Tag Archives: seeking

Increase Your Portfolio’s Return By Dropping International Funds

Summary International stocks have underperformed historically – performing even worse in the recent past. Multiple hypothetical portfolios demonstrate the poor returns of international stocks. Short periods of outperformance by international stocks do not make up for their overall performance. Will International Stocks Really Outperform? With emerging markets in the dumps and international funds trailing the returns of domestic funds, analysts everywhere are calling for investment in international stocks, claiming that the chronic underperformance is a sign that they are “due” to outperform. International stocks may very well outperform in the next few years. There is nobody who can know that for sure. I am here to present the facts, and the facts show that international stocks have not been delivering on the promise of outperformance given their higher risk. An investment portfolio built entirely from U.S. stocks can outperform international portfolios while avoiding the political and currency risks of other smaller countries. Hypothetical Portfolios For the sake of this hypothetical situation, let us assume that the owner of this portfolio will be investing in 100% equities and plans to maintain that portfolio for the next decade before moving into some safer bonds. The owner of this portfolio currently has $300,000 invested. Let us see how this portfolio would have performed from 2005 to 2015. First, a control sample: 100% U.S. equities for the entire investment period, invested in the broadest manner possible with the Vanguard Total Stock Market ETF (NYSEARCA: VTI ). In this case, the portfolio would be worth $654,240 at the end of the investment period. Not too shabby, the portfolio has more than doubled with an annualized rate of 8.12% ( Source ). Let’s say the investor wished to broadly diversify his equity portfolio with companies from around the world, putting the U.S. weighting at around 40% with the Vanguard Global Equity Fund (MUTF: VHGEX ). In this case, the portfolio would be worth $533,880 at the end of the investment period. The portfolio has increased at an annualized rate of 5.93%. The investor has missed out on $120,360 ( Source ). Perhaps the investor believed that emerging markets would be a good addition to his U.S. equities. Let’s say the investor allocated 20% to emerging markets with the Vanguard FTSE Emerging Markets ETF (NYSEARCA: VWO ) and 80% to Vanguard Total Stock Market ETF. In this case, the portfolio would be worth $625,080 at the end of the investment period. The portfolio has increased at an annualized rate of just over 7.542%. The investor has missed out on $29,160 ( Source ). Let me note that emerging markets are the only international option I would consider. Emerging markets have outperformed U.S. markets from time to time and their current weakness has much to do with the strong U.S. dollar and oil prices. However, emerging markets do not represent all international stocks and therefore I still stand by the statement that international stocks, as a whole, underperform – as seen by the performance of broad international funds such as VHGEX. In all hypothetical portfolios, the investor would have been better off simply investing in the United States market and would have even paid lower fees (and perhaps taxes as well) while doing so. The below table and graph illustrate the results of including international stocks in your portfolio. (click to enlarge) (Excel, using data from Vanguard.com) (click to enlarge) (Excel, using data from Vanguard.com) International Stocks have Underperformed Historically U.S. funds have beaten international funds the past five, 10, 15, 20 and 25 years. Over the past 25 years, large-cap U.S. funds have gained an average 691%, vs. 338% for international funds. The graph below illustrates the difference in performance. (Please note I am not in favor of investments in managed futures. Managed future data is subject to extreme survivorship bias and the results are thus skewed. Survivorship bias is the logical error of concentrating on the people or things that “survived.” inadvertently overlooking those that did not because of their lack of visibility.) (click to enlarge) (AutumnGold) Small Bursts of Outperformance by International Stocks Don’t Make Them a Good Investment Some will argue that there are periods of time when international stocks outperform. This is true. However, these periods of time are often small and they haven’t made up for the underperformance both historically and lately, assuming investors invest gradually over time. For long term investors, a long history of strong performance is needed before an investment can be made. The United States stock market has provided that performance for over a century now. The below chart shows the periods of outperformance for domestic and international equities for roughly the past 20 years. As you can see, in the mid-80s international stocks did very well and mildly outperformed in the mid-2000s. However, in all other years the U.S. stock market outperformed and overall U.S. stocks came out far ahead as mentioned earlier, assuming you didn’t throw all your money into international stocks in 1984. However, most people invest over time and if you had done that, you would have had higher returns with domestic stocks. (Bason Asset Management) For the past 15 years domestic stocks have pulled ahead of international stocks by a fairly wide margin. This is achieved even when the domestic market returns are relatively normal compared to historical averages. International stocks have simply underperformed consistently. You would be very hard pressed to find an international broad market fund that has beaten a U.S. broad fund from inception to date with reasonable fees, assuming the inception dates are relatively similar and that the funds didn’t start around 1984. The Vanguard International Explorer Fund is one exception I have found as it has performed very well since inception in 1996. Unfortunately, over the past 10 years it has returned less than 6% annually. Having a Portfolio of Pure U.S. Stocks Outperforms and Provides International Exposure Investing in U.S. stocks doesn’t mean you lose out on foreign growth potential. In fact, U.S. companies are very savvy and have the luxury of being able to choose which countries to do business in. There is no reason the U.S. equity market can’t benefit from the growth of other nations. Companies in the S&P 500 get 46.2% of their earnings from overseas . If you are looking for diversification to reduce the risk of a drastic drop in your portfolio value, international stocks won’t help you. The 2008 stock market crash showed that all equities fell drastically at the same time. Investing in one country or another made no difference. So do the smart thing: invest in domestic funds and enjoy the decent returns, as boring as they may be.

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.

Stock Screening And EV/EBIT

Summary This begins a series of articles communicating my investment philosophy, strategy, and process. I’ve always used stock screens. They’re basically a necessity and more people use them than those just using explicit screening tools. What you screen for matters, and I like to use EV/EBIT for reasons explained below. Screening and using rules like EV/EBIT are fundamental to adding a passive, systematic layer to my investment process, which I feel complements the deep research and intuition. As a new investment manager, I’d like to begin communicating my investment philosophy and strategy in a coherent way. A series of articles will be part of the process of communicating my process. In this, the first article, I will focus on how I source ideas and why I do it this way. Screening I begin with a stock screen. A stock screen is a query of the universe of public securities. There are tens of thousands of public companies globally. There’s too many for one person to do detailed research over any reasonable period (say 1 market cycle or 5-10 years). Unfortunately, I’m one person, so screening it is. There are some gifted investors who manage to be more than one person and who avoid screens. Warren Buffett famously went through every company in the Moody’s stock manuals from A-Z in his partnership days. Others who avoid explicitly using screens and don’t go A-Z rely on intuition to find companies worth analyzing. For example, perhaps an investor reads every new idea published on Value Investors Club or Seeking Alpha, two popular investment research sites I use later in my process. I’d argue this is still screening, just using non-financial criteria. These investors are screening for securities based on the criteria that they are covered on VIC or SA. Criteria are the heart of stock screening and I think they’re a necessity. Evolution What criteria do I use? Since I began investing several years ago, I’ve tried many different criteria. I began with pre-made screens like the Piotroski F-Score, Magic Formula, Ben Graham’s Net-Nets, and others. Gradually I moved toward making my own screens with tools like finviz.com . After a few years, I moved in a different direction. I’d done a lot of reading about the underperformance of most active managers and behavioral psychology. I’d begun playing poker and thinking about the future more in terms of odds and possibilities than certain outcomes. These and other factors led me to use stock screening for more than just finding stocks with metrics that I intuitively like. I began wanting the screens to return a basket of stocks that, based on extensive historical data, would outperform on average. I became interested in systematic strategies. Helpful books on this path were: Joel Greenblatt’s The Little Book that Beats the Market , which I’ve read several times Tobias Carlisle and Wesley Grey’s Quantitative Value James O’Shaughnessy’s What Works on Wall Street Investing on the long side is not zero sum. Stocks in the US have gone up just under 10% nominally and just under 7% really since the 1800s. But as an active investor, I am implicitly not content with market performance. I am trying to achieve what most active investors covet: long-term, sustained market outperformance. Alpha. When you think of market performance as “zero,” the market is zero sum. From there, it is a good idea to frame the question not as “How do I invest?” but instead “How do I sustainably outperform?” Base Rates I think a big part of the answer is by selecting stocks from baskets that outperform. Surely among the unmanageable tens of thousands of stocks out there, there are many baskets of a few hundred, selected based on various criteria, that have historically outperformed. Indeed there are. The academics are all over this. Here I will highlight and contrast just two though. Momentum One is momentum. This is buying stocks that have increased recently and either selling them when they begin to decline (“trend following”) or just holding them for a designated period like one year. This takes many forms because there are many definitions of “increased recently.” Has it increased in the last minute, hour, day, week, month, 50 days, 200 days, year, or 5 years? In general, I’ve gathered that over periods of measurement less than a year, momentum predicts outperformance. Once you extend it further to 5 years, this actually reverses. Momentum then underperforms and stocks that have performed the worst over the prior 5 years (“dumpster diving”) outperform. Here is some data from What Works on Wall Street to support the claim that momentum has predictive value. I won’t elaborate on the details of the tests but they did seem substantive and compelling: Strategy (from universe of All Stocks) Geometric Average Return 1951-2003 All Stocks 13.00% 50 Best 1 year price performance (“1YPP”) 12.61% 50 Worst 1YPP 4.06% Strategy (from universe of Large Stocks) Geometric Average Return 1951-2003 Large Stocks 11.71% 50 Best 1YPP 14.73% 50 Worst 1YPP 9.11% Strategy (from universe of All Stocks) Geometric Average Return 1955-2003 All Stocks 12.55% 50 Best 5YPP 6.89% 50 Worst 5YPP 16.77% Strategy (from universe of Large Stocks) Geometric Average Return 1955-2003 Large Stocks 11.18% 50 Best 5YPP 8.11% 50 Worst 5YPP 14.16% Valuation Metrics – EV/EBIT Another is valuation metrics. A valuation metric is a metric designed to measure the value of a company relative to something else. Valuation metrics are a price tag. They are what you pay over what you get. I label this general category “valuation metrics” because the one metric I am most interested in is not the only valuation metric that predicts market outperformance. Most valuation metrics have significant predictive value. Low PE and Low PB were identified as having predictive value several decades ago and still have substantial predictive value (read: they still work). But there is one that works better than the rest and that is the Enterprise Value to Earnings before interest and taxes multiple or EV/EBIT. First, what is Enterprise Value? Enterprise value is the true economic price of an entire company. It is the company’s market capitalization (share price x number of shares), with adjustments for the cash, debt, and other obligations the company has. Second, what is Earnings before interest and taxes? This is the company’s bottom line, its net income, with interest and tax costs added back. This is done to make performance comparable. A company’s capital structure (the amount of debt and cash it has) changes and this can also be a point of difference between companies. If we want to compare the operating performance of a company with that of another company or its own performance in a prior year, we get rid of the interest and tax to isolate for what we’re trying to measure. Put simply, EBIT is a purer measure of the profitability of most companies’ operations than any other number on the income statement. Together, EV and EBIT create a very powerful metric because they are both very sound measures of what they independently seek to capture: price and profit. As I mentioned, EV/EBIT is a quite powerful metric. I’ve done the following backtest in Bloomberg: US stocks Excluding utilities and financials Market cap > $20mm Equal weight (about 200 holdings at any one time) 1 year holding period Annual rebalancing Lowest 10% of the market on EV/EBIT From 1995-2015 (furthest back I could go with the test) This strategy generated annual returns of 21.68% versus 9.43% for the S&P 500. There are some other predictors in there like the inclusion of micro-caps, which historically outperform, and equal weighting, which outperforms, but there’s nothing wrong with that given that I don’t size based on market cap in my accounts and am able to invest in micro-caps. The biggest issue with this test is the limited sample size of only 20 years, but that’s all I could get with the data I had. In Quantitative Value, Carlisle and Grey subject EV/EBIT to many things that are “proper” for academic studies, but unnecessary and really detract from performance, and yet EV/EBIT still performs really well. They also did the lowest 10% of the market on EV/EBIT and excluded utilities, financials, REITs, and ADRs, but they also: Excluded any company from the universe with a market cap less the 40th percentile on the NYSE which translated in the study to less than $1.4B in 2011 dollars Market cap weighted instead of equal weighted Nevertheless, they found that the strategy returned 14.55% annually over 48 years from 1964-2011, beating the S&P 500 by 5.03% per year. Further, the top decile (highest 10% of population on EV/EBIT) underperformed the market by 2.43%/yr, so there is a spread of about 7.5% in annual performance between the top and bottom deciles. The most meaningful takeaways there are that the predictive ability still holds up with rigorous testing and over many market cycles (almost 50 years is a good-sized sample). Finally, EV/EBIT is one of the metrics used in the Magic Formula. The Magic Formula takes the 3500 largest stocks by market cap in the US and assigns a number rank to each based first on return on invested capital, a profitability metric, and then on EV/EBIT. So each stock has two rankings. These rankings are added together. The 30 stocks with the highest (smallest number) combined rank are equal weighted and rebalanced annually. According to Greenblatt, this strategy did like 30% annual returns over almost 20 years ending around when the book was first published in. Note that it’s been a while since I last read the book so those numbers may not be precise, but the bottom line is that the results were really good. Some issues here are the limited sample size in terms of years and the size of the basket, but the results are still compelling. Studies trying to replicate Magic Formula have found that the inclusion of ROIC actually detracts from its performance. In other words, EV/EBIT’s predictive ability is driving more than 100% of the performance. But Why? So EV/EBIT and momentum both perform well. But why? I don’t think it is enough only to have historical predictive value. It also makes sense. The test I use is “would I look for this if I were analyzing any one stock or business for prospective purchase?” If it doesn’t make sense but looks good and we go with it, we assume a major risk: data mining. One study attempting to illustrate data mining found that 99% of S&P 500 movement over 12 years was predicted by butter production in Bangladesh. Correlation does not equal causation. Past predictive value does not equal future predictive value. Source: Forbes And this is why I really like EV/EBIT. It makes sense. If I were looking at an individual company, a low EV/EBIT would look very appealing to me. In fact, I often value stocks, in part, using this metric. It also makes sense that buying things at lower prices is a good strategy. Momentum does not make as much sense to me. Why buy things now when it’s gotten so much more expensive? Except for certain luxury items, the appeal of most products decreases as the price increases. Conclusion So this is a big part of my process. I screen based on EV/EBIT, generate a list of a few hundred companies, and go through them one by one. There is intuition involved, but I’d say the list generation process is pretty systematic. Both are important and I like where my strategy is positioned. There are elements of both deep analysis and disciplined rules in my process and I think that’s a good place to be. I don’t know if I’ll always be using EV/EBIT and I doubt it will always be my primary focus, but I think the more important point is to have a defined process that makes sense, and, for me, to stay positioned at the crossroads of active and passive investing, rules and intuition as the lines between these seeming dichotomies blur in the future.