, no-play, most people do pass. It's mostly a matter of effort. You'll also learn how to use our cutting-edge technology. There's nobody, nothing in the world, nobody in the world that has anything like what we have for going through filings, building models, and producing research. You'll be able to produce research for clients, journalists, consultants, and investors. We expect our analysts to improve our models and technology. We expect you to help us make markets more efficient. What really makes unique— makes New Constructs unique is really how much we invest in our new analysts. It's not just about the accounting, finance, and technology training. You get to be part of a very cooperative and empowering environment that's 100% transparent. The only gating factor on how much you can contribute is how much you want to learn, how fast you want to learn, and how hard you want to work. We have an internal wiki for everything we do. How we create our model portfolios, how we treat footnotes, how we order office supplies. If someone else has figured something out, we don't want to make someone else do that again. We want our new people to stand on the shoulders of the folks who are already here, to leverage the intelligence, the intellectual gains that we have made in the past. Which means there's no ceiling for your ability to contribute and advance. Join a talented group of individuals who care to do things right. All the oars are pulling in the same direction at New Constructs, and I'm very proud of that. I'm also very proud of our ability to develop young individuals into more mature professionals, more competent professionals. We take a great deal of pride, Lee Manetta-Culler and I do, in creating an environment that empowers everyone To be more successful. Because the more you do, the more I can do, the more the company can do. And we depend on you to do that. And we bring people in straight out of college for the most part, because most of the time, if you've been to business school, you've learned too much stuff the wrong way. We're bringing people in straight out of college with a decent amount of accounting background, right? And a desire to learn, an enthusiasm for finance. And that's all you need. That and your ability to work hard, and you can be successful here. Again, we want you to help us improve our models and technology. You know, our most recent group of analysts that came in spent a lot of time reviewing our website and making a lot of great suggestions for changes. And we love that because they're fresh to the website. They hadn't seen it before. Sometimes we've seen it a few too many times, and so it's good to have an outside perspective. And the platform that you're able to work with and is again, as I mentioned before, really unique. We're the only firm in the world that's, that's combined a data gathering infrastructure with modeling and delivery. We're the only research firm that actually gathers our own data and produces our own research. Capital IQ, Compustat, World Scope, those firms, they're in the data gathering business. What they do with 3,000 people in India, we do with 15 here in Nashville, Tennessee. That's how we make technology work for us. We'd rather have a small group of really smart, motivated folks using technology to become more powerful than we would, than we would have an entity or an organization that's just looking to throw more people at the problem. So we collect data directly from the SEC or from any source for that matter. We can collect data from a private equity firm. We can collect data from a company directly. It doesn't matter where it comes from. We know how to deal with it. Again, we've been through 120,000 filings. We've seen where the bodies are buried. We've seen how the sausage is made. You wouldn't believe some of the things we've seen. It's hard to explain what companies think they can get away with. And part of the problem is that when the SEC is only looking at one filing every 3 years, which is their mandate— I don't know if you knew that, but the SEC only has to look at One annual report every 3 years for every company. So, you know, companies will roll the dice every now and assume that nobody's looking. We're always looking. There's a calculation engine that sits on top of our database. That's how the models are made. All right? And that calculation engine is flexible. Our clients give us new ideas for formulas. They give us custom formulas and calculations. We're happy to put those in. We're not in the business of selling religion. Right. We're in the business of being an efficiency tool. And then delivery: API, Thomson One, Scottrade, Interactive Brokers. Our systems will work through all of those platforms. As an example of some of the work we've done in the past, I'd love to talk about this article that we did on Eastman Kodak in March of 2011. What we found is that they had a Return on plan asset assumption for their pension of 8.7%, the single highest assumption for all the publicly traded companies we covered in 2010. It allowed Eastman Kodak to boost revenues by over 2%, earnings many times more than that, even though that pension plan was underfunded by $2.6 billion or 3 times the market cap. Let's see here. We're making money from a pension plan that's drastically underfunded. Red flag, right? At the same time, we saw that the valuation of the stock implied the company's profits were going to grow 10% compounded annually for over a decade. Expensive valuation, misleading earnings. Title of the article was Dead Company Walking. 9 months later, they claimed bankruptcy. Now, it took 9 months for our research to really hit the marketplace. The turnaround time is much faster these days. days. It took 9 months back in early 2011. Much faster these days. This is one of my favorite slides because when I showed it to the Director of Enforcement at the SEC, he literally jumped out of his chair. And what we're saying to the SEC is, hey, don't try to boil the ocean. There's too much data out there. You need tools to go through and identify patterns that help you identify early indicators for fraud. What we found for this company Dynergy was that in the 3 years prior to getting busted for fraud, there were 16 write-down charges that amounted to $3.85 billion. That's after tax, by the way. $3.85 billion, or 346% of the net assets on the balance sheet at the time they were busted for fraud. What does that mean? For every dollar of assets left on the balance sheet, They'd written off $3.46. Isn't that the opposite of creating shareholder value? Taking the money investors give you and writing it down to a lower level? That's shareholder value destruction. Creating value is when you make more money than what the investors have given you. You know, one of the other things that you're going to be doing here is, is really going through the filings and finding things that matter. If you ever heard of XBRL, you probably know that XBRL does not count or does not apply to the management discussion and analysis section of filings. Yet we're finding material hidden items in every one of— and on average, every filing we— or for every company we cover. So material hidden item is an unusual gain or charge that's buried in the MD&A in this situation, or the footnotes. And it's not something you can see on the income statement because it's buried within the cost of goods sold or SG&A, some other line item on the income statement. So you never know it's there. The only way you know it's there is if you dig through the MD&A and pull it out. And you're never going to get that data from any— from most any other data source, including XBRL. The balance sheet matters too. The balance sheet matters too. And in this period from 2009— and this was actually, I think, only about 2/3 or 3/4 of the way through 2014— we found almost 33,000 write-downs. Write-downs matter. We show that for Dynergy. It matters for Dynergy. And it matters for understanding capital allocation, for sure. And this is the product. If you haven't seen it, it looks like this. You throw in a list of tickers and And you get our ratings. Red is bad, green is good. Very simple, right? Note that we've got mutual fund, ETFs, and stocks all here apples to apples. Why? Because we're, you know, we cover ETFs and mutual funds in the same way we cover stocks, right? An ETF and a mutual fund at the end of the day is just a collection of stocks. So why not build a model for a mutual fund or an ETF that's just like the stock? And that's what we do. And we're the only firm, I think, in the business that does that. If you want to know more about our ratings, we show our clients everything. We show them the components behind the ratings, quality of earnings and valuation. And there's more on our website, the education section. You can learn about this. And I highly recommend if you're coming in for an interview, we're more impressed by people who know what we do based on our website than people that don't take the time to do that. But all the details you need to know about our rating are here. You can add companies to portfolios. You can see the model. You can download into Excel. You can download a PDF report. We're 100% transparent, not just with our internal clients and analysts like you guys, but also our external clients. We want people to know how much work we do. We're proud of it. We want our external clients and our internal clients to challenge our competitors, to show them how much work they do, because we know it's not as much as what we do here at New Constructs. And we've got screening tools, of course. We're covering 3,000 Stocks, 7,000 mutual funds, 450 ETFs. We can screen easily in a matter of seconds across all of those asset types. How does New Construx compare to other research offerings? Pretty well. The main areas where we, I think, are different and can really outshine folks is in the modeling and transparency. Yeah, there are a few other firms out there that provide models, especially lower on the list. Those models are a joke, right? It's just basically throwing some financial data into Excel spreadsheet. Nobody out there can link their data in their models directly to the SEC filings in the way that we do. There are some firms that can link financial data back to the filings. That's great, but nobody's got a model that makes use of that data and links that back to the models— back to the filings, excuse me. So we show people, we make adjustments to the income statement to calculate economic earnings and return on capital. We show people what those adjustments are, not just where we make them on the income statement, where we make them in our net operating profit after tax calculation, but we show them where that data comes from in the filings. The idea is that we want everyone to trust us. We want people to know how much work we do. We want you to look behind the curtain. One of the few firms that covers stocks ETFs and mutual funds. A lot of firms talk about ROIC and economic earnings. I don't really believe that anyone does it with the integrity that we do it, mainly because I know that we're going through the footnotes in the MD&A. Some firms are. SIFRA is pretty good, right? They've got an analyst team that does some of this work, but it's not systematic. They don't have technology. And trust me, going through filings, the smarter you are, the harder it is. They're not doing it as systematically and exhaustively as we are for every single filing. Morningstar talks a big game with respect to return on capital and economic earnings, but are they doing this work in the footnotes? I don't think so. Can they show us? Can they show us how they calculate return on capital or economic earnings? Not that we can find. Not anything in the public domain. Same is true with EVA Dimensions. EVA Dimensions is taking a data feed from Compustat. I started New Constructs and created a data collection tool Because new comp— because Compustat is not good enough for sophisticated investors. And now we're making it available, you know, through our partnerships with Scottrade and Interactive Brokers to everybody. Because guess what? Bad data shouldn't be acceptable to anybody. We're also independent. Notice here that we point out that Morningstar is not independent, EV Dimensions is not independent, and, you know, a lot of these firms, most of these firms are not truly independent in the same way that we are. A little bit more about our technology. You know, Lee Manetta Coe likes to call it value investing at scale or value investing 2.0. I think that's a great way to think about what it is we do because the filings have gotten so long you just can't go do the old Graham and Dodd method. It just takes too long. It's all the type— take all the time you have to read through 10 years of filings and build a model for one company for probably, if you did it right, at least a week, probably a month if you've never done it before. So what we have is, is an expert verified knowledge base of over 120,000 filings. We have a procurement system to get these new documents in. They get cleansed and processed, automatic parsing and data extraction based on what you see here. Then we push things through models and other analytics engines. Then we go to human verification where we need it. And that information gets passed back into the system over and over until we get things right. Then we have our final dataset that informs the mining engine, which further informs the automated data extraction and parsing. And at the end of the day, we've got awesome output. This is sort of a lot of tech speak, but it gives you a bit of a sense of, of how the system works. It's a production-proven learning system across syntactic, semantic, and modeling domains. Very unique. The key asset is those 120,000 filings that are expert verified. And the tool you use is going to look something like this. This is the original version. I don't like to give away in a public domain exactly how our technology works because there's no reason for me to make this easy for everybody. But this is what we had in 2003. Very simple. Again, the filing, the database, and a simple parsing tool. And the parsing tool could move the analyst through the filing based on blobs of words and blobs of numbers. So nothing is ever typed in, and keystrokes move from line item to line item, number to number, and also send data into the proper bucket, right? You've got a bucket for all this information, and it's the bucketizing of all this data that's so powerful across 120,000 filings. If we've put This item in the same bucket 120,000 times out of the 120,000 times we've seen it. Well, guess what? A machine can do it. Machine could probably do that after about 500 times, right? That's why our database of over 120,000 filings is so good, and it's getting— and it's growing faster and faster. We started this work at about 70,000 filings about a year ago, right? And we're already at 120,000. It took us, you know, 12, 13 years to get to 70,000. It's taken us Less than a year to get to $120,000. And it's not just about tables. It's also about footnotes, right? And we've got a lot of really unique proprietary buckets and footnotes to deal with the unique nature of footnotes. And this is where a knowledge of finance comes in. You don't know how to treat this data if you're just an accountant. Or if you're just a data collector. How do you know what an non-cash charge on cost of sales means? We know because we use data, because we've been— we've run a hedge fund, we've been a sell-side analyst, we've been writing research and analysis and run real money against live bullets. We know how to use— do this work. We specialize in it, and we've been doing it for a long time, so we're really good at it. So the benefit, you know, here to you as you're listening to this today is that you've had somebody— you get to benefit from the fact that people have been through other analysts before you. 120,000 filings. Made all these subtle distinctions, put this data into a database so that a machine can learn and do more of it. So you're spending a lot less time doing things, repetitive, mundane things that have been done before. Most of what you do will be the parsing and collection of new data and teaching the technology. And then of course, figuring out ways to update the models, figuring out ways to update other processes, other processes that we follow here. So that's been about 30 minutes. With that, I'm going to pause here for some questions and, and see what you all might have to, to say about what you've heard so far or what you'd like to learn. One of the first questions I have here is, how long is the rest of the training program? The first part of the training program with me is 2 weeks. The rest of it takes, you know, I think 5 to 6 months. There are lots of tests along the way. We've done this program a lot of times. We tweak it a little bit every time we go through. We get feedback from analysts when they go through the program so we can make sure, you know, that we're maximizing their ability to learn, maximizing their ability to be as successful and to contribute as much as possible. To the company. That's the idea. We want to bring you up to speed as fast as possible so you can contribute as much as possible. That way we get the most out of you, and we're willing to invest a lot in you on the front end to make that happen. Some of the largest problems that new analysts face? You know, look, the work's— it's hard work. You know, the training program, if you're not prepared, Is going to be a real challenge. There's no simple way to put that. If you've not— and we're going to send you the materials in advance— if you've not studied those in a large amount of detail, if you come in behind, it's very difficult to catch up. It's important to be— it's important to make sure you're as prepared as you can possibly be when you get here. And that's what I've come to expect over the years. You know, the great thing about every single training program I have done, back to the days when I was training at Credit Suisse, every single training program I've done, the majority of people pass, like 80%, 90%. A lot of times there's, you know, everybody passes. And so I know, I know how to do this. We know how to do this. And at the end of our, you know, at the end of the day, it's in our best interest for you to pass. Bring in a bunch of people, they all fail, what are we left with? A big investment, a lot of time, and nothing to show for it. So, you know, we're all aligned here, but we want to make sure you're fully aligned, you're fully bought in, because guess what? We're investing a lot in you. We're going to put a lot of work into making you as productive as possible. The timeline going forward in the interview process, you know, as you reply to our head of recruiting, you'll get answers and you'll get transparency on that, but I believe there's a modeling exercise, there's an essay, And depending on how well you do on that, you'll be selected for a phone interview. And depending on how well you do on that, you'll be invited into an in-office visit. Very few people get invited in for a visit. Very few. We tend to hire most of the people we bring in. So, you know, look, everything's about time allocation. So we're looking to screen people out as strong as we can because we're getting thousands of resumes. And we're not— and I don't believe in looking at resumes. You know, you better— you wanna have a good one, of course, but I'm not gonna trust a resume. I'm gonna trust what you can do. So I'm gonna see how well you do on that modeling exam or modeling exercise, see what your essay looks like, see what kind of enthusiasm, what kind of effort you're willing to show. And then when we talk to you, we wanna know how much you know about new constructs. Everything we do is on the web. It's easy to find that out. The interview process will be completed sometime, I think, early next year. Let us know if you've got something pressing and need to know sooner than that, and we'll facilitate that. But typically, we finish that up, I believe, I think we like to finish that up in January. And then we have to go dark for a little while because we've got filing season. And then, you know, if we haven't filled all the slots, sometimes interviewing will go into March, late February and March. The position does not require a finance background. Really, you need to know about accounting. We'll teach you all the finance you need to know. You need to know the basics of accounting. So if you've not had any accounting, I would study up on that. We, you know, we don't, you know, in terms of our analyst program, there aren't a lot of technical skills. SQL, a lot of Excel, Aqua Studio. I'm not familiar with all those, but feel free to write into our head of recruiting, Alan Jackson. He can share that with you. Now, our engineers will be using Python, natural language processing, Java, and a host of other tools. Having technical experience is going to help you because we're working directly with engineers. I mean, that's the thing about New Constructs. Analysts work alongside engineers to develop cutting-edge technology. Cutting-edge technology that we think will change investing and make the capital markets more efficient. What should you do as a potential analyst from now to the beginning of the program to be as ready as possible? Learn as much as you can about new constructs. The more you know when you're here, the quicker you can be, you can be productive. And the better you'll be in the training program. The education section of our site, you know, there's a lot there. And I tell you, we had a candidate last year came in who went through every single page of that, and he had great feedback on how we could make it better. Made a difference. You know, that was— all of our hiring decisions are pretty tough. Anything you can do to distinguish yourself that shows that you are into what it is we're doing is important. We come in, we talk to people, and they talk about all the stuff they've done. They don't know anything about new constructs. Not impressed. I'm, you know, uh, we'll be honest with you about that. What we're doing here is unique. We want people to have enthusiasm about it. We're doing things that have never been done before. No one's created machine learning technology to collect data, build models. No one's created value investing 2.0 in the way we have. We think that makes us exciting. And honestly, I don't think anyone gives young analysts a better platform for growing and maturing than we do. With all the training, with our wiki on everything we do internally, you'll see that there is, you know, there are no secrets here. There's no seniority. There's only competency. People advance in new constructs based on their abilities, nothing else. So, the more you can do to know about what we do, and again, we'll send you the training materials ahead of time. But the more you can do, the better. The more you can study that, the better. On what industry does New Constructs mainly focus? All industries. All company sizes. You know, we want to actually build models for all— every company in the market. Now, it's hard to do that right now. We cover 3,000 of the most actively traded companies. And that's about 99% of the US market cap and 95% of the global market cap. But we are very close to, and not far, you know, 3 to 6 months away from covering almost all companies in the market. How many new analysts are we looking for? Kind of depends on how many good ones are out there. We take typically 2 to 5 in every session. What qualities or skills do we look for in an ideal candidate? Enthusiasm, hard work, intelligence, strong ethical background, a desire to make the capital markets more efficient, a desire to make yourself to be a better person, a more competent professional, a good communicator, a desire to learn that is unquenchable. And of course, you know, We want you to know about new constructs. If this is the job you want, you know, then we expect you to do some real diligence on that front. The training happens— are training sessions only given at specific times during the year? Correct. We take a training class. We typically allow you to get some familiarity with the systems for a few weeks. We take up— sorry, we take a new analyst class, and we bring you in, and we get you familiar with the system, the computer, password, email, you know, so you get comfortable. And after a few weeks, you start the training program. And once that— we only do that training program once a year. Compensation is competitive. It changes a little bit, but I think we, you know, I'm not exactly sure the exact number we start people at, to be honest with you, because I haven't looked at that in a while, but it's very competitive. Look, we're looking to get talented people. We're not looking to scrape the bottom of the barrel. We think our value proposition is very strong because you're getting a lot more than just cash compensation in New Constructs. You're getting a training program. You're getting an education. You're getting an education in accounting, finance, valuation, capital markets. You're getting an education in technology. You're getting an education on communication. You're getting an education on how a highly productive, highly functional business environment works. What we do with 10 to 15 people, some of the largest investment banks in the world have not been able to do. Thomson Reuters can't do it. S&P Capital IQ can't do it. Bloomberg can't do it. So, you know, we've got— it's a unique environment. It's a unique environment. So, you know, I urge you, we're going to be competitive in compensation. You're going to be wrong. But you need to think about the big picture. Right? You know, we've had people come in before who said, you know, I got paid a lot more money, but my job was 1,000 dials a day. That was a long time ago when our compensation wasn't as competitive. But you gotta keep in mind, not just what you make in year 1 out of school, what are you gonna make in year 5 and year 10? And what you make in year 5 and year 10 is a function of how much intellectual capital you develop early in your career. You can make a lot of money and a lot of jobs right out of the gate, but where's that going to leave you in 5 or 10 years? How are you going to make the real big money if you don't really build intellectual capital? And that's what we're about here at New Constructs— building intellectual capital. What qualities do successful analysts have? I believe I've already answered this, but it's hard work, intelligence, Strong character, enthusiasm for the capital markets, enthusiasm for new constructs. With respect to what do I mean by basic accounting skills, you know, look, usually if you, if you've done, you know, at least a couple of levels of accounting in school, you'll be all right. A little bit of, you know, the The more finance, the better. You want to know the basics of income statements, balance sheets, cash flow statements, how to create one from the other, right? If you have an income statement and a balance sheet, can you create a cash flow statement? Okay. And you need to understand, you know, how income statements, balance sheets, and cash flow statements work. You need to understand some basics around modeling, how to discount cash flows. How to forecast cash flows. That's what you need to know. Besides 10-Ks and 10-Qs, what other financial forms do you research? Not many others. I mean, we want to get into proxy statements. We want to get into private versions of 10-Ks and 10-Qs, right, what private companies do. But you're going to, you know, tend to do a variety of things. We have projects all the time that come up, like doing research on the fintech industry. Doing research on the history of technical analysis, doing research on how to calculate the cost of capital, cost of debt, get that kind of data. There's a lot of things that go into building our models that are not just about reading 10-Ks that analysts have an opportunity to build competency around. The cool thing is you're typically not starting from zero. You, you're starting from zero in terms of the project, but there tends to be a lot of, you know, real wealth of information and knowledge around most everything we do And that's a nice stepping stone into any project that people— Have we ever considered expanding? I don't really know what that question means. If you can re-enter that one and let me know what you think about expanding. In terms of the number of people we have, you know, we're not really that interested in expanding beyond what we have. As I tell, you know, we do regular company-wide meetings and I do Once a quarter, a face-to-face with everybody in the company. And look, there's a lot of interaction here. It's a very flat organization. But I don't have any desire to have 100, 200, you know, 50, 30, 40 people at New Constructs. No desire for that. I'd rather have a small group of really highly talented, capable, positive, enthusiastic people leveraging technology to do what 3,000 people do in India or Czechoslovakia or whatever, right? I don't need a big organization. Can't avoid bureaucracy. We work with some big organizations. Can't avoid it. Smart people don't want that. I want really smart, effective, um, what can I say, enthusiastic people. Special ops as opposed to— Great. Fronts, so to speak, right? Rather a bunch of Navy SEALs than, you know, a bunch of, uh, than a bunch of, um, privates, you know, in our business. Yes, New Constructs does reimburse you for successful completion of CFA exams, um, and materials and all that kind of stuff. If you pass the CFA, we'll pay for it. Uh, you know, we do allow employees to trade. All of your trades have to be approved by our compliance officer. Um, none of your trades can be in stocks, ETFs, or mutual funds that are on our blacklist. Um, so, you know, we don't really like you to do a lot of trading. Um, you can, and people do, uh, but, you know, we want— you know, we just— it's, it's not, it's not ideal, right? Uh, we allow it. We've got specific policies that make it make it allowable. And we've got certain blacklists that you're not allowed to touch or trade on, but we'd rather you focus on doing your work here than trying to run your own personal portfolio. Because, you know, look, we know how hard it is to do that kind of work, and it's not, it's not easy to do in your spare time on the weekends. The training period is paid, but it is not the full salary, so you're sort of on a A test period. I forget the term for that. So, you know, look, if you don't pass those first 2 weeks, we'll let you go. You will be paid, and it may be at the full rate. I'm not sure. It's close to it. Our turnover rate for analysts is fairly low. You know, we've had analysts— analysts that have been with us for the longest tend to be the most successful. You know, one of our analysts was with us for 5 years. He went on to Columbia Business School and was the, you know, got the only scholarship that Columbia gave out in the couple years that he was there. Superstar student, number 1 in the class, went on to work for a very high-profile private equity firm. Basically could have any job he wanted. You know, another analyst went on to take a very senior position in technology and management at Vanderbilt. We've had folks move into accounting, valuation, other stuff. You know, the background you get at New Constructs is very attractive. Don't get me wrong. You'll know more about finance and accounting than just about anybody in the business. And I think if you read some of our reviews on Glassdoor, if you get a chance to talk with any of our analysts, ask them about what some of their colleagues that are at the same stage of their careers are doing. You know, especially investment banking, Wall Street. Look, I've been there. I was on Wall Street for just about 7 years. I still have got friends who do that work. It's not nearly as glorious as it once was, and it was never that glorious. You know, most of investment banking, you're putting together PowerPoints and you sit around and, you know, a lot of my friends in investment banking, they'd say that we'd sit around in the office all day playing Tetris. That's how old it was, how old I am, because that was a game that people played. Playing Tetris. Waiting for the MD to come back. The MD comes back at the end of the day, gives them a bunch of work to do. They have to work all night so that the data is ready for the MD, the PowerPoint presentation. You know, that's not what we're about. We want to empower you with real knowledge so you can make, you know, we want you to be interested. We want you to be happy to work here. We're not looking just to churn through you and just go on to the next person because we know that there's a line of people waiting out the door just to have this job because it pays so well. That's not my mentality. It's not our mentality. We want, we want an empowering environment. I can't say that enough. We want an empowering environment where everybody's looking to grow. We don't want a bunch of turnover, so it tends to be very low. Right now we do not require any Series 7 or 63 types of certifications. We are a publisher of information. We are not providing advice. We're just like the Wall Street Journal, Investment Business Daily, Investors Business Daily. We're putting out information. We got opinions. We operate under the First Amendment. We're not in the business of directly providing advice, so we do not need other certifications. Those are all of our questions. If I don't see anything else come in here in the next few seconds, we're going to call it a day. Thank you very much. If you have additional questions in the future, just let us know. We'll send you a copy of our slides. used in this presentation. And again, you can contact us at recruiting@newcontracts.com. Thank you very much, and we appreciate you being with us today. Thank you.