Tag Archives: asset

The Limits Of Risky Asset Diversification

Do you want to reduce the volatility of your asset portfolio? I have the solution for you. Buy bonds and hold some cash. Now once upon a time, in ancient times, prior to the Nixon Era, no one hedged, and no one looked for alternative investments. Those buying stocks stuck to well-financed “blue chip” companies. The diversification from investor behavior is largely gone (the liability side of correlation). Spread your exposures, and do it intelligently, such that the eggs are in baskets are different as they can be, without neglecting the effort to buy attractive assets. But beyond that, hold dry powder. Think of cash, which doesn’t earn much or lose much. Think of some longer high quality bonds that do well when things are bad, like long treasuries. Photo Credit: Baynham Goredema . When things are crowded, how much freedom to move do you have? Stock diversification is overrated. Alternatives are more overrated. High quality bonds are underrated. This post was triggered by a guy from the UK who sent me an infographic on reducing risk that I thought was mediocre at best. First, I don’t like infographics or video. I want to learn things quickly. Give me well-written text to read. A picture is worth maybe fifty words, not a thousand, when it comes to business writing, perhaps excluding some well-designed graphs. Here’s the problem. Do you want to reduce the volatility of your asset portfolio? I have the solution for you. Buy bonds and hold some cash. And some say to me, “Wait, I want my money to work hard. Can’t you find investments that offer a higher return that diversify my portfolio of stocks and other risky assets?” In a word the answer is “no,” though some will tell you otherwise. Now once upon a time, in ancient times, prior to the Nixon Era, no one hedged, and no one looked for alternative investments. Those buying stocks stuck to well-financed “blue chip” companies. Some clever people realized that they could take risk in other areas, and so they broadened their stock exposure to include: Growth stocks Midcap stocks (value & growth) Small cap stocks (value & growth) REITs and other income passthrough vehicles (BDCs, Royalty Trusts, MLPs, etc.) Developed International stocks (of all kinds) Emerging Market stocks Frontier Market stocks And more… And initially, it worked. There was significant diversification until… the new asset subclasses were crowded with institutional money seeking the same things as the original diversifiers. Now, was there no diversification left? Not much. The diversification from investor behavior is largely gone (the liability side of correlation). Different sectors of the global economy don’t move in perfect lockstep, so natively the return drivers of the assets are 60-90% correlated (the asset side of correlation, think of how the cost of capital moves in a correlated way across companies). Yes, there are a few nooks and crannies that are neglected, like Russia and Brazil, industries that are deeply out of favor like gold, oil E&P, coal, mining, etc., but you have to hold your nose and take reputational risk to buy them. How many institutional investors want to take a 25% chance of losing a lot of clients by failing unconventionally? Why do I hear crickets? Hmm… Well, the game wasn’t up yet, and those that pursued diversification pursued alternatives, and they bought: Timberland Real Estate Private Equity Collateralized debt obligations of many flavors Junk bonds Distressed Debt Merger Arbitrage Convertible Arbitrage Other types of arbitrage Commodities Off-the-beaten track bonds and derivatives, both long and short And more… one that stunned me during the last bubble was leverage nonprime commercial paper. Well guess what? Much the same thing happened here has happened with non-“blue chip” stocks. Initially, it worked. There was significant diversification until… the new asset subclasses were crowded with institutional money seeking the same things as the original diversifiers. Now, was there no diversification left? Some, but less. Not everyone was willing to do all of these. The diversification from investor behavior was reduced (the liability side of correlation). These don’t move in perfect lockstep, so natively the return drivers of the risky components of the assets are 60-90% correlated over the long run (the asset side of correlation, think of how the cost of capital moves in a correlated way across companies). Yes, there are some that are neglected, but you have to hold your nose and take reputational risk to buy them, or sell them short. Many of those blew up last time. How many institutional investors want to take a 25% chance of losing a lot of clients by failing unconventionally? Why do I hear crickets again? Hmm… That’s why I don’t think there is a lot to do anymore in diversifying risky assets beyond a certain point. Spread your exposures, and do it intelligently, such that the eggs are in baskets are different as they can be, without neglecting the effort to buy attractive assets. But beyond that, hold dry powder. Think of cash, which doesn’t earn much or lose much. Think of some longer high quality bonds that do well when things are bad, like long treasuries. Remember, the reward for taking business risk in general varies over time. Rewards are relatively thin now, valuations are somewhere in the 9th decile (80-90%). This isn’t a call to go nuts and sell all of your risky asset positions. That requires more knowledge than I will ever have. But it does mean having some dry powder. The amount is up to you as you evaluate your time horizon and your opportunities. Choose wisely. As for me, about 20-30% of my total assets are safe, but I have been a risk-taker most of my life. Again, choose wisely. PS – if the low volatility anomaly weren’t overfished, along with other aspects of factor investing (Smart Beta!) those might also offer some diversification. You will have to wait for those ideas to be forgotten. Wait to see a few fund closures, and a severe reduction in AUM for the leaders…

Sticking With Your Asset Allocation

By Seth J. Masters Careful analysis can help investors pre-experience the outcomes they’re likely to see with various allocation decisions. But an investment plan will work only if an investor has the emotional fortitude to stick with it. That’s easier said than done, particularly with a more aggressive portfolio, when market conditions are rough. Let’s look at the growth of $1 million in three portfolios from January 2005 through June 2015, assuming a withdrawal of $50,000 per year. In one case, the investor maintains a portfolio allocation with 80% in global stocks and 20% in municipal bonds. In the second, the investor stays in a much more conservative 30/70 portfolio. And in the third, the investor begins with 80/20, but panics after a 30% loss and switches out of stocks and into cash on November 1, 2008. He remains in cash through March 31, 2012, and returns to 80/20 thereafter. The Display below shows how each of these investors would have fared. With only 30% in stocks, the conservative investor wouldn’t have lost a great deal in the 2008 stock market slump, but neither would he have picked up much in the roaring bull market that followed. Altogether, after spending $50,000 a year, he would have ended up with $940,000 at midyear 2015 – not too bad considering his regular portfolio withdrawals. The steady 80/20 investor would have suffered a wrenching loss of 46% in the stock market slump, but she would have still wound up with the highest final portfolio value: $1,150,000, after spending outlays. The market timer who jumped into cash as the stock market was going south and returned to stocks somewhat late would have been left with only $670,000, far less than both the steady 30/70 investor and the steady 80/20 investor. Indeed, his portfolio’s ending value would have been more than 40% less than the ending value of the 80/20 investor who stuck with her allocation, although his worst drawdown was nearly as large. This illustrative case is – unfortunately – similar to what many investors actually did after 2008. Lots of investors who had flocked to global stocks in the years before the bubble burst stampeded out in 2009, 2010, and 2011, to the tune of $309 billion in outflows. It took until 2013 – by which time the global stock market had already rallied 55% – for fund flows to flip back into stocks. In market cycle after market cycle, most investors sell low and buy high. At Bernstein, we advised clients after the market slump to stick with their long-term strategic asset allocations, including their exposure to equities. One measure of the value of good investment advice, in our view, is the money saved by avoiding big mistakes. The value of that advice can be significant and quantifiable, as this example shows. Even so, there’s a deeper dimension to good investment advice that goes beyond such numbers. Planning carefully and thoroughly can create greater understanding of investment trade-offs, which leads to better life decisions. These benefits are hard to measure precisely, but nonetheless hugely valuable. The views expressed herein do not constitute research, investment advice, or trade recommendations and do not necessarily represent the views of all AB portfolio-management teams.

Tactical Asset Allocation: Beware Of Geeks Bearing Formulas

By Wesley R. Gray, Ph.D. How Should I Tactically Allocate my Assets? A lot of investors ask this question as their wealth grows and the number of financial products grows exponentially. In order to generate a response, investors pay money to professional finance geeks who often present complex formulas as a solution to the asset allocation problem. Last year, when I was asked to present a seminar on the subject at the Morningstar ETF conference , I developed a tongue-in-cheek title for it: ” Beware of Geeks Bearing Formulas .” In this short research piece, we explore this seminar in detail. Our goal as evidence-based investors, and not story-based investors, is to set the record straight on the value of complexity in the context of asset allocation. Bottom line: simple seems to be better. Defining Tactical Asset Allocation (TAA) What exactly is tactical asset allocation? I like to work backward to forward, since it helps to build the concept. Allocation (A) : Our baseline, or static allocation to assets in our universe. E.g., 50% stocks, 50% bonds, rebalanced annually. Asset (A) : Financial assets that can be traded with reasonable liquidity. A key component of being “tactical” is being liquid, which implies that hedge funds, private equity, and other asset classes with limited liquidity rights should be avoided in the context of “tactical” asset allocation. E.g. Stocks, bonds, commodities, alternatives (if liquid). Tactical (T) : Changing our baseline allocation based on some tactical rules. E.g., 50% stocks, 50% bonds -> 30% stocks, 70% bonds based on a market valuation signal . So there you have it, tactical asset allocation is tactically investing in liquid assets in order to beat a static benchmark allocation. Basic Asset Classes: There is an old investor adage that you shouldn’t put all of your eggs in one basket. For my classes, I dive into correlation mathematics to prove this point (see below), but the conceptual benefit of diversification is grounded in common sense. (click to enlarge) But how do we identify the eggs that go into our diversification basket? Meb Faber highlights in his Ivy Portfolio book, and reemphasizes in his new book Global Asset Allocation , that you don’t need to get fancy when it comes to asset class selection. One can capture the big muscle movements of the world by simply allocating across 5 asset classes: Domestic Equity = S&P 500 Total Return Index International Equity = MSCI EAFE Total Return Index Real Estate = FTSE NAREIT All Equity REITS Total Return Index Commodities = GSCI Index Fixed Income = Merrill Lynch 7-10 year Government Bond Index (click to enlarge) We label the return series as follows throughout the analysis: S&P 500 = S&P 500 Total Return Index EAFE = MSCI EAFE Total Return Index REIT = FTSE NAREIT All Equity REITS Total Return Index GSCI = GSCI Index LTR = Merrill Lynch 7-10 year Government Bond Index Common Asset Allocation Techniques We discuss five common asset allocation techniques that are commonly utilized in one form or the other by academics and/or practitioners. 1. Tangency Portfolio/ Max Sharpe Portfolio Modern portfolio theory, inspired by Markowitz ‘s work on mean-variance-analysis in the early 1950s, identified the optimal trade-off between risk and reward for a portfolio. Of course, the underlying assumptions serving as the foundation for this so-called “optimal” algorithm stretch the imagination, but the intellectual construct and concepts are rock solid. The punchline from modern portfolio theory is the so-called “tangency portfolio.” This portfolio is identified by the “x” with a vertical line through it and sits on the CAL (capital allocation line). For those of you who haven’t taken an investment management course in a while, the CAL represents all combinations of risk-free rate and the tangency portfolio. These are “optimal” portfolios because there is no possible way to achieve a higher risk/reward. The optimal allocation weights for a 100% risk investor (i.e., no allocation to risk-free bonds) are the tangency portfolio weights. (click to enlarge) The results are hypothetical results and are NOT an indicator of future results and do NOT represent returns that any investor actually attained. Indexes are unmanaged, do not reflect management or trading fees, and one cannot invest directly in an index. Additional information regarding the construction of these results is available upon request. 2. Minimum Variance Portfolio Many readers are probably familiar with minimum variance portfolios. As the name implies, minimum variance portfolio weights are identified such that the portfolio’s expected variance is minimized. We can’t get too excited over the minimum variance portfolio – being low variance doesn’t necessarily mean something is a good investment. We need to consider expected return. In a modern portfolio theory context, the minimum variance portfolio (represented by the diamond below) is actually sub-optimal and should never be used. Instead, an investor can simply hold a small portion in risk-free bonds and the tangency portfolio to achieve a result with the same risk, but higher return. (click to enlarge) The results are hypothetical results and are NOT an indicator of future results and do NOT represent returns that any investor actually attained. Indexes are unmanaged, do not reflect management or trading fees, and one cannot invest directly in an index. Additional information regarding the construction of these results is available upon request. Interestingly, even though there is no theoretical basis for its use, the minimum variance algorithm is often used in practice… 3. Risk Parity Portfolio Risk parity has been widely advocated recently, partly due to the success of the strategy’s largest proponent – Bridgewater Associates, LP. The basic concept behind risk parity is to equalize risk allocations across asset classes. For example, consider a traditional 60/40 stock/bond portfolio allocation. The “problem” with this allocation is that a large portion of the portfolio’s risk is driven by the stock allocation. Let’s say 90 percent of the risk is driven by the 60 percent allocation to stocks, and only 10 percent of portfolio’s risk is driven by the 40 percent allocation to bonds. Risk parity argues that we should allocate to stocks and bonds such that 50 percent of the portfolio’s risk is driven by the stock allocation and 50 percent is driven by the bond allocation. For example purposes, let’s say that a 50/50 risk contribution implies an 80 percent allocation to bonds and a 20 percent allocation to stocks. The figures below attempt to explain this via illustrations. Also, here’s a post that explains risk parity logistics. 4. Momentum Portfolio Momentum strategies overweight assets that have relative strength over the mid-term (e.g., 1 year) and underweight assets that have performed relatively poorly over the mid-term. This basic concept has been applied across asset classes, asset sectors, and on individual securities. As an example, the chart below shows the invested growth of high momentum portfolios and low momentum portfolios back to 1927. The data is from the French library . The historical performance of momentum strategies speaks for itself. In an asset allocation context, a momentum strategy will allocate more to relatively strong performing assets and relatively less to poor performing assets. (click to enlarge) The results are hypothetical results and are NOT an indicator of future results and do NOT represent returns that any investor actually attained. Indexes are unmanaged, do not reflect management or trading fees, and one cannot invest directly in an index. Additional information regarding the construction of these results is available upon request. 5. Simple Trend-Following Portfolios Simple moving averages represent a classic trend following strategy. The rule is simple: If the market is above the 200-day moving average rule, hold, otherwise go to cash. Wharton Professor Jeremy Siegel found that this simple technical rule outperforms a buy-and-hold approach, both in absolute terms and on a risk-adjusted basis. In general, while efforts to time the market should be viewed with skepticism, certain systematic timing strategies that have been explored in academia appear to reduce risk, without significantly impacting long-run returns. In particular, the application of simple moving average rules has been demonstrated to protect investors from large market drawdowns, which is defined as the peak-to-trough decline experienced by an investor. Siegel, in his book, “Stocks for the Long Run,” explores the effect on performance on the Dow Jones Industrial Average from 1886 to 2006, when applying a 200-day moving average rule. (click to enlarge) Red circles highlight episodes where the current market price breaks the 12-month moving average. The results are applied on the S&P 500. The results are hypothetical results and are NOT an indicator of future results and do NOT represent returns that any investor actually attained. Indexes are unmanaged, do not reflect management or trading fees, and one cannot invest directly in an index. Additional information regarding the construction of these results is available upon request. Performance of Common Techniques Let’s run a horse race on the various asset allocation strategies described above. The back test period is from 1/1979 to 12/2013. Our core 5 assets are: S&P 500 = S&P 500 Total Return Index EAFE = MSCI EAFE Total Return Index REIT = FTSE NAREIT All Equity REITS Total Return Index GSCI = GSCI Index LTR = Merrill Lynch 7-10 year Government Bond Index (prior to 6/1982, Amit Goyal Data) Our back test asset allocation strategies are: RISK_PARITY = Risk parity on core 5 asset classes, 3-year rolling windows MOM_TAA = Relative momentum on core 5 asset classes, calculated using 12-month momentum MAX_SHARPE = Tangency portfolio weights on core 5 asset classes, 3-year rolling windows (weights constrained [-1,1]) MIN_VAR = Minimum variance portfolio weights on core 5 asset classes, 3-year rolling windows EW_INDEX = Equal-weight, monthly rebalanced across core 5 asset classes EW_INDEX_MA = Equal-weight, monthly rebalanced across core 5 asset classes, with 12-month moving average rule RANDOM = ¼ random chance of moving to risk-free rate, monthly rebalanced across core 5 asset classes Results are gross of management fee and transaction costs and for illustrative purposes only. These are simulated performance results and do not reflect the returns an investor would actually achieve. All returns are total returns and include the reinvestment of distributions (e.g., dividends). Max Sharpe weights are constrained between -1 and 1. Data is from Bloomberg and publicly available sources. Summary Statistics: Benchmarks (click to enlarge) The results are hypothetical results and are NOT an indicator of future results and do NOT represent returns that any investor actually attained. Indexes are unmanaged, do not reflect management or trading fees, and one cannot invest directly in an index. Additional information regarding the construction of these results is available upon request. Over the time period, the S&P 500 and 10-Year bond exposures perform the best. It is no wonder that a 60/40 portfolio is so popular these days-the strategy cherry picks the best performing assets over the past 30+ years. Summary Statistics: Asset Allocation with Core 5 The EW_INDEX strategy and the RANDOM strategies serve as benchmarks for the tactical asset allocation models (their construction is outlined above). The results can be summarized as follows: The tangency portfolio, or “max-sharpe” method perform the worst and cannot even compete with the benchmarks. Minimum variance beats the tangency portfolio, which is ironic, given the theoretical underpinnings for the tangency portfolio. Nonetheless, the strategy, while risk-managed, does poorly on upside returns, underperforming the simply 10-Year bond CAGR. The risk parity methodology performs admirably, with strong risk-adjusted statistics and strong drawdown containment. Momentum also performs admirably, with the highest CAGR, however, the strategy has to contend with large drawdowns. The EW index with trend-following performs the best, capturing much of the upside, but preventing large drawdowns. (click to enlarge) The results are hypothetical results and are NOT an indicator of future results and do NOT represent returns that any investor actually attained. Indexes are unmanaged, do not reflect management or trading fees, and one cannot invest directly in an index. Additional information regarding the construction of these results is available upon request. Overall, risk parity, momentum and EW w/ MA look like the top performers. Summary Statistics: Asset Allocation with Core 4 As a robustness test, we run all our tests for all tactical asset allocation models with and without 10-Year Treasury Bond exposure. We do these tests because the 10-Year has been on an epic tear over the past 30 years, which makes it challenging to ascertain whether a tactical strategy is lucky or good when a system chooses a large position in Treasury Bonds. If a tactical system is robust it should work on 2 assets, 4 assets, 5 assets, or 50 assets. Again, similar to the last table, we present the summary statistics for the EW_INDEX and RANDOM, which serve as benchmark performance guidelines when fixed-income is not included as an asset class. (click to enlarge) The results are hypothetical results and are NOT an indicator of future results and do NOT represent returns that any investor actually attained. Indexes are unmanaged, do not reflect management or trading fees, and one cannot invest directly in an index. Additional information regarding the construction of these results is available upon request. The results can be summarized as follows: Risk parity completely blows up and no longer works. Clearly, the results associated with risk parity are dependent on 10-Year Treasury exposure. Minimum variance and tangency portfolios do not beat the benchmarks. Momentum squeaks out a small gain on a risk-adjusted basis relative to the benchmarks, but the edge is much lower. The EW index with trend-following performs the best, capturing much of the upside, but preventing large drawdowns. We highlight the drawdowns associated with the top-performing asset allocation systems, but exclude 10 years as an allocation choice. The only system that provides robust drawdown protection is the trend-following system. (click to enlarge) The results are hypothetical results and are NOT an indicator of future results and do NOT represent returns that any investor actually attained. Indexes are unmanaged, do not reflect management or trading fees, and one cannot invest directly in an index. Additional information regarding the construction of these results is available upon request. So Trend-Following looks to be the winner – Time To Go All-In? Based on the results over the past 30+ years, trend-following looks to be the most effective and the most robust form of tactical asset allocation… But how has the trend-following system performed since the 2008 financial crisis? Well, in a word, terribly. The chart below highlights the performance path of the EW buy & hold strategy versus the EW w/ trend-following index. (click to enlarge) The results are hypothetical results and are NOT an indicator of future results and do NOT represent returns that any investor actually attained. Indexes are unmanaged, do not reflect management or trading fees, and one cannot invest directly in an index. Additional information regarding the construction of these results is available upon request. Conclusion There is no panacea when it comes to tactical asset allocation. The evidence seems to suggest that trend-following rules are the most effective and the most robust, but as the recent 5-year run highlights, NOTHING WORKS ALL THE TIME. Original Post