Tag Archives: return

Making Sense Of Long-Term Returns

By Michael Batnick, CFA All advisers face the same challenge: How can we best help investors understand what sort of long-term returns they can rationally expect? This is an extremely important topic. It forms the basis of Social Security projections, pension estimates, and determining how much a household needs to save to retire comfortably. What’s often absent from a discussion on stock returns is the many ways in which returns can be measured. There are a lot of questions: What is the appropriate time period? Does one year make more sense than three years? What about a rolling return versus an annual return? When do we start measuring? Should we include the Great Depression or look at post World War II numbers? If you can’t see the importance of this conversation yet, it may be time for a quick reminder. Let’s go over a couple of different ways that we could measure the return of the S&P 500 Index. Remember as you’re reading this that it’s our job to make sure investors understand these nuances. Price Return vs. Total Return If you invested one dollar in the S&P 500 in 1928 (no, this was not possible at the time), it would have been worth ~$109 by the end of August 2015. If you were to measure the total return, however, that $1 jumps from $109 to $3,362! Nominal Return vs. Real Return It’s always important to account for inflation. If we do that, our $1 invested in 1928 becomes $342 in 2015. Compounding at 6.8% after inflation is still an impressive long-term return, even if it is just a tenth of what the total return looks like before inflation is accounted for. Average Return vs. Compound Return The S&P 500 (total return) has averaged nearly 12% a year since the mid-1920s, however, investors’ wealth would have compounded at just under 10%. The reason there is such a large gap between arithmetic and compound returns is because the 12% average returns are not earned in a straight line. There were years like 2008, when the index fell 37%. Once stocks lose 37%, they need to gain 58% to get back to even. As we often find ourselves explaining to the investing public, there are major differences between average annual returns and the returns of any individual year. In the chart below, you’ll notice that the average return of 7.5% (price only) was rarely seen in any one year. Only about 5% of the time did investors generate returns even close to the average. S&P 500 (Price Only) Perhaps a better way to present this data is the distribution of returns. S&P 500 Distribution of Annual Returns (Price Only) This can provide investors with a better idea of what the range of possibilities is. Expecting an average return of X% over a 20-year period is one thing, but being prepared for the outlier years and surviving them is something else entirely. And, of course, these outlier years can happen one after another. How does it change the way that you look at the world if you learned about markets during a year when they performed terribly? It’s a helpful exercise to break returns into different time periods to demonstrate the life-cycle experience an investor might have had. The chart below shows “bull” (green) and “bear” (red) market regimes throughout history. S&P 500 (Log Scale) People born in 1900 would probably count the Great Depression as the formative experience of their investing life cycle. It’s hard to imagine that living and working through it would not leave an indelible impression. Although every period in history is unique, one thing we can say with certainty is that bull and bear markets are permanent features of investing. Take a look at the returns in the table below. In the last 90 years, there were several periods of time when investors’ wealth compounded at very low rates. Pointing to average historical returns is little comfort to investors in the depths of a protracted bear market. Likewise, when markets get overextended, people tend to throw caution to the wind, learning nothing from history. Of course, we have to consider the reliability of the data itself. In an eye-opening paper published in The Journal of Investing, entitled ” The Myth of 1926: How much Do We Know about Long-Term Returns on US Stocks ?” Edward McQuarrie looks at the Center for Research in Security Prices (CRSP) database , which many argue is the gold standard for historical stock returns. He writes: “1) The CRSP time frame, which begins in 1926, excludes more than 50% of the historical record of widespread, large-scale stock trading in the United States, which goes back almost 200 years; and 2) for more than 50% of its time frame, the CRSP dataset excludes the majority of stocks trading in the United States, especially the smaller and more vulnerable enterprises. Putting these two facts together, we may say that CRSP provides comprehensive price series data for less than 20% of the total US stock trading record, aggregating across time period and type of stock.” McQuarrie shares some interesting insights about the way we think about historical stock returns. While not suggesting that the CRSP has failed in its due diligence, he makes the point that there are listing requirements that have undoubtedly omitted stocks from the database. We have seen that different starting periods and different ways of measuring returns can have significant implications for investors. So what if anything can we conclude and suggest to our clients? Here are a few things to remember: Past performance is absolutely not predictive of future results. Data can be manipulated! Sticking with an investment plan during a bad year (or a series of bad years) is what will make them successful. The results of diversification are predictable even if the results of an investment are not. Having a command of these issues and laying them out for our clients beforehand will make for a much more enlightening – and realistic – presentation. Disclaimer: Please note that the content of this site should not be construed as investment advice, nor do the opinions expressed necessarily reflect the views of CFA Institute.

A Case For Active Investment Management

Summary Investing in fundamentally strong companies. Active Management vs. Benchmarking. Potential for reduced exposure to declining markets. “The most successful investment managers generally possess three qualities: independent thought, discipline, and consistency of application” – John Train in his book The Money Masters. “It is impossible to produce superior performance unless you do something different from the majority.” – Sir John Templeton. Screening for Fundamentally Strong Companies For over 15 years I have been a multi-asset class investor, advisor and analyst. My teams over the years have managed a variety of active strategies. While different in focus, every equity based strategy incorporates fundamental investment principles. Regardless of the fad of the day or the hot company everyone is talking about, consistent performance and risk management depends on these principles. I have recently collaborated with a group of CFA charterholders to form an all-cap equity strategy from our most successful strategies with the sole purpose of generating exceptional risk adjusted returns. Below is a summary of the parameters we use. All Alpha Strategy Parameters Price to Book < 1.5 7 years of positive operating margin 3 years roe > 15% Lowest 20% of growth adjusted free cash flow multiple Companies with above average operating and net margin within their respective industry Below average debt to equity Positive cash flow ROA growing D/E declining Current ratio, gross margin, asset turnover growing Cash flow > net income Consistent earnings growth Momentum parameters Thanks to Henry Crutcher and Equities Lab for creating a great quantitative tool that enables us to generate and successfully back test the performance of our fundamental and technical based strategies for the periods we don’t have actual trading history. See the output since 1997 from the program below. Here is a list of every trade for the past 15 years. Recently passing companies: (click to enlarge) The results from the model were strong. Upon verifying the data, 13.12% annualized is accurate. I then combined it with a proprietary risk management model that helps us anticipate significant market declines and the results were even more encouraging. I nvesting in fundamentally strong companies Investing “is pursued most successfully in a simple, straightforward way.” – Brad Perry, Winning the Investment Marathon. Buy stocks of high-quality companies at good prices and continue holding them as long as the companies’ performance merits doing so. Do this consistently and the probability an investor will enjoy above average returns substantially increases. Below are brief descriptions of the investment parameters. 1. Price to Book < 1.5 As a primary measure of value, the price to book ratio is an initial screen that seeks to pass securities that have moved away from their true value due to neglect and are typically out of favor. These securities over time have proven to be successful investments. 2. 7 years of positive operating margin Consistent operating margins are a positive sign a company's underlying business is successful and seemingly sustainable. 3. 3 years roe > 15% Strong and consistent return on equity is essential. 4. Lowest 20% of growth adjusted free cash flow multiple Using price/free cash flow multiplied by 5 year growth of free cash flow is a valuation measure. 5. Companies with above average operating and net margin within their respective industry This measure helps us choose the leaders in each investment’s respective industry. 6. Below average debt to equity Because overleveraged companies are not attractive. 7. ROA growing We prefer the companies we invest in to get better at what they do over time. Additionally, we look for companies that invest internally and that return produces consistently growing ROA. Otherwise, our money is better invested elsewhere. This is a year over year measure. 8. D/E declining Efficient use of debt is important, as well as consistent retirement of debt. 9. Current ratio, gross margin, asset turnover growing Measures of liquidity, profitability and business activity. 10. Cash flow from Operations > net income This is a simple accrual accounting check to avoid companies that may be attempting to manage earnings. 11. Consistent earnings growth Earnings growth attracts attention. We again use year over year measures that help us identify companies that are poised to move. 12. Momentum parameters in the form of relative strength play an important role in our growth oriented screen. It helps identify companies with attractive price movement but remain appropriately valued. In addition, we tend to focus our attention to price movers that are within 15% of recent highs. Active Management vs. Benchmarking So I guess you now have me pegged as an active investor. I personally don’t consider myself active or passive, I consider myself a fundamentally based technical investor, meaning I buy when it makes sense and sell when things start looking uncertain. My current domestic exposure, managed with a beta weighted futures overlay on a long portfolio, is 100% hedged due to current volatile economic conditions. The exposure metric was derived by analyzing market valuations and economic indicators. It is updated monthly, which may also be considered an actively managed strategy. Regardless of my bias, active management has taken a beating over the past few years and rightfully so, in many instances, such as the “active” managers that are more concerned about underperforming than actually providing value to their clients. In other cases, active management can provide an investor peace of mind and tremendous value if the strategy is fundamentally sound and is implemented consistently. William Sharpe stated in the Arithmetic of Active Management (The Financial Analysts’ Journal Vol. 47, No. 1, January/February 1991. pp. 7-9): If “active” and “passive” management styles are defined in sensible ways, i t must be the case that 1. before costs, the return on the average actively managed dollar will equal the return on the average passively managed dollar and 2. after costs, the return on the average actively managed dollar will be less than the return on the average passively managed dollar The problem with this statement from William Sharpe is that it assumes the active manager seeks to benchmark a specific market such as large cap, small cap, etc. As a business, active managers live and die on performance against their respective benchmarks. Knowing this, many use enhanced benchmarking. Enhanced benchmarking involves an active manager investing in an essentially passive portfolio of securities that mimic a benchmark. However in addition to this passive allocation, these active managers will use derivatives or some other portable alpha to “enhance” portfolio performance in an attempt to reduce the risk of underperforming the benchmark and providing the possibility of outperforming at any random time. Additionally, active managers may also stray from their benchmark allocations by adding smaller cap and potentially higher returning securities. This is known as style drift and measured by tracking error. Oftentimes, these additional measures do not add sufficient alpha to offset higher risk and fees. These are reasons a high percentage of active managers perform poorly after fees compared to passive index investing. Potential for reduced exposure to declining markets As seen in the Business Cycle Overlay data, the potential for reduced exposure to declining markets can be substantial if executed properly. The model effectively reduces equity risk when valuations become rich and economic conditions warrant more caution. Returns from effectively managing downturns is termed the buy-and-hold equalizer. The buy-and-hold equalizer (Why Market Timing Works, Journal of Portfolio Management, Summer 1997), represents the increased leverage an active investment strategy gains by preserving capital during a market drop. The more money an investor has to invest when the market turns up, the greater the performance leverage. The following passage is from NAAIM . When properly implemented, active management strategies should lessen an investor’s exposure to declining markets, blunting the impact of bear markets and preserving capital and the majority of prior gains. Moving out of the market prior to the majority of a decline means you have more money to invest when the market heads upward. Active investment management is most effective over a full market cycle (3 to 5 years). The reality of down markets provides the rational for active management. Down markets hurt investors in a number of ways. First, the more investors lose money in a down market, the more they lose valuable time and opportunity. Over the past 70 years, the major indices spent nearly 60% of the time sitting out bear markets and then returning to earlier highs. Only about 40% of the time were real gains being made. Through the use of active management strategies, money managers seek investment approaches that moderate the volatility of the market, helping investors stay the course and benefit from the long-term gains of the market and improve risk adjusted returns. Additionally, active management offers potential benefits beyond performance. Unlike with passive approaches, active managers are not required to invest cash inflows at the time of receipt when market conditions or prices may not be conducive. They can screen for quality and use buy/ sell triggers as a means of reducing risk. While a passive manager must own everything in an index, an active managers have the freedom to look for attractive stocks across the targeted universe. Summary Active management is an effective tool if used properly. It can not only lead to larger gains, but also reduce risk. However, it is very important for investors to understand the underlying investment strategy of a particular investment regardless of whether it is active or passive. Moreover, an investor should compare the statistics of an active strategy (Total Return, Standard Deviation, Calmar Ratio, Sharpe Ratio, Information Ratio, and Tracking Error) to that of a similar passive to determine if the higher fees are producing sufficient additional gains to warrant an investment. I will follow up this article with regular investment and economic analysis specific to these strategies, highlighting passing companies and providing economic rationale for managing an investment portfolio. Follow me to stay informed.

An ETF Leveraged Pairs Strategy That ‘Works’ (But Would Still Be A Terrible Investment)

Summary In general, shorting pairs of leveraged ETFs does not generate favourable returns. An exception to this is shorting the volatility future TVIX, XIV pair, with this giving seemingly excellent returns. But this strategy is not advised, with the investor effectively selling financial catastrophe insurance. The theory The core equation describing the expected return of a leveraged ETF is as follows: Here ‘underlying return’ is simply the return on the asset the ETF leverages, anything from SPY, industry-specific equity funds, VIX futures and various commodities. λ specifies the ETF’s leverage; typically this is -1 (i.e. inverse), 2 or sometimes 3. Finally, σ is the standard deviation of the underlying return. The equation can be split into two, showing the key drivers of the return: The return on the underlying, leveraged λ times: The decay from volatility: It is the second – volatility decay – term that generates much of the criticism of leveraged ETFs. It reduces the return unless the ETF is unlevered i.e. λ = 1 or has no volatility i.e. σ = 0. Its adverse impact increases with leverage and the volatility of the underlying. The practical reason for volatility decay is the ETF’s daily rebalancing: a, say, 10% fall in the underlying, followed by a 10% rise will leave the underlying unchanged but see a leveraged ETF lose money. A leveraged ETF’s return is, however, not necessarily negative. It depends on the balance between the underlying’s return and the volatility decay factor. For example, SPY – representing the S&P 500 – has a (conservative) expected return of, say, 6% p.a. and a standard deviation of, say, 20% p.a. Plugging these numbers into the above formula gives a long-run expected return of ~8% for a 2x leveraged SPY ETF. This is well below the naïve 2 x 6% = 12% expectation, but is an improvement on the unlevered 6%. It is nevertheless at the cost of more than proportionally increased volatility. The theory applied to shorting leveraged ETF pairs Moving on to this article’s main subject, shorting pairs of leveraged ETFs. Applying the equation to shorting a pair of ETFs with leverage λ and -λ: The next step needs some algebra. Take the above equation and expand out (using Taylor’s series), neglecting any term higher than order 2 (these terms will be small in comparison). Then with λ = 2: Examining this equation shows the return will be positive for realistic pairs of leveraged ETFs: an asset’s return standard deviation (σ) will be bigger than its expected return (U). By shorting a pair of ETFs with opposite leverage and the same underlying, the return of the underlying cancels out and does not impact the strategy’s result. The strategy instead collects the (on average) losses generated by the interaction of the asset’s volatility and the daily rebalancing. In practice: Shorting UPRO and SPXU These two ETFs are designed to give 3x and -3x the compounded daily return on the S&P 500. Shorting $100k of both gives the following return chart: …equating to a stable before cost return of ~2% p.a. Unfortunately, the after cost return is ~-5%! These costs are principally the cost of borrowing the shares to short. I have UPRO costing ~5% p.a. to borrow and SPXU ~3.5% p.a. Notwithstanding the theory above, the market is efficient and has reached such by increasing borrow costs to unusually high levels. Similar results occur for all – bar one – pairs of leveraged ETFs that I have examined. In practice: Shorting TVIX and XIV The exception are a couple of volatility ETFs, TVIX and XIV. TVIX is designed to return 2x the VIX futures short term index. XIV is designed to return -1x the same index. Because the fund’s leverages are not equal and opposite, this strategy involves shorting $2 of XIV for every $1 of TVIX. It results in the following return chart, for a $100k notional investment: After costs, it yields a return of ~10% p.a. with a Sharpe ratio of ~ 2 (compared to the S&P 500’s ~ 0.5). It is also possible to leverage this strategy further; as shown it starts at -$33k TVIX and -$67k XIV, but (if you have portfolio margin) your broker may allow multiples of these amounts. The strategy works because of the exceptionally high volatility of the underlying VIX futures, together with the ETF’s relatively large tracking errors. The large drawdown in early 2012 was caused by a short squeeze on TVIX. Its price rose well above its net asset value. The short squeeze occurred because the issuing bank reached its internal risk limits in respect of VIX futures. It hence stopped creating new TVIX units, removing the normal mechanism for keeping the ETF’s price near its net asset value. Holders of this strategy may well have had their TVIX shares called at the worst possible time – the minimum of the black curve – missing out on the subsequent recovery. The key problem with this strategy is, however, its tail risk. Gains from shorting a stock are limited to 100% of its value. Losses are unlimited. A large enough single-day increase in the value of VIX could see the strategy lose more than 100% of the notional investment. In particular, if a day sees the VIX short term futures index double or more, XIV – if it functions as designed – will go to zero. But TVIX can continue to rise, generating unhedged, potentially unlimited losses for the strategy. I suspect this is the main reason that the market allows this apparent inefficiency. Executing the strategy is equivalent to selling financial catastrophe insurance. Additional disclosure: I am sometimes long / short XIV, but do not execute this strategy.