Author Archives: Scalper1

How Many Stocks Should You Own? Remember Warren Buffett’s Advice

Summary Diversification is trumpeted as a key point of proper portfolio design. Warren Buffett disagrees with diversification, with a single caveat. The return spread among stocks suggest that every new holding you add is more likely to be a loser than a winner. If you asked SeekingAlpha readers why investors should own more than one stock, the overwhelming response would easily be diversification. The idea is simple: the more holdings you have, the less exposure you have to unsystematic risk (risk associated with a particular company or industry). Now, if you asked a follow-up question, “How many stock holdings you should have?”, you would end up with a hotly debated topic. On page 129 of my copy of The Intelligent Investor , legendary money manager Benjamin Graham advocates holding 10 to 30 positions. Modern portfolio theory supported this advice, and many continue to follow its preachings religiously. According to this theory, if you own 20 well-diversified companies, each held in equal amounts, you’ve eliminated 70% of risk (as measured by standard deviation) and reduced volatility. Can’t argue with the math (or can you?), and diversification has been harped on by many as the foundation of any properly constructed portfolio. It is likely that anyone that has had a financial advisor or even discussed finances with a family friend has heard this advice before. Always spread your capital across multiple sectors and markets is in that person’s best interest. Makes sense right? Who doesn’t want less volatility and risk? Warren Buffett apparently. “Diversification is protection against ignorance. It makes very little sense for those who know what they’re doing.” – The Oracle of Omaha Himself So, Do You Know What You’re Doing? Of course, modern portfolio theory and its offshoots were theorized between the ’50s and ’70s. Volatility is up since then, and stocks have become increasingly uncorrelated with the underlying market. To more clearly illustrate this point, stocks increasingly don’t follow a normal distribution pattern: * Source: Investopedia The results of the above image have been repeated over and over in recent market studies. The key takeaway for an individual investor is that the odds of a stock you own outperforming the stock market is actually worse than 50/50 , contrary to what many investors might think off hand. The reason for this is because overall market returns have been boosted by just a handful of “superstar” stocks, like Apple (NASDAQ: AAPL ) or Microsoft (NASDAQ: MSFT ). If you don’t own something like the next Apple or Microsoft in your portfolio (roughly 1 in 16 odds), then well, you’re likely doomed to underperform. So if you have a portfolio of 16 stocks, what are the odds you have that one in sixteen superstar company included based on random chance? Just 38%. Let us say you get lucky and manage to stumble upon a superstar. Now the question is whether you will continue to hold it as it multiplies. Enter the disposition effect . Retail investors have a tendency to sell winners (realizing gains too early) and hold onto losers, following the thought process that today’s losers are tomorrow’s winners. How many investors held on to Apple from $7.00/share in the early 2000’s all the way up to more than $700.00/share (split-adjusted) today? The answer is likely very few. Retail investors took the profit from the double or triple (if they even held that long) and likely didn’t reinvest back in because they had sold in the past. None of this changes the fact that the more companies you own, the more you will inevitably track the index of the positions you hold. In order to generate alpha (abnormal return adjusted for risk), it is a fact that the more stocks you own, the less likely you will be able to generate that alpha. The more holdings you have, the more likely you will have just tracked the index that your holdings are a part of, but in an inefficient way. For all your trouble, you are out both your free time and likely higher trading costs. The question then is why bother with all the headaches of investing in numerous individual companies you buy individually, if you could simply just buy the index and take it easy? If you take a look at major hedge fund and money manager holdings, it is clear that concentrated holdings are used to drive alpha. Visiting the Oracle of Omaha’s portfolio, the man clearly practices what he says. The top five holdings of Berkshire Hathaway (NYSE: BRK.A ) (NYSE: BRK.B )[Wells Fargo (NYSE: WFC ), Kraft Heinz (NASDAQ: KHC ), Coca Cola (NYSE: KO ), IBM (NYSE: IBM ), and American Express (NYSE: AXP )] constituted 67% of his portfolio as of September 30, 2015. 43 scattered holdings constituted the remaining 33%. As for diversifying across sectors versus buying what you know and understand, 37% of Buffett’s holdings fall in the Consumer Staples sector and 35% in Financials. The man clearly doesn’t buy utilities just because portfolio theory tells him he should in order to reduce his risk. Conclusion Thousands of people will read this article. Are you smarter than two thirds of them? If you don’t believe that, buy ETFs, sit back, and be content with market returns. If you think you’re smarter than two thirds of readers of this article (I suspect 95% of you believe that), then the takeaway is slightly different. Diversification, for the sake of diversification, is stupid. Buy what you know, can understand, and believe in the long-term potential of. Don’t understand bank stocks? Reading their SEC filings even gives me headaches, and I work at one. If you don’t understand the company, chances are you aren’t going to pick a winner other than by dumb luck. You shouldn’t lose sleep at night for not having exposure to an industry you can’t adequately review, and it is likely your portfolio returns will thank you for it. As far as how many positions to have, hold as few positions as you are comfortable with when it comes to risk and volatility in order to increase alpha on your high conviction positions. For most investors, that sweet spot still likely falls within modern portfolio theory guidance, around 15 to 25.

November 2015 U.S. Fund Flows Summary

By Tom Roseen For the third month in four investors were net redeemers of fund assets, withdrawing $19.1 billion from the conventional funds business (excluding ETFs) for November. For the fifth consecutive month stock & mixed-asset funds suffered net redemptions, handing back some $24.0 billion for November (their largest net redemption since December 2014), while for the fifth month in six fund investors were net sellers of fixed income funds, removing $3.9 billion from the macro-group for November. For the second month in a row money market funds witnessed net inflows, taking in $8.8 billion for November. Despite a better-than-expected jobs report at the beginning of November, M&A news in the biotech industry, and a jump in financials, investors remained wary during the month in anticipation of the Federal Reserve’s raising interest rates in December. The Labor Department said the U.S. economy added 271,000 jobs for October-above the consensus-expected 185,000. Softer European Union gross domestic product data, weak economic reports from China, and worse-than-expected retail sales data mid-month led to one of the largest weekly losses in months. A large slide in oil prices placed a further pall over equities. However, comments by Fed policy makers indicating they would raise interest rates in a slow and careful manner, accompanied by news that the European Central Bank (ECB) will combat low inflation by deploying stimulus measures in December, helped ease investors’ concerns, leading to one of the largest weekly gains in the S&P 500 in almost a year. Strong earnings reports and an increase in quarterly dividends from the likes of Intuit and Nike were offset by news of slowing growth in emerging markets and by ongoing geopolitical concerns. Energy and mining shares were hit particularly hard during the month as concerns over excessive oil supplies and disappointing Chinese economic data played on investor psyche. The Mixed-Asset Funds macro-classification (+$4.5 billion) attracted the only net inflows of Lipper’s five equity macro-classifications, while USDE funds experienced the largest outflows (-$23.1 billion). Large-cap funds (-$9.3 billion) suffered the largest monthly net redemptions of the capitalization groupings for the fourth consecutive month. Again, in contrast to its open-end fund counterpart, the ETF universe witnessed its tenth consecutive month of net inflows, taking in $24.1 billion for November. For the third month in a row authorized participants (APs) were net purchasers of equity ETFs-injecting $23.7 billion (their largest net inflows since March), and for the fifth month in a row they were also net purchasers of bond ETFs-although injecting only $0.5 billion for November. Surrounded by uncertainty and looking for greater clarity by the ECB on its proposed monetary easing, for the fourth month in five APs’ appetite for USDE ETFs topped that for all other types of equity ETFs. The macro-classification witnessed the strongest net inflows (+$14.1 billion) of Lipper’s five equity-related macro-classifications, followed by World Equity ETFs (+$5.7 billion), Sector Equity ETFs (+$4.4 billion), and Mixed-Asset ETFs (+$0.3 billion). The Alternatives ETFs macro-classification (-$0.8 billion) suffered the only net outflows for the month. If you’d like to read the entire November 2015 FundFlows Insight Report with all its tables and charts, please click here .

New Valuation Approach – PTR: PTR-Based Fund Delivers Over 63% Annual Returns In Big Data Simulations

A new approach to stock valuation looks at the relationship of the stock price to the value of the patent technology owned by the firm. Simulations indicate that stocks with low price-to-technology ratios outperform the market. Investors may wish to include PTR valuations as part of a stock-screening exercise. A former student approached me with a new model for stock valuation that appears to have great promise. Wisdomain.com has a database with comprehensive information on patents which has been used by intellectual property professionals to manage technology. Recently, the company figured out a Price/Technology ratio that appears to be a powerful tool for screening technology investments. PTR challenges the conventional principles of long-term value investing. It takes a completely objective approach to valuation through the mining of intellectual property big data and combining it with financial big data. It is an investment indicator that provides insights into the future performance of investments by identifying undervalued companies that possess patented technologies. Because patent valuation is technology valuation, PTR uses a proprietary algorithm based on technology valuation and total market capitalization data to identify undervalued technology companies. PTR = Market Capitalization Σ (Total Value of Patents) Σ (Total Value of Patents) = Total Technology Asset Value Technology assets play a key role in facilitating the competitiveness of a company in most industries. Since the sum of the value of all of the patents owned by a company is a good proxy for the value of the technology assets owned, it can be considered to be tied to the future potential profitability of the company. Although the formula is similar to the P/E ratio in that the companies with relatively lower PTR values are considered to be the undervalued companies, it is also completely different. Historical simulations of a PTR index formed by PTR funds comprised of the top 20 lowest PTR stocks exceed the NASDAQ’s average returns by 46.4% in the 1st year and 71.9% in the 2nd year. Similarly, the simulations show that the low PTR funds outperform the S&P 500 by 5.8% in the 1st month and 78.8% by the 2nd year. The PTR Index outperforms the market 100% of the time during the simulation period, and funds held over longer periods result in higher returns relative to the market. (click to enlarge) Simulation period = 2010-2015; PTR, NASDAQ, and S&P 500 values have been normalized to 1,000; Funds purchased on a daily basis over the course of the simulation period to minimize the effect of daily variations in stock prices and obtain the average performance values of the funds over the investment periods within the simulation period. The PTR investment model shown above is based on long-term investments into funds comprised of 20 low PTR companies. There were individual cases among the 20 lowest PTR stocks where the stock demonstrated negative returns; however, funds created by combining the 20 lowest PTR stocks have been shown to deliver positive returns. Although investments into individual stocks with the lowest PTR values do not guarantee positive returns, the PTR as a stand-alone indicator has proven to be quite successful. The top 15 companies with the lowest PTR values that are currently traded on the NASDAQ and NYSE are as follows. DMRC , ESIO , CKP , RIGL , IMMU , SNMX , UIS , ROVI , SGI , ARRY , OCLR , AMD , IMI , XNPT and HTCH . (click to enlarge) Although the simulations above demonstrate that the PTR is a breakthrough investment indicator for technology-driven companies, analysts are still in the early stages of developing the methodologies to maximize profitability through the application of the PTR. Some interesting findings to date have shown that the PTR stocks in the smaller market capitalization categories demonstrate better performance relative to PTR stocks in the larger market capitalization categories. With this level of performance, it will be interesting to see what else the PTR has in store for us.