Skyworks Solutions (SWKS) and PMC-Sierra (PMCS) terminated their $2 billion merger deal late Monday, after the Apple (AAPL) iPhone chip supplier said it would not raise its bid once again, clearing the field for Microsemi (MSCC) to be the acquirer. PMC-Sierra on Friday recommended Microsemi’s latest bid. With Skyworks unwilling to nudge up its offer, PMC-Sierra terminated the deal and will pay Skyworks an $88.5 million breakup fee. Skyworks
Several months ago we posted an article called ” Bring Data ” where we showed the importance of having abundant data for system development and validation. This was further reinforced to us recently when someone actually brought us additional U.S. stock sector data. Previously, we only had Morningstar sector data that went back to 1992, which we used to construct our Dual Momentum Sector Rotation (DMSR) model. (S&P sector data also goes back to only the early 1990s.) DMSR was shown in my book as one example of other ways you might use dual momentum. When we were given equivalent Thompson Reuters U.S. stock sector data back to 1973, we immediately extended our DMSR back test to include this additional data. After incorporating the new data, DMSR still looked considerably more attractive than buying and holding the S&P 500 index. But one could argue that the performance of models using broad-based equity indexes, such as Global Equities Momentum (GEM), now looks better than DMSR. Here are the comparative performance figures from January 1974 through October 2105: GEM DMSR S&P 500 Average Annual Return 17.36 15.86 12.21 Standard Deviation 12.32 14.55 15.43 Sharpe Ratio 0.89 0.67 0.42 Maximum Drawdown -17.84 -33.96 -50.95 Results are hypothetical, are NOT an indicator of future results, and do NOT represent returns that any investor actually attained. Indexes are unmanaged, do not reflect management or trading fees, and one cannot invest directly in an index. Please see our website’s Performance and Disclaimer pages for more information. Because the monthly correlation between GEM and DMSR is only 0.59, sector rotation can still have a useful but modest role to play in a diversified equities-oriented portfolio. But DMSR is not the best choice as a core portfolio holding. Sector rotation programs that use data no further back than the early 1990s to develop their models may be in for a rude awakening someday if future drawdowns are higher and returns are lower than they expect based on back testing with a limited amount of data. Along the same lines, there are also momentum-based portfolios popping up on the internet all the time now, some even labeled as “dual momentum,” that are modeled on the basis of only 10 or 15 years of ETF data. Momentum may be robust enough that future results won’t suffer much because of this. But those who think they are constructing optimal models this way are just fooling themselves. Overfitting modest amounts of data is one of the most pernicious problems in the development of investment models. Those who do this may argue that the markets change over time, so the best model parameters from years ago may not be as relevant as today’s best parameters. This may be true. However, what is also true is that today’s parameter values are also likely to be sub-optimal when moving forward in time. The following chart from my book, Dual Momentum Investing , shows what I mean: Chart courtesy of Tony Cooper The S&P 500 is highlighted in different colors for each 15 year period. You can see that the latest period, 1999-2013, looks different from the preceding period, 1984-1998. 1999-2013, in fact, looks more like the earlier 1969-1983 period. 1984-1998 is also different from its preceding period, 1969-1983 and similar to the earlier years 1954-1968. If you had used each 15-year period to develop your model, you would have had something unsuited for each of the next 15-year periods. You would likely be better off using all four periods to formulate a model rather than just the last 15-year period. The more data you use, the more likely you are to have a robust model that will hold up reasonably well in the future, even though it isn’t the best fit to any one particular period. The 12-month look back parameter we use for our GEM and ESGM dual momentum models was found to work well in 1937 by Cowles & Jones . It has been used extensively in momentum research since then and has held up well out-of-sample. But there is a lot more history than that to help give us more confidence in momentum. Let’s take a look at some of that now. We focus on stocks as our core asset since they have historically offered the highest risk premium to investors. U.S. stocks, in particular, have given investors the best long-run returns. Other assets can create a drag on long-run portfolio performance. They also lose some importance as diversifiers once you use a trend following overlay like absolute momentum to help attenuate your downside risk exposure. The longest back test on stock market momentum is by Geczy and Samonov (G&S). Their 2013 paper called ” 212 Years of Price Momentum: The World’s Longest Back Test 1801-2012 ” compared the top one-third to the bottom one-third of U.S. stocks sorted monthly by relative momentum. Over this entire sample period, the top equally weighted momentum stocks outperformed the bottom ones by 0.4% per month with a highly significant t-stat of 5.7. Prior to this study, momentum outperformance on U.S. stocks had been found significant back to 1926. G&S showed that stock momentum was also positive and statistically significant from 1801 to 1926. G&S also found that stock market momentum was remarkably consistent. In only 2 of the 21 decades from 1801 through 2012 did long-only momentum under perform buy-and- hold, and these were by just -1.2% and -0.7% annually. In all the other 19 decades, momentum outperformed buy-and-hold by an average of 3.8% annually. This year G&S came out with a new study called, ” 215 Years of Global Multi-Asset Momentum: 1800-2014: Equities, Sectors, Currencies, Bonds, Commodities, and Stocks .” Here G&S expanded their momentum study to cover six different asset classes, including bonds, stock sectors, and equity indices, which are the ones we use in our momentum models. [1] G&S demonstrated the outperformance of momentum inside and across all asset classes except commodities. Here is a chart from their paper showing the log cumulative equally weighted average of the 6 asset classes plus the cross asset momentum excess returns. The strongest momentum effect is in country equity indices, which had a long-only monthly excess return over buy-and-hold of 0.52% with a highly significant t-stat of 11.7, compared to 0.29% with a t-stat of 6.4 for individual U.S. stocks and 0.24% with a t-stat of 15.5 for all assets. G&S also show that long-only absolute (time series) momentum outperformed buy-and-hold by 0.15% per month with a t-stat of 11.2. For those who want to further their momentum education, I suggest you first read the seminal paper by Jegadeesh and Titman (1993) that started the modern momentum renaissance. Next, learn about absolute momentum from Moskowitz et al (2012) or Antonacci (2013). Then follow up with Geczy and Samonov (2015) to satisfy yourself as to the efficacy and robustness of momentum investing based on 215 years of empirical evidence. [1] Equity indexes are equally as good as individual stocks (or better, according to G&S) in capturing the momentum effect. Indexes are much easier to use and avoid the enormously high transaction costs associated with rebalancing momentum-based stock portfolios.
Summary Dividend income is a great way to increase cash flow while not having to liquidate positions and taking money out of the market. Historically, dividend-paying companies have outperformed non-dividend-paying companies thus this strategy may boost overall portfolio return. Companies that make up dividend-paying ETFs can vary from traditional broad market ETFs, so splitting your portfolio up can help diversify your holdings. For a majority of investors, regular “stock picking” is not of interest to them. The shear amount of work and patience involved in the process tends to push the masses towards passive management, where the debate between mutual funds and ETFs begins. Without a doubt, there has been a lot of movement into ETFs due to their lower-fee structure as well as their overall net-of-fees performance compared to mutual funds. Over the past few months, I’ve begun to do a deeper dive on the value of high dividend yield ETFs to see if they are truly worth the hype. Many of the most successful investors preach the importance of investing in companies that pay steady dividends. It’s easy to understand the appeal of such companies; the ability to return cash to shareholders shows that the company is, usually, being managed well and investors can generally expect a stream of cash to supplement any unrealized gains in their shares. I’m of the personal opinion that, to some degree, companies pay dividends to keep shareholders from selling their shares. In other words, giving investors a bit of cash to pad their pockets may deviate them from selling their position when they are in need of cash – something that tends to occur increasingly during economic downturns. Of course, these dividends come at the cost of less capital appreciation, but many investors like the little bonus they see in their investment account. If you are someone who believes you should just spend the interest, not the principal, then high-dividend ETFs should peak your interest. In addition, corporations have been distributing record amounts of dividends back to shareholders recently, showcasing a need for investors to broaden their exposure. Concept of High-Dividend ETFs As the name implies, these types of funds typically offer higher payout yields compared to the average ETF. They tend to come in all shapes and sizes, so it’s important to understand that many of these funds are outside of your investment objectives. For example, most individual investors would not have the risk tolerance for the UBS ETRACS Monthly Pay 2X Leveraged Mortgage REIT ETN (NYSEARCA: MORL ), which has a current dividend yield of over 30% and is considered one of the highest yielding ETFs out there unless they were looking for specific exposure the real estate market. There are, however, some more general high-yield ETFs that are of interest to someone looking to mix up their investments which maintaining their overall asset allocation. For example, someone may want to have 50% of their funds invested in U.S. Equities. Instead of having that portion of your portfolio in something like the PowerShares QQQ Trust ETF (NASDAQ: QQQ ), you could split up your U.S. Equity exposure and invest some of that money in a higher yielding ETF like the Global X Super Dividend U.S. ETF (NYSEARCA: DIV ). Of course, the industry makeup of these two funds are vastly different – QQQ is highly focused in the technology sector while DIV has more exposure to Utilities and Real Estate, but this could actually prove to help with overall diversification for your investment in a particular economy like U.S. Equities. One of the reasons I have tried to increase my exposure to dividend-paying stocks and ETFs is because, according to a study by BlackRock, they have outperformed non-dividend paying companies over the long-term. As you will see below, this is the case both in bull markets and bear markets. Risks One negative view has surfaced regarding dividend ETFs recently. An article on Bloomberg showcased that for the first time ever, dividend ETFs are projected to have an outflow of capital for the year. Although there are many reasons for this phenomenon, including investors choosing to change their investment mix to other markets that may not be as much dividend-paying as growth-oriented, it is a trend that needs to be watched to ensure there isn’t significant downward pressure on the actual price of these ETFs. As always, it is important when using ETFs in your portfolio to review and understand the underlying investments (i.e. companies) that are held in the portfolio. As long as dividend-paying companies continue to perform well and corporations continue to pay and grow their dividend, there shouldn’t be any significant risk to these funds. Portfolio Strategy For an investor looking to produce some extra income, and potentially even diversify their portfolio more, high-yielding ETFs are a great product to help you achieve this goal. What I would recommend, especially at the beginning, would be to structure your portfolio in a way that only half of a given asset allocation is invested in a high-yield ETF to begin with. Similar concept to my example above, let’s say you currently have a portfolio of 30% Fixed Income, 40% U.S. Equities, and 30% International Equities. I would recommend keeping 15% of your Fixed Income investments the same and the other 15% I would find a high-yield bond ETF to keep the same exposure to fixed income, but with more income; keep in mind that, especially true with fixed income, higher yield is typically higher risk investments. Similarly, I would take 20% of your U.S. Equity allocation and invest in a high-yield U.S. Equity ETF, like DIV I mentioned above. Finally, I would take 15% of the funds I have in International Equities and find a similar type of non-North American ETF that offers a high-yield. One such example would be the FlexShares International Quality Dividend Index ETF (NYSEARCA: IQDF ). Something like the Arrow Dow Jones Global Yield ETF (NYSEARCA: GYLD ) may work as well, keeping in mind that as a “Global” ETF it would still have exposure to the U.S. market so you need to be careful to ensure your overall portfolio allocations are still intact. As always, if this type of investment is of interest to you I highly recommend speaking to a licensed financial professional to see which funds match your overall risk and return objectives.