Tag Archives: seeking-alpha

Pioneer ILS Interval Fund Assets Up 18% To $64.4m

U.S. mutual fund manager Pioneer Investments reports that total net assets for its interval style insurance-linked securities and reinsurance linked investment fund, the Pioneer ILS Interval Fund (MUTF: XILSX ), have grown 18% to $64.4m. Pioneer Investments has added just under $10m to the net asset total for its ILS Interval fund in the three months from May to end of July, reaching $64.4m by that date. When Artemis last reported on this fund, at the end of April 2015, Pioneer had reported $54.66m of assets managed . Pioneer Investments launched the ILS Interval fund in late 2014 and the strategy was its first dedicated ILS and reinsurance linked investments fund. Pioneer also invests in ILS assets within other multi-asset class mutual funds. Once again the increase is mostly due to additional capital inflows into Pioneer’s ILS Interval fund, resulting in the managers making new investment allocations and taking on new positions in the quarter. Allocations to securities by the fund, which invests in a mix of catastrophe bonds, reinsurance sidecar notes and other collateralized reinsurance quota share notes, reached $62.99m at 31st July, up from $54.590m at the 30th April. During the three-month period, Pioneer added new catastrophe bond positions in Alamo Re Ltd. (Series 2015-1) , Compass Re II Ltd. (Series 2015-1) , Ibis Re II Ltd. (Series 2013-1) and Sanders Re Ltd. (Series 2013-1) . The managers of the Pioneer ILS Interval Fund also added a number of private ILS transactions during the three months, including investments in the Arlington, Clarendon and Kingsbarn Kane SAC segregated account transactions and an investment in a Series 2015-2 transaction from reinsurer TransRe’s Pangaea Re sidecar-style SPI. The Interval ILS Fund’s largest single holding remains the Gullane Kane SAC segregated account transaction, a privately transformed reinsurance deal, as well as holdings in Munich Re’s Eden Re II sidecar, Brit’s Versutus , Swiss Re’s Sector Re and PartnerRe’s Lorenz Re . Pioneer continues to find steady growth opportunities for its interval ILS fund. Alongside the other investments that Pioneer makes in ILS and reinsurance linked investments, this dedicated interval fund will stand well-positioned to take advantage of attractive opportunities to raise and deploy more capital. Pioneer Investments has over $1.6 billion in ILS and reinsurance linked assets across the fund’s and strategies that allocate to re/insurance-linked investments. Editor’s Note: This article discusses one or more securities that do not trade on a major U.S. exchange. Please be aware of the risks associated with these stocks.

Upgrade Your Investment Approach And Put Some Fears To Rest

Despite the pleas of many consultants and wealth managers for investors to ignore tumult in the markets, the fact is that oftentimes such fears are warranted. Although long term investors should not impulsively react to small market moves, they should be alert to signs that things are “not right”. The mean-variance approach to investing is a very common one, but time has revealed a great number of weaknesses that unnecessarily expose its adherents to risk. The Kelly criterion is a very useful approach to investing that also corresponds more closely to the way markets actually work. The investment services industry as a whole has been slow to disseminate improvements in investment theory and practice. We are born with some pretty good warning mechanisms and most people are pretty good at sensing when things are not right. Martin J. Dougherty makes exactly this point in his book Special Forces Unarmed Combat Guide : “Victims of assault often say afterwards that they could see it coming.” He continues, “The problem, then, is not being able to spot danger but being willing to act on this information and avoid it.” While this is just one manifestation of our defense network, it does highlight our natural ability to “spot danger”. It also highlights the imperative of being able to act on useful warnings. Given that volatility and risk are endemic to the exercise of investing, there is no particular reason why most market behavior should cause undue duress for a well-informed investor. And yet times of unsettled markets and high volatility can keep a lot of investors awake at night, including seasoned investment professionals. Oftentimes, concerns revolve around a sense of uncertainty – a sense that something isn’t quite right or that something is being missed. Sometimes it comes from an uneasy feeling that a prescribed course just doesn’t seem right. Indeed, it may just be that one’s approach to investing is the source of discomfort as much or more than market moves. Two common approaches to investing vary substantially in their assumptions and in the logic of how they aim to get you from point A to point B. If you are feeling uneasy, it may be a good time to make sure that your investment approach will allow you act so as to avoid danger. One approach focuses on the importance of diversification and uses statistical analysis to design portfolios that maximize returns for a given level of risk. It is well entrenched in investment theory and practice. This approach is characterized by graphs that show the upper and lower bounds of growth in assets and gives assurance that if you just stick to the plan, you will have an extremely high chance of meeting your investment goals. It makes a lot of sense and is hard to refute. Another approach is described by William Poundstone in Fortune’s Formula as being one that “offers the highest compound return consistent with no risk of going broke.” It is well recognized in investment theory, though probably less so in practice. It can certainly be characterized by wide swings, but gives the assurance that if you just stick to the plan, you will maximize your wealth over your investment horizon. It makes a lot of sense and is hard to refute. This juxtaposition of strategies highlights a common investment challenge: how can you tell which one is better and/or which one is more appropriate for you? Do you know which one your financial planner or wealth manager or consultant uses? These are exactly the types of fundamental questions that are so critical to long term investment success but are so rarely discussed thoroughly. The fact is that both approaches have merit to them, but both also rely on important assumptions. The first approach is referred to as the mean-variance framework and is a part of a body of thinking called “modern portfolio theory”. While the mean-variance approach correctly highlights the importance of diversification, it does so at the expense of some serious structural shortcomings (For an excellent, though technical discussion, see Michael Mauboussin’s interview with the physicist Ole Peters here ) . One of the flaws of the approach is that it models returns using only mean and variance. Unfortunately, the reality is that return distributions have other dimensions that are extremely important to investors. Considering only mean and variance is akin to describing a three dimensional object with only two dimensions. The description will be at best incomplete and at worst, wholly unrepresentative. The implication is that all of those great graphs of wealth accumulation are at best possibilities and at worst complete fantasy. Another important flaw of the mean-variance framework is that it relies on expectation values. In theory, according to Ole Peters, expectation values represent an “ensemble of imagined parallel universes” and can potentially serve as the “basis for sensible behavior”. In practice, however, most firms simply apply averages from the past, but these past actualities fall well short of representing all imaginable future possibilities. In other words, since (arguably) most firms do not populate the model with the right information, one cannot expect it to produce useful results. Garbage in, garbage out. This common deficiency almost completely undermines the case for using mean-variance as an investment strategy. The second approach is referred to as the Kelly criterion and gained notoriety as a betting system. Michael Mauboussin gives a nice overview in “Size Matters” here : “Based on information theory, the Kelly Criterion says an investor should choose the investment(s) with the highest geometric mean return. This strategy is distinct from those based on mean/variance efficiency.” In general, Mauboussin continues, “The Kelly Criterion works well when you parlay your bets, face repeated opportunities, and know what the underlying distribution looks like.” Poundstone adds, “The Kelly criterion is meaningful only when gambling profits are reinvested. A practical theory of investment must largely be a theory of reinvestment.” This is a key point: most people do think of and act on investments as discrete opportunities that change over time and not as a singular procedure that operates like a reliable machine. In this way, the Kelly approach seems to correspond with the way many people actually invest. According to Poundstone, “They [most people] buy stocks and bonds and hang on to them until they have a strong reason to sell. Market bets ride by default.” It is also natural to recognize the importance of reinvestment: One good investment does not a retirement make. You need to keep it up. Poundstone clarifies the strategy: “The Kelly formula says that you should wager this fraction of your bankroll on a favorable bet: edge/odds. The edge is how much you expect to win, on the average, assuming you could make this wager over and over with the same probabilities. It is a fraction because the profit is always in proportion to how much you wager.” As Mauboussin puts it, “As an investor, maximizing wealth over time requires you to do two things: find situations where you have an analytical edge; and allocate the appropriate amount of capital when you do have an edge.” An important condition for the Kelly approach is that the system only works as long as the investor “stays in the game long enough for the law of large numbers to work.” Further, it is also natural to think of calibrating the magnitude of investments according to their attractiveness. While the Kelly approach does require one to have an edge in order to make an investment, it doesn’t require one to invest when no edge exists. This all makes common sense – which ought to make it easier to adhere to even in tough times. Conversely, investors may have trouble adhering to a mean-variance approach because it isn’t that hard to perceive problems with its assumptions and logical consistency. For one, it’s not an inherently bad idea to look to past returns for an indication of what future returns might be, but why should that be the only input? Other things matter a lot such as valuations and your starting point. Likewise with assessing diversification benefits. It’s not bad to look at past cross correlations for starters, but why not also consider the potential for increased global interconnectedness to increase correlations and reduce diversification benefits in the future? Arguably the biggest issue with the mean-variance approach, however, is that it understates risk. It would make sense that unprecedented levels of central bank intervention the last seven years is a factor that ought to be incorporated into one’s investment approach, and yet mean-variance ignores it. It is also true that sometimes bad things do happen and it makes sense to try to avoid them. The mean-variance approach is very weak at adapting to change: it essentially says that since the vast majority of the time you don’t get attacked in dark alleys, you shouldn’t worry about dark alleys. Thus, although this approach is an industry standard and used by countless wealth managers, financial planners, consultants, and other industry participants, it actually serves as a very weak foundation upon which to base one’s investments. It treats the market as a utility, reliably cranking out returns, but that isn’t how the market actually works – as anyone who follows it knows all too well. As a result, it may well be that much of the anxiety investors feel in regards to unsettled markets has a lot to do with the discord that they feel in regards to the mean-variance approach. To be fair, it is not like the mean-variance framework is an obviously bad idea that never should have taken hold. The theory is over fifty years old though and a great deal has been learned during that time to improve and refine investment approaches. As one example among many, advances in behavioral economics have been a major development. Indeed it is one of the weaknesses of the investment services industry that it has been slow to disseminate many of the useful advances in investment theory and practice nearly as quickly as markets have evolved. The Kelly approach isn’t the end of the line either, but it does represent progress. Just like walking alone down a dark alley at night can intuitively seem like a bad idea, so can navigating through markets with an investment strategy that you don’t really trust. Neither may seem incredibly risky at the time and you might even be able to get by unscathed a few times. Don’t let anyone convince you that such actions are a good idea though. People are usually pretty good at spotting danger; make sure you are just as good at responding to it. If you don’t have a good idea of where to go, ask for help. (click to enlarge)

A Simple SPY Top-Off Portfolio

Summary A one-third UPRO, two-thirds cash portfolio mimics SPY (with some small tracking error and a net 0.32% expense ratio). Putting the two-thirds cash allocation in a short-term bond ETF like BSV allows you to recoup the 0.32% expense ratio, plus earn a little extra. Since UPRO’s inception in 2009, not including trading costs, the UPRO/BSV top-off portfolio has generated a CAGR of 15.3%, compared to SPY’s 14.3%. Going back to 1994, a 3x SPY/short-term bond portfolio has beaten SPY in 21 out of 22 years, with an average 3.1% annual outperformance. For S&P 500 investors, I see little downside to implementing a UPRO/BSV portfolio to consistently beat SPY. Background I’ve written a few articles on combining leveraged ETFs with cash or the underlying index to realize portfolios with certain properties (see for example Build Your Own Leveraged ETF ). There are a few neat things you can accomplish: Achieve any leverage between 0 and the highest multiple leveraged ETF available. Achieve a leverage multiple of an existing ETF by combining cash with a higher multiple leveraged ETF, potentially reducing your net expense ratio. Achieve net leverage of 1 by holding for example one-third of your money in a 3x leveraged ETF, and the remaining two-thirds in cash. The last point leads to the natural question: If I can mimic the SPDR S&P 500 Trust ETF ( SPY) while tying up only 33% of my available balance, why not put the remaining 67% to work in a low-risk fund that generates a few extra percentage points in growth every year? One-Third UPRO, Two-Thirds BSV The ProShares UltraPro S&P 500 ETF (NYSEARCA: UPRO ) is a leveraged ETF that aims to multiply daily S&P 500 gains by a factor of 3. It has an expense ratio of 0.95%. The Vanguard Short-Term Bond ETF (NYSEARCA: BSV ) is a short-term bond fund with an expense ratio of 0.10%. Let’s take a look at how a one-third UPRO, two-thirds BSV portfolio would have performed over these funds’ mutual lifetimes. (click to enlarge) Sure enough we get a nice little top-off with the UPRO/BSV strategy. The compound annual growth rate was 14.3% for SPY, 15.3% for UPRO/BSV rebalanced daily with no fees, and 14.8% for UPRO/BSV rebalanced whenever the effective leverage went below 0.9 or above 1.1 (with a $7 trading fee). Sharpe ratios were 0.058, 0.063, and 0.061, respectively. Of course, the greater your portfolio’s balance, the more your growth would look like the blue curve rather than the red one, since you can rebalance very frequently without trading costs hurting you very much. I know, an extra 1% isn’t that much. But just like a 1% expense ratio can really hurt you over time, a 1% boost every year can really make a big difference. If you go year by year you see that UPRO/BSV tends to tack on an extra 1-2% to SPY’s annual growth, although it doesn’t always. Annual growth of SPY and UPRO/BSV portfolios. Year SPY BSV UPRO/BSV (no fees) UPRO/BSV (fees) 2009 22.3% 2.1% 23.7% 23.4% 2010 13.1% 3.8% 15.5% 14.0% 2011 0.9% 3.0% 2.3% 2.2% 2012 14.2% 1.5% 14.9% 14.2% 2013 29.0% 0.2% 28.3% 28.1% 2014 14.6% 1.4% 14.9% 14.9% 2015 -7.1% 1.4% -6.6% -7.2% One-Third 3x Leveraged ETF, Two-Thirds VBISX We can only look at UPRO/BSV back to 2009, but it’s easy enough to switch UPRO for a hypothetical 3x SPY ETF, and switch BSV for the Vanguard Short-Term Bond Index Fund Investor Shares (MUTF: VBISX ), so we can go back further. For the 3x SPY ETF, we’ll assume no tracking error and a 0.95% annual expense ratio, mimicking UPRO. The correlation between daily gains for the simulated 3x SPY ETF and UPRO since UPRO’s inception is 0.997. The correlation between monthly gains for BSV and VBISX since BSV’s inception is 0.963. Let’s see how one-third 3x SPY, two-thirds VBISX would have performed since 1994. (click to enlarge) The top-off portfolios achieved nearly double the balance of SPY over the 20.5-year period. Sharpe ratios were 0.033 for SPY, 0.043 for 3x SPY/VBISX with no fees, and 0.043 for 3x SPY/VBISX with fees. Of course it is important to note that VBISX has done really well since 1994, with a CAGR of 4.4%. Note that the top-off portfolio with fees beat SPY in 21 out of 22 years (all except 1994), and on average beat SPY by 3.1%. You can see the consistent annual outperformance below. (click to enlarge) Another way to visualize the outperformance of the top-off portfolio relative to SPY: (click to enlarge) A Portfolio Optimization View I came to the one-third 3x SPY, two-thirds short-term bonds portfolio from the perspective of mimicking SPY by combining a 3x leveraged ETF with cash, but then putting the cash to work to gain an extra few percentage points. But you can also view the strategy from a portfolio optimization perspective. A short-term bond fund like BSV has positive alpha simply from the fact that it yields a certain small percentage annually from maturing bonds of various durations. So in periods when SPY is flat, BSV still tends to grow (i.e. it has positive alpha). Indeed if you regress monthly VBISX gains vs. monthly SPY gains going back to 1994, VBISX has alpha of 0.0036 (p < 0.001), meaning it gains on average 0.36% in months when SPY is flat. Typical Stocks/Bonds Story? It is well-known that holding both stocks and bonds tends to improve risk-adjusted returns. But if you hold an S&P 500 index fund in addition to bonds, your net beta drops below 1 and you often sacrifice raw returns. The UPRO/BSV approach is unique in that it keeps beta at 1 (assuming BSV has no correlation with SPY), while increasing both risk-adjusted and raw returns. Something like a free lunch. Upping the Ante A natural extension of the UPRO/BSV top-off strategy is combining UPRO with a longer duration bond fund. For example I like one-third UPRO, two-thirds BND, for a bigger top-off. But BND is much more variable than BSV, and also much more sensitive to rising interest rates. Another way to "up the ante" so to speak is to aim for some leverage greater than 1, say 1.25 or 1.5. You can still combine UPRO with BSV to get some extra growth at any leverage below 3, but the greater your net leverage, the greater your allocation to UPRO has to be, and the less you have left over to grow in BSV. Risks Many investors may not be comfortable with a portfolio that requires a significant allocation to a leveraged fund. Indeed, there are risks associated with leveraged funds. In particular: If SPY ever experiences an intraday loss of one-third its opening price, you could lose the entire balance in the leveraged ETF. While leveraged S&P 500 ETFs like UPRO have historically had very little tracking error, daily gains may occasionally deviate from the target multiple. In between rebalancing periods, you may suffer some irrecoverable losses due to volatility decay. It is important to note that while the top-off strategy uses leveraged ETFs, the target net leverage for the portfolio is 1. In that sense, the portfolio is not prone to the greatly amplified volatility (and potentially catastrophic drawdowns) usually associated with leveraged ETFs. It is very important to understand these issues before implementing the SPY top-off strategy. Indeed, many investors may decide that the potential for slightly higher annual returns does not justify the added risks. I personally believe that the risk/reward for the strategy is favorable. Conclusions A one-third UPRO, two-thirds BSV portfolio should behave very similarly to a 100% SPY portfolio, but often generate an extra 1-4% annual return. You'll have to monitor your effective leverage (multiply your UPRO allocation by 3) and rebalance when it deviates much from 1, but for a reasonably sized portfolio this should not detract much from your extra gains relative to SPY. Of course, you don't have to use UPRO and BSV. Other 3x S&P 500 ETFs and short-term bond funds should perform similarly. And if you want an extra boost, consider pairing the leveraged ETF with an intermediate or long-term bond fund, or a total bond fund. But your annual gains will be more variable, and you may suffer losses as interest rates rise. I am currently implementing the SPY top-off strategy with UPRO and BND, but may switch to UPRO and BSV in the near future for a more consistent, albeit smaller, bonus. Ideally, I'll beat SPY by a little bit every year, and eventually be happy.