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Should REIT Investors Only Use A Buy And Hold Strategy?

Using REITs as an example I respect Brad’s expertise and experience in identifying the better choices of long-term, income-growth REITs. I have no such credentials. So I took his choices as listed in his report, and only included those where my special information could contribute. What I bring to the party is the daily updated next few months’ price range forecasts of market-makers [MMs] for over 2,500 widely-held and actively-traded equities, including hundreds of REITs. Their forecasts are derived from their hedging actions (real money bets) taken to protect firm capital required to balance buyers with sellers in filling volume block trade orders of billion-$ fund management clients who are adjusting portfolio holdings. Those forecasts are forward-looking additions to the reward/risk challenge, providing explicit downside price exposure prospects, as well as comparable upside gain potentials. Conventional risk/reward evaluations usually are based on only one forward-looking dimension: EPS and its growth potential. Everything else is drawn from history. Past P/E ratios and past price behaviors. Worse yet, the downside guess is typically a symmetrical measure (standard deviation) of price change, including upside differences from a mean value as well as downside ones. And the longer-term historical periods measured assume that neither the size of the variances nor their upside to downside balance varies over the time period. The assumption is that “risk” is static. Do today’s market prospects look like they did six months ago? Or a year ago? We also use history as a guide. But we try to make more sensible comparisons, because we have the information at hand to do so. We can look to the history we have collected live as the market has evolved daily in the past 15+ years since Y2K. We know what was being estimated by those arguably best-informed pros in the market, in terms of their stock-by-stock, day-by-day real money self-protecting actions. Real behavioral analysis of folks doing the most probable “right” things, not everyday man making errors of perception. We look to see how prices actually changed following prior forecasts that had upside-to-downside balances like those being seen today. And recognizing that today’s competitive scene continues to evolve, we limit our look back to the most recent five years, 1,261 market days. How that looks for this sample of REITs Click to enlarge This table has columns of holding periods following the date each forecast was made, increasing cumulatively up to 16 weeks of five market days. It has rows showing the annual rates of change (CAGRs) in each of the holding periods, for the forecasts counted in the #BUYS column. Those forecasts are a total in the blue 1: 1 row, so they are the average of the several REITs. The row above the blue row includes about half of the total sample, counting all forecasts where the upside prospect was twice the downside, or better. The next higher row includes only those forecasts where the upside was three times the downside. That process continues to the top row where only the forecasts that had huge positive upside balances, or had no downside at all, existed. The bottom half of the table below the blue row is just the inverse of the top half. In some ways, it is the more interesting part of the table. It shows that for these REITs the MMs pretty well identified the points in time where price problems were upcoming. It also shows that those issues would eventually recover, and at a later date probably be part of the forecasts shown in the upper half of the table. It also justifies the notion that if time is not a problem for the investor (he/she has adequate financial resources to deal with current retirement needs or sufficient time remaining before retirement to get there), then buy and hold works for them as a strategy in these cases. But if time is closing (or has closed) in on the retiree, then an active investment strategy of moving away from troubled REITs and into more favorably positioned ones can provide capital gains, along with the payout income of the alternative. It takes work and attention that is not required with B&H. But the CAGRs that can be added are not trivial. The REIT illustration has broader application Brad makes a strong case that, focused as he is on REITs, they should make up only a minor part of the investor’s portfolio. The table he uses from asset manager 7Twelve, showing year-by-year returns for various asset groups is instructive. Here is a copy of that table: Click to enlarge It has to be enlarged to be readable, but it is worth the effort. The yellow-highlighted years of best asset performance HOLLER * for attention to active asset-class portfolio management if you expect to beat the “market” average. The simple arithmetic average of the best asset gains each year was +31% and the worst averaged -14%. What typically is taken as the “market” average year was +5% simple, but the CAGR for the S&P 500 over the 15 years is about zero. *(A little Maine human: I had an Uncle who sometimes referred to advertising “written in letters large enough that you had to holler to read ’em”). Robyn Conti’s survey of investors in retirement showed that only 55% of them had over $200,000 portfolios. Of that 55, 31% had over $1 million. Some 5% admitted to less than $200,000 and the other 40% may have none. Trying to live better than social security and what a 401(k) plan may provide is pretty tough from even an 11% yield on $200,000 if it all was in REITs at the above table’s average. But as Brad makes clear to all nest featherers, we should use several baskets. Trouble is, the varied asset classes all present active-management alternatives if you have the insights. Here is how the Dow Jones stocks have fared over the past five years, based on MM forecasts: Click to enlarge Clearly, over the last five years, there have been hundreds of instances in these 30 stocks where substantial lasting capital gain advantages could be had, and as many or more where major capital calamities could be avoided. And these are the most closely watched stocks. Bigger and more frequent increments are being offered regularly elsewhere. Conclusion For many retirees, (the 31% in Robyn Conti’s survey with over $1 million portfolios and some of the 24% slightly less well-heeled), where REIT investments are concerned, buy and hold is a well-earned and satisfying strategy. But both her report and Brad Thomas’ advice open the consideration of earning more comforting resource reserves by the investor taking an active part in building and maintaining a more rapidly growing portfolio. We are particularly sensitive to the problems of those within 15 years of retirement who, by buy and holding SPY or similar market-average investment, may have lost any opportunity for growth over the last 15 years. They probably can’t afford to repeat that experience without a love for a future greeter role at the local Wal-Mart.

Protect Your Portfolio Against Risks

Uncertainty in the market is increasing, which means that investors want to insure themselves against risks. Hedging is one way to protect a portfolio against losses. Hedging with options is a popular method that has a lot of shortcomings. A market-neutral portfolio is a hedging method in which the distinguishing feature is the lack of correlation with the market. A market-neutral portfolio enables investors to make a profit when the market takes a nosedive, but this method has to be used carefully. It’s not uncommon to hear that there is a bubble forming in the market. The more a market grows, the more participants start to voice such concerns and the more convincing their arguments sound. However, aside from bubbles such as the dotcom crash in 2000 or the crisis of 2008, there are other situations that impact investors negatively. The slowdown of the Chinese economy, the crisis in Greece and the expectation of increases in interest rates are all factors of uncertainty that put pressure on the market this year. The increase in uncertainty on the market means that a lot of investors want to insure themselves against risks and retain profits made during years of rapid growth. The simplest way to protect yourself against risks is to have a cash position. This position is the least affected by risks and allows investors to take advantage of the opportunities that may present themselves if the market crashes. For example, the recent Flash Crash allowed market participants to purchase stocks of great companies at low prices. Nonetheless, cash positions have one major disadvantage – during periods of market growth, they significantly limit potential returns. Hedging is another way to insure a portfolio against risks. A hedge is a position in an instrument that serves to decrease potential losses on a position in another instrument. Hedging with options is one of the most popular ways to hedge. Options can be used to create all sorts of different hedging strategies. Let’s look at a few basic examples. Protective puts . One of the simplest hedging strategies – the purchase of put options with a strike price at the level of tolerable losses. Let’s look at a scenario in which an investor purchases a stock for $100 and in which the amount he/she is willing to lose is 15%. After purchasing a put option with a strike price of $85, the investor will ensure that the most he or she will lose is 15%. The investor is paying a premium when he/she buys put options – essentially paying for insurance against risk. Collar . The premium an investor must pay to purchase a put option can be quite large. The system of hedging a portfolio with a collar allows to decrease these risk insurance costs. In this strategy, the investor simultaneously purchases a protective put and sells an out-of-the-money call option. By selling the call option, the investor receives a premium that can cover part of the expenses for purchasing the put option. In some cases, the premium received from the sale of a call option can be higher than the premium spent for the purchase of the put option. Thus, the investor essentially gets paid for hedging their position. However, in selling the call option, the investor limits potential income from the long position. This is why the collar strategy only makes sense if the investor expects the price of stocks they purchase to not exceed the strike price of call options they sell. In spite of the popularity of these strategies, hedging with options has a number of serious disadvantages. First, the options market is too difficult to navigate for many individual investors, which is why they prefer to not trade instruments they don’t understand. Second, liquid options don’t exist for all securities, or premiums on the options can be very high. Options strategies described above help to limit losses of the portfolio. But smarter way of hedging is reducing the exposures of the portfolio to different kinds of risk. A better hedge is one that would not only cut down on potential losses, but would eliminate a portfolio’s correlation with the market and other risk factors such as sector specifics (this is relevant, for example, for the Energy sector, which dropped significantly when oil prices fell). A market-neutral portfolio is one such hedging strategy. The idea behind a market-neutral portfolio is that the investor takes a long position on a number of instruments in the portfolio, and shorts the rest. In this way, if the portfolio is put together correctly, there is an opportunity to make profits regardless of how the market behaves. The most popular example of a market-neutral portfolio strategy is pair trading, which is when an investor takes long position in one stock and shorts another (with different weights) in case of widening of spread between their prices. The expectation is that the spread will eventually be become narrower. Pair trading is quite simple in theory, but difficult to carry out in practice. In order to be implemented successfully, investors have to find the right pairs to pair trade. It is best to have more than one pair so that a potential loss on one would be covered by profits from the others. Moreover, it is necessary to determine the weights on long and short positions in each pair, since the securities can have different beta coefficients against the market. Pair trading opportunities do not come up systemically, which is why an investor has to constantly monitor pairs – not a good strategy for those who prefer to only trade occasionally. There has to be a stop-loss for each pair, since the difference between each pair may never diminish, but rather continue to increase in the future. Finally, broker commissions for short positions may make opening a short position on a security in a potential pair impossible. A much simpler implementation of the market-neutral portfolio strategy is as follows. The investor longs stocks and shorts index futures (with adjustment for the beta of the long part of the portfolio against the index). This portfolio would have a correlation with market that is close to zero because of the short part. Profits will depend on how much better than the market the long stocks perform on a risk-adjusted basis. In other words, this portfolio will allow the investor to extract the alpha of securities in the long position. With the development of ETFs, constructing such portfolios has become a lot easier. Instead of shorting futures (the price of E-mini futures does not allow investors to use them to hedge small portfolios), inverse ETFs can be used – ProShares Short S&P 500 ETF (NYSEARCA: SH ), for example. Moreover, sector risks can be hedged by using sector ETFs as hedges. An investor could profit on recent biotech plunge by hedging portfolio of best biotech stocks with iShares Nasdaq Biotechnology ETF (NASDAQ: IBB ). An important advantage of this portfolio is the fact that it does not require a large number of trades. All the investor has to do is occasionally correct the size of the position in the hedge to make sure that it doesn’t differ too much from the long position (with respect to the beta). Here is an example of a backtesting of implementation market-neutral portfolio strategy. We conduct backtesting, starting on 01/01/2008. The backtesting period’s start date was set to 01/01/2008 to include periods of both market decline and market growth. We apply simple screening to choose stocks for the portfolio. On the first step of the screening we limit the universe of 500 US companies with the largest market cap to 100 with the lowest 1-year volatility. On the second step we pick top 20 stocks by dividend yield from 100 stocks that have been chosen on previous step. This portfolio presumably should generate excess return against the market on a risk-adjusted basis. In order to make portfolio “market neutral” we should add hedge to the portfolio. As a hedge we would use short position in SPY. The proportion of assets allocated in hedge should be equal to beta of the portfolio against hedge. Then beta of the hedged portfolio would be equal to zero. In other words, hedged portfolio would be market-neutral portfolio. We would rebalance this portfolio quarterly. Rebalancing is necessary because: It insures that stocks in the portfolio match our screening criteria; It helps to adjust allocation of assets in long and short parts of the portfolio, so that the beta of hedged portfolio would be zero. Beta of the portfolio is recalculated on each rebalancing date. (click to enlarge) At the selected interval, the portfolio has an Annualized Return that is comparable to S&P 500 (NYSEARCA: SPY ). The Maximum Drawdown is much lower, while the Sharpe Ratio is higher. Of course, hedging a portfolio like this is not free. In this case, the price is that a neutral portfolio will show moderate returns during market boom periods. Investing always involves risk: the market is volatile, and this volatility is influenced by both fundamental factors and by noise. Forecasting a market drop is almost impossible, which is why it makes sense to hedge portfolios during periods of uncertainty in order to avoid significant losses. A market-neutral portfolio is a type of hedging that allows investors to limit losses and make profits in any market conditions, since the profitability of such portfolios does not depend on market shifts. But during market booms, such portfolios will be less profitable than regular ones. This is why investors with moderate risk tolerance can employ this hedging strategy periodically, when uncertainty is high.

Retirement Portfolios – Volatility, Taxes, And Risk

Summary This article refines a previously-presented method for qualifying investment portfolios as suitable for retirement. It uses simple formulas for the effect of taxes on returns and volatilities, which leads to a surprising result: an investor in a higher tax bracket can accept a lower volatility. The method also extends the previous analysis to cover more volatile portfolios, such as those trading XIV and VXX. Introduction A previous article introduced a method for comparing investment portfolios based on back-test results. It considered a recently-retired person who: – Invests an initial amount at the start of retirement, – withdraws a percentage of the initial amount each year, adjusted for inflation, and – holds a portfolio with an expected volatility and return for the duration of their retirement. The previous article showed how to make a go/no-go decision about investing in a portfolio, based on its expected after-tax annualized return, after-tax annualized volatility of returns, and historical inflation. However, back-tests provide pre-tax returns and volatilities, not after-tax figures, and the current level of inflation remains below the mean historical level. To improve the usefulness of the method, this new article shows how to decide whether to invest in a portfolio based on its expected pre-tax returns and volatilities, and based on other-than-historical inflation rates. As before, this article defines risk as a number with direct impact on the retiree, the chance of running out of money during retirement; rather than as a more abstract number, the annualized volatility of returns. A prudent retiree would first seek to reduce risk, the chance of running out of money, to a negligible level. That ensured, the retiree would next seek to increase the portfolio’s balance at the end of retirement to leave a legacy. Simulation method As in the previous article, this analysis uses a Monte Carlo simulation tool at portfoliovisualizer.com to test the risk of a portfolio with a given volatility and return. Table 1 shows the input parameters for the simulation. For each volatility shown in the table, the analysis tried various values of expected return until the simulation output showed a 99% probability of success. This means that at the preset annual withdrawal and volatility settings, 99% of Monte Carlo trials showed a positive balance at the end of retirement. In other words, the retiree did not go broke. The expected return setting that yields 99% probability of success represents the average annualized return necessary throughout retirement to reduce risk to a negligible level at the given settings for annual withdrawal and volatility. Defining negligible risk as 99% probability of success (1% risk) seems appropriate considering the severity of the consequences of running out of money. The simulation tool also provides a median end balance, the retiree’s legacy at the end of retirement in 50% of Monte Carlo trials at the given withdrawal rate and volatility settings, and at the expected return necessary for 99% probability of success at those settings. The simulator shows median end balance discounted for inflation, and therefore expressed in the same dollars as the initial invested amount at the start of retirement. This procedure yielded (volatility, return) pairs at 1% risk of going broke for withdrawing an inflation-adjusted fixed amount annually, equal to 3% of the initial amount. It also provided the median end balance at this volatility, return, and withdrawal rate. Simulation results The simulation tool provided the results in Table 2, where: “Median annual return” = (Median end balance / Initial amount)^(1/30)-1. This gives the median annual rate of return during retirement after inflation and withdrawals at the selected withdrawal rate, the selected volatility, and the rate of return required to reduce risk to 1%. Consider, for example, a portfolio with 15% volatility – similar to the historical volatility of the S&P 500 index. Suppose inflation remains near zero. Table 2 shows that a retiree would need an average annual return of 12% in this portfolio for an acceptable risk of going broke. If the portfolio in fact delivers this 12% return, year after year, then the investor will benefit from a median return after withdrawals of 9%, and the original investment of $1M will rise to a median legacy of $13M at the end of retirement. While this median performance seems more than adequate, remember that there remains a 1% chance of leaving no legacy at all. Each row in Table 2 represents a hypothetical portfolio. Each portfolio has the same 1% risk of going broke, but the portfolios with higher volatility require higher annual returns to reduce risk to that level, and as a consequence, investors benefit from higher median annual returns, and their heirs should benefit from greater legacies. An investor who chooses a higher-volatility portfolio at the same level of risk should expect to experience a jumpier account balance and to leave a greater legacy. Effect of inflation Chart 1, graphed from Table 2, shows how annual return required for 99% success probability increases with volatility. A portfolio with annual return on or above the line has acceptable risk. The lines in Chart 1 can be considered “lines of equal risk,” or in this case, “lines of 1% risk.” The difference between the two lines in Chart 1 is close to the mean historical inflation rate (4.18%). Over the range studied here, the annual return required for 99% success probability can reasonably be estimated as the zero-inflation annual return (lower line in Chart 1), plus the expected inflation rate. For simplicity, the remainder of this article assumes zero inflation, which is close to the situation today. Chart 2, also graphed from Table 2, shows how median annual return (and therefore the investor’s legacy) also increases with volatility. As explained above, each row in Table 2 gives returns for a different volatility, but all rows have the same 1% risk. Similarly, all points on the same line in Chart 2 have the same 1% risk. For these curves, annual return was selected to reduce the worst-case risk to 1% at a given volatility and withdrawal rate. Chart 2 shows that for two portfolios with equal risk, an investor leaves a larger legacy by selecting the portfolio with higher volatility, provided that it delivers the required higher return. Chart 2 also shows, like Chart 1, that the difference between the two curves is close to the mean historical inflation rate (4.18%). Over the range studied here, the median annual return with inflation can reasonably be estimated as the zero-inflation median annual return (lower line in Chart 2), plus the expected inflation rate. Required pre-tax return Until now, the analysis has not considered the effect of taxes. The required return as a function of volatility in Chart 1 must apply to after-tax returns and volatilities, because those are what affect the balance in the retiree’s account. This begs a question, what are the corresponding pre-tax volatilities and returns? Define “Rtn” as the required annual after-tax return for a given after-tax volatility (“Vol”), that is, the annual return required for 99% probability for reaching the end of a 30-year retirement, making 3% annual withdrawals, and assuming zero inflation. At a marginal tax rate “Tax,” the after-tax return: Rtn = (1-Tax)*PreRtn, where PreRtn is the pre-tax return (Equation 1). The after-tax volatility is reduced by the same ratio: Vol = (1-Tax)*PreVol, where PreVol is the pre-tax volatility (Equation 2). Equation 2 holds true for volatility because volatility is a standard deviation (“σ”), and for a random variable X and a constant m: σ(m*X) = m*σ(X). For example, at a tax rate of Tax = 50%, for a portfolio to provide an after-tax volatility of Vol = 15% and an after-tax return of Rtn = 12%, it must have a pre-tax return of PreRtn = Rtn/(1-Tax) = 24%, but it can have a pre-tax volatility as high as PreVol = Vol/(1-Tax) = 30%. Table 3 and Chart 3 show after-tax and pre-tax (volatility, return) pairs for 1% risk. The after-tax volatilities and returns come from Table 2, and the pre-tax volatilities and returns come from applying the simple equations in the preceding paragraph to the after-tax figures. Table 3 and Chart 3 provide pre-tax figures for 50% and 25% marginal tax rates: For example, in Chart 3, portfolio “K” has 45% after-tax volatility, which, from Chart 1, requires 67% after-tax return for 1% risk. With 25% tax, this corresponds to pre-tax volatility of 60% and pre-tax return of 89%. With 50% tax, this corresponds to pre-tax volatility of 90% and pre-tax return of 133%. Back-test results are pre-tax. By the way, these stratospheric volatilities and back-test returns are included here for exceptional strategies, such as those trading derivatives of derivatives (XIV and VXX). Charts 3b and 3c show an expanded view of more usual volatilities and returns. Consequently, Charts 3, 3b, and 3c provide an investor with a way to qualify a portfolio for retirement – it must fall above the line in these charts that corresponds to investors’ marginal tax bracket. If an investor used the lines in the previous article (which were after-tax lines) to qualify a portfolio based on back-tested volatility and return (which are pre-tax figures), this would have been too stringent a qualification test. In effect, the investor would have required a return above the green line in Chart 3, when a return above the yellow or red line would have sufficed. To take inflation into account, the investor needs to shift the curves in Chart 3, 3b, or 3c upward by the expected inflation rate. Chart 3b shows an expanded view of the low-volatility part of Chart 3: Chart 3c shows an expanded view of the midrange of Chart 3: Charts 3, 3b, and 3c show that at a given back-test volatility – which is a pre-tax volatility – the required back-test return – which is a pre-tax return – is lower for a higher tax rate. This non-intuitive result occurs because taxes not only reduce returns, but also reduce volatility. When an investor does poorly, so does the tax collector. Effectively, the tax collector shares the investor’s risk along with the investor’s returns. This analysis has other interesting (and perhaps non-intuitive) consequences: Consider a strategy with back-tested (pre-tax) average annual return of 25% and volatility of 40%. Row F in Table 3 shows that this has acceptable risk for an investor in the 50% tax bracket, but row H in Table 3 shows that it is too risky for an investor in the 25% tax bracket. This investor needs the tax collector to share more of the risk. Now, consider a strategy with a back-tested (pre-tax) average annual return of 20% and volatility of 40%. Rows F and H in Table 3 show that this is too risky for an investor in either tax bracket. However, if that investor keeps 25% of the retirement account in that portfolio and 75% in cash at zero return and zero volatility, the account would have a pre-tax return of 25% * 20% = 5% and a pre-tax volatility of 25% * 40% = 10%. Rows B and C in Table 3 show that this is enough return at this volatility to reduce risk to an acceptable value for an investor in either tax bracket. Discussion and conclusion Investors could use this method to qualify portfolios for retirement investments, based on back-tested returns and volatilities, and taking taxes and inflation into account. The method extends to cover unusually volatile portfolios: even those with 50% volatility can provide acceptable risk after taxes and inflation, provided they maintain acceptable returns. This opens a door toward including non-traditional portfolios – such as those trading VXX and XIV – in a prudent retiree’s account. This method is subject to the classical limitation of back-tests: they do not consistently predict future results. Most investors will want to maintain a mix of qualified portfolios, including a traditional core. Acknowledgement: The author thanks Dr. Toma Hentea for reviewing and clarifying the article. Appendix: Alternative calculations with a pseudo-Sharpe ratio Although Charts 3, 3b, and 3c provide enough information to make a go/no-go decision about investing in a portfolio, there is another method for looking at the data. Both methods reach the same decision in the same situation. For the second method, portfolio back-tests provide not only (volatility, return) pairs, but they also provide a ratio of annualized return to annualized volatility. This is similar to a Sharpe ratio, except it assumes a risk-free return of zero (close to the situation today). Table 4 and Chart 4 show the required return/volatility for 1% risk, using the data from Table 3. Chart 4 shows that the required return/volatility ratio (“pseudo-Sharpe ratio”) for 1% risk increases with volatility over the range studied. It also shows that the pseudo-Sharpe ratio required for a given portfolio (“A” through “L”) does not change with the investor’s tax situation. This follows directly from equations 1 and 2, because volatility and required return change by the same proportion when changing tax situations. Like Chart 3, Chart 4 provides an investor with a method to qualify a portfolio – its pseudo-Sharpe ratio must fall above the curve in Chart 4 for that investor’s marginal tax bracket. Chart 4b provides an expanded view of the lower-volatility part of Chart 4: Charts 4 and 4b show that at a given back-test volatility, the required back-test pseudo-Sharpe ratio for 1% risk is lower for a higher tax rate. As in Charts 3, 3b, and 3c, this occurs because the tax collector shares the investor’s risk along with the investor’s returns.