Tag Archives: damon-verial

5 Outperforming CEFs That Are Insulated From Market Corrections

Summary The 2015 market correction caused a 10% drop across the market, but some CEFs were unaffected. Investing in market-neutral CEFs can help you protect your portfolio in the event of an event. I present a list of the 5 most profitable CEFs that are also uncorrelated to the general market. The previous market correction was a three-day selloff that led us to a market that trended sideways for two months. In total, the market lost 10% of its value before climbing back to its original place: (click to enlarge) Knowing not to freak out and to hold onto your investments is good, but having investments that are uncorrelated to the general market in the first place is better. This article is a follow-up to two other articles on investments uncorrelated to the S&P 500. The first article was on investment categories; the second on index funds. This article will be on CEFs, as per a reader request: (click to enlarge) Correlation In my previous article, I used a five-year lookback period. But if we are to really consider these investments uncorrelated to the market, they should not fall when the market does. Hence, the following comment: For this purpose, in this article, I will only be looking at the most recent market correction as my lookback duration. Thus, the correlation calculation will be from August to November, 2015. Whenever we look at the correlation of two investment instruments, we must use the log of those investments. In this way, we find the correlation of returns, not simply price movement. The result will tell us whether two investments are likely to give the same returns over our lookback period. I wrote some R code to screen CEFs according to the following criteria: Trading above $5 (therefore not a penny stock). Has a correlation of less than 0.3 (in magnitude) to the SPDR S&P500 Select ETF (NYSEARCA: SPY ). I then arranged those CEFs in order of greatest return over the past year. I chose the top five CEFs in this list to present to you. Because the top five actually had 3 municipal bond CEFs, I went down the list to add 2 more CEFs outside of this category. The Winners Nuveen Long/Short Commodity TR (NYSEMKT: CTF ) This CEF is a portfolio of long and short futures contracts. CTF purposefully plays a flat game, not taking too many long or short positions. Though it would have been nice to see CTF short energy, making their shareholders lots of cash over the past couple years, CTF has avoided such high-volatility trades. Though CTF’s Nav growth is rather slow, dipping into negative territory, this CEF is trading at a decent discount: -4.36%. The yield is currently 7.54%. Whether CTF can maintain these payouts at its current Nav growth is questionable. The discount is disappearing, however. The discount bottomed out at over -20% in 2014 and has recently bounced back. Thus, if you’re interested in getting in on this high-yield CEF, you should consider doing it soon. Remarkably, CTF is the only CEF in the top five that is not a bond-based fund. Correlation with market-correction phase SPY: 0.27 Babson Capital Corporate Invs (NYSE: MCI ) Here, the focus is on non-investment grade corporate debt. The equities involved are conversion rights, preferred shares, and warrants. Because of the inclusion of conversion rights, the debt here is convertible, which can lead to a dilution of shares. Nevertheless, the yield is high, at 6.80%. However, the surge in price has caused MCI to outgrow its Nav. The Nav sits at a stable 14.70, while the CEF trades at over $17. This CEF is selling at a 10.82% premium. If you buy this CEF, you will be overpaying for the portfolio. But for a long-term investment, MCI seems to provide noteworthy returns. Correlation with market-correction phase SPY: 0.19 Municipal Bond CEFs EV NJ Municipal Bond (NYSEMKT: EMJ ) Blackrock VA Municipal Bond (NYSEMKT: BHV ) Blackrock Muniyield Arizona (NYSEMKT: MZA ) These CEFs offer generous distribution rates of around 5.00. Both BHV and MZA trade at a premium, while EMJ trades at a slight discount. That discount is soon to be gone, as it has been shrinking over the past year. Buying a municipal bond fund can especially benefit you via tax exemptions if you live in a state with high taxes, as these bonds are tax-free investments in most cases. However, realize that EMJ will cause you to pay capital gains taxes on your investment, as it is currently trading at a discount. All of these regions – New Jersey, Virginia, and Arizona – are, to my knowledge, in good shape. But you should perform due diligence and ensure that the local governments aren’t facing problems of paying their debts. Residents in states with high taxes, such as New York, New Jersey, and California, should consider these CEFs. EMJ’s correlation with market-correction phase SPY: -0.09 BHV’s correlation with market-correction phase SPY: 0.25 MZA’s correlation with market-correction phase SPY: -0.11 Doubleline Opportunistic Credit (NYSE: DBL ) With a yield of 8.22, it’s no surprise that DBL isn’t trading at a discount. DBL has almost consistently been trading at a premium. But there have been dips into the discount region. An investor looking for a good deal might keep an eye on DBL and buy at one of these rare discounts. Just remember that a drop in the premium/discount will also typically drop the yield toward the sector’s average. In addition, as time goes on and rates increase, credit-based CEFs such as DBL will likely take a hit. You should also consider leverage here, as rates will likely be rising in the future. Higher leverage implies higher borrowing fees for the fund. DBL might be a good short-term hold, but you should consider dropping it for non-credit CEFs with less leverage before rates rise. Correlation with market-correction phase SPY: 0.02 Strategic Global Income (NYSE: SGL ) Speaking of leverage, here’s a non-leveraged CEF. Previously trading at one hell of a discount, SGL is now trading at “only” a -4.12% discount. This offers the highest discount of all the market-neutral CEFs we looked at today, with a yield of 9.42%. As the name suggests, SGL invests in global bonds. Its holdings branch from Argentina to Russia. These bonds are diversified, with both sovereign paper and corporate notes in the mix. Although a portfolio of such a wide geographical array of holdings is more likely than a focused portfolio to encounter a holding that cannot repay its debt, the fact that SGL is diversified should minimize such problems. The risk is there, but the reward is higher, I believe. This fund doesn’t have many downsides other than the exposure to iffy countries (the average credit rating of SGL’s holdings is still A) and the fact that SGL is taxable. Correlation with market-correction phase SPY: 0.11 Conclusion Overall, we have a wide selection of market-neutral CEFs that can help us generate stable income even during a market correction or crash. Of the five we looked at, I would recommend SGL most to investors in low-tax states, while recommending the municipal bond CEFs to investors in high-tax states. But no matter your choice, rest assured that these CEFs will be least affected by another market correction. Obviously, I simply don’t have the time to cover every industry. While reading this article, you probably thought of at least one investment that should have gone in my “Winners” section. Let me know about it in the comments section below. Request a Statistical Study If you would like for me to run a statistical study on a specific aspect of a specific stock, commodity, or market, just request so in the comments section below. Alternatively, send me a message or email.

A Seasonal Biotech Portfolio Alternative To ‘Sell In May’

Summary The common sense strategy of sell in May fails to beat a buy-and-hold ETF strategy. I tested an alternative seasonal strategy to find it safer, but not better than the buy-and-hold strategy. Modifying the seasonal strategy to allocate capital to biotech instead tech beats the buy and hold strategy in at least two ways. This article is a return to the “sell in May” philosophy, which I previously outlined here . As it is now November, those who subscribe to this philosophy are getting ready to enter the market. If you are one such investor, I implore you to first read the following article, in which I show you how the iShares Nasdaq Biotechnology ETF (NASDAQ: IBB ) can more than double the effectiveness of your strategy. Sell in May The first thing I want to do is set a benchmark to which I will compare the portfolio strategy I plan to introduce here. Let’s take it a step further and use two benchmarks: buy and hold and sell in May. Buy and hold: Buy the SPDR S&P Trust ETF (NYSEARCA: SPY ) and continue holding, never selling Sell in May: Buy the SPY in October and switch to Treasury bills in May As you can see from the figure below, the buy and hold strategy actually beats the sell in May strategy over the past 10 years. This only bolsters my original article that states the sell in May strategy only holds is special occasions and should not be relied upon in the long-term. The upside is that you protect yourself a bit from the drawdowns, but as you’ll see in a bit, an even better strategy exists. So let’s stop with the mystery and great straight to the strategy… after one more portfolio strategy introduction. In this article , a different type of seasonality-based portfolio strategy is introduced. You can skip reading the article, as I’ll explain it in a nutshell in the following section. Kaepple’s seasonality Kaepple states that his extensive research of market seasonality led him to three main conclusions. First is to buy tech stocks during the market rally season, typically November to January (that’s now!). Second is to switch over to energy stocks during the winter. Then, in May, switch to cash (or bonds). In September, get into gold for one month, and then switch back to cash. I wondered how this strategy would do compared to the buy-and-hold and sell in May strategies. So, I ran a backtest. The strategy follows: November to January: Buy the Technology Select Sector SPDR ETF (NYSEARCA: XLK ) February to May: Buy the Energy Select Sector SPDR ETF (NYSEARCA: XLE ) June to August: Stay out of the market September: Buy the SPDR Gold Trust ETF (NYSEARCA: GLD ) November: Stay out of the market Here are the results of this strategy: As you can see, the results of this strategy were better than the buy-and-hold strategy. Not in performance – they both performed equally well. However, this strategy reduced the drawdown and showed a stable upward trend. This portfolio allocation strategy could have protected you from much of the damage that most investors suffered in 2008. In addition, although we were in specific sectors via XLK and XLE, this portfolio was less volatile than simply buying the SPY. That is, this is a safer portfolio allocation strategy with fewer downsides. But couldn’t hedging do the same? After all, this strategy didn’t outperform the buy-and-hold strategy. But what if we focused on an even more specific sector during the market rally period? Choosing an individual stock, of course, would be too risky, as you’d be putting all your eggs in one basket. But what about focusing on a very specific subsector of the tech sector? My thoughts immediately turned to biotech, of which there are several good ETFs. Though I am long on the ALPS Medical Breakthroughs ETF (NYSEARCA: SBIO ), this ETF is relatively new, precluding it from backtesting. Instead, I reached for the next best thing: the iShares Nasdaq Biotechnology ETF . Thus, the new strategy invests in IBB from November to the end of January. The results follow. Now we’re talking! Half the max drawdown of the buy-and-hold strategy with double the cumulative gains! In addition, just like the original sector portfolio strategy with the XLK, this portfolio would have weathered the 2008 storm. Conclusion for Investors The conclusion is basically in the last image – a strategy that switches into different sectors of the market throughout the year is safer than an index fund and brings in double the revenue. (Devil’s Advocate: How does this compare to buying and holding IBB? Answer: Same cumulative returns with 30% lower max and average drawdowns.) As the first backtest shows, buy and hold beats sell in May but an IBB-focused seasonal strategy beats them both with no obvious disadvantages. Anyone using a seasonal strategy such as the “sell in May” strategy should reconsider how they play this game. If you’re looking for something easy, this is your four-trade-a-year investment strategy. And it should be rather cost effective to switch four times a year. No, it’s not a flamboyant investment strategy but it beats most mutual funds. If you’re interested in seeing some tweaks to this strategy, ask me in the comments section or via mail. I’ll be rolling out my premium Seeking Alpha backtesting newsletter soon, in which I backtest your strategies. Before I launch it, I’m willing to run a backtest on your portfolio allocation strategy or trading strategy per gratis. Request a Statistical Study If you would like for me to run a statistical study on a specific aspect of a specific stock, commodity, or market, just request so in the comments section below. Alternatively, send me a message or email.

Higher Interest Rates Lead To Increased Volatility – How To Prepare For A Volatile Market

Summary Again, the Fed is threatening to raise interest rates. The results of my statistical study show that increasing interest rates leads to an increase in overall market volatility. Whether liquidating or investing in an increasingly volatile market, you have several strategies that can give you an advantage. I have had several requests for statistical analyses on individual stocks, but recently I was asked to look into the correlation between interest rates and volatility. This request does not come as a surprise for two reasons. First, although Chairwoman Yellen recently passed on raising interest rates , others are stating that, regardless, we will see a rise in interest rates this year . Many are asking what will happen to the market once this happens. Second, the VIX and its associated ETF, the iPath S&P 500 VIX Short-Term Futures ETN (NYSEARCA: VXX ), are looking increasingly bumpy. This time of year tends to bring bumps in the VIX, with a dip and subsequent rally. Investors are wondering what will happen to the VIX (which can be thought of as an overall measurement of how risky the market is at the current time) if interest rates increase. An increase in interest rates could just be the catalyst to bring back market volatility. But does an increase in interest rates truly bring an increase in volatility? Though I could find a few articles online claiming this fact, I found no previous statistical analyses on the subject. Some images backing the claim of a correlation between interest rates and volatility are examples of exactly what you don’t want to rely on as an investor: curve-fitting. I’ve seen too many “analysts” run models over and over until they find a couple of curves that seem to line up. This is exactly what the following two images display: The first chart shows the T-bill yield and VIX apparently lining up in perfect accord. But there are three problems here: First, a logarithmic transform was applied to the VIX line. This changes the shape of the VIX line. I suspect this was done to make the VIX curve better resemble the yield. While logarithmic scales can be useful for looking at indexes or stocks – especially when comparing two stocks trading at drastically different ranges – logarithmic scales should not be used without reason. A proper statistical model first states that the logarithmic scale should be used and gives reason for using it. I suspect that this analyst simply found the logarithmic conversion to produce the curve he wanted, meaning he was playing with data to confirm his conclusion rather than performing a true analysis. Second, the yield was transposed two years. Again, this is likely an action with the motive of making the two curves match. If the yield was not transposed to the right, the graph would show the opposite of what the author wanted – i.e., the graph would imply that yield and the VIX have a negative correlation! It simply makes no sense to move one index two years forward in time. This is especially true when the T-bill used is only a 3-month T-bill! Is the analyst trying to say that the VIX today can predict the price of a 3-month T-bill two years from now?! The second chart is equally absurd. This time, the VIX is plotted with the 2-year and 10-year yield curve (i.e., the slope of the yield curve, measuring the difference between the yield of a 10-year bond and 2-year bond). The absurdities follow: First, this analyst does the same as the previous analyst; he moves the entire yield curve forward two years. Again, this would imply that the VIX today is predicting something precisely two years from now. This is another sign of curve-fitting. Second, the analyst inverts the yield curve. There is simply no reason to do so – unless, of course, your goal is to get a desired look to your chart so you can draw a conclusion, which is the exact definition of curve fitting. Interpreting the inverse of a function in words is a difficult task – so knowing that the VIX is correlated with the 2-year future inverse of the yield curve tells us nothing! As you have probably concluded, we need a more formal way of determining the relationship between interest rates and the VIX. In this study, I set up the following set of hypotheses and test them statistically: Set 1: H0: The VIX is uncorrelated with yield rates H1: The VIX is correlated with yield rates Set 2: H0: The VIX is uncorrelated with the yield curve H1: The VIX is correlated with the yield curve The Study As you can see, the test will be simple – no data transformations or curve-fitting. I collected the data from the VIX for each day, starting from 2004. I did the same for the bond market. Because the stock market and bond market have a few days per year in which one market is closed while the other is open, I removed such dates from the analysis. I did so to allow a one-to-one comparison for the VIX and yield each day in the market. Thus, daily movements in the VIX and movements in the bond market will be tracked. For the VIX data, I used the closing values. For the bond data, I used 2-year bonds, which is more or less the “middle ground” for bonds. For the yield curve, I used the difference between 1-month and 20-year bonds, giving the widest and most sensitive curve. If anyone has any qualms with these choices, please let me know in the comments section below and I can rerun the analysis with your chosen values (e.g., daily VIX highs vs. 20-year bonds). I used an alpha level of 0.05 as the comparison point for the p-value. Correlation tests for the hypotheses that reported p-values less than 0.05 would be considered evidence for the rejection of H0, giving strong evidence for H1. The Results The results follow: Yield Yield Curve Correlation with VIX -0.2680 0.3581 p-value for correlation depreciated dollar -> increased yield curve -> increased VIX But the yield curve is actually moderated by the supply and demand of capital. Decreases in the money supply (e.g., M2 money supply), increased government deficits, and less money flowing into savings can all increase the yield curve, thereby spiking market volatility. In addition, commodity prices affect the yield curve. Generally, decreasing prices steepen the yield curve because they decrease short-term inflation expectations. This pulls the left side of the yield curve downward, making the curve steeper on the whole. In other words, when commodity prices drop, the yield curve steepens, and the VIX should see an increase. But our current market, in which commodity prices are at all-time lows, doesn’t seem to have an increased VIX, which is interesting from a theoretical standpoint. Overall, the picture is complicated: (click to enlarge) Investment Strategies for a Volatile Market For now, we can expect that the yield curve will steepen and prepare our portfolios for such an event. I don’t recommend buying the VXX outright because it’s a garbage imitation of the VIX and will cause you to lose money in the long run. However, a spike in VIX should result in a spike in the VXX, which could leave you with a handful of cash should you have call options on this ETF. But let’s look at some more realistic strategies (I hate the VXX). If volatility increases and you are a risk-averse investor, the easiest “safe” strategy is to exit the market – as reasonably as you can – before increased volatility hits. Of course, most people reading this are likely “buy-and-hold” investors, so such a method might be lost on you. One fundamental idea behind the buy-and-hold strategy is that you don’t want to miss those days with the most significant returns, which tend to happen during days of high market volatility. Of course, if you’re in the market all the time, you’re also gaining exposure to those days with the most significant losses. And a significant loss hurts a lot more than a significant gain. Going from 100 to 80 requires a 20% drop, but going from 80 to 100 requires a 25% gain. The uphill battle is harder. Perhaps the best selling strategy is a staged sale strategy. In this strategy, you sell predetermined chunks of your stocks and either hold cash or reinvest (see below). The staged sell is like the opposite of dollar cost averaging. If you don’t want to worry about market timing but want to liquidate, staged selling is your best bet. Nevertheless, for buy-and-hold investors, volatile markets can be gold mines. An increase in volatility in the general market will not hurt the fundamentals of a company. Thus, a volatile market will allow you access to sporadic dips on stocks with solid fundamentals. This is a good time to buy such stock. However, when buying, realize that some things are different in a volatile market. If you’re not in the habit of buying with limit orders, get into that habit now. Volatile markets move quickly and have high volume; your market order is likely much different from that what you expect. In addition, the bid-ask quotes you’re looking at now might be very different from the real bid-ask quotes. And then there’s increased delays and slippage… This is all general strategy. What about choosing individual stocks during a volatile market? As stated, a volatile market gives you access to a myriad of stocks that hit dips simply as a result of increased volatility on the stock. In the past, such a low would often be explained by the company’s fundamentals. But in a volatile market, the lows that looked large in the past will soon be considered the norm. As a fundamental investor, your best bet is to ignore the daily changes in stock price and instead set a buy limit order that you consider to be “too low.” Set the order as “good for the month” and get your stock at a discount. As for the types of stock to add to your portfolio, choose stock that are relatively safe and undervalued during periods of increased volatility. REITs make good choices. Switching out low-yield dividend stocks for high-yield dividend stocks makes sense, just as switching out growth stocks for value stocks makes sense. Depending on your portfolio, this might be a good time to step back and question the purpose of the portfolio. Are you focused on growth? Passive income via dividends? In the previous case, you should have an existing exit strategy. Perhaps now is the time to take your profits and look to restructure your portfolio with undervalued growth stocks. If your goal is passive income, holding on to your current dividend stocks and REITs makes sense in terms of your overall objective, and you might have no exit strategy at all. But at this time, a day’s worth of research into your current dividend stocks’ fundamentals can give you some clues as to whether dropping the stock for cash (or switching it out for a better option) is the right choice. Overall, for investors, getting defensive as the market has a seizure isn’t the right strategy because you should have been defensive in the first place. But let’s assume you need to get defensive all of the sudden. What are some immediate actions you can take? Switching out common stock for preferred stock is a good choice because preferred stock tends to have lower beta – i.e., it’s less correlated with general market moves. Dropping the beta of your overall portfolio can ensure that your portfolio contains companies that you believe are fundamentally strong and yet will not be hit hard by market corrections. Here’s a general common-to-preferred and visa versa strategy for volatile markets: Switch out common stock for preferred stock when the market appears to be overbought. You’ll have sold common stock at a high, switching them for preferred stock that are more protected against drops. If the market does drop for an extended time, drop the preferred stock, which protected value and brought you dividends, in favor of common stock, which you can now buy at a low. Overall, you want to drop your portfolio’s beta when you believe the volatility is coupled with a downward trend. You should still perform well during the good times at the same time you’re protecting your capital with a low-beta portfolio. The following are some low-beta stocks I recommend: Pfizer (NYSE: PFE ) Wal-Mart (NYSE: WMT ) Avista (NYSE: AVA ) Request a Statistical Study If you would like for me to run a statistical study on a specific aspect of a specific stock, commodity, or market, just request so in the comments section below. Alternatively, send me a message or email.