Tag Archives: income

A Better Way To Run Bootstrap Return Tests: Block Resampling

Developing confidence about a portfolio strategy’s track record (or throwing it onto the garbage heap), whether it’s your own design or a third party’s model, is a tricky but essential chore. There’s no single solution, but a critical piece of the analysis for estimating return and risk, including the potential for drawdowns and fat tails , is generating synthetic performance histories with a process called bootstrapping. The idea is based on simulating returns by drawing on actual results to see thousands of alternative histories to consider how the future may unfold. The dirty little secret in this corner of Monte Carlo analysis is that there’s more than one way to execute bootstrapping tests. To cut to the chase, block bootstrapping is a superior methodology for asset pricing because it factors in the reality that market returns exhibit autocorrelation. The bias for momentum – positive and negative – in the short run, in other words, can’t be ignored, as it is in standard bootstrapping. There’s a tendency for gains and losses to persist – bear and bull markets are the obvious examples, although shorter, less extreme runs of persistence also mark the historical record as well. Conventional bootstrapping ignores this fact by effectively assuming that returns are independently distributed. They’re not, which is old news. The empirical literature demonstrates rather convincingly a strong bias for autocorrelation in asset returns. Designing a robust bootstrapping test on historical performance demands that we integrate autocorrelation into the number crunching to minimize the potential for generating misleading results. The key point is recognizing that sampling historical returns for analysis should focus on multiple periods. Let’s assume that we’re looking at monthly performance data. A standard bootstrap would reshuffle the sequence of actual results and generate alternative return histories – randomly, based on monthly returns in isolation from one another. That would be fine if asset returns weren’t highly correlated in the short run. But as we know, positive and negative returns tend to persist for a stretch, sometimes in the extreme. The solution is sampling actual histories in blocks of time (in this case several months) to preserve the autocorrelation bias. The question is how to choose the length for the blocks, along with some other parameters. Much depends on the historical record, the frequency of the data, and the mandate for the analysis. There’s a fair amount of nuance here. Fortunately, R offers several practical solutions, including the meboot package (“Maximum Entropy Bootstrap for Time Series”). As an illustration, let’s use a couple of graphics to compare a standard bootstrap to a block bootstrap, based on monthly returns for the US stock market (S&P 500). To make this illustration clear in the charts, we’ll ignore the basic rules of bootstrapping and focus on a ridiculously short period: the 12 months through March 2016. If this was an actual test, I’d crunch the numbers as far back as history allows, which runs across decades. I’m also generating only ten synthetic return histories; in practice, it’s prudent to create thousands of data sets. But let’s dispense with common sense in exchange for an illustrative example. The first graph below reflects a standard bootstrap – resampling the historical record with replacement. The actual monthly returns for the S&P (red line) are shown in context with the resampled returns (light blue lines). As you can see, the resampled performances represent a random mix of results via reshuffling the sequence of actual monthly returns. The problem is that the tendency for autocorrelation is severed in this methodology. In other words, the bootstrap sample is too random – the returns are independent from one another. In reality, that’s not an accurate description of market behavior. The bottom line: modeling history through this lens could, and probably will, lead us astray as to what could happen in the future. Let’s now turn to block bootstrapping for a more realistic profile of market history. Note that the meboot package does most of the hard work here in choosing the length of the blocks. The details on the algorithm are outlined in the vignette. For now, let’s just look at the results. As you can see in the second chart below, the resampled returns resemble the actual performance history. It’s obvious that the synthetic performances aren’t perfectly random. Depending on the market under scrutiny and the goal of the analytics, we can adjust the degree of randomness. The key point is that we have a set of synthetic returns that are similar to, but don’t quite match, the actual data set. Note that no amount of financial engineering can completely wipe away uncertainty. The future can and probably will deliver surprises, for good and ill, no matter how clever our analytics. Nonetheless, bootstrapping historical data (or in-sample returns via backtests) can help separate the wheat from the chaff when looking into the rearview mirror as a preview of what lies ahead. But the details on how you run a bootstrap test are critical for developing comparatively high-confidence test results. In short, we can’t ignore a simple fact: market returns have an annoying habit of exhibiting non-random behavior.

Lack Of Earnings Quality And Debt Downgrades Limit S&P 500’s Upside

Four in a row. That’s how many consecutive 3-point baskets Andre Iguodala scored against the Houston Rockets in last night’s playoff game. There has also been a “4 for 4″ in the financial markets. One after another, major banks have lowered their year-end targets for the S&P 500. Most recently, the global equity team at HSBC shaved its year-end target to 2,050 from 2,100. On the surface, HSBC’s cut is less severe than other bank revisions to S&P 500 estimates. That said, J.P Morgan pulled its projection all the way down from 2200 to 2000. Credit Suisse? Down to 2,050 from 2,200. And Morgan Stanley slashed its year-end projection from 2175 to 2050. So what’s going on? We had four influential banks expressing confidence in the popular benchmark a few months earlier. Their analysts originally projected total returns with reinvested dividends between 5%-10% in the present 12-month period. Now, however, with the S&P 500 only expected to finish between 2000-2050, these banks see the index offering a paltry 0%-2%. Another way some have phrased it? Excluding dividends, there is “zero upside.” Here is yet another “4 for 4” that makes a number of analysts uncomfortable. Year-over-year quarterly earnings have fallen four consecutive times. That has not happened since the Great Recession. And revenue? Corporations have put forward year-over-year declines in sales growth for five consecutive quarters. That hasn’t happened since the Great Recession either. The bullish investor case is that the trend is going to start reversing itself in the 2nd half of 2016. However, forward estimates of earnings growth and revenue growth are routinely lowered so that two-thirds or more companies can surpass “expectations.” And it is not unusual for estimates to be lowered by 10%. Take Q1. Shortly before the start of the year, Q1 estimates had been forecast to come in at a mild gain. Today? We’re looking at -9% or worse for Q1. Over the previous five years, Forward P/Es averaged 14.5. They now average 16.5 on earning estimates that will never be realized. In essence, S&P 500 stock prices are sitting a softball’s throw away from an all-time record (2130), while the forward P/E valuations sit at bull market extremes that do not justify additional appreciation in price. And what about earnings quality? Wall Street typically presents two kinds: Generally Accepted Accounting Principles (GAAP) earnings and non-GAAP earnings that excludes special items, non-recurring expenses and a wide variety on “one-time charges.” The foolishness of non-GAAP presentations notwithstanding, one might disregard the manipulation when non-GAAP and GAAP are within the usual 10% range. This was more or less the case between 2009 and 2013. By 2014, however, the gap between the two different earnings per share reports began to widen. By 2015, “manipulated” pro forma ex-items earnings exceeded actual earnings per share by roughly $250 billion, or 32%. Can you spell c-h-i-c-a-n-e-r-y? Of particular interest, there was a similar disconnect between GAAP and non-GAAP in 2007. Non-GAAP in the year when the last bear market began (10/07) was 24% higher than GAAP earnings per share. It follows that the discrepancy today in earnings quality is even wider than it was prior to the stock market collapse. “But Gary,” you protest. “As long as the Federal Reserve and central banks are exceptionally accommodating, stocks should excel.” In truth, however, the long-term relationship between the SPDR S&P 500 Trust ETF (NYSEARCA: SPY ) and the Vanguard Total Bond Market ETF (NYSEARCA: BND ) demonstrate that the bond component of one’s portfolio has been more productive over the last 12 months than the stock component. Bulls can point to the market’s eventual ability to shake off the euro-zone crisis of 2011. That was the last time that the SPY:BND price ratio struggled for an extended length of time. Back then, however, the Federal Reserve offered two aggressive easing policies – “Operation Twist” and “QE 3.” Today? Stocks are not only extremely overvalued on most historical measures, but the Fed has only lowered its tightening guidance from four hikes down to two hikes. Is that really enough ammunition to power stocks to remarkable new heights? “Okay,” you acknowledge. “But rates are so low, they are even lower than they were in 2013. And that means, going forward, there is no alternative to stocks.” Not only does history dispel the myth that there are no alternatives to stocks , but many corporations that have been buying back their stocks at attractive borrowing costs are now at risk of debt downgrades, higher interest expenses and even default. For example, the moving 12-month sum of Moody’s debt downgrades hopped from 32 a year ago to 61 in March of 2016. Meanwhile, the longer-term trend for the widening of credit spreads between investment grade treasuries in the iShares 7-10 Year Treasury Bond ETF (NYSEARCA: IEF ) and high yield bonds in the iShares iBoxx $ High Yield Corporate Bond ETF (NYSEARCA: HYG ) suggest that the corporate debt binge may soon come to an ignominious end. Foreign stocks, emerging market stocks as well as high yield bonds all hit their cyclical tops in mid-2014, when the credit spreads were remarkably narrow. The IEF:HYG price ratio spikes and breakdowns notwithstanding, the general trend for 18-plus months has been less favorable to lower-rated corporate borrowers. The implication? With corporate credit conditions worsening at the fastest pace since the financial crisis , companies may be forced to slow or abandon stock share buybacks. What group of buyers will pick up the slack when valuation extremes meet fewer stock buybacks? Click here for Gary’s latest podcast. Disclosure: Gary Gordon, MS, CFP is the president of Pacific Park Financial, Inc., a Registered Investment Adviser with the SEC. Gary Gordon, Pacific Park Financial, Inc, and/or its clients may hold positions in the ETFs, mutual funds, and/or any investment asset mentioned above. The commentary does not constitute individualized investment advice. The opinions offered herein are not personalized recommendations to buy, sell or hold securities. At times, issuers of exchange-traded products compensate Pacific Park Financial, Inc. or its subsidiaries for advertising at the ETF Expert web site. ETF Expert content is created independently of any advertising relationships.

REITs Provide A Surprisingly Big Head Start Over Real Estate Direct Investment

If you’ve decided you want to allocate some of your savings to real estate, you may want to compare the merits of publicly listed REITs, like BlackRock’s REIT ETF (NYSEARCA: IYR ), versus investing in buildings directly through private investment partnerships. 1 The many individual benefits of REITs add up to a surprisingly big head start over private investment vehicles. While discerning private investors should be able to identify individual properties with higher returns than the average REIT-owned property, they need to generate returns about 4% higher just to catch up with the efficiencies of REITs. As detailed in the table below, this 4% comes from four main sources: higher costs, higher taxes, less diversification and lower liquidity of private investments. This 4% hurdle translates into an 8% hurdle for return on equity when the property investment is 50% leveraged with debt. 2 A major worry of REIT investors is that it’s impractical to analyze all of the REIT’s individual holdings, resulting in the risk of buying real estate at a substantial premium to fair Net Asset Value [NAV]. Unfortunately, US REITs are not required to give an estimate of their NAV and so we have to rely on several specialist research companies to make those estimates. As you can see in the chart below, over the past 25 years, REITs have averaged a 4% premium to NAV, within a wide range of a 45% discount in 2009 to a 35% premium in 1997. Given the enormity of the task of valuing thousands of properties without specific, inside details about each property, we shouldn’t expect these third party NAV estimates to be very accurate. Indeed, it appears that the divergences may be exaggerated by the NAV estimates lagging public market price moves. Making a simple adjustment for this lag reduces the volatility of the divergence from NAV by about 40%, and brings the average to a 1% premium, as shown by the black bars. I didn’t list this as a cost or benefit of REITs vs. private holdings, because, depending on timing, this could reduce or enhance returns. To flesh out a plausible negative scenario, let’s assume an investor bought REITs at a 10% premium and sold them 15 years later a 10% discount. That would cut the REIT head start of 4% a year down by only about 15%, in terms of the required return on the underlying unleveraged property investment. The return reduction could turn out to be even less than that, because when REITs trade at a premium to NAV, it is possible for them to add to their property portfolios by issuing shares to private sellers, and thus the premium to NAV can come down without harming returns. I’d be remiss if I didn’t list any benefits of holding property directly. Some argue that illiquidity can be a blessing in disguise, forcing investors to hold for the long term. Ignorance of daily price fluctuations may make the private investing experience more blissful too. Indeed, it may be that many large fortunes have arisen from people feeling ‘locked’ in to the companies they built or the properties they bought. Property investors also derive comfort and psychic value from the tangibility of their property investments, and the ability to touch and see their investments may make their investments feel less risky than more abstract and indirect holdings through REIT ETFs. Finally, while REITs may be the dominant structure for delivering passive real estate exposure 3 , private capital may remain the preferred structure for certain activities such as development and aggregation, even if ultimately for sale to REITs. The benefits of REITs are already well known. Investors have been enthusiastically voting for REITs with their investment dollars for a long time, bringing the value of REITs close to $1 trillion. REITs currently own about 1/8 of commercial real estate in the US, up from less than 1% in 1990. 4 REITs are on track to own over 50% of all US commercial real estate by 2040 even if these trends slow down by half. I hope this note has been helpful in cataloguing and attempting to quantify the relative merits of REIT vs. private ownership, summing up to a 4% hurdle that privately owned properties need to exceed relative to REITs. At Elm Partners, we use REIT ETFs, particularly Vanguard’s (NYSEARCA: VNQ ), for property exposure in our globally diversified portfolios. In a future note, I’ll address the more fundamental question of the long-term expected return of real estate given today’s valuation levels. Table: Comparison of REIT vs. private real estate investing 0.7% Avoiding transactions costs . Typically, when buying a building, an investor will incur about 5% as brokerage, legal, transfer tax and other fees, and loan arrangement fees of 2%, which together equate to about 0.6% pa over the 15-year investment horizon we assume throughout this analysis. 5 When investing in a REIT, these costs have already been paid. 0.5% REITs typically have lower borrowing costs. I assume REITs can borrow about 1% more cheaply from banks than private borrowers on individual properties. 0.9% REITs generally benefit from lower management costs due to economies of scale, and lack of carried interest. This calculation assumes REITs have 0.5% lower management fees and no 15% carried interest. The cost savings can be much higher in the case of small properties managed by the investor, if the investor were to accurately bill himself for the value of his time. 0.6% Tax savings will vary depending on the characteristics of the investor and the site of the property. One benefit of ownership through a REIT is that income that is passed out as dividends are not subject to state (or city) tax, in most states. For high tax sites, like NY or CA, this can amount to a tax saving of 10% of income, assuming that the ultimate investor is in a low or no tax state. REITs allow for longer-term holding than private investments, as the manager usually has an incentive to realize gains to be paid his incentive fee. A further potential saving is that private ownership structures usually throw off miscellaneous itemized deductions which many high rate US taxpayers cannot deduct. 6 For non-US investors, the tax savings of REITs over direct investments might be 0.8% greater. 7 1.0% Substantial diversification is provided by REIT ETFs, such as SCHH and RWR , which hold over 100 individual equity REITs. These REITs in turn provide ownership in thousands of properties in different locations and of different types, many of them large properties in prime locations that would be hard for most investors to access through private ownership. I estimate this effect perhaps over-simplistically by assuming a private portfolio will be 25% riskier than a diversified REIT ETF, and so the investor would need to get 25% more return for bearing that risk. 0.5% Liquidity : REITs are liquid. Private property takes time to transact, and the decisions to buy or sell may depend on the desires and personal circumstances of the manager of the property or other investors in the private deal. REITs are easily marginable, which allows investors to efficiently raise temporary liquidity. Listed options markets that have developed around REITs give investors even greater flexibility. An overview of the academic literature on pricing illiquidity [link prompts PDF download; see page 27 especially] by A Damodaran of NYU suggests a number much higher than 0.5%, but I am sympathetic to the notion that liquidity is valuable but overpriced by the market. 4.2% Total Head Start of REITs vs. Private Ownership Click to enlarge Notes 1 In this note, I am using the term REIT to refer to publicly traded equity Real Estate Investment Trusts in the US. There are other types of REITs and also there is a large and growing non-US REIT market. 3 REITs are one of the most indexed of all market segments, with Vanguard, BlackRock and StateStreet owning about 30% of the large REITs, twice the ownership level in other large US equities, mostly for their index broad market and REIT index offerings. StateStreet recently created a new sector fund just for real estate, XLRE. Expense ratios for REIT ETFs range from 0.07% for Schwab’s to 0.43% for iShares. 4 Size of US commercial real estate market according to this study was $10T in 2009, which I assume has grown to $12T today. Size of REIT market cap and leverage ratio from reit.com . REIT market ownership from 1991 based on the rate of growth of market cap of REITs being 22% and the NAREIT REIT price index growing at 4.7% pa over the period. 5 Further assumptions are 5% initial property yield, growing 2% a year, and leverage of 50% at a rate of 4%. 6 For this calculation, I assumed 5% lower tax rates and that 33% of management expenses are non-deductible for the private investor. 7 Investing through a REIT ETF such as IDUP LN can eliminate capital gains tax, reduce the income tax rate by over half to 15% and eliminate the drag of non-deductible miscellaneous itemized deductions. This should not be taken as tax advice. Acknowledgments Thanks to Chip Parkhurst, who did much of the research for this note as a summer intern at Elm Partners; my friend Larry Hilibrand, for invaluable help from start to finish; and my colleagues at Elm Partners. Disclosure: I am/we are long VNQ, IYR, VNQI. 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.