Low Volatility

A suite of S&P Low Volatility ETFs offering core holdings across market cap and international markets.

Low volatility as core

Contrary to fundamental investment theory, academic studies show that high volatility stocks have long underperformed low volatility stocks. This contradiction between theory and data is often referred to as "the low-volatility anomaly".*

  • If a strategy can successfully identify less volatile equities - the results should be a less volatile portfolio
  • If a strategy can capture the low volatility anomaly - the results should be a less volatile portfolio with better risk-adjusted returns
  • If a strategy is expected to outperform its benchmark in all market environments - it is not a low volatility strategy

*For a more comprehensive study of this anomaly see: Aye Soe, "The Low-Volatility Effect: A comprehensive Look" S&P Dow Jones Indices, August 2012, Baker, Bradley and Wurgler, "Benchmarks as Limits to Arbitrage: Understanding the Low Volatility Anomaly" Financial Analysts Journal, Volume 67, Number 1, Jan./Feb. 2011, Clarke, De Silva and Thorley, "Minimum-Variance Portfolio Composition" The Journal of Portfolio Management, Volume 37, Number 2, Winter 2011; Blitz and van Vliet, "The Volatility Effect: Lower Risk without Lower Return" Robeco, April 17, 2010 and Ang, Hodrick, Xing and Zhang, "The Cross-Section of Volatility and Expected Returns" Journal of Finance, Vol. LXI, No. 1, Feb. 2006.

  • Behavioral Explanations: Preference for lotteries and overconfidence
  • Structural Explanations: Leverage constrained and limits to arbitrage

Case Study: Tech Bubble

To help illustrate the potential benefits of an dynamic approach to low volatility investing, consider the Tech Bubble (late 1990s and early 2000):

  • A constrained low volatility approach, which typically tethers its allocation to a +/- percentage allocation
    within the parent index , could have been required to hold an allocation in the technology sector despite
    the fact that the sector was in the midst of a meltdown.
  • In contrast a dynamic, low volatility approach would have allocated to stocks demonstrating lower volatility rather than maintaining "market-like" exposure to a sector. Through scheduled rebalancing, allowing the strategy to shift weight across sectors to position around emerging volatility, this approach may have provided investors some downside protection when the bubble burst. While being constrained to maintaining exposure in the technology sector prior to the Tech Bubble may have seemed like a good idea, the sector's subsequent 73% cumulative decline more than erased the returns gained by many investors on the upswing.

PowerShares by Invesco and Bloomberg LP., as of Sept. 30, 2017. An unconstrained approach can result in industry or sector concentration, which may subject it to greater risk and impact by market volatility than investments with sector constraints, such as optimized minimum volatility strategies.

A portfolio of low volatility stocks may contribute to investment diversification by mitigating risk and increasing potential return for an investor's overall asset allocation.

Through a low volatility equity approach, investors could potentially limit the amount of fixed income needed to achieve certain risk levels which may be particularly beneficial during rising interest rate environments.

Dive deeper with the Low volatility: Exploring the anomaly presentation

Download Presentation

Time to dynamically rotate

Building a core holding with a dynamic, low volatility factor approach can help investors rotate in and out of sectors to address market volatility. As shown in the graph below, over the 12-month period ending Feb. 29, 2016, the methodology reduced exposure to utilities while increasing exposure to health care in times of changing market conditions through scheduled quarterly rebalancing.*

Sector Allocation Chart

Source: Bloomberg L.P.
*The S&P 500® Low Volatility Index shown above rebalances on the third Friday in Feb., May, Aug., and Nov. Investors cannot invest directly in an index.

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sectorperf: 4.03}, {x: Date.UTC(2015, 7, 31), y: 10.91, sectorperf: -6.03} ] } ,{ name: 'Industrials', type: 'area', data: [ {x: Date.UTC(2011, 3, 29), y: 7.17, sectorperf: 1.62}, {x: Date.UTC(2011, 4, 31), y: 6.97, sectorperf: -1.21}, {x: Date.UTC(2011, 5, 30), y: 5.6, sectorperf: -0.97}, {x: Date.UTC(2011, 6, 29), y: 5.27, sectorperf: -8.24}, {x: Date.UTC(2011, 7, 31), y: 6.43, sectorperf: -1.33}, {x: Date.UTC(2011, 8, 30), y: 6.25, sectorperf: -4.89}, {x: Date.UTC(2011, 9, 31), y: 6.35, sectorperf: 7.31}, {x: Date.UTC(2011, 10, 30), y: 5.35, sectorperf: 1.04}, {x: Date.UTC(2011, 11, 30), y: 5.45, sectorperf: 3.96}, {x: Date.UTC(2012, 0, 31), y: 5.68, sectorperf: 3.62}, {x: Date.UTC(2012, 1, 29), y: 5.37, sectorperf: 3.59}, {x: Date.UTC(2012, 2, 30), y: 5.4, sectorperf: 3.13}, {x: Date.UTC(2012, 3, 30), y: 5.21, sectorperf: -2.36}, {x: Date.UTC(2012, 4, 31), y: 4.42, sectorperf: -6.83}, {x: Date.UTC(2012, 5, 29), y: 4.59, sectorperf: 7.2}, {x: Date.UTC(2012, 6, 31), y: 4.68, sectorperf: 2.47}, {x: Date.UTC(2012, 7, 31), y: 3.64, sectorperf: 1.25}, {x: Date.UTC(2012, 8, 28), y: 3.59, sectorperf: 0.03}, {x: Date.UTC(2012, 9, 31), y: 3.65, sectorperf: 1.39}, {x: Date.UTC(2012, 10, 30), y: 6.38, sectorperf: -0.03}, {x: Date.UTC(2012, 11, 31), y: 6.51, sectorperf: 1.11}, {x: Date.UTC(2013, 0, 31), y: 6.25, sectorperf: 0.61}, {x: Date.UTC(2013, 1, 28), y: 8.06, sectorperf: 2.82}, {x: Date.UTC(2013, 2, 28), y: 8.15, sectorperf: 5.9}, {x: Date.UTC(2013, 3, 30), y: 8.06, sectorperf: 2.58}, {x: Date.UTC(2013, 4, 31), y: 8.58, sectorperf: 4.87}, {x: Date.UTC(2013, 5, 28), y: 8.54, sectorperf: 0.01}, {x: Date.UTC(2013, 6, 31), y: 8.77, sectorperf: 6.91}, {x: Date.UTC(2013, 7, 30), y: 13.48, sectorperf: -0.65}, {x: Date.UTC(2013, 8, 30), y: 13.78, sectorperf: 4.2}, {x: Date.UTC(2013, 9, 31), y: 13.75, sectorperf: 4.14}, {x: Date.UTC(2013, 10, 29), y: 12.84, sectorperf: 4.25}, {x: Date.UTC(2013, 11, 31), y: 13.03, sectorperf: 2.5}, {x: Date.UTC(2014, 0, 31), y: 13.02, sectorperf: -2.7}, {x: Date.UTC(2014, 1, 28), y: 13.55, sectorperf: 3.24}, {x: Date.UTC(2014, 2, 31), y: 13.33, sectorperf: 0.4}, {x: Date.UTC(2014, 3, 30), y: 13.2, sectorperf: 0.83}, {x: Date.UTC(2014, 4, 30), y: 16.61, sectorperf: 2.03}, {x: Date.UTC(2014, 5, 30), y: 16.38, sectorperf: 0.73}, {x: Date.UTC(2014, 6, 31), y: 16.4, sectorperf: -3.8}, {x: Date.UTC(2014, 7, 29), y: 13.02, sectorperf: 3.48}, {x: Date.UTC(2014, 8, 30), y: 13.09, sectorperf: -0.27}, {x: Date.UTC(2014, 9, 31), y: 13.04, sectorperf: 4.34}, {x: Date.UTC(2014, 10, 28), y: 11.97, sectorperf: 3.04}, {x: Date.UTC(2014, 11, 31), y: 12.11, sectorperf: 1.27}, {x: Date.UTC(2015, 0, 30), y: 11.85, sectorperf: -2.68}, {x: Date.UTC(2015, 1, 27), y: 11.59, sectorperf: 5.34}, {x: Date.UTC(2015, 2, 31), y: 11.6, sectorperf: -0.27}, {x: Date.UTC(2015, 3, 30), y: 11.71, sectorperf: -1.23}, {x: Date.UTC(2015, 4, 29), y: 14.11, sectorperf: 1.55}, {x: Date.UTC(2015, 5, 30), y: 14.09, sectorperf: -1.93}, {x: Date.UTC(2015, 6, 31), y: 13.81, sectorperf: 2.16}, {x: Date.UTC(2015, 7, 31), y: 14.90, sectorperf: -4.28} ] } ,{ name: 'Information technology', type: 'area', data: [ {x: Date.UTC(2011, 3, 29), y: 4.58, sectorperf: 2.05}, {x: Date.UTC(2011, 4, 31), y: 4.55, sectorperf: 1.08}, {x: Date.UTC(2011, 5, 30), y: 4.6, sectorperf: -2.81}, {x: Date.UTC(2011, 6, 29), y: 4.61, sectorperf: -2.1}, {x: Date.UTC(2011, 7, 31), y: 3.57, sectorperf: -5.53}, {x: Date.UTC(2011, 8, 30), y: 3.53, sectorperf: -3.55}, {x: Date.UTC(2011, 9, 31), y: 3.68, sectorperf: 10.72}, {x: Date.UTC(2011, 10, 30), y: 4.36, sectorperf: -0.36}, {x: Date.UTC(2011, 11, 30), y: 4.34, sectorperf: 1.39}, {x: Date.UTC(2012, 0, 31), y: 4.65, sectorperf: 6.63}, {x: Date.UTC(2012, 1, 29), y: 4.44, sectorperf: 2.8}, {x: Date.UTC(2012, 2, 30), y: 4.45, sectorperf: 2.77}, {x: Date.UTC(2012, 3, 30), y: 4.41, sectorperf: 0.1}, {x: Date.UTC(2012, 4, 31), y: 4.33, sectorperf: -5.47}, {x: Date.UTC(2012, 5, 29), y: 4.41, sectorperf: 5.13}, {x: Date.UTC(2012, 6, 31), y: 4.38, sectorperf: 0.19}, {x: Date.UTC(2012, 7, 31), y: 5.2, sectorperf: 1.93}, {x: Date.UTC(2012, 8, 28), y: 5.21, sectorperf: 1.9}, {x: Date.UTC(2012, 9, 31), y: 5.07, sectorperf: -2.87}, {x: Date.UTC(2012, 10, 30), y: 3.59, sectorperf: -0.84}, {x: Date.UTC(2012, 11, 31), y: 3.61, sectorperf: 0.47}, {x: Date.UTC(2013, 0, 31), y: 3.59, sectorperf: 4.17}, {x: Date.UTC(2013, 1, 28), y: 3.61, sectorperf: 1.69}, {x: Date.UTC(2013, 2, 28), y: 3.67, sectorperf: 6.42}, {x: Date.UTC(2013, 3, 30), y: 3.59, sectorperf: 1.63}, {x: Date.UTC(2013, 4, 31), y: 2.79, sectorperf: 0.03}, {x: Date.UTC(2013, 5, 28), y: 2.77, sectorperf: -0.27}, {x: Date.UTC(2013, 6, 31), y: 2.86, sectorperf: 7.85}, {x: Date.UTC(2013, 7, 30), y: 2.97, sectorperf: -1.05}, {x: Date.UTC(2013, 8, 30), y: 3.03, sectorperf: 4.07}, {x: Date.UTC(2013, 9, 31), y: 3.01, sectorperf: 4.06}, {x: Date.UTC(2013, 10, 29), y: 3.11, sectorperf: 5.02}, {x: Date.UTC(2013, 11, 31), y: 3.21, sectorperf: 4.31}, {x: Date.UTC(2014, 0, 31), y: 3.09, sectorperf: -5.9}, {x: Date.UTC(2014, 1, 28), y: 4.9, sectorperf: 1.91}, {x: Date.UTC(2014, 2, 31), y: 4.72, sectorperf: -1.85}, {x: Date.UTC(2014, 3, 30), y: 4.55, sectorperf: -1.72}, {x: Date.UTC(2014, 4, 30), y: 2.99, sectorperf: 0.64}, {x: Date.UTC(2014, 5, 30), y: 2.92, sectorperf: 0.15}, {x: Date.UTC(2014, 6, 31), y: 3.02, sectorperf: -0.6}, {x: Date.UTC(2014, 7, 29), y: 5.76, sectorperf: 0.08}, {x: Date.UTC(2014, 8, 30), y: 5.96, sectorperf: 2.63}, {x: Date.UTC(2014, 9, 31), y: 5.97, sectorperf: 5.28}, {x: Date.UTC(2014, 10, 28), y: 2.83, sectorperf: 3.17}, {x: Date.UTC(2014, 11, 31), y: 2.81, sectorperf: -0.76}, {x: Date.UTC(2015, 0, 30), y: 2.73, sectorperf: -3.03}, {x: Date.UTC(2015, 1, 27), y: 4.85, sectorperf: 8.67}, {x: Date.UTC(2015, 2, 31), y: 4.9, sectorperf: 0.56}, {x: Date.UTC(2015, 3, 30), y: 4.85, sectorperf: -2.81}, {x: Date.UTC(2015, 4, 29), y: 4.11, sectorperf: 2.17}, {x: Date.UTC(2015, 5, 30), y: 4.1, sectorperf: -2.06}, {x: Date.UTC(2015, 6, 31), y: 4.02, sectorperf: 2.56}, {x: Date.UTC(2015, 7, 31), y: 4.07, sectorperf: -0.91} ] } ,{ name: 'Materials', type: 'area', data: [ {x: Date.UTC(2011, 3, 29), y: 3.51, sectorperf: 1.59}, {x: Date.UTC(2011, 4, 31), y: 3.58, sectorperf: 4.07}, {x: Date.UTC(2011, 5, 30), y: 5.61, sectorperf: 0.68}, {x: Date.UTC(2011, 6, 29), y: 5.46, sectorperf: -5.19}, {x: Date.UTC(2011, 7, 31), y: 4.97, sectorperf: -3.54}, {x: Date.UTC(2011, 8, 30), y: 4.83, sectorperf: -4.92}, {x: Date.UTC(2011, 9, 31), y: 4.9, sectorperf: 7.17}, {x: Date.UTC(2011, 10, 30), y: 1.69, sectorperf: 1.66}, {x: Date.UTC(2011, 11, 30), y: 1.73, sectorperf: 4.08}, {x: Date.UTC(2012, 0, 31), y: 1.81, sectorperf: 4.18}, {x: Date.UTC(2012, 1, 29), y: 1.73, sectorperf: 4.43}, {x: Date.UTC(2012, 2, 30), y: 1.78, sectorperf: 5.52}, {x: Date.UTC(2012, 3, 30), y: 1.87, sectorperf: 5.97}, {x: Date.UTC(2012, 4, 31), y: 2.48, sectorperf: -1.66}, {x: Date.UTC(2012, 5, 29), y: 2.51, sectorperf: 4.5}, {x: Date.UTC(2012, 6, 31), y: 2.43, sectorperf: -2.41}, {x: Date.UTC(2012, 7, 31), y: 3.24, sectorperf: 1.99}, {x: Date.UTC(2012, 8, 28), y: 3.26, sectorperf: 2.16}, {x: Date.UTC(2012, 9, 31), y: 3.35, sectorperf: 2.56}, {x: Date.UTC(2012, 10, 30), y: 2.54, sectorperf: 4.38}, {x: Date.UTC(2012, 11, 31), y: 2.56, sectorperf: -0.08}, {x: Date.UTC(2013, 0, 31), y: 2.5, sectorperf: 2.36}, {x: Date.UTC(2013, 1, 28), y: 2.61, sectorperf: 3.81}, {x: Date.UTC(2013, 2, 28), y: 2.61, sectorperf: 4.94}, {x: Date.UTC(2013, 3, 30), y: 2.46, sectorperf: -2.53}, {x: Date.UTC(2013, 4, 31), y: 2.74, sectorperf: 1.4}, {x: Date.UTC(2013, 5, 28), y: 2.7, sectorperf: -0.9}, {x: Date.UTC(2013, 6, 31), y: 2.71, sectorperf: 4.52}, {x: Date.UTC(2013, 7, 30), y: 4.1, sectorperf: -2.36}, {x: Date.UTC(2013, 8, 30), y: 4.08, sectorperf: 1.42}, {x: Date.UTC(2013, 9, 31), y: 4.06, sectorperf: 3.9}, {x: Date.UTC(2013, 10, 29), y: 7.01, sectorperf: 0.5}, {x: Date.UTC(2013, 11, 31), y: 7.18, sectorperf: 3.4}, {x: Date.UTC(2014, 0, 31), y: 7.16, sectorperf: -2.97}, {x: Date.UTC(2014, 1, 28), y: 5.05, sectorperf: 5.6}, {x: Date.UTC(2014, 2, 31), y: 4.98, sectorperf: 0.54}, {x: Date.UTC(2014, 3, 30), y: 4.97, sectorperf: 1.71}, {x: Date.UTC(2014, 4, 30), y: 8.08, sectorperf: 2}, {x: Date.UTC(2014, 5, 30), y: 8.02, sectorperf: 1.39}, {x: Date.UTC(2014, 6, 31), y: 8.14, sectorperf: -2.52}, {x: Date.UTC(2014, 7, 29), y: 7.05, sectorperf: 3.81}, {x: Date.UTC(2014, 8, 30), y: 7.41, sectorperf: 4}, {x: Date.UTC(2014, 9, 31), y: 7.04, sectorperf: -0.46}, {x: Date.UTC(2014, 10, 28), y: 4.8, sectorperf: 1.69}, {x: Date.UTC(2014, 11, 31), y: 3.77, sectorperf: 1.37}, {x: Date.UTC(2015, 0, 30), y: 3.62, sectorperf: -4.73}, {x: Date.UTC(2015, 1, 27), y: 3.74, sectorperf: 8.14}, {x: Date.UTC(2015, 2, 31), y: 3.54, sectorperf: -5.47}, {x: Date.UTC(2015, 3, 30), y: 3.63, sectorperf: 0.45}, {x: Date.UTC(2015, 4, 29), y: 2.93, sectorperf: 1.06}, {x: Date.UTC(2015, 5, 30), y: 2.83, sectorperf: -4.91}, {x: Date.UTC(2015, 6, 31), y: 2.65, sectorperf: -2.69}, {x: Date.UTC(2015, 7, 31), y: 1.87, sectorperf: -7.57} ] } ,{ name: 'Telecommunication services', type: 'area', data: [ {x: Date.UTC(2011, 3, 29), y: 3.92, sectorperf: 0.83}, {x: Date.UTC(2011, 4, 31), y: 3.94, sectorperf: 2.2}, {x: Date.UTC(2011, 5, 30), y: 3.96, sectorperf: -1.54}, {x: Date.UTC(2011, 6, 29), y: 3.79, sectorperf: -5.87}, {x: Date.UTC(2011, 7, 31), y: 3.71, sectorperf: 0.2}, {x: Date.UTC(2011, 8, 30), y: 3.67, sectorperf: -2.54}, {x: Date.UTC(2011, 9, 31), y: 3.59, sectorperf: 4.22}, {x: Date.UTC(2011, 10, 30), y: 3.79, sectorperf: 1.03}, {x: Date.UTC(2011, 11, 30), y: 3.83, sectorperf: 3.67}, {x: Date.UTC(2012, 0, 31), y: 3.78, sectorperf: -1.24}, {x: Date.UTC(2012, 1, 29), y: 3.99, sectorperf: 3.35}, {x: Date.UTC(2012, 2, 30), y: 3.86, sectorperf: 0}, {x: Date.UTC(2012, 3, 30), y: 3.91, sectorperf: 3.11}, {x: Date.UTC(2012, 4, 31), y: 4.07, sectorperf: -1.03}, {x: Date.UTC(2012, 5, 29), y: 4.11, sectorperf: 5.02}, {x: Date.UTC(2012, 6, 31), y: 4.25, sectorperf: 4.73}, {x: Date.UTC(2012, 7, 31), y: 3.92, sectorperf: -2.25}, {x: Date.UTC(2012, 8, 28), y: 3.94, sectorperf: 3.04}, {x: Date.UTC(2012, 9, 31), y: 3.75, sectorperf: -4.54}, {x: Date.UTC(2012, 10, 30), y: 2.98, sectorperf: -2.72}, {x: Date.UTC(2012, 11, 31), y: 2.98, sectorperf: -0.4}, {x: Date.UTC(2013, 0, 31), y: 2.91, sectorperf: 3.31}, {x: Date.UTC(2013, 1, 28), y: 2.66, sectorperf: -0.67}, {x: Date.UTC(2013, 2, 28), y: 2.62, sectorperf: 3.63}, {x: Date.UTC(2013, 3, 30), y: 2.69, sectorperf: 7.1}, {x: Date.UTC(2013, 4, 31), y: 1.76, sectorperf: -7.97}, {x: Date.UTC(2013, 5, 28), y: 1.8, sectorperf: 2.49}, {x: Date.UTC(2013, 6, 31), y: 1.71, sectorperf: 0.09}, {x: Date.UTC(2013, 7, 30), y: 0.98, sectorperf: -3.99}, {x: Date.UTC(2013, 8, 30), y: 0.96, sectorperf: -0.03}, {x: Date.UTC(2013, 9, 31), y: 0.98, sectorperf: 8.49}, {x: Date.UTC(2013, 10, 29), y: 0.94, sectorperf: -2.73}, {x: Date.UTC(2013, 11, 31), y: 0.93, sectorperf: -0.14}, {x: Date.UTC(2014, 0, 31), y: 0.91, sectorperf: -3.96}, {x: Date.UTC(2014, 1, 28), y: 0.95, sectorperf: -4.17}, {x: Date.UTC(2014, 2, 31), y: 1.03, sectorperf: 9.83}, {x: Date.UTC(2014, 3, 30), y: 1.03, sectorperf: 3.12}, {x: Date.UTC(2014, 4, 30), y: 0.93, sectorperf: -0.64}, {x: Date.UTC(2014, 5, 30), y: 0.91, sectorperf: -0.31}, {x: Date.UTC(2014, 6, 31), y: 0.96, sectorperf: 1.95}, {x: Date.UTC(2014, 7, 29), y: 0.95, sectorperf: -1.77}, {x: Date.UTC(2014, 8, 30), y: 0.97, sectorperf: 0.8}, {x: Date.UTC(2014, 9, 31), y: 0.91, sectorperf: 0.16}, {x: Date.UTC(2014, 10, 28), y: 1.97, sectorperf: 1.67}, {x: Date.UTC(2014, 11, 31), y: 1.85, sectorperf: -6.29}, {x: Date.UTC(2015, 0, 30), y: 1.82, sectorperf: -0.86}, {x: Date.UTC(2015, 1, 27), y: 2.05, sectorperf: 6.55}, {x: Date.UTC(2015, 2, 31), y: 1.99, sectorperf: -3.62}, {x: Date.UTC(2015, 3, 30), y: 2.13, sectorperf: 6.24}, {x: Date.UTC(2015, 4, 29), y: 2.2, sectorperf: -1.13}, {x: Date.UTC(2015, 5, 30), y: 2.22, sectorperf: -1.37}, {x: Date.UTC(2015, 6, 31), y: 2.11, sectorperf: 0.27}, {x: Date.UTC(2015, 7, 31), y: 2.28, sectorperf: -3.11} ] } ,{ name: 'Utilities ', type: 'area', data: [ {x: Date.UTC(2011, 3, 29), y: 27.13, sectorperf: 2.87}, {x: Date.UTC(2011, 4, 31), y: 27.11, sectorperf: 2.07}, {x: Date.UTC(2011, 5, 30), y: 27.72, sectorperf: -0.49}, {x: Date.UTC(2011, 6, 29), y: 28.02, sectorperf: -1.32}, {x: Date.UTC(2011, 7, 31), y: 29.93, sectorperf: 3.18}, {x: Date.UTC(2011, 8, 30), y: 30.63, sectorperf: 0.21}, {x: Date.UTC(2011, 9, 31), y: 30.05, sectorperf: 3.86}, {x: Date.UTC(2011, 10, 30), y: 29.15, sectorperf: 1.29}, {x: Date.UTC(2011, 11, 30), y: 29.59, sectorperf: 3.77}, {x: Date.UTC(2012, 0, 31), y: 28.75, sectorperf: -3.43}, {x: Date.UTC(2012, 1, 29), y: 28.97, sectorperf: 0.8}, {x: Date.UTC(2012, 2, 30), y: 28.58, sectorperf: 1.53}, {x: Date.UTC(2012, 3, 30), y: 28.81, sectorperf: 1.82}, {x: Date.UTC(2012, 4, 31), y: 29.84, sectorperf: 0.95}, {x: Date.UTC(2012, 5, 29), y: 29.99, sectorperf: 4.01}, {x: Date.UTC(2012, 6, 31), y: 29.33, sectorperf: 2.9}, {x: Date.UTC(2012, 7, 31), y: 27.96, sectorperf: -4.17}, {x: Date.UTC(2012, 8, 28), y: 27.86, sectorperf: 1.46}, {x: Date.UTC(2012, 9, 31), y: 28.43, sectorperf: 1.88}, {x: Date.UTC(2012, 10, 30), y: 29.08, sectorperf: -4.21}, {x: Date.UTC(2012, 11, 31), y: 29.31, sectorperf: 0.21}, {x: Date.UTC(2013, 0, 31), y: 29.22, sectorperf: 4.64}, {x: Date.UTC(2013, 1, 28), y: 29.19, sectorperf: 2.51}, {x: Date.UTC(2013, 2, 28), y: 29.16, sectorperf: 4.9}, {x: Date.UTC(2013, 3, 30), y: 29.77, sectorperf: 5.93}, {x: Date.UTC(2013, 4, 31), y: 28.78, sectorperf: -8.03}, {x: Date.UTC(2013, 5, 28), y: 28.8, sectorperf: 0.84}, {x: Date.UTC(2013, 6, 31), y: 28.84, sectorperf: 4.31}, {x: Date.UTC(2013, 7, 30), y: 25.01, sectorperf: -5.71}, {x: Date.UTC(2013, 8, 30), y: 24.75, sectorperf: 1.13}, {x: Date.UTC(2013, 9, 31), y: 24.61, sectorperf: 4.01}, {x: Date.UTC(2013, 10, 29), y: 22.9, sectorperf: -1.52}, {x: Date.UTC(2013, 11, 31), y: 22.77, sectorperf: 0.78}, {x: Date.UTC(2014, 0, 31), y: 23.99, sectorperf: 2.65}, {x: Date.UTC(2014, 1, 28), y: 23.38, sectorperf: 4.02}, {x: Date.UTC(2014, 2, 31), y: 23.46, sectorperf: 2.61}, {x: Date.UTC(2014, 3, 30), y: 24.26, sectorperf: 5.36}, {x: Date.UTC(2014, 4, 30), y: 22.75, sectorperf: -1.54}, {x: Date.UTC(2014, 5, 30), y: 23.28, sectorperf: 4.62}, {x: Date.UTC(2014, 6, 31), y: 22.78, sectorperf: -5.86}, {x: Date.UTC(2014, 7, 29), y: 19.83, sectorperf: 4.68}, {x: Date.UTC(2014, 8, 30), y: 19.5, sectorperf: -2.49}, {x: Date.UTC(2014, 9, 31), y: 20.19, sectorperf: 8.69}, {x: Date.UTC(2014, 10, 28), y: 17.54, sectorperf: 1.38}, {x: Date.UTC(2014, 11, 31), y: 18.35, sectorperf: 4.77}, {x: Date.UTC(2015, 0, 30), y: 19.11, sectorperf: 3.62}, {x: Date.UTC(2015, 1, 27), y: 13.15, sectorperf: -7.15}, {x: Date.UTC(2015, 2, 31), y: 13.04, sectorperf: -1.18}, {x: Date.UTC(2015, 3, 30), y: 13.09, sectorperf: -1.7}, {x: Date.UTC(2015, 4, 29), y: 2.74, sectorperf: 0.83}, {x: Date.UTC(2015, 5, 30), y: 2.64, sectorperf: -5.72}, {x: Date.UTC(2015, 6, 31), y: 2.72, sectorperf: 7.25}, {x: Date.UTC(2015, 7, 31), y: 4.55, sectorperf: -2.23} ] } ]

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Large Cap

S&P 500 Low Volatility

  • Potential to mitigate risk and preserve wealth with upside participation
  • Underlying Index: S&P 500® Low Volatility Index
  • Total Expense Ratio: 0.25%
  • Inception: May 5, 2011

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XMLV

Mid Cap

S&P MidCap Low Volatility

  • Provide lower risk exposure to historically higher risk segments of the market-cap spectrum
  • Underlying Index: S&P MidCap 400 Low Volatility Index
  • Total Expense Ratio: 0.25%
  • Inception: Feb. 15, 2013

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XSLV

Small Cap

S&P SmallCap Low Volatility

  • Provide lower risk exposure to historically higher risk segments of the market-cap spectrum
  • Underlying Index: S&P SmallCap 600 Low Volatility Index
  • Total Expense Ratio: 0.28%
  • Inception: Feb. 15, 2013

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XRLV

ex-Rate Sensitive

S&P 500 ex-Rate Sensitive Low Volatility

  • Constructed to mitigate the risks of rising interest rates
  • Underlying Index: S&P 500® Low Volatility Rate Response Index
  • Total Expense Ratio: 0.25%
  • Inception: April 9, 2015

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FXEU

Europe Currency Hedged

Europe Currency Hedged Low Volatility

  • Potentially lower risk and higher returns through a Eurozone low-volatility index methodology
  • Underlying Index: S&P Eurozone Low Volatility USD Hedged Index
  • Total Expense Ratio: 0.25%
  • Inception: May 7, 2015

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FXEP

EuroPacific Currency Hedged

Developed EuroPacific Currency Hedged Low Volatility

  • Potentially lower risk and higher returns through a EuroPacific low-volatility index methodology
  • Underlying Index: S&P EPAC ex. Korea Low Volatility USD Hedged Index
  • Total Expense Ratio: 0.25%
  • Inception: Sept. 24, 2015

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FXJP

Japan Currency Hedged

Japan Currency Hedged Low Volatility

  • Potentially lower risk and higher returns through a Japanese low-volatility index methodology
  • Underlying Index: S&P Japan 500 Low Volatility USD Hedged Index
  • Total Expense Ratio: 0.25%
  • Inception: Sept. 24, 2015

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EELV

Emerging Markets

S&P Emerging Markets Low Volatility

  • Potential to mitigate risk and preserve wealth with upside participation in emerging markets
  • Underlying Index: S&P BMI Emerging Markets Low Volatility Index
  • Total Expense Ratio: 0.45%
  • Inception: Jan. 13, 2012

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IDLV

International Developed

International Developed Low Volatility

  • Potential to mitigate risk and preserve wealth with upside participation in developed markets
  • Underlying Index: S&P BMI International Developed Low Volatility Index
  • Total Expense Ratio: 0.35%
  • Inception: Jan. 13, 2012

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S&P 500® Index is an unmanaged index considered representative of the U.S. stock market.

S&P 500® Low Volatility Index is compiled, maintained and calculated by Standard & Poor's and consists of the 100 stocks from the S&P 500® Index with the lowest realized volatility over the past 12 months.

Volatility is the annualized standard deviation of index returns. Risk-adjusted returns is a measure of how much risk is taken on by a security to produce a certain level of return.

There are risks involved with investing in ETFs, including possible loss of money. Shares are not actively managed and are subject to risks similar to those of stocks, including short selling and margin maintenance. Ordinary brokerage commissions apply. The Fund's return may not match the return of the Underlying Index.

Securities that pay high dividends as a group can fall out of favor with the market, causing such companies to underperform companies that do not pay high dividends.

Unforeseen market conditions may prevent the low volatility portfolios from achieving its goal of providing low volatility.

The prices of equity securities change in response to many factors, including the historical and prospective earnings of the issuer, the value of its assets, general economic conditions, interest rates, investor perceptions and market liquidity.

Foreign securities have additional risks, including exchange-rate changes, decreased market liquidity, political instability and taxation by foreign governments.

Investment in securities in emerging market countries involves risks not associated with investments in securities in developed countries.

The low volatility portfolios are non-diversified and can invest a greater portion of their assets in securities of individual issuers than a diversified fund. As a result, changes in the market value of a single investment could cause greater fluctuations in Share price than would occur in a diversified fund. This may increase the low volatility portfolios' volatility and cause the performance of a relatively small number of issuers to have a greater impact on the low volatility portfolios' performance.

Investing in securities of small and medium capitalization companies involves greater risk than customarily associated with investing in larger, more established companies.

Note: Not all products are available through all firms.

S&P® is a registered trademark of Standard & Poor's Financial Services LLC (S&P) and Dow Jones® is a registered trademark of Dow Jones Trademark Holdings LLC (Dow Jones). These trademarks have been licensed for use by S&P Dow Jones Indices LLC. S&P® and Standard & Poor's® are trademarks of S&P and Dow Jones® is a trademark of Dow Jones. These trademarks have been sublicensed for certain purposes by Invesco PowerShares Capital Management LLC (PowerShares). The Index is a product of S&P Dow Jones Indices LLC and/or its affiliates and has been licensed for use by PowerShares. The Fund is not sponsored, endorsed, sold or promoted by S&P Dow Jones Indices LLC, Dow Jones, S&P or their respective affiliates and neither S&P Dow Jones Indices LLC, Dow Jones, S&P or their respective affiliates make any representation regarding the advisability of investing in such product(s).