A Look at New Asset Allocation and Hedged Equity ETFs

In May, PowerShares launched a trio of groundbreaking new products—dubbed “autonomic” funds by the PowerShares marketing pros—based on indexes from New Frontier Advisors, a Massachusetts-based quantitative research and investment consulting company that uses a methodology called Resampled Efficiency™, a patented portfolio optimization technique.

The Autonomic Growth NFA Global Asset Portfolio (PTO), the Autonomic Balanced Growth NFA Global Asset Portfolio (PAO), and the Autonomic Balanced NFA Global Asset Portfolio (PCA) are essentially prefabricated ETF portfolios that rebalance themselves every quarter according to the target allocation ratios stated in each fund’s prospectus.

The indexes underlying these “ETFs of ETFs” are compiled and calculated by New Frontier Advisors, a Massachusetts-based quantitative research and investment firm. While these new funds are all PowerShares products, ETFs from other issuers will be incorporated “if the asset exposure sought is not available through a PowerShares ETF.” The autonomic funds make good on this promise.

As of early July, the index underlying PCA, for instance, held emerging market and REIT ETFs from Vanguard and fixed-income funds from iShares, which offers the most complete range of U.S. Treasury-linked ETFs on the market. According to Robert Michaud, a managing director at New Frontier and the co-inventor of the patented portfolio optimization process, PowerShares ETFs currently account for just around 60 percent of PCA’s net assets.

The three new funds offer investors three different levels of risk, obtained by varying the ratio of equity to fixed income in each underlying portfolio. PTO, the most aggressive autonomic fund, has a target asset allocation of 90 percent equity and 10 percent fixed income. PAO has a ratio of 75 percent equity to 25 percent fixed income, and PCA is 60 percent equity and 40 percent fixed income.

The annual fee for the new autonomic funds is 0.25 percent in addition to a “proportionate share of the fees and expenses of the underlying ETFs” in which they invest. In the original prospectus materials, PowerShares estimated these additional fees would total 0.61 percent per fund per year, although this figure could change as the fund is rebalanced. The funds could be an appealing choice for investors who are looking for an off-the-shelf product that provides an instant, low-maintenance risk-adjusted portfolio. They also provide an interesting alternative to the lifecycle funds that have been available for years from the actively-managed mutual fund side.

What truly sets these new PowerShares products apart from the other “funds of funds” on the market is the New Frontier indexes on which they are built. As Robert Michaud describes it, the problem with the traditional portfolio optimization is that it is a very “literal process.” The New Frontier indexes use a more sophisticated—Michaud, who pursued a Ph.D. in Finance from UCLA acknowledges that it’s been called ‘fuzzy’—approach that takes into account uncertainty in investment information and attempts to predict how thousands of different portfolios will behave given a variety of future market conditions. The New Frontier indexes are rebalanced monthly, but trades are made only when the statistical characteristics of a different portfolio indicate that it ought to perform better than the current set of holdings.

Investors considering adding an autonomic fund need to make sure they are getting the best fund for the market sectors they want exposure to. Leaving all the decisions in the hands of PowerShares and the New Frontier algorithm may not necessarily produce that result. Some commentators have speculated that these new products are an attempt by PowerShares to breathe new life into some of its more thinly traded and poorly capitalized ETFs, such as its Dynamic Europe Portfolio (PEH), a component of the current PAO index and a fund that has only attracted about $10 million in assets since it launched a year ago.

Readers of the ETF Report will recall that Claymore shuttered around a dozen of its undercapitalized funds earlier this year, a fate that other fund sponsors certainly would like to avoid. By bundling underperforming products into all-in-one ETFs, sponsors may be hoping to give their weaker funds a boost…at investors’ expense.

130/30 Funds

Hedge funds pioneered the “130/30” strategy—a 130 percent long position combined with a 30 percent short position—in an attempt to maximize risk-adjusted returns. Now exchange-traded fund sponsors are building innovative new products around this concept.

ETF innovator First Trust—in concert with JPMorgan Chase (JPM)—has launched the Enhanced 130/30 Large Cap Index (JFT), an exchange-traded note with a long position equal to 130 percent of the value of its underlying index and a short position equal to 30 percent of the value of its underlying index.

The 130/30 strategy evolved as hedge fund managers realized that by ranking the securities within any given universe, they could improve their results by shorting the lowest-ranked third—essentially betting that it would fall in value—and taking a leveraged long position on the highest-ranked third.

The new 130/30 fund from First Trust applies this basic idea to the 2,500 largest U.S. stocks as measured by market capitalization. To compile the index, this universe is ranked by both growth and value factors—including price appreciation, sales growth, and book-to-price and cash-flow-to-price ratios. Although the full process is a bit more involved, the separate growth and value rankings are computed and then a final ranking is determined based on a sum of each security’s growth and value ranks. The stocks go through a liquidity screen and the ETF will take short positions in the lowest-ranked 30 percent. The index is rebalanced every quarter.

As an exchange-traded note, JFT is a debt instrument whose ultimate value depends not only on the fluctuations of its underlying index but also on the financial health of the issuer. The maturity date for shares of JFT is May 25, 2023, at which time a holder of the note will be entitled to $50 (the issue price) multiplied by a factor based on any increase in the underlying index.

ProShares, the fund sponsor known for its inverse and leveraged ETFs, is planning to launch a similar 130/30 fund, but its product is still in registration with the Securities and Exchange Commission.

• More on choosing the right ETF

Comments

[ETF Planet]

it looks like they have added outside funds, in PTO as of July 10th:

iShares MSCI Emerging Markets Index Fund 4.63%
Vanguard ETF Emerging Markets 4.60%

[scimitar]

I own the JFT ETN - it's down a little right now, but the performance has been great and I get access to a basic hedge fund strategy without having to do anything myself.

There's even an ETF for private equity now - I think it's PSP. Worth a look if you're in to hedge-fund-like strategies.

[Smart ETF]

New asset allocation strategy? Don’t drink the punch! There is nothing new about this asset allocation strategy or methodology; nor is this quantitative based. First, Funds of ETF’s exist, there is nothing unique about an asset allocation fund of ETF’s. Second, New Frontier Advisors, the distribution arm of Nothfield, does not use a quant model to come up with their solution. It’s built on the same platform as all the other archaic asset allocation solutions designed in the 1950’s; what you call Mean Variance Optimization (MVO), Modern Portfolio Theory (MPT), and in some cases its updated versions called Black-Litterman Model (BLM) and Arbitrage Pricing Theory APT), such as you will find in the software offered by Zyphyr Associates.

Third, the methodology of resampling was developed by Richard Michaud in 1999 and adds little, if any, value to a generic asset allocation model. It only serves to average efficient frontiers that are based on averages (maybe the fund should be called the average of averages). MVO-Resampling works in 3 steps like this:

Step 1: a) Estimate returns, risk (using standard deviation) and dependency (linear correlation) for a set of assets using historical data. b) Run a Monte Carlo simulation to create a new data set. Calculate the return, risk and the dependency of the new data set.

Step 2: Create an efficient frontier using the new inputs. (Repeat steps 2 and 3 500 times).

Step 3: Calculate the average allocations to the assets for a set of predetermined return
intervals. This is the new efficient frontier (Oh yes, slap a U.S. Patent #6,003,018 on this methodology to make it look new).

In New Frontier’s whitepaper they highlight the ‘Fallacies of Mean-Variance’, yet they still rely on it. Why put a band-aid on a broken model? The REAL NEW STUFF is called Extreme Value Theory (EVT) and firms using this methodology have significantly out-performed your average of averages model. EVT is based on Noble Prize winning concepts from this millennium (2002), not from Markowitz’s work from 1952 & 59’ (yes, 50 years ago). Phillip Anderson, another recent Nobel Laureate in Physics, states “Much of the real world is controlled as much by the “tails” of distributions as by means or averages: by the exceptional, not the mean; by the catastrophe, not the steady drip.” “We need to free ourselves from “average” thinking”. In summary, it’s better than doing nothing…….in a rising market. These models suggest you will earn 10% a year based on 80 years of historical data; the average over that time frame. Note the domestic market is down for the past 10 years; so much for being average.