With volatility having soared lately and nobody really knowing what’s coming – we’ve seen that the market can go both up and down with considerable ferocity, but don’t know which kind of days will occur more frequently – hedging is likely to loom larger as a vital topic.
I’ve recently written about using triple short ETFs to hedge an income portfolio and described some ETFs that go long one asset class and go short another. These are basic, straightforward approaches. The former is a do-it-yourself strategy; with the latter, you know exactly what the funds are doing (the long and short exposures are permanent) and need only compare prospects for two asset classes.
But what about the fancy new breed of ETFs that shift asset classes based on proprietary quantitative algorithms (i.e., they aren’t disclosing details of how they make their allocations and even if they did, most investors probably wouldn’t understand the math)? This may become an important topic: If the market remains traumatic, expect the marketing and PR departments of the firms that sponsor hedge-oriented ETFs to kick their efforts into high gear.
It’s easy to locate hedged ETFs. In StockScreen123, I screened for ETFs whose “method” is classified as “hedged.” Table 1 lists the results as of this writing, sorted from best to worst by price performance over the past month. For comparative purposes, I also inserted the ETFs designed to track the S&P 500 and Russell 2000.
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The ETFs whose names begin with 2x are the ones I discussed in my August 4 article.
To give you an idea of things you can think about if or when you look at these ETFs, I’m going to focus on two from a firm called IndexIQ; IQ Hedge Macro Tracker (NYSEARCA:MCRO) and IQ Hedge Multi strategy Tracker (NYSEARCA:QAI). MCRO looks to replicate the performance of hedge funds pursuing macro strategies (attempts to profit from changes in global economic developments) and emerging markets strategies. QAI looks to replicate what I’ll call the kitchen sink: “The return characteristics of hedge funds using multiple hedge fund investment styles, including long/short equity, global macro, market neutral, event-driven, fixed income arbitrage, and emerging markets.” There’s another one on the list from IndexIQ but it, like some others on the list, leans toward resources. I’d rather look at MCRO and QAI since they more clearly illustrate the impact of hedging algorithms as opposed to resources bets that are sometimes right and sometimes wrong.
The IndexIQ funds are known for their efforts to deliver hedge fund-like returns without hedge fund-like baggage (very high fees, illiquidity, lack of transparency, inaccessibility to the average investors, etc.). They do this by studying well-established indexes of hedge fund performance and then by selecting a diversified set of ETFs whose combined performance characteristics seem most likely to replicate the indexes. Needless to say, and understandably, IndexIQ is very tight-lipped about the details of how it goes about doing this. But to me, the task it's taking on seems daunting, since it would seem that much would depend on hedge fund portfolios remaining pretty much in character over time: If there are significant shifts, it might turn out that an ETF collection which replicated past performance might not do likewise in the future. I presume IndexIQ uses statistical techniques that go beyond what any of us could accomplish by downloading ETF price data, hedge fund index data, and running it all through Excel’s multiple regression tools. But we have no way of saying that because the IndexIQ “secret sauce” is just that: Secret.
So ultimately, all a prospective investor can do is examine the performance of the ETFs and make judgments based on that. Let’s give it a shot.
For starters, we want to see if these hedge-like funds can adequately protect us from the ravages of the downturns we’ve been seeing. Admittedly, this is a small -- minuscule, in fact -- sample. But it’s an important one. If your house burns down, you expect to collect on your fire insurance policy. You absolutely, positively will not tolerate a response like, “We’ve paid in due course every day for the past 10 years, except for the day when you had your fire, when we had to temporarily suspend operations. So we regret to inform you we won’t be making any payment.” You can’t automatically ignore tiny samples. It depends how tied they are to the conditions being studied.
Figures 1 and 2 show how MCRO and QAI respectively fared relative to the S&P 500 during the recent market tailspin. These charts are from Yahoo Finance.
Figure 1 – MCRO, One-Year Price Trend
Figure 2 - QAI, One-Year Price Trend
Actually, those results are pretty good. The mild declines experienced in the most recent days are about as satisfying as most mainstream investors (i.e. non short-sellers) could reasonably have expected. So our initial impression should be quite favorable.
But what about non-crisis periods? Consistent with their mixed-asset characteristics, both funds have heavy exposure to fixed income. As of June 30, QAI was 64.5% invested in fixed income ETFs and it was essentially the same as of Aug. 9. At June 30, MCRO’s fixed-income exposure was less, but a still substantial 47.2%, and it increased modestly to 51.2% by Aug. 9.
Heavy fixed-income exposure has certainly been a blessing lately. But how did the funds come to be so heavily exposed to fixed income? Was it a successful tactical decision? In other words, are they normally more equity heavy (U.S. and/or elsewhere) with the models having beefed up in fixed income at the right time? Or is heavy fixed income exposure a normal feature of these portfolios and likely to remain so in all market circumstances? These are important questions. As much as we appreciate the downside protection, we need to consider how much upside we’re giving away during good periods. We know we have to give up some gains. Hedging is about reducing volatility and that necessarily entails sacrificing return. The question is: How much positive return do we have to forego?
These are not easy questions to answer since the funds haven’t been around long. Here are longer price histories for both.
Figure 3 – MCRO, Two-Year Price History
Figure 4 – QAI, Two-Year Price History
The visuals provide some sense of full performance. You can get numbers from the IndexIQ website. There, you’ll see that total return for MCRO between its June 9, 2009 inception and July 31 was 7.04%. That’s an annualized return of about 3.3%. For QAI, total return from its March 25, 2009 inception was 6.27%, or an annualized return of about 2.6%.
Are those numbers good? In one sense, they seem to be reasonable. Risk was dramatically reduced and these returns are a heck of a lot better than what many investors have been getting from CDs and high-quality fixed-income funds.
But does the inquiry end there? We understand the risk-reward characteristics we’re seeing reflect a decision to diversify beyond U.S. equities. But how much additional “benefit” are we getting from the proprietary hedge-fund replication protocols used by IndexIQ that determine their specific diversification decisions?
For purposes of benchmarking, I established a naïve ETF screen on StockScreen123 that gives me a “permanent” list of just two funds: The S&P 500 SPDR (NYSEARCA:SPY) and the iShares Barclay 20+ Year Treasury ETF (NYSEARCA:TLT). Figure 5 shows the result of a backtest of the strategy assuming I rebalance every four weeks to bring SPY and TLT to equal portions of the portfolio.
Numerically, my simple strategy gained 25.5% through Aug. 9, meaning unlike the index IQ numbers, my results include the impact of the recent tailspin. That works out to an annual rate of 12.0%.
Figure 6 shows how the strategy would have performed longer term, from March 31, 2001.
Numerically, that was a gain of 71.9%, or an annual rate of 5.4%. Bear in mind that my strategy does not include returns from dividends; those are included in the IndexIQ numbers.
Depending on where you trade, commission may be an issue. Interestingly, though, if you rebalance once per year instead of once every four weeks, the returns are little changed (the winning positions are allowed to run longer, which can help in trending markets). From March 31, 2001 through Aug. 9, the total gain improved a bit to 79.2%. Over the past two years, the total gain was 23.6%, modestly lower reflecting less market trending.
Figure 7 shows an IndexIQ presentation of data for five years ending Sept. 30, 2008 showing returns for the indexes IndexIQ aims to have its ETFs track. The chart is not specifically labeled as being through Sept. 30, 2008, but I am able to infer that based on matching data in another, clearly labeled, chart it does provide.
Meanwhile, for the five years ending Sept. 30, 2008, my naïve 50-50 SPY-TLT strategy (assuming positions are re-weighted to 50% just once per year) delivered an annual price return (i.e. not counting dividends) of 6.0%.
Bear in mind that my strategy is spectacularly naïve. I used TLT for the fixed-income vehicle because it was the first such ticker to come to mind. I likewise did not investigate the pros or cons of other U.S. equity vehicles, global equities, or a more broadly diversified collection of ETF-based asset-class exposure, nor did I attempt to develop any rules that would lead me to emphasize or downplay certain ETFs based on conditions, nor did I work, here, with short or leveraged ETFs.
Hedged ETFs remain a very young category. On the surface they seem to deliver in terms of downside protection in times of market crisis. But be careful. It looks like these IndexIQ funds delivered recently not because of the merits of their models but instead based on the general wisdom of asset-class diversification, something you could very easily implement on your own. Splitting your assets 50-50 between SPY and TLT is not going to get you on TV, it’s not going to get you invited to speak at conferences, it’s not going to get you interviewed, it’s not going to get you tenured if you’re a professor, and it’s not going to incite backers to pound on your door looking to team up building an asset management shop or an indexing boutique. But so far, it looks like it may do more for your brokerage account than what you can get from following the rocket scientists.
By the way, I almost feel guilty about having picked on IndexIQ. I was most interested in looking closely at it because hedge funds and hedge-fund replication has been such a hot topic, and perhaps a bit because of the hoops it made me jump through to get the “White Paper,” which I couldn’t have gotten at all had I not actually been a registered investment advisor. To register on its site, I had to use my e-mail address at the asset management firm with which I’m affiliated; you can’t register with a regular yahoo.com, gmail.com or aol.com address. Even so, I have to acknowledge that the IndexIQ funds look better than many others in the so-far less-impressive-than-it-seems category.
Disclosure: I have no positions in any stocks mentioned, and no plans to initiate any positions within the next 72 hours.