Tag Archives: blue

What To Do When Your Stocks And Bonds Portfolio Reaches Minimum Volatility

Summary Investors typically increase exposure to bonds as they near retirement, hoping to reduce volatility and drawdown risk. It is very possible to reach a point where further increasing exposure to bonds will increase rather than decrease volatility. This phenomenon is more likely to occur with longer duration bond funds. Once you reach minimum volatility for a two-fund stocks and bonds portfolio, you can further reduce risk by (1) buying treasuries or (2) switching to a shorter term bond fund. There is no general result for which strategy is preferred, but (2) tends to give better returns and may be easier to implement. Expected Returns and Volatility as you Increase Bond Exposure Suppose you are implementing a basic stocks and bonds portfolio comprised of two Vanguard mutual funds: Vanguard 500 Index Fund Investor Shares (MUTF: VFINX ) and Vanguard Long-Term Bond Index Fund (MUTF: VBLTX ). Using historical data going back to Feb. 28, 1994, here is how expected returns and volatility of the VFINX/VBLTX portfolio vary with asset allocation. (click to enlarge) Here the top-right point represents 100% VFINX/0% VBLTX; the next data point is 90% VFINX/10% VBLTX; and so on until the bottom-most point, which is 0% VFINX/100% VBLTX. As you near retirement, you may increase your VBLTX allocation to reduce risk. If you go from 90% VFINX/10% VBLTX to 60% VFINX/40% VBLTX, for example, you reduce your expected returns a little (0.041% to 0.037%), while reducing volatility considerably (1.06% to 0.70%). Further increasing the VBLTX allocation reduces volatility, but only to a point. At 25.8% VFINX/74.2% VBLTX, you reach the leftmost point on the curve, and further increasing VBLTX allocation actually increases volatility while reducing expected returns. Of course, there is never a good reason to increase volatility and decrease expected returns. So looking back at the past 21.5 years, you would never have wanted to allocate more than 74.2% to VBLTX in a VFINX/VBLTX portfolio. Longer Duration Bond Funds Have Lower Critical Points The expected returns vs. volatility curve doesn’t always have a clear critical point like we saw for VFINX/VBLTX. In general, longer duration bond funds are more likely to exhibit this phenomenon. You can see this when you compare the curve for VFINX paired with VBLTX to VFINX paired with Vanguard’s short-term and intermediate-term bond funds, VBISX and VBIIX . (click to enlarge) Looking at the blue curve, VFINX/VBISX does have a minimum volatility point, but it’s at a very high VBISX allocation (4.3% VFINX/95.7% VBISX). Note however that if you’re using VFINX and VBISX you probably wouldn’t want to go higher than 90% VBISX, as doing so sacrifices considerable expected returns while reducing volatility very little (if at all). The green curve is in between the first two, with minimum volatility at 12.7% VFINX/87.3% VBIIX. I would not recommend going any higher than 80% VBIIX, though, from an expected returns/volatility standpoint. Reducing Volatility Beyond the Critical Point What do you do if you want to further reduce volatility after reaching your portfolio’s critical point? I see two reasonable options: Allocate some of your portfolio to treasuries (e.g. 10-year US treasury bonds). Swap for a shorter duration bond fund. Let’s go back to the first two-fund portfolio, VFINX/VBLTX. Suppose we’re at 25.8% VFINX/74.2% VBLTX and we recognize that we’ve reached minimum volatility. We would like to reduce volatility to one-fourth that of VFINX (the leftmost dotted line in the previous figures, at 0.298). We can’t do it with all of our assets allocated to VFINX or VBLTX. Let’s consider option (1). Allocating some of your portfolio to cash would pull the red curve down and to the left. But if you’re going to have cash, you may as well get some interest on it. So instead of cash let’s say we generate risk-free returns on whatever percentage we pull out of our VFINX/VBLTX portfolio, from investing those assets in US treasuries for example. The next figure shows the expected returns vs. volatility curves for various allocations to a risk-free investment that returns 1.5% annually. (click to enlarge) To clarify, the highest curve the same as we saw before; the next highest is 10% receiving risk-free 1.5% annual returns, and the remaining 90% split to VFINX/VBLTX in 10% increments; and so on until the lowest curve (which you can barely see), which is 90% risk-free 1.5% annual returns, and the remaining 10% split to VFINX/VBLTX in 10% increments. The first curve to extend to a volatility of 0.298 is the one with 40% allocated to the risk-free investment. For this portfolio, we would have to allocate the remaining 60% of our assets to 30% VFINX/70% VBLTX, to achieve an expected return of 0.0226% with volatility of 0.298%. Now let’s consider option (2). The next figure is the same as the last one, but with the curves for VFINX/VBIIX and VFINX/VBISX included. (click to enlarge) Interestingly, swapping VBLTX for VBISX lets us reach a volatility of 0.298 with a mean daily return slightly higher than that reached with VFINX/VBLTX and 40% risk-free. A 24.7% VFINX/75.3% VBISX portfolio has means returns of 0.0232%. A natural question is how the risk-free rate affects whether strategy (1) or (2) is better. For the Vanguard funds examined here, strategy (1) would always outperform strategy (2) if the risk-free rate was 4% or higher (i.e. rarely or never). Strategy (2) would always outperform strategy (1) if the risk-free rate was 0% (i.e. you held cash rather than treasuries). For risk-free rates between 0% and 4%, it really depends on the particular level of volatility you’re trying to achieve. Conclusions I think a lot of investors operate under the assumption that increasing exposure to bonds reduces volatility. But in fact there is often a point where further increasing exposure to bonds increases volatility and reduces expected returns. You don’t want to go past that point. To reduce volatility further than your two-fund portfolio allows, you can either allocate some of your assets to a risk-free investment, say US treasuries, or you can switch to a shorter duration bond fund. I favor the second strategy, as it tends to allow for greater expected returns and seems logistically easier to implement. More generally, I think it is very important to know where your portfolio is at in terms of the expected returns vs. volatility curve. You should have a good idea of how any potential change in asset allocation or choice of funds affects your portfolio’s characteristics.

Bluebird Bio Drug Trial Results Ding Blue-Sky Hopes

Biotech startup Bluebird Bio (BLUE) tumbled more than 20% Thursday after the company’s treatment for a genetic form of anemia produced disappointing trial results. Bluebird will present results from six studies of its lead product LentiGlobin BB305 at the American Society of Hematology conference next month, and on Thursday the abstracts of those and other presentations were released to the public. LentiGlobin deploys gene therapy to treat sickle

Portfolio Optimization With Leveraged Bond Funds

Summary Bond funds are great because they generate alpha and usually have negative correlation with stocks. Using the leveraged version of a bond fund can drastically improve portfolio optimization (i.e. produce greater expected returns for a given level of volatility). I use SPY/TLT and SPY/TMF to illustrate. SPY/TLT Portfolio Optimization Consider a two-fund portfolio optimizaton problem based on the SPDR S&P 500 ETF Trust (NYSEARCA: SPY ) and the iShares 20+ Year Treasury Bond ETF (NYSEARCA: TLT ). Often the goal is to maximize the ratio of expected returns to volatility (Sharpe ratio). I don’t like that approach, because when you maximize Sharpe ratio, you tend to get a portfolio with great risk-adjusted returns but relatively small raw returns. Instead, let’s say the goal is to choose an asset allocation that maximizes expected returns for some level of volatility that you can tolerate. A good way to do that is to look at a plot of mean vs. standard deviation of daily returns for various asset allocations. Here is that plot using SPY and TLT data going back to 2002. (click to enlarge) The red curve shows mean and standard deviation of daily portfolio gains for various asset allocations. The points represent 10% asset allocation increments. The top-right point is 100% SPY, 0% TLT; the next point is 90% SPY, 0% TLT; and so on until the bottom-most point on the other end of the curve, which is 0% SPY, 100% TLT. Suppose you want no more than three-fourths the volatility of SPY, or a standard deviation no greater than 0.93%. Looking at the graph, we want to be right around the third data point from the upper-right end of the curve. That data point represents 80% SPY, 20% TLT. This is the optimal allocation for an investor who wants to maximize returns at three-fourths the volatility of SPY. SPY/3x TLT Portfolio Optimization Let’s see how replacing TLT with a perfect 3x daily TLT fund (no expense ratio, no tracking error) affects the portfolio optimization problem. (click to enlarge) The red curve shows the same data as in the first figure, it just looks different because I had to zoom out to accommodate the SPY/3x TLT curve. Here I show asset allocations in 5% increments for the blue curve. The lowest point on the blue curve is 100% SPY, 0% 3x TLT; the next point is 95% SPY, 5% 3x TLT; and so on until the rightmost point, which is 0% SPY, 100% 3x TLT. Interestingly, increasing 3x TLT exposure from 0% reduces volatility and increases mean returns up until about 25% 3x TLT. Over the volatility range 0.884%-1.235%, you can do substantially better in terms of maximizing mean returns for a given level of volatility with SPY/3x TLT compared to SPY/TLT. Going back to the first example, at a volatility of 0.93%, or three-fourths the volatility of SPY, the best mean return you can achieve with SPY/TLT is 0.039%, with 80.1% SPY and 19.9% TLT. The best you can do with SPY/3x TLT is 0.059%, with 65.5% SPY and 34.5% 3x TLT. Daily returns of 0.059% and 0.039% correspond to CAGRs of 16.0% and 10.3%, respectively. For another interesting special case, suppose you can tolerate the volatility of SPY. With SPY/TLT, the optimal portfolio is 100% SPY and 0% TLT, with a mean daily return of 0.040%. With SPY/3x TLT, the optimal portfolio is 48.4% SPY and 51.6% 3x TLT, with a mean daily return of 0.069%. Also noteworthy is the fact that SPY/3x TLT portfolios are capable of achieving volatility greater than SPY, while SPY/TLT portfolios are not. This could be appealing to aggressive investors. A Real 3x Bond Fund: TMF So far, I’ve shown that a perfect 3x daily TLT fund would be extremely useful for portfolio optimization. The next question is whether such a fund exists, and how “perfect” it is in regard to expense ratio and tracking error. There are a few options, but I think the most relevant is the Direxion Daily 20+ Year Treasury Bull 3x Shares (NYSEARCA: TMF ). TMF was introduced on April 16, 2009, and has a net expense ratio of 0.95%. The next figure shows that indeed TMF effectively multiplies daily TLT gains by a factor of 3. The correlation between actual TMF gains and 3x TLT gains over TMF’s 6.5-year lifetime is 0.996. (click to enlarge) I realize that TMF does not attempt to track 3x TLT, but rather 3x the NYSE 20 Year Plus Treasury Bond Index (AXTWEN). But practically speaking TMF operates very much like a 3x TLT ETF. Let’s go ahead and re-examine the mean vs. standard deviation plot for SPY/TLT, SPY/3x TLT, and SPY/TMF over TMF’s lifetime. (click to enlarge) This is interesting, and slightly disappointing. As in the previous plot, we see that SPY/3x TLT achieves drastically better mean returns for particular levels of volatility compared to SPY/TLT. The orange curve for SPY/TMF is also higher than SPY/TLT, but not as much so as SPY/3x TLT. It seems that TMF’s reasonable expense ratio and tiny tracking error do detract somewhat from the optimization problem. But we still see that increasing exposure to TMF from 0% to about 20% reduces volatility and increases expected returns, and SPY/TMF does much better than SPY/TLT for those who can tolerate volatility between 0.722% and 1.022%. Leveraged Bond Funds Multiply Alpha and Beta As I’ve argued in other articles (e.g. SPY/TLT and SPXL/TMF Strategies Work Because of Positive Alpha, not Negative Correlation ), the reason bond funds compliment stocks so well is that they generate positive alpha. A bond fund with zero or negative alpha has no place in any portfolio; you would be better off using cash to adjust volatility and expected returns. Anyway, bond funds are special because they generate alpha. Ignoring tracking error and expense ratio, a leveraged version of a bond fund multiples both the alpha and beta of the underlying bond index. We can see this with TLT and TMF. Over TMF’s lifetime, their alphas are 0.061 and 0.173, and their betas are -0.492 and -1.493, respectively. TMF’s alpha is 2.84 times that of TLT’s, and its beta is 3.03 times that of TLT’s. 3x greater alpha does not immediately render 3x TLT the better choice for portfolio optimization. You have to look at the effect on both expected returns and volatility, which are both functions of alpha and beta. Suppose you can achieve the same portfolio volatility with c allocated to SPY and (1-c) to TLT, or with d allocated to SPY and (1-d) to 3x TLT. If you subtract the expected return of the SPY/TLT portfolio from the expected return of the SPY/3x TLT portfolio, you get: (d-c) E[X] + [3(1-d) – (1-c)] E[Y] where X represents the daily return of SPY, and Y the daily return of TLT. Whether this expression is positive or negative depends on d, c, E[X], and E[Y] (which can also be expressed as alpha + beta E[X]). For SPY and TLT, the expression is always positive, which means that SPY/3x TLT provides better expected returns than SPY/TLT for any level of volatility that both can achieve. Conclusions Leveraged bond funds appear to be extremely useful for portfolio optimization. In the case of SPY and TLT, we saw that using a 3x version of TLT, like TMF, allows us to: Improve expected returns for a particular level of volatility. Achieve the same volatility as SPY, but with drastically better expected returns. Take on extra volatility beyond SPY’s in pursuit of greater raw returns. In practice, TMF’s expense ratio and tracking error detract somewhat from the performance of an ideal SPY/3x TLT portfolio. But SPY/TMF still allows for substantial improvements over SPY/TLT in terms of maximizing returns for a given level of volatility.