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Leveraged Cybersecurity ETFs Are Debuting At A Dangerous Time

Summary Direxion launched two leveraged cybersecurity ETFs this past week. These ETFs may be debuting at a time when the popularity of cybsecurity stocks has already cooled and valuations are still very high. History has taught us the dangers of investors choosing to chase past performance or chasing “hot” stocks. It was probably just a matter of time before Direxion – one of the primary issuer of leveraged and inverse ETFs – jumped on the popularity of cybersecurity stocks. This past week, Direxion launched the Direxion Daily Cyber Security Bull 2X Shares ETF (NYSEARCA: HAKK ) and the Direxion Daily Cyber Security Bear 2x Shares ETF (NYSEARCA: HAKD ) options on the cybersecurity sector. But like many products that get launched after the initial popularity soars, the timing often proves to be a dangerous investor trap. The first ETF to jump on the trend – the PureFunds ISE Cybersecurity ETF (NYSEARCA: HACK ) – has quickly racked up well over $1B in assets and was up over 30% within 8 months of its debut. Cybersecurity stocks have cooled off though thanks to the global economic environment and now the fund is up just marginally since it opened. HACK data by YCharts Followers of behavioral finance will tell you all about investors’ tendency to chase past returns and how it often results in buying high and selling low. You probably won’t be surprised to learn that AUM began ramping up at their fastest pace as cybersecurity stocks were peaking earlier this summer. Just in time for these investors to experience the subsequent pullback. Which is why launching a leveraged cybersecurity ETF right now is dangerous. Investors are still being told in the mainstream media that cybersecurity companies are “hot” and money is still pouring into these products. Even after the recent pullback, many of these cybersecurity companies are trading at very rich multiples. Many of these companies still have yet to turn a profit so measuring them by P/E would be unfair. Instead, let’s use the P/S ratio to try to gauge valuation levels. The S&P 500 as a whole currently trades at a P/S multiple of 1.63. Popular stocks in the sector include Palo Alto Networks (NYSE: PANW ) at 16.98, FireEye (NASDAQ: FEYE ) at 11.13, Fortinet (NASDAQ: FTNT ) at 8.97 and Checkpoint (NASDAQ: CHKP ) at 9.33. While the P/S ratio isn’t necessarily an all-in-one measure, it does go to say that even after the recent pullback cybersecurity companies are still very expensive and could indeed fall much further. Looking back at the Nasdaq bubble in 2000 gives us many examples of investments launched at the wrong time. Take the Jacob Internet Fund (MUTF: JAMFX ). This fund was one of the first mutual funds targeting primarily internet stocks at the time. In the six month period from roughly October 1999 through March 2000, the Nasdaq Composite rose over 175%. The Jacob Internet Fund debuted in December 1999 right as tech stocks were about to hit their peak. What happened next is still a good lesson in the dangers of chasing performance or “hot” stocks. The Jacob Internet rose around 20% in the few months after its debut but by the second half of 2001 the fund had lost around 95% of its 2000 peak value. JAMFX data by YCharts That’s not to suggest that a crash like that is imminent in cybersecurity companies but it does make very clear that jumping into a cybersecurity ETF – especially a leveraged cybersecurity ETF like the two launched last week that are designed to magnify the returns of the sector – could be especially dangerous. Conclusion Direxion is well within their boundaries launching these two ETFs right now but it might not be doing the average investor any favors. These ETFs have a triple whammy of risks – investing in risky cybersecurity stocks, investing in leveraged securities and investing when much of the frothy returns may have already been had. These ETFs are very much a case of “buyer beware” for investors. Disclosure: I am/we are long FEYE. (More…) I wrote this article myself, and it expresses my own opinions. I am not receiving compensation for it (other than from Seeking Alpha). I have no business relationship with any company whose stock is mentioned in this article.

The Dividend Discount Model And You: Proper Use And Limitations

Summary The dividend discount model is a simple valuation model for dividend investors to use in valuation. Like all models, it is only as good as the inputs used. Regardless of its drawbacks, the use of models forces investors to forecast company results and evaluate their own risk tolerance, which can only be positive for investor returns and contentment. Valuation can be a tricky subject for investors managing their own portfolios. As investors, we might like a particular company, its business, and its future prospects. But what exactly is a fair price to pay? Sure, we can look at valuation measures like P/E and EV/EBITDA and compare those numbers against historical values, but then we are just speculating that the company will return to its long-run average. Is there a better way? Financial models can be one answer to that problem. Novice investors usually start with the dividend discount model. The dividend discount model is an extremely simple, conservative valuation technique for evaluating dividend-paying stocks. While every model has its weaknesses, I believe that at the bare minimum, applying the dividend discount model to your holdings encourages you to think about, understand, and then model your portfolio holdings. Understanding the application and foundations of the dividend discount model is fairly simple. It fits into the broad bucket of discounted cash flow analysis. What we are trying to accomplish when using the model is to put a value on what a company’s future dividend cash flow is worth to us in today’s money. When we talk about “discounting” those future cash flows, we’re adjusting those numbers to reflect its value today. For example, because of the time value of money, a payout of $1,000 one year from now is worth less than $1,000 to you today. Money today has the ability to earn returns and avoid inflation, something that money in the future cannot claim. The median point where we are ambivalent between two amounts of money at different times can help us calculate our required rate of return, along with evaluating the riskiness of holding a particular stock we are analyzing. So, if our required rate of return is 8%, the discounted value of $1,000 one year from now is $925.93 ($925.93 * 1.08 = $1,000). The Basic Formula (click to enlarge) What you’ll notice from the formula is that it assumes a constant dividend growth rate. We all know dividend growth rates vary from year to year, but in the best case for modeling, we attempt to use what the long-run average will be. The weakness here as well is that the greater the dividend growth, the more minor differences between your hypothesized growth and real-world results can skew our model. So this simplistic model works best for securities with lower dividend growth rates and stable earnings. For income investors, using this model for utilities stocks should spring to mind quickly. Real-World Application Example Below, we have an example of ALLETE (NYSE: ALE ), a utility that generates energy for customers in Wisconsin, Michigan, and other surrounding states. It currently trade at $48.55/share. I’ve written a fairly pessimistic article on ALLETE , but we can see if the results from the dividend discount model back or disprove my thesis, based on various inputs. ALLETE currently yields $2.02/share annually, and has grown its dividend at an average 2.2% annual rate for the past five years, so we’ll use those numbers to run our valuation, along with an 8% required rate of return. We will assume the dividend will be $2.12 next year. P = 2.12 / (.08 – .022) P = 2.12 / 0.058 P = $36.55/share Based on this valuation, we come to a fair value of $36.55/share, or roughly 25% below current prices. To show how the model can be sensitive, let us instead change our assumptions. Perhaps based on our research, we find that going forward, management will be able to raise the dividend 3.25% annually instead of 2.2%, because maybe we have found information that has led us to believe the utility will be allowed a higher rate of return by its regulators. Additionally, we find that our own required rate of return is only 7% for ALLETE, because the stock has less financial risk than we previously thought. P = 2.12 / (.07 – .0325) P = 2.12 / 0.0375 P = $56.53/share Our calculated fair value per share is now $56.53, or more than 15% above current prices. Which is correct? That depends, based on your analysis of management’s ability to continue to raise dividends into the future and your own assumptions on the riskiness of the holding, which factor into your required rate of return. Multi-Step Models What if we think the dividend will grow at 3.5% for the next five years for ALLETE, and then 2.25%, after using an 8% required rate of return? The dividend discount model can be adapted to be used for multiple stages of growth to suit the reviewer’s needs. Year One Dividend = $2.12 * 1.035 = $2.23 Year Two Dividend = $2.23 * 1.035 = $2.31 Year Three Dividend = $2.31 * 1.035 = $2.39 Year Four Dividend = $2.39 * 1.035 = $2.47 Year Five Dividend = $2.47 * 1.035 = $2.56 Year Six Dividend = $2.56 * 1.025 = $2.62 Once we have the values, we can then discount those to their net present value: $2.23 / (1.08) = $2.06 $2.31 / (1.08) 2 = $1.98 $2.39 / (1.08) 3 = $1.90 $2.47 / (1.08) 4 = $1.82 $2.56 / (1.08) 5 = $1.74 We can then apply the constant growth model we used previously to determine their value, based on the fifth-year dividend value: P = 2.62 / (.08 – .0225) P = 2.62 / 0.0575 P = $45.57/share This value has to be discounted to net present value as well. P = 45.57 / (1.08) 6 P = 45.57 / 1.5868 P = $28.72 Add up the values of the five higher-growth dividends with your constant growth value: P = 2.06 + 1.98 + 1.90 + 1.82 + 1.74 +1.65 + 28.72 P = $39.87/share Conclusion Like any and all financial models, the dividend discount model is sensitive to the inputs used to value the security. Thus, financial modeling isn’t the grand answer to record-beating returns, and I wouldn’t advocate for retail investors to bury themselves in Excel spreadsheet models. However, financial modeling can force investors to think about issues that are extremely important to the stock valuation process, which can drive critical re-evaluations of your positions based on your own inputs and expectations. Disclosure: I/we have no positions in any stocks mentioned, and no plans to initiate any positions within the next 72 hours. (More…) I wrote this article myself, and it expresses my own opinions. I am not receiving compensation for it (other than from Seeking Alpha). I have no business relationship with any company whose stock is mentioned in this article.

How To Limit Your Market Risk

Summary As the bull market has continued, so have predictions about its demise. We note the latest one, and the problem presented by such predictions. We discuss ways to limit market risk and describe one method. We show an example of that method using an automated approach. The Latest Bearish Prediction As the current bull market has powered on, there has been no shortage of predictions of its eventual end. The latest such prediction appeared in an article by James Fontanella-Khan and Abash Massoudi in Saturday’s Financial Times (“Value of megadeals this year beats dotcom-boom record to reach $1.2tn”). The authors detailed this year’s record volume of mergers and acquisitions and then warned, But if history is anything to go by, activity might well be at a peak. Data from Dealogic show that sustained deal-making cycles from 1997 to 2000 and from 2005 to 2008 were followed by sharp stock market falls The Problem Presented by Bear Market Predictions The problem presented by bear market predictions such as the one above is what to do with the information, particularly when we’re not given a time frame when we can expect the bear market to begin. If you got out of the market at the first one of these predictions, you would have missed most of the current bull market. On the other hand, if you do nothing to protect yourself, and the prediction comes to pass soon, you may regret your inaction. A solution to this problem is to stay invested, but take steps to limit your market risk. First, we should clarify the difference between market risk and idiosyncratic risk. Market Risk versus Idiosyncratic Risk Idiosyncratic risk , in a portfolio comprised of common stocks, can also be thought of as stock-specific risk: it’s the risk of something bad happening to one of your stocks. The chance that one of the companies you own shares of may become the subject of a criminal probe, as Volkswagen (OTCQX: VLKAY ) recently did , is an example of idiosyncratic risk. Idiosyncratic risk can be limited via diversification. Market risk , or systemic risk, is the risk of a decline in the market as a whole, as happens during crashes and bear markets. Since most stocks decline in those cases, market risk can’t be limited via diversification. In order to limit market risk, you need things in your portfolio that will go up in value when everything else is going down. Ways to Limit Market Risk Adding short positions. If you are short some stocks, most likely those will decline in value during a market decline (ideally, you’d want to be short stocks that will decline even if the market doesn’t decline). Seeking Alpha contributor Chris DeMuth, Jr. offered some specific short ideas in an article earlier this month (“Preparing for a Market Collapse, Part II”). One challenge with this is that you may need to allocate a significant percentage of your portfolio to short positions to significantly limit your market risk. If you allocate half of your portfolio to short positions, for example, by investing exclusively in pairs trades, you can eliminate all market risk, and make your portfolio market neutral. This requires some facility with short selling though. Buying inverse ETFs. These include unleveraged inverse ETFs such as ProShares Short S&P 500 (NYSEARCA: SH ), ProShares Short Russell 2000 (NYSEARCA: RWM ), and ProShares Short Dow 30 (NYSEARCA: DOG ), which seek daily returns equal to -1x the returns of the indexes in their names, and leveraged inverse ETFs, such as ProShares Ultra Short S&P 500 (NYSEARCA: SDS ), and ProShares Ultra Pro Short S&P 500 (NYSEARCA: SPXU ), which seek daily returns equal to -2x and -3x, respectively, the daily returns of their indexes. There are two problems with using inverse ETFs to limit market risk. The first is that, because these ETFs react to their underlying indexes in a linear fashion, as in the case with adding short positions to your portfolio, you would need to allocate a significant percentage of your portfolio to them to significantly limit your market risk. The second problem is that, unlike short positions in individual equities, which can potentially produce positive returns in a bull market, inverse ETFs will produce negative returns. So, they will act as a drag on your performance in up markets. For those two reasons, inverse ETFs are not a good way to limit market risk in a typical portfolio (they can be useful tools for market timers, or for those who wish to bet against a particular country or sector, but neither of those scenarios is the subject of this article). Hedging. An advantage of hedging over the previous two methods of limiting market risk is that, because options react to their underlying securities in a non-linear fashion, a small dollar amount allocated to them can protect a much larger underlying security or portfolio. We showed an example of that, with a particular put option on the S&P 500 ETF (NYSEARCA: SPY ), in an article about the August 24th market meltdown. On that day, SPY dropped 4%, the triple-levered inverse ETF SH rose 13%, and that particular put option on SPY (pictured nearby) was up nearly 80%. Hedging can be used to limit market risk in a diversified portfolio, or to limit both market risk and idiosyncratic risk in a concentrated portfolio. We offered an example of the second kind of hedging in a previous article (“Keeping a small nest egg from cracking”). In this one, we’ll look at hedging market risk in a diversified portfolio. Hedging Market Risk If your portfolio is diversified enough so that your idiosyncratic, or stock-specific risk has been ameliorated, you can hedge market risk by buying optimal put options on ETFs that track a relevant index. Puts (short for put options) are contracts that give you the right to sell a security for a specified price (the strike price) before a specified date (the expiration date). Optimal puts are the ones that will give you the level of protection you are looking for at the lowest cost. Step One: Choose A Proxy Exchange-Traded Fund Although mutual funds and some stocks can’t be hedged directly, you can still hedge a diverse portfolio of mutual funds and non-hedgeable stocks against market risk by buying puts on a suitable exchange-traded fund, or ETF. The first consideration is that the ETF will need to have options traded on it, but most of the most widely-traded ETFs do. The second consideration is that the ETF be invested in same asset class as your portfolio. Let’s assume your portfolio consists of large cap U.S. stocks, or mutual funds that invest in them. An ETF you could use as a proxy would be the SPDR S&P 500 Index , which, as its name suggests, tracks the S&P 500 Index. Step 2: Pick A Number Of Shares In order to hedge an equity portfolio against market risk, you would want to hedge an equivalent dollar amount of your proxy ETF. By dividing the dollar amount of your portfolio by the current share price of your proxy ETF, you can get a number of shares of the ETF that you need to hedge. Bear in mind that options contracts cover round lots of shares (generally, a round lot = 100 shares), so if your number of shares includes an odd lot, you can either hedge the next highest round lot of shares, or slightly over-hedge the next lowest round lot of shares. Step 3: Pick a Threshold Threshold, in this context, means the maximum decline in the value of your position that you are willing to risk. Generally, the larger the decline, the less expensive the hedge, and vice-versa. In some cases, a threshold that’s too small can be so expensive to hedge that the cost of doing so is greater than the loss you are trying to hedge. I sometimes use a 20% decline thresholds when hedging equities, an idea borrowed from a comment by fund manager Dr. John Hussman: An intolerable loss, in my view, is one that requires a heroic recovery simply to break even … a short-term loss of 20%, particularly after the market has become severely depressed, should not be at all intolerable to long-term investors because such losses are generally reversed in the first few months of an advance (or even a powerful bear market rally). Step 4: Find the Optimal Puts Given the time frame over which you are looking to hedge, you’d want to find the put options that would protect you against a greater-than-X% decline (where X is your threshold) at the lowest cost. When doing so, you’d want to keep in mind the cost of the hedge: for example, if you can only tolerate a 20% decline, and there’s a put option with a strike price 20% below the current market price, but it would cost 5% of your portfolio to buy it, then you are actually risking a 25% decline in that case. In most cases, the optimal puts will be out-of-the money, but on occasion they may be in-the-money. An Automated Approach Here we’ll use a hedging app to facilitate finding the optimal puts for an investor with a $787,000 portfolio invested in large cap U.S. stocks, who’s unwilling to risk a decline of more than 20% over the next six months. Steps 1-3: Since our investor is in large cap U.S. stocks, we’ll use SPY as a proxy ETF. So we enter “SPY” in the Ticker Symbol field in the screen capture below. As of Monday’s close, SPY traded at $196.46 per share, so to get our number of shares, we’ll divide 787,000 by 196.46, and enter the result, rounded to the nearest share (“4006”) in the Shares Owned field. In the Threshold field, we enter the largest decline our investor is willing to risk over the next six months, in percentage terms (“20”). Step 4: We tap “Done”, and a few moments later, are presented with the optimal puts: As you can see at the bottom of the screen capture above, the cost of this hedge was $9,960, or 1.27% of our investor’s portfolio value. Note that, to be conservative, the app calculated the cost using the ask price of the puts. In practice, you can often by puts for less (i.e., at some price between the bid and ask), so the actual cost of this hedge would likely have been less. How This Hedge Would Protect Your Portfolio Remember, the reason we picked SPY in this case is because our hypothetical investor’s funds were invested in blue chip US stocks. If those funds drop in value due to a market decline, most likely, the S&P 500 Index will have dropped as well. And if the S&P has dropped, the ETF tracking it, SPY, will have dropped too. If the S&P 500 drops more than 20% — if it drops 20.5%, 30%, 40%, or even more — the put options above will rise in price by at least enough so that the total value of a $787,000 position in SPY + the puts – the initial cost of the puts will have only dropped by 20%, in a worst-case scenario. Hedging A Portfolio Of Stocks And Bonds The example above is simplified in that we’ve assumed our hypothetical investor’s portfolio is entirely invested in equity funds. But what if he had some bonds or bond mutual funds? In that case, we could use a similar process to hedge his portfolio against market risk, except instead of using just one proxy ETF, we’d use one per each asset class. So, for example, if 60% of the investor’s assets were in blue chip US stocks, and 40% in investment grade corporate bonds, we might scan for optimal puts on a number of shares of SPY equal to 60% of the portfolio, and then scan for optimal puts on a number of shares of the iShares iBoxx $ Investment Grade Corporate Bond ETF (NYSEARCA: LQD ) equal to 40% of the portfolio. Editor’s Note: This article discusses one or more securities that do not trade on a major U.S. exchange. Please be aware of the risks associated with these stocks. Disclosure: I/we have no positions in any stocks mentioned, and no plans to initiate any positions within the next 72 hours. (More…) I wrote this article myself, and it expresses my own opinions. I am not receiving compensation for it (other than from Seeking Alpha). I have no business relationship with any company whose stock is mentioned in this article.