ENVX - 22 Things I Learned About Investing In 2022 (Part 3)

2023-04-03 15:09:00 ET

Summary

• I cover a wide variety of topics in this article, including buying call and put options as alternatives to leveraged long and short positions.
• I also discuss how to deal with preferred dividend payments in terms of company earnings, bid-ask spread costs, and how to relate your number of positions to your transaction costs.
• I suggest doing a kind of static discounted cash flow analysis instead of projecting future growth, negotiating your margin interest rate, and differentiating momentum strategies between individual stock momentum and industry/sector momentum.

2022 was an excellent year for me. OK, I didn’t make as much from my investments as I did in 2020 or 2021—who did?—but a 22% return isn't bad.

But more important than how much I earned is how much I learned. Was this a better year than most? I don’t know. I learn a lot every year. But with every lesson I learn, I realize how stupid I was the year before.

So here are some things I learned in 2022, in no particular order at all. This is the final article in a series of three, and will discuss eight things—the other fourteen are covered in Part One and Part Two .

1. Call options, as a form of leverage, are very undependable

When I started buying calls and puts near the beginning of 2022, doing so made sense to me. I got the idea from reading Jim Cramer’s Real Money . (It’s not a bad book, despite what Cramer has since become; it was written way back in 2005.) In it, Cramer writes,

I used both puts and calls to tremendous effect when I first started out as a little investor and ultimately at my multi-million-dollar hedge fund. Over the years I found that options were a fantastic way to make a little money into a lot of money. As I am a constant risk-reward hunter, I loved the idea that I could risk some money on calls to make much bigger money than I could make buying common stock. I also loved the idea that I could bet against a stock using puts without worrying about a short squeeze. . . .

This appealed to me. Certainly buying puts seemed a lot better than shorting because the upside of shorting is limited to 100% per stock and the downside is unlimited. And buying calls made sense because it struck me as similar to using much greater leverage than simply going long.

But I didn’t pay enough attention to something Cramer wrote later in that chapter:

When you know that you have something big, either way, the best way to play it is in puts or calls. But if it isn’t big—and about 99 percent of the situations I hear daily aren’t big—it is better to use the common stock.

I bought too many call options on stocks that I wasn’t actually terribly certain about. As a result, I did quite poorly. Overall, over the course of a year I invested about $300,000 in call options and only got back about half of that. That hurt.

Put options, on the other hand, required more conviction, in part because they’re so damn expensive. Fewer than 5% of the puts I wanted to buy struck me as cheap enough for me to actually purchase. Also I had no alternative for these stocks. If I wanted to bet against Peloton Interactive, Inc. ( PTON ), buying puts was far safer than shorting the stock. So, I invested $240,000 in puts and made $216,000 in profits for a 90% return. (And indeed, a large chunk of that was from Peloton puts.)

I realize that 2022 was an unusual year, and that in most other years I would have done much better with call options than I did and much worse with puts. Nonetheless, I’ve decided to only buy puts in the future, simply as an alternative to shorting, and to simply go long on the stocks I believe will appreciate.

2. Subtract preferred dividend payments when considering earnings

When a company calculates its earnings, it deducts all of its interest expenses—except one. It does not subtract its preferred dividend payments.

Preferred stock functions a lot like debt. When a company needs more money, it can borrow it from a bank, sell bonds, sell preferred shares, or issue more equity; selling bonds and selling preferred shares are quite similar. Just like bonds, preferreds have contractual dividends, have par value, can be redeemed early, and sometimes have a fixed maturity date. If the company liquidates, preferred stock owners, just like debt holders, get seniority over stockholders (though bondholders have seniority over preferred stockholders).

But because of the peculiarities of generally accepted accounting principles ((GAAP)), in their financial statements, companies deduct payments to preferred stockholders only after calculating their earnings attributable to the company. (They must do so in order to arrive at earnings attributable to common shareholders.)

In order to get a true picture of a company’s income, then, preferred dividend payments should be deducted. And these can be substantial. For example, General Electric’s ( GE ) preferred dividend payments amounted to more than a third of its net income last year.

FactSet and Compustat both subtract preferred dividends when they calculate EPS. FactSet also subtracts them when they calculate net income, return on assets, profit margin, and so on, but Compustat does not. In this regard, FactSet’s figures give investors a better picture of how much a company is actually earning than do those from Compustat, at least in my opinion.

But analyst estimates rarely take preferred dividends into account. That’s why you’ll find a huge discrepancy among companies that pay preferred dividends between the analyst actuals for the most recent quarter and the EPS adjusted by data providers for the most recent quarter, with analyst actuals almost always higher.

Before I discovered this in 2022, I was relying a great deal on earnings estimates and unadjusted Compustat numbers for vital earnings data. Now I’ve revised my formulae to take preferred dividends into account.

3. You end up paying about half of the bid-ask spread on each trade

Before last year, I was quite uncertain about this number. But I then did a massive study comparing my fills to the most recent price prior to placing my order. This study included straight limit orders, some modified after placement; VWAP orders; and relative peg orders. It included extremely large and extremely small orders, on many of which I got some price improvement by my brokers (Fidelity and Interactive Brokers). The only kinds of orders I excluded were those placed prior to market open and those for which there were no fills on the day of the order prior to my placing it. The data was a mess, but after some smoothing, the relationship in the heading above was pretty clear.

4. Why DCF analysis is so unreliable, and why a simplistic version might actually work better

Discounted cash flow, or DCF, analysis depends primarily upon the following variables: a company’s unlevered free cash flow over the next ten years, its cost of equity, its cost of debt, and its “permanent” growth rate in the distant future. A company’s cost of debt isn’t that hard to figure out, and most analysts peg the permanent growth rate to historical GDP growth. But future cash flows and cost of equity tend to be wild guesses at best. This is true whether one bases future cash flows on a fixed growth rate or something else; basing that fixed growth rate on past growth is a terrible idea, as growth in free cash flow tends to mean revert.

A simplified version might work better. We want to arrive at an intrinsic value that we can compare to the company’s enterprise value. We assume that the company’s free cash flow, cost of equity, and cost of debt will be constant in perpetuity, setting its growth rate at zero. The intrinsic value of the company will then be its free cash flow divided by its cost of capital, where the cost of capital is the weighted average of the cost of debt and cost of equity according to how much debt and equity the company has.

For free cash flow, we can use current and future estimates plus the taxable portion of the most recent annual interest expense or, if we want to be more careful, an average of the company’s unlevered free cash flow over the last five years, adjusting for inflation and trimming outliers, and weighting more recent figures higher.

For cost of debt, we can use the average of the interest expense divided by the company’s debt over the last five years, again trimming for outliers.

We can set the cost of equity between 7% and 13% depending on the company’s historical share turnover and price variability (decent proxies for risk), but since the cost of equity should never be lower than the cost of debt, there has to be some flexibility with that 13% maximum.

Finally, in calculating the cost of capital, we should cap the weight of the cost of debt at 30%; a company with a huge amount of debt should not have a lower cost of capital than a company with very little debt.

(I’m indebted for these ideas to the second edition of Value Investing by Bruce Greenwald, Judd Kahn, et al.)

We end up with an intrinsic value that’s almost always between five and fifteen times the company’s unlevered free cash flow.

For banks, insurance companies, and other financial companies that use debt as a source of income, you’d want to compare their intrinsic value to their market cap rather than to their enterprise value. So you’d ignore interest expense and cost of debt and simply use free cash flow and cost of equity.

Not long ago I wrote an article about the best performing value factors, of which unlevered free cash flow to enterprise value and free cash flow to price are two. The performance seems to improve to some degree if you use the above calculations to take into account cost of capital or cost of equity.

5. Your number of positions should be proportional to your transaction costs, not your assets under management

Before 2022, I believed that as your assets under management go up, you need to have more positions in order to keep your transaction costs down. I still believe that, but the assets under management, or AUM, shouldn’t drive your position count. Instead, your transaction costs should. If you can reduce transaction costs without increasing position count, then there’s no reason to increase the latter.

Transaction costs can be attributed to two factors: market impact and the bid-ask spread. The amount traded has nothing to do with the bid-ask spread, but it certainly affects market impact. Let’s say you’re trading Espey Manufacturing & Electronics ((ESP)). The spread is about 1.66% of the price, the daily dollar volume is about $53,000, and the daily volatility is about 2.2%. If you were paying only spread costs, you’d expect to pay about 0.8% per trade. If you were paying only market impact costs, those are approximately the daily volatility times the square root of amount traded divided by the daily dollar volume. So if you were trading $53,000 worth, you’d be paying 2.2% and if you were trading only $10,000 worth you’d be paying about 0.96%. You’d then average the spread costs and the market impact costs for the total cost per trade, and then multiply by two to get the round-trip costs.

One approach to determine how many positions to hold, therefore, is to do some math to optimize the total portfolio return given that each additional position will probably lower your return but also reduce your transaction costs. That’s what I was doing before 2022, and believe me, it was mathematically pretty complex.

But there were too many variables for it to really work. Another approach to reducing transaction costs is to increase your holding period. You can also reduce transaction costs by buying and selling over several days rather than all at once. Placing VWAP orders cuts your market impact by almost 50%. Moving from high-volatility to low-volatility stocks will decrease your transaction costs, as will buying stocks with higher volume.

In 2022, I realized something. If I were to run back-tests to optimize the number of positions in a strategy given a certain amount of slippage per transaction, I would get a very different answer if I were to use a high slippage or a low slippage. With very little slippage, it would make sense to buy the top five stocks in terms of rank and sell them if they went down in rank past twenty-five. With very high slippage, it would make much more sense to buy the top twenty stocks and sell them when they went down to 120 or 150 in rank. A whole different portfolio management approach was optimal, all depending on slippage costs. And I could run simulations to determine the appropriate buy and sell rules, which would then determine my number of positions.

6. Margin rates are negotiable

I can only speak about Fidelity here, but their customer service reps listen to their clients. I was able to shave four or five percentage points off my margin rates by simply calling and asking (and suggesting I might move my account to Interactive Brokers instead). I know of a number of other traders who have done the same. Margin rates are not set in stone.

7. Industry momentum doesn’t work like individual stock momentum

For individual stocks, the tendency to mean revert predominates over periods less than one month and more than two years. Momentum predominates for periods between three months and one year, and the factor is most effective when you exclude the most recent month. For sectors, subsectors (industry groups), industries, and subindustries, on the other hand, momentum is effective even for the most recent month. I have no idea why and how industry momentum works; not only does it contradict the law of reversion to the mean, but it does so consistently and much more strongly than individual stock momentum. Obviously, sometimes there are dramatic turnarounds, but in general it’s a very useful factor. I’ve found a six-month to nine-month measure to be most effective, but for catching turnarounds, even a one-month measure can work.

8. Companies that have never had positive operating income are best avoided when going long

Peter Lynch suggests avoiding what he calls "Whisper Stocks" in One Up on Wall Street . He doesn't define them precisely, but he does mention that "usually there are no earnings."

Most of these firms are biopharmaceuticals and SPACs, but this rule also excludes companies like Uber Technologies ( UBER ), Snowflake ( SNOW ), Cloudflare ( NET ), Palantir Technologies ( PLTR ), and NIO ( NIO ). Every back-test I’ve run for going long works better if you exclude companies like these, which are practically impossible to price. On the other hand, shorting some of these, or buying puts on them, can be profitable. (I’m currently holding puts on two such companies, Aspen Aerogels ( ASPN ) and Enovix Corporation ( ENVX ), and my Aspen puts have almost doubled in value.)

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