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Strategic Asset Management Launches New Global Long/Short Fund

The long/short “hedged” fund was pioneered in the late 1940s in response to the economic tumult of the prior two decades. The idea behind it was to reduce exposure to the fluctuations of the “market” by partially offsetting long positions with short ones. If the stock picker was good, this meant the fund could outperform during bull and bear markets, and the downside during the latter would be mitigated. Strategic Asset Management’s First Fund Global long/short equity funds take things a step further than Alfred Jones, “hedged” fund originator, was able to take them in 1949, when investors were largely constrained by national borders. Rather than limiting themselves to U.S. equities, global long/short equity funds are open to investments from all over the world, and the Strategic Global Long/Short Fund (MUTF: SGFAX ), just launched on February 23, employs this strategy with a split “value/growth” approach. The new fund is advised by Strategic Asset Management, Ltd., a Cayman Islands corporation, and its portfolio manager is Mauricio Alvarez, Chief Executive Officer of the Adviser. This appears to be the company’s first U.S. mutual fund. The fund’s investment objective is twofold: First, to provide attractive returns through a combination of long-term capital appreciation and current income. Secondarily, to preserve capital in down markets. In pursuit of these objectives, the fund takes long and short positions in U.S. and foreign equities across all capitalization levels, with at least 40% of assets invested in companies generating a majority of their revenue outside the U.S. Global Long/Short Exposure The fund’s long exposure is expected to range from 100% to 140%, with the use of leverage; while its short exposure is expected to range from 0% to 40%. This will leave the fund with a relatively high beta compared to other long/short equity funds. The average beta, relative to the S&P 500 Index, for funds with a track record of 3-years or more is 0.53. On the long side, a “top-down” security selection process is used to identify undervalued equities and/or equities with favorable growth characteristics. On the short side, the fund focuses more keenly on firms with deteriorating growth. Currently, the fund is available in A-class shares only, which have a 1.97% net-expense ratio and a $1,000 initial minimum investment. The prospectus also refers to C-class shares, but doesn’t list a ticker symbol. Their intended net-expense ratio is 2.72%, and they have the same $1,000 initial minimum. For more information, view the fund’s prospectus .

Estimating Return-Shortfall Risk For Portfolios

Failure isn’t an option, but it happens. Modeling the possibility that a portfolio strategy will stumble isn’t exactly cheery work, but it’s a productive and necessary exercise for stress testing what the future can do to the best-laid plans for investing. The good news is that there’s a rainbow of options for estimating the potential for trouble. But it’s usually best to start with a basic framework before venturing into more exotic realms. A solid way to begin is by calculating the probability that a portfolio’s return will fall short of a particular benchmark or return. Larry Swedroe, Director of Research for the BAM Alliance, last month wrote about the probability of underperformance from the perspective of four factor premiums. The technique is to assume a normal distribution of returns and model the outcome under a variety of scenarios. Normal distributions are problematic, of course, due to fat-tail risk. But as Swedroe correctly points out, a normal distribution is “reasonable for multi-annual returns data because annual returns data is approximately normally distributed for diversified portfolio.” The details for the number crunching are straightforward. Several years ago The Calculating Investor outlined the procedure with an Excel spreadsheet. Let’s expand the concept a bit by applying the normal distribution function in R via the pnorm() command. Assume we’ve designed a portfolio with a 10-year time horizon and expected annualized volatility (standard deviation) of 15%. Holding those variables constant, here’s the probability of generating a below-zero return over that span based on a range of expected returns for the portfolio: Not surprisingly, the risk of suffering a negative result is substantial if we’re assuming a low return. A 1% annualized return carries a 40%-plus risk a sub-zero performance over a 10-year stretch. But as expected return rises, the risk of below-zero performance falls. As the portfolio’s projected return approaches 10%, the risk of losing money fades to a virtually nil possibility, given the assumptions about volatility and time horizon. For another perspective, let’s vary the time horizon while holding the expected return and volatility constant by assuming the portfolio will earn 5% annualized with 15% standard deviation. As the next chart below shows, running the numbers through a normal distribution model tells us that the risk of sub-zero performance is considerable at short time horizons. Starting at around 15 years, shortfall-return risk falls below a 10% probability. In other words, the longer the time horizon, the lower the probability of losing money. Finally, let’s model various levels of expected volatility while holding constant the time horizon (10 years) and projected return (5%). The third chart below quantifies what intuition implies: higher portfolio volatility increases the probability of suffering a loss. There are many variations on the simple examples above. For example, we can easily model the risk of falling short of the risk-free rate, an inflation-adjusted benchmark, or any other yardstick that’s considered relevant. We can also crunch the data by factoring in a fat-tails assumption for added reality. Ultimately, the goal is to design a modeling framework that’s customized for a specific portfolio. The point is that a basic quantitative application is useful for deciding how a given portfolio might fare under extreme conditions. For instance, the procedure outlined above may reveal that a given set of assumptions is highly sensitive to small changes – a sensitivity that may not be obvious without a formal modeling effort. In that case, it may be time to go back to the drawing board for designing an asset allocation. After all, the price tag is always lower for discovering problems in the design stage as opposed to finding enlightenment when real money is at stake. The future’s still uncertain, of course, but the first priority for the art/science of risk modeling is about minimizing the potential for surprises. Our capacity for insight is limited and so deploying diagnostic tests about what could happen fall well short of providing definitive clarity for the morrow. Estimating shortfall risk is no panacea, but it’s still useful. In fact, the only thing that’s worse than running this modeling procedure is not doing it at all.

Comments On Mistakes And Buffett’s Original Berkshire Purchase

I was reading through the 2014 (last year’s) Berkshire Hathaway ( BRK.A , BRK.B ) annual report and 10-K, looking for a few things, and happened to reread Buffett’s letter from last year. I wrote a post a couple weeks ago concerning buybacks and Outerwall (NASDAQ: OUTR ), and how a company that is buying back stock of a dying business is not a good use of capital. I noticed a passage in last year’s letter that is relevant to the topic – Buffett himself was attracted to buybacks on a dying business, Berkshire Hathaway, in the early 1960s. Berkshire was a Ben Graham cigar butt – it was trading at around $7, and had net working capital of $10 and book value of $20. It was a classic “net net” – a stock trading for less than the value of its cash, receivables, and inventory less all liabilities. Buffett liked the fact that Berkshire was (a) trading at a cheap price relative to liquidation value, and (b) using proceeds from the sale of plants to buy back shares – effectively liquidating the company through share repurchases. Here is what Buffett was looking at when he originally bought shares in this company in the early 1960s: Like Outerwall, Berkshire’s business was in secular decline. In fact, it had been dying a long time, as the meeting notes from a 1954 Berkshire board meeting stated: “The textile industry in New England started going out of business forty years ago”. Also like Outerwall, Berkshire was buying back stock. One difference (among many, of course) between Berkshire then and Outerwall now is that Berkshire was closing plants and using proceeds to buy back shares. From the 1964 Berkshire report (which can be found on page 130): “Our policy of closing plants which could not be operated profitabily was continued, and, as a result, the Berkshire King Philip Plants A and E in Fall River, Mass. were permanently closed during the year. The land and buildings of Plant A have been sold and those of Pant E offered for sale… Berkshire Hathaway has maintained its strong financial positiona nd it would seem constructive to authorize the Directors, at their discretion, to purchase additional shares for retirement.” Outerwall, on the other hand, is producing huge amounts of cash flow from its operations, not from the sale of fixed assets. Liquidation versus Leveraged Buyout Another difference is that Berkshire was in liquidation mode, and was buying out shareholders (through buybacks and tender offers) from cash proceeds it received from selling off plants. Outerwall hasn’t been liquidating itself through buybacks-instead it has leveraged the balance sheet by issuing large amounts of debt, using the proceeds to buy back stock, which has reduced the share count, but not the size of the balance sheet or the amount of capital employed. Outerwall had total assets of around $1.3 billion five years ago, roughly the same as it does now (goodwill, however, has doubled due to acquisitions). These assets were financed in part by $400 million of debt and $400 million of equity in 2010. Today, the company’s assets are financed by roughly $900 million of debt, and shareholder equity is now negative. Outerwall has historically produced high returns on capital, and it’s a business that doesn’t need much tangible capital to produce huge amounts of cash flow (an attractive business), but has been run similar to companies that get purchased by private equity firms – leverage up the balance sheet, issue a dividend (or buy out some shareholders), thus keeping very little equity “at risk”. It’s a gamble with other people’s money, and sometimes it results in a home run (sometimes, of course, it doesn’t). So, Berkshire in the 1960s was more of a slow liquidation. Outerwall is basically a publicly traded leveraged buyout. In the case of BRK, shareholders who purchased at $7 were rewarded with a tender offer of just over $11 a few years later. But that’s the nature of cigar butt investing – sometimes at the right price, there is a puff or two left that allows you to reap an outstanding IRR on your investment. In Buffett’s case, had he taken the tender offer from Seabury Stanton, his IRR on the BRK cigar butt investment would have been around 40%. He didn’t, though, and the rest is history. It’s interesting to note another mistake that he points out in last year’s letter – one that I think is rarely mentioned, but was very costly. Instead of putting National Indemnity in his partnership, which would have meant it was 100% owned by Buffett and his partners, he put it into Berkshire Hathaway, which meant that he and his partners only got 61% interest in it (the size of the stake that Buffett had in BRK at the time). I think this could have been Buffett’s way of doubling down on Berkshire (then, a dying business with terrible returns on capital). He thought he could save it (not the textile mills, but the entity itself) by adding a good business with solid cash flow and attractive returns to a bad business that was destroying capital. Obviously, as Buffett points out, he should have shut down the textile mills sooner, and just used National Indemnity to build what is now the company we know as Berkshire Hathaway. Two Mistakes to Avoid Two takeaways from this, which, in Buffett’s own words, were two of his greatest mistakes: It’s usually not a good idea to buy into bad businesses, even at a price that looks attractive If you are in a bad business, it probably doesn’t make sense to “double down” – for most of us, this could mean averaging down and buying more shares. In Buffett’s case, it was already a 25% position in his portfolio, and he “doubled down” by throwing good money after bad (putting National Indemnity – a good business – inside a textile manufacturer, instead of just a wholly owned company inside of Buffett’s partnership. The good news – things have worked out just fine for Buffett and for Berkshire. Although the textile mills unfortunately had to finally shut down for good, National Indemnity has come a long way since Buffett purchased it for $8.6 million in 1967 (see the original 2-page purchase contract here ; no big Wall Street M&A fees on this deal). National Indemnity now has over $80 billion of float and over $110 billion of net worth, making it the most valuable insurance company in the world. The insurance business that started with National Indemnity paid dividends to Berkshire last year of $6.4 billion, and holds a massive portfolio of stocks, bonds, and cash worth $193 billion at year end. Buffett estimated his decision to put National Indemnity inside of Berkshire instead of in his partnership ended up costing Berkshire around $100 billion. It’s refreshing when the world’s best investor humbly lays out two of his largest mistakes, his original thesis, and the thought processes he subsequently had in regard to those investments. It’s also nice to note that despite two large mistakes, things worked out okay. I own shares in Berkshire, purchased for the first time ever just recently, and I’ll write a post with a few comments on the recent 10-K and annual report soon.