A year ago I posted my first annual summary of investment performance on Seeking Alpha, and with this article I document the latest chapter in my now seven-year history as an individual investor. As before, the focus will be on my single stock picks, but I’ll briefly summarize my activity in other asset classes (more on that can be found in my last article, “Portfolio Strategy 2018”). My estimated 2017 pre-tax return on single stocks, net of fees and hedging costs, was 25.8%, well above the S&P 500’s 21.8%.
Much of my trading activity revolved around Monsanto, my top holding from February to October (and my main short position in karma). I also incorporated Morningstar StockInvestor picks into my holdings. In addition to Monsanto, I detail several other S&P-outperforming short-term trades below, along with stocks I held throughout the year.
Below is my overall single stock return, net of fees and hedging costs, over the five years available in my active brokerage accounts. All figures in the My Return column except 2016 are pre-tax. I plan to make a post-tax revision to the 2017 figure in April.
Calculating a time-weighted rate of return on my single stock holdings became a rather joyless endeavor after I began using a second brokerage (Vanguard), and could no longer rely on the time-weighted rates reported by my Merrill Edge account for the total figure. I’ve included a section at the end of the article (Rate of Return Methodology) to explain how I calculated the 2017 return.
My portfolio value in all asset classes increased by 55%. 71% of the increase came from investment returns, and 29% from cash contributions. Of the investment returns, 44% came from cryptocurrencies, a remarkable result considering that cryptos were 1% of my portfolio at the end of 2016, and that I made no crypto purchases in 2017 aside from crypto-to-crypto conversions. I do report these assets on my tax returns, though (it feels good to be a one-percenter in one way, at least), so that gain will soon look less impressive.
Below is a side-by-side comparison of my single stocks at the end of 2016 and 2017, with the rightmost column showing each 2017 holding’s 1-year unrealized capital gain:
Notable Stock Trades
Before I go into individual trades, I’ll point out that finishing the year with 14 new holdings is notable in itself -- and beyond what I expected -- but somewhat a product of heavy profit-taking in Monsanto and cryptocurrencies at a time when market valuations made me hesitant to deploy new cash in concentrated positions.
I mentioned a year ago that Alphabet (GOOG) and Coca-Cola (KO) were on my watchlist, and adding Wal-Mart was part of the same allocation goal (the Diversification strategy) I cited in the context of Coca-Cola. As with Alphabet, adding Microsoft (MSFT) was an effort to bring my underweight tech sector allocation more in line with the S&P’s.
I added Enterprise Products (EPD), Priceline (PCLN), WPP (WPP), Express Scripts (ESRX), Unilever (UL) and Compass Minerals (CMP) in the interest of increasing my exposure to professional stock picks (for more on this, see my last article). Simon Property Group (SPG) was an attempt to diversify my real estate exposure after Boston Properties (BXP) was downgraded by Morningstar. CVS Health (CVS), General Electric (GE) and SCANA (SCG) came in the last two months of the year, as they were among the few higher-quality names available at bargain prices.
Despite the onerous demands of cataloguing my portfolio now, 64% of my single stock return can be credited to a fairly short list of 10 top-performing holdings:
Amazon (AMZN): Although I don’t label it a tech stock in my sector allocation targets, Amazon clearly benefited from 2017’s tech rally, and keeping it among my top holdings improved my otherwise modest exposure to that rally. I reduced it gradually throughout the year, though, as I’ve grown increasingly uneasy about its valuation.
Apple (AAPL): Its bargain price relative to tech peers, and status as a top Berkshire holding, made Apple easy to hold throughout the year.
Baidu (BIDU): Losing the mobile payment race to Alibaba and Tencent was a big blow, but governance concerns with the former and valuation concerns with the latter have kept them off my China watchlist. My 42% return on Baidu was only disappointing by comparison.
Berkshire Hathaway (BRK.B): My top holding before and after Monsanto, Berkshire has been a constant presence in the portfolio since June 2012, and has never disappointed.
First Solar (FSLR): After recouping my loss over a 3-year holding period, I exited this near $58 in October. My views on the solar industry changed a lot in those 3 years, as a promising growth story became overshadowed by the risk of long-term oversupply across the energy landscape.
General Motors (GM): My only other current holding dating back to 2012. Patience during the recall scandal, as well as confidence in their impressive balance sheet and manufacturing efficiency, began to pay off this year, with the help of buzz around their autonomous vehicle program.
Monsanto (MON): As mentioned earlier, I bought this heavily in February (around $109), as it was trading well below Bayer’s offering price, and I assumed that its appearance in Berkshire's portfolio reflected a higher probability of the deal closing. Its weighting peaked around 15% of my single stocks, and I sold most of it near $122 in October.
Union Pacific (UNP): The railroad industry is one of my favorite economic moat stories, and I expect this to remain among my top holdings over the long term.
Visa (V): The secular shift from cash to digital payments is a favorite growth story of mine. I exited PayPal in July on valuation concerns, and I increasingly have that concern with Visa, but I’ve tried not to hurry profit-taking too much.
Wal-Mart (WMT): Seeing it as one of few solid names in today’s brutal retail environment, I added Wal-Mart near $68 in February to resolve my underexposure to consumer staples. I didn’t buy it with growth potential in mind, and the fourth quarter rally on its e-commerce success took me by surprise.
Another 8% of my single stock return came from three short-term holdings which beat the S&P while I owned them:
Chicago Bridge & Iron (CBI): I bought this in mid-August, as the market seemed dismissive of the value unlocked by the announced sale of the company’s technology unit, as well as a $12 billion revenue backlog which made shares look cheap under even the most modest positive margin assumption. I realized a 28% average return in late August and September.
Equifax (EFX): I bought this between September 14 and 18, believing the security breach unlikely to jeopardize the firm’s place in the longstanding credit bureau oligopoly. Though I was comfortable holding the shares for as long as it took to recover from the panic, they seemed reasonably valued by mid-December, so I sold them for a 22% average return.
O’Reilly Automotive (ORLY): The ordeal of owning Bed Bath & Beyond was still fresh in my mind when O’Reilly sold off in July, but I decided that their dual-market parts business was a much more differentiated breed of retail, and I pocketed a 31% return in December.
As with most portfolios, mine developed a few red spots during the year. Here are two notable stocks I exited at a loss:
Bed Bath & Beyond (BBBY): I wrote extensively on this in my article “Bed Bath & Beyond the Star Rating”. In summary, Bed Bath taught me an important lesson in placing quality above valuation metrics in my investment decisions. I exited this value trap at a -18% average loss in July, fortunately avoiding a much greater loss had I held until year-end.
Valeant Pharmaceuticals (VRX): Amidst the carnage that began in late 2015 with allegations of overpricing and accounting malpractice at Valeant’s subsidiaries, I bought the first dip that year between $78 and $102, then exited in December (miraculously avoiding a huge loss over the following months), and re-entered in March 2016 between $29 and $39. I might have held on longer than I did, had the aforementioned scandal been Valeant’s only problem. Unexpectedly severe competition on their core products, however, combined with massive debt, put the company’s long-term solvency into question. Calculating my overall loss here is tricky since I increased and reduced the position several times. My lifetime loss divided by my peak cost basis in June 2017 was -19%. Of the shares I bought in March 2016 and sold on my February 28, 2017 exit date, the average loss on them was -61%.
Rate of Return Methodology
As mentioned earlier, moving a minority of my assets to a second brokerage has complicated my effort to obtain a time-weighted rate of return on single stocks. I’ve attempted to reproduce the time-weighted calculation I previously relied on in my Merrill edge account by periodically entering “snapshots” of my single stocks’ market value and year-to-date dollar return into a spreadsheet, then calculating a percent return across each period between two snapshots.
I calculate each period’s percent return by dividing that period’s dollar return (as reported by the brokerages) by the average of the period’s starting and ending market value. By multiplying all of these intermediate percentages together (without rounding), I get the 25.8% reported at the top of the article.
I took 22 of these snapshots throughout 2017, though not with the best of consistency, as the first is from March 26, and I had another lapse in data collection from August 12 to October 28. Aside from that, the longest period between two snapshots was 22 days.
For further verification, I did a simple single-period calculation using the market values on December 31, 2016 and December 31, 2017. The single-period result was 23.1%, which likely understates the actual return for two reasons: (1) the single period’s average market value was above that of a snapshot I took on a comparable median date, July 1, thus giving it a larger divisor than the comparable time-weighted one, and (2) my Merrill Edge account, which contains a majority of my holdings (but also a large cash position diluting its return -- 8% of the account on December 31, 2017, for example), reported a 24.0% return, higher than the single-period result.
I developed a custom software platform, using Python and MySQL, which stores my lifetime trade history and provides some statistics on it. I hope to add a feature that will provide a more accurate 2017 return for use in future articles. Collecting the extra historical price data, however, and writing a new algorithm to process it, is a big effort alongside my finance-unrelated day job.
Disclosure: I am/we are long ALL ASSETS, UNLESS OTHERWISE STATED. I wrote this article myself, and it expresses my own opinions. I am not receiving compensation for it. I have no business relationship with any company whose stock is mentioned in this article.