Index Strategy Trend

Index strategies can be categorized into two broad types: Passively, by replicating the market or market segments and Actively, by extracting from the market a basket of companies that can outperform the market, or to put in a more trending, popular word, the former one is referenced as named index version 1.0, and the latter as index version 2.0.

Index 1.0 is created by aggregating the whole market, or further segment it into geographical regions/countries, or into different sector/industries.

Examples include well-known ETFs such as PowerShare QQQ Trust, tracking Nasdaq 100, Dow Diamonds Trust, tracking DJIA 30, Standard & Poor’s Depository Receipts Trust (SPDR or Spider), tracking S&P 500, iShares Russell 3000 ETF, tracking Russell 3000 index, iShares MSCI Japan Index Fund, tracking MSCI Japan, Energy Select Sector SPDR Trust, tracking Energy Stocks in S&P 500.

A lot of dollars are tied to ETFs tracking index 1.0. At present, the funds based off this kind of version1.0 indexes are still quite domineering in markets. They aim to fully replicate the market passively, therefore, not only are they designed to have the identical stock component (if the number of holdings is too large to replicate, the sampling method is applied) but also to be exactly weighted as the market. There is a preponderance of evidence indicating these passively market tracking strategies beats “actively managed funds” – including both mutual funds and hedge funds, triggering and expediting more and more capital flowing from actively managed funds to ETFs.

However, are investors complacent with these pure passive investment strategies – index 1.0? Is it possible to have the market-mimicking as a framework, and then add further layers of smart-picking to yield alphas from index strategies?

About a decade ago, indexers, who constantly challenge themselves to meet their clients need, employed a “smart beta” concept or approach to emphasize the active facet of index creation. Instead of simple market value weighting scheme, they tried and constructed equal-weighted index products. The rationale to do so is two-fold: to mitigate the single-security risk and to gain upside potential in small and mid-cap stocks.

For example, the Guggenheim S&P500 Equal Weight ETF (RSP |A-74) is extremely successful, amassed an impressive $6 billion in assets and outperformed its counterpart SPY on a return basis since March 9, 2009 (290.2% versus 212.4%). (

The concept of “smart beta” is more precisely and comprehensively defined as strategies applying systematic rules on choosing, weighting and rebalancing index components, aiming to beat the market. Such an approach seeks alpha rather than simply gaining beta exposure, hence, “smart beta”. It is essentially the concept of index 2.0, too.

A pioneering firm – Sabrient LLC expressed this idea early on by stating, “Quantitative Indexing Strategies for ETF is the future”. They launched several specialty ETFs that divert from the plain vanilla market, toward an active, alpha-factor based direction. An example of these ETFs is Claymore/Sabrient Stealth ETF, tracking Sabrient Stealth Index, STH, with companies that are “flying under the radar” of Wall Street analysts, but which have displayed robust growth characteristics.

Another pioneer is Invesco with their PowerShare Series. For example, PowerShare Water Resources Portfolio, tracking the Palisades Water Index, PHO, is comprised of companies that focus on the provision of portable water, the treatment of water, and the technology and services that are directly related to water consumption. In another example, the PowerShares FTSE RAFI U.S. 1000 Index Portfolio (NYSE: PRF), which applies a fundamental weighting approach to the 1,000 largest U.S. equities, a big leap from conventional ways to weigh components based on their market capitalizations.

Another index provider, Research Affiliates LLC of Pasadena, CA, has become widely known for its fundamental indexing. Chairman Robert Arnott has observed that equally weighting, a given index of stocks historically adds about 180 bps/yr of return versus market cap weighting and fundamental weighting tacks on an additional 80 bps/yr above equal weighting.

As Index 2.0, or alpha-seeking, enhanced index strategies are gaining more and more popularity, its evolution has been progressing rapidly, too.  A wider variety of factors, derived from richer, bigger data source,  including fundamental, technical, and sentimental, transaction, satellite, supply-chain, macroeconomic data, allows index creators to extrapolate and fine-tune signal/factor from the broad market universe with huge noises,  and form subset of “top-ranked stocks” that can consistently beat the market, yet operate in a passive fashion.

Today, several quantitative firms provide such rules-based enhanced indexes (a.k.a., “active quant”). They typically focus on a smaller number of stocks (e.g., 50-100), rebalance quarterly, and often have relatively high turnover (which admittedly reduces the tax advantages of the ETF). A few examples of these quant-based ETFs are PowerShare Dynamic Large Cap Value Portfolio, PWV, launched in 2005 with a total return of 41%. PowerShares Dynamic Industrial Sector Portfolio, PRN, launched in 2006, with 20% total return. Claymore/Zacks Sector Rotation Portfolio, XRO, launched in 2006, with a total return of 31%. Claymore/Sabrient Insider Portfolio, NFO, launched in 2006, with 19% total return as of 2008.

Lastly, it’s worth noting that these smart beta ETF or indexes are not obligated to track stocks only, they can track anything like bonds, commodities, private equities, spin-offs, intellectual properties, currencies, or even virtual vehicles such as BitCoin. For example, iShares Lehman 20+ year Treasury Bond Fund, tracking Lehman Bros 20+ year, TLT; StreetTRACKS Gold Shares Trust, tracking Gold bullion price, GLD; United States Oil Fund, L. P., tracking WTI crude oil price, USO.

Some investment products are designed for hedging or betting against major market indexes. One example is the ProShares UltraShort QQQ (ticker QID), which is a “double inverse” play on the NASDAQ 100. It gains around 2% if the index falls 1%, and vice versa.


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