What’s it Worth, Anyways? The Things I Learned from a Value Investor

Yesterday, I had the privilege to speak with Scott Conyers, a local Portland-based investment manager who runs the fittingly-named Scott Conyers Capital Management. Mr. Conyers is a self-proclaimed value investor who takes a conservative approach to investing, with a primary focus on analyzing the intrinsic values of companies and their respective stocks.

A week before this interview happened, I started reading One Up on Wall Street by Peter Lynch. I bring this up because this book has made me realize how I have been researching new groundbreaking technology in complex (and oftentimes abstract) mathematical modeling this entire year, but I have almost entirely neglected traditional approaches to investment. Sure, it’s nice to be on the cutting-edge, but you also need to understand what exactly you are cutting. I’ve interviewed high frequency traders, market makers, quants, VCs, and financial engineering students, but not once have I spoken to a good old value investor. After my conversation with Mr. Conyers, I’m starting to feel a bit stupid for not reaching out to one sooner (it’s funny how reading advanced papers on complicated subjects can make you feel comfortably intelligent, which is actually one of the hallmarks of dumb people [dumb people often think they’re the smartest etc…] but I can philosophize another time).

Anyways, back to Mr. Conyers and value investing. Before trading algorithms began to steadily take over Wall Street beginning in the 1980s, pretty much all risky investing was value investing. Back then, you could invest in bonds or treasuries, but these tend to be much safer investments than stocks. Nowadays, we’re so spoiled with complex positions such as puts and calls that we forget how risky stocks can be. The general idea behind value investing is to speculate the future or current value of a company, and to invest in its stock accordingly. In principle, it sounds simple: If the current intrinsic value of a stock > current market price of the stock, then invest in the company. Likewise, if you speculate that the future value of a stock is greater than what it is currently valued at, then you invest again.

In practice, things can get muddier. For one, how do you calculate the intrinsic value of a company and its stock? For two, what if the speculated growth isn’t significant enough to out-pace fees and inflation?

Mr. Conyers was able to provide some invaluable insight into these questions, and more:

*Note: The conversation has been paraphrased.


S.A: Mr. Conyers I would like to thank you once again for offering to help with my project and my research. So, to start things off, I understand you work with finding inefficiencies by comparing the intrinsic value of a company to its market price. Could you explain how you go about finding the intrinsic value of a company?

S.C:I’ll give you an idea of how my business works, which isn’t too different from any other money management firm. You get an initial investment from a client, and you are given permission to invest money into different stocks and assets. Obviously, my goal is to make money for the client, and I take a set percentage of the profits. So there’s a lot of ways to go about this, this is where you have hedge funds, venture capitalists, and all sorts of investment strategies.

I am a value investor, and you are correct that that means I would like to understand the intrinsic value of a company and its stock. Value investing is pretty specific, and it is definitely different from momentum investors or growth investors because they anticipate growth, and growth companies.

Most of my work involves comparing the intrinsic value of a stock to its market value, and comparing hype of the news to how this hype is reflected in the markets. This last part is interesting, because a lot of the time, the markets are influenced by what others are thinking, this is where the hype and bubbles come into play. So, if I recognize that a company is greatly hyped up by the media or by influential investors, but this same company has a disproportionately low intrinsic value, this is a sign to stay away from that company’s stock.

A good example of this is how standard, trusted companies can change over time. For example, Google and Facebook and Tesla and Starbucks were all trusted by investors, and so their stock prices went up consistently thanks to this positive feedback and image. But now, as we’ve seen, no one is considering Tesla or Facebook to be safe bets any more.

I never bought Starbucks stock, maybe regrettably, because I thought it was always overpriced, but this stock has kept on growing. This is one problem of value investing, as a company can be severely overvalued, but can continue to grow at the same time.

S.A: What made you think Starbucks was overvalued?

S.C: I just didn’t see the growth potential others were seeing, I didn’t think it was possible or profitable for there to be multiple Starbucks on each block. In other words, I never envisioned that a city like Portland could have over a hundred Starbucks stores. But never underestimate a company which sells addictive substances, like coffee or cigarettes.

So to get back to your question, to calculate intrinsic value, you take all the future cash flows of a company, which is approximated through earnings, and discount them back to today’s value.

The discounting is taking into account inevitable losses, such as what is lost is through inflation, fees, or other risks. So, if you find that future earnings minus these discounts is still greater than what the current market price reflects, your intrinsic value is greater than the market value. Obviously, this is a simplification of all the math and calculations, but the general idea is the same. Some financial experts have tried methods to calculate how risky a stock is or will be in the future, and they weigh this into their calculations as well.

Take Lyft for example, which makes no money, so how do we figure out it’s worth? We look at what might happen in the future: Maybe Lyft will raise prices to counter losses, but this would also drive away customers. Maybe all the talk about driverless cars will come true, which it probably won’t, and Lyft will save huge amounts of money by not having to pay drivers.

So it all goes back to speculating on how a company will operate in the future: When I didn’t buy Starbucks, I thought there was no way they could open so many locations in the future, so that was my speculation. Turns out I was wrong, because they did, but that’s only one example. That’s the same view I have on Lyft and Uber today.

S.A: You mention on your website that you employ a conservative investment approach? How would you define the difference between a liberal investment approach and a conservative one?

S.C: Liberal would not be the opposite of conservative in this case, conservative just means I think the companies I invest in will exist ~40 years from now. Sustainable companies, to me, that’s what I mean by conservative investing. That’s why I work to analyze the intrinsic value of the companies.

S.A: Not trying to unveil any trading secrets here, but I am just curious if you guys employ any quantitative models / algorithms in shaping your clients’ portfolios?

S.C: I’m not here to bash on quants or people involved in that, but those guys who use those types of models don’t care about the companies themselves, they’re only working in arbitrage.

There’s a clear disconnect between the models they use and looking at the speculative value of companies, future cash flows, markets. I don’t consider them to be creating any value, they’re just feeding off of inefficiencies, and the markets would do fine without them. If one day, all quantitative trading stopped suddenly, the market would still be liquid. It’s clearly a zero sum game, so for them to win, someone has to have lost.

This is not to discourage you though! In the back of your head, you should always remember the true intrinsic value of a company, which doesn’t get reflected through these algorithms.

The movie The Hummingbird Project comes to mind, as this shows the extent of the measures that are taken just to cut off milliseconds of time off trades so someone else can be overcharged.

S.A: So I’m guessing you don’t use quant algorithms to influence your investment decisions?

S.C: Again, my main focus is the intrinsic value. Now, interest rates are super low, they’ve been super low for a while, and the president wants them even lower. They’ve been too artificially low for the past 15 years. I’m mentioning this because the interest rates are so low right now that some of the traditional mathematical equations value investors use aren’t valid. There’s some formulas which require you to divide by federal interest rates, but once you start dividing by smaller and smaller fractions, the numbers can blow up and this is very misleading. So things are definitely changing and we need to adapt to that, but there’s a lot of traditional trading formulas that I will use. For instance, there’s the required rate of return formula, which is referred to as k. That’s then used for other formulas, like return on investment and discounting techniques.

In terms of other math models I use, we also use tools which give predicted return on investments, which works by analyzing patterns of returns on investments in the past. This might be more similar to what you’re talking about in using AI or math to analyze patterns, but these won’t completely inform my decision to invest or not to invest.

S.A: How much do you analyze market cycles when looking at the potential value of an investment? Do these cycles influence your decision to invest in a position, or is it more about the fundamentals (intrinsic value)?  

S.C: In my day, there were people called chartists which looked at a chart of stock prices. There’s definitely logic to looking at patterns, as these types of patterns happen for a reason, and if that reason is rooted in human behavior, it is bound to happen again and again.

One great example of this are pressure points when a stock reaches a previous high, because people will anticipate a fall again. When a stock is rising and reaches a new historical high, it becomes difficult for the stock to rise past this historical high because most people are afraid the stock will start to fall at this point, like it did when it reached this high in the past. The same goes with the snowball effect of bubbles, which definitely follow predictable patterns. 2008 is a fantastic and recent example of this.

Interestingly enough, I’m not seeing any bubbles today. Again, I decide whether or not we’re in a bubble by looking at the intrinsic value. All the farmers by my house are planting hazelnut trees, and there’s no way there’s such a sudden surge in demand for hazelnuts, so I’d say there’s a hazelnut bubble going right now.

Cycles were talked about all the time at economics school, but since then, we’ve realized (we think we’ve realized) that these cycles are meaningless because we can counter them with artificial interest rates. You don’t have to balance your budget, because you can just print money. Economics is changing for sure. If we’re heading into a cycle, then this will definitely influence my decision making, as I consider it part of the future value, and therefore part of the intrinsic value. I need to look at which companies will do well in the cycle. Again, cycles really build off themselves, which is why they definitely need to be acknowledged.

S.A: Do you think this artificial counter-approach to cycles will come to an end, or is this the new future of economics?

S.C: It will work, right up until it doesn’t. This happens in all historical examples, so why would it not happen this time. There’s a possibility that this will actually be the new future of economics, at which point we would all need to adjust our approaches.  

S.A: I think we’ve touched on all of my questions, and before we end, I just want to say that finance and investing, specifically quant finance, is definitely a huge interest of mine which I will keep working on in the future. I’d like to ask if there’s some final advice you would give me going forward as a future investor?

S.C: I got an engineering undergraduate, but I got an MBA after. I used 5% of what I learned from my MBA, and the rest of the 95% came from experience. Living life is better than reading about it.

When you get to be in your 20s, bright young people like you tend to get stuck to academia, and you can end up spending so much time doing work that is meaningless in terms of real experience and results. You should definitely pursue a higher education and develop your skills, but you really need to get out and work in the field.

There’s clearly a lot to unpack here, so I will try to make my summary concise. Here’s a list of key takeaways from my conversation with Scott Conyers:

  • Mr. Conyers talks about the concept of value investing, which is a form of money management much different from the arbitrage and trading algorithms I’ve been researching all year.
  • Value investing involves calculating the current and future intrinsic values of companies, which is a much more holistic way of analyzing a company’s value as opposed to analyzing and reproducing patterns in the markets.
  • Value investing does involve a lot of math, but this math is focused on discounting, return on investments, and speculating future earnings. Again, this comes back to calculating the intrinsic, or perceived, value of a company.
  • Mr. Conyers believes quant finance tends to ignore the intrinsic value of companies, though I surmise he was thinking of HFT rather than analytical hedge funds. According to him, quant investors simply use their technology and algorithms to find small inefficiencies which they can capitalize on — A clear zero-sum game.
  • Mr. Conyers’ final advice to me, or anyone who is a future investor, is to get out in the field of investing to gain actual experience, rather than confining my abilities to academia and theory.

Though all of these points are fascinating, I was very interested by Mr. Conyer’s explanation of how artificially low interest rates have literally changed certain fundamental approaches to investing. By suppressing natural market cycles through unnaturally low interest rates, the Fed has essentially changed the economy as a whole.

Realistically, this knowledge doesn’t help with my project itself, in regards to coding, Word2Vec, or backtesting. But I believe there’s a priceless value to understanding how so-called normal investing works, from the perspective of someone who has been doing it for nearly 30 years. As I will also discuss in my report on One Up on Wall Street, value investing truly offers a lot insights into how companies gain and lose value, which is what really drives the markets (without the companies, there would be no stock market). Algorithmic trading has proven its expansive capabilities to us, and I believe these capabilities are only growing in direct relation with time. As of now, there’s certainly a human touch to investing which algorithms haven’t been able to replicate. I do think we are getting closer though, especially with NLP and automatized sentiment analysis.

Maybe all of the traditional wisdom offered by value investors is now rendered useless by algorithmic trading, or the artificial suppression of market cycles by the Fed. Maybe the future of investing is already here, and there’s no point in looking back. But, as is the case with training neural networks, the more information the better.

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