Introduction to factor investingThe balance between risk and return efficiency

This document is intended only for Qualified Investors in Switzerland and for Professional Clients and Financial Advisers in other Continental European countries (as defined in the important information), for Professional Clients in Dubai, Jersey, Guernsey, Isle of Man, Ireland and the UK, for Institutional Investors in the United States and Australia, for Institutional Investors and/or Accredited Investors in Singapore, for Professional Investors only in Hong Kong, for Qualified Institutional Investors, pension funds and distributing companies in Japan; to wholesale investors (as defined in the Financial Markets Conduct Act) in New Zealand, for Accredited Investors as defined under National Instrument 45–106 or financial professionals in Canada, for certain specific Qualified Institutions and/ or Sophisticated Investors only in Taiwan.

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What is factor investing?Factor investing has attracted much attention recently, but traces its roots back to the 1960s. It is an approach to investing which seeks to gain exposure to certain factors with the potential to outperform broad, market-capitalisation weighted benchmark. A factor can be thought of as any characteristic of a financial asset that is an important determinant of its risk and return. There are two broad groups of factors: historically, macroeconomic factors have been perhaps the most important drivers of financial markets; more recently, greater attention has been placed on factors representing particular investment styles.

Fig 1. Performance of common factor strategies (%) at end of year MSCI World Min. VolatilityMSCI World MomentumMSCI World Eql. WeightedMSCI World

MSCI World QualityMSCI World Value WeightedMSCI World High Dividend Yield

Source: Invesco, MSCI as of 30 September 2016 (total return, in USD). All of the factor indices shown have been created comparatively recently, and therefore, contain elements of hindsight and selection bias. Please see MSCI disclosures at the end of this document for further information on MSCI factor indices, index inception dates and back-tested past performance. Past performance is no guarantee of future results. Please note the x axis labelling denotes the end of each full year.

Macroeconomic factorsMacroeconomic factors include the sensitivity of financial assets to economic variables, such as inflation, monetary and liquidity developments, economic growth and currency movement. For example, when inflation is low and falling and economic growth is relatively weak, fixed income markets have typically performed well. When economic growth in emergingeconomies is stronger than in advancedeconomies, emerging equity markets mayperform more strongly. In all cases it is actual versus expected developments that are the key drivers of financial markets. Many fund managers tend to place a great deal of emphasis on the interpretation of these macroeconomic factors. In many cases, however, the link between macroeconomic developments and financial market performance has been quite weak. Several studies have shown, for example, little or no correlation between economic growth and equity market returns.1

Equity factorsEquity factors have their roots in academic literature and a large body of empirical evidence. ‘Value’ is perhaps the best-known equity factor. It seeks to capture the positive link between equities that have low prices relative to their fundamental value and higher returns than a benchmark index in the long run. Value investing is a well-known style, tracing its roots back to Graham and Dodd’s classic 1934 book ‘Security Analysis’. Several other equity factors have been identified since the 1970s. Six of these are now commonly recognised as those with the most robust foundations in theory and empirical evidence.

Fig 2. Common equity factors

Systematic factors

Value

Low size (small cap)

Momentum

Minimum/Low volatility

Dividend yield

Quality

Seeks to capture

Excess returns to stocks that have low prices relative to their fundamental value and higher returns than a benchmark index in the long run

Excess returns of smaller firms (by market capitalisation) relative to their larger counterparts

Excess returns to stocks with stronger past performance

Excess returns to stocks with lower than average volatility, beta, and/or idiosyncratic risk Excess returns to stocks that have higher-than-average dividend yields

Excess returns to stocks that are characterised by low debt, stable earnings growth, profitability, and other ‘quality’ metrics

Commonly captured by

Price/book ratio, price/earnings ratio, cash earnings, net profit, dividend yields, cashflow

Market capitalisation (full or free float)

Relative returns (3-mth, 6-mth, 12-mth, sometimes with last 1-mth excluded) historical alpha, earnings expectation

Standard deviation (1-yr, 2-yrs, 3-yrs), downside standard deviation, standard deviation of idiosyncratic returns, beta

Dividend yield

Return on equity, earnings stability, dividend growth stability, strength of balance sheet, financial leverage, accounting policies, strength of management, accruals, cashflows

Six equity factors There are six prominent equity factors: value, size, volatility, momentum, quality and dividend yield. MSCI produces world indices showing the performance of each of these factors since 1997* (see figures 1 and 2). If you take the whole period from 1997 to September 2016, each factor has a higher total return than the MSCI World Index, which weights constituents according to market capitalisation. More fundamentally, each of the factors has an investment rationale based in academic literature, recently focusing on behavioural rationale. Each also has strong empirical support. In many cases, that empirical support has been tested across a very wide range of countries and time periods. The findings have not gone unchallenged, however, and it is important to keep in mind some of the important caveats.

*The inception dates of the MSCI indices are after 1997. All information presented prior to the inception dates is back-tested. Back-tested performance is not actual performance, but is hypothetical. Although back-tested data may be prepared with the benefit of hindsight, these calculations are based on the same methodology that was in effect when the index was officially launched. Index returns do not reflect payment of any sales charges or fees. Past performance cannot guarantee future results. An investment cannot be made in an index. Please see the MSCI disclosures at the end of this document for further information.

Source: Invesco at 30 November 2016.

Six equity factors

Value: cheaply valued stocks expect to produce higher returnsThe simple rationale for the value factor is that it makes sense to expect that buying an asset which is cheaply valued will produce higher subsequent returns than buying when it is expensively valued. That was the original basis of Graham and Dodd’s work, noted previously. The greater return potential of ‘value’ versus its opposite of ‘growth’ was identified by Basu2 in 1977 and has been widely researched and measured since then. Several different measures of value can be used. MSCI currently identifies ‘value’ stocks according to their dividend yield (the higher the yield, the better the value) and the price/book and price/earnings ratios (in both cases a lower ratio represents better value). Individual stocks are screened according to these characteristics and the index comprises those which rank as the best value. Other measures have also been found to have positive excess returns including value ratios that use cashflow and net profit.3

It is worth noting that the value factor can remain out of favour, and underperform overall market-capitalisation weighted indices for long periods of time. From 1926 to 2016, on the basis of the performance of the ‘US value’ factor measured by Kenneth French, greater performance was observed.4 However, Michael Fraikin, Global Head of Research of the Invesco Quantitative Strategies team, comments that the factor “did not work over the first 20 years of that period or over the last 30 years”. On that basis the concept of ‘long-term outperformance’ can require a very long-term timeframe indeed. Over such long periods Fraikin is also concerned about the effects of selection and survivorship bias on the findings: many new companies will be created, many old ones will not survive and how well such developments are reflected in the available indices needs to be assessed with caution.

Size: small cap stocks expect to produce better returns than large cap stocksThe small cap effect − that small cap stocks have greater return potential than large cap stocks − was first identified in 1981 by Banz.5 His study showed that between 1926 and 1975 US small cap stocks produced an average return of 1% per month more than large cap stocks. Banz’s original research was followed by an investigation of the ‘small cap’ effect in many markets around the world, which found it to exist almost universally.6 The rationale for the small cap effect is based on a number of factors including: that smaller companies may have better growth prospects; that they are under-researched by the financial markets; that small firms’ shares have lower liquidity and consequently carry a risk premium to compensate for this extra risk; and that there may be a general investor preference for larger stocks that are generally perceived to be safer. One challenge related to the small cap factor stems from the reaction to Banz’s

original US research. It prompted the launch of a number of US small cap funds and inflows into these funds helped to maintain stronger performance of US small versus large cap stocks from 1981–1983. But from 1981–2001 average US small cap returns were 0.7% per month lower than large cap returns.7 The phenomenon of strong performance of small relative to large caps in the initial research, followed by poor subsequent performance, has been identified in all markets apart from Switzerland and has been described as an example of ‘Murphy’s Law’.8

Just as with the value factor, therefore, while the small cap factor shows stronger performance over many long-term time periods, there can be important deviations from this, lasting several years.

Volatility: low volatility stocks expect to outperform high volatility stocks The rationale for why stocks with historically low volatility may produce higher risk-adjusted returns is that they are typically stable, more defensive companies. Although they may have more limited growth prospects, they tend to have stronger balance sheets, typically pay dividends and can grow earnings and dividends even in a lower economic growth environment. The low-volatility factor was first identified in the early 1970s by Haugen and Heins.9 They showed that, over long time horizons, such low- volatility stocks produced higher risk-adjusted returns than stocks with historically higher volatility. Because this behaviour runs contrary to the traditional capital asset pricing model it is known as the ‘low-volatility anomaly’. One potential issue with the low-volatility factor is that some investors may see such stocks as an alternative to other traditionally defensive assets such as government bonds. In practice, however, even defensive areas of the equity market can be more volatile than such government bonds, especially during times of heightened overall market volatility.10

Momentum: stocks that have performed strongly in the past are expected to continue doing soThe momentum factor describes the phenomenon that stocks that have performed well in the past have tended to continue to do so — at least over the near term. It was first identified in 1993 by Jegadeesh and Titman11

who found that buying past winners and selling past losers was a strategy that produced excess returns. The most widely cited theories of why such momentum strategies have worked rests on the findings of behavioural finance. Notably, investors may tend to over-react or under-react to news, which leads them to hold onto rising stocks and they display ‘confirmation bias’ — which means they take note of only good news for a rising stock and vice versa. It is worth noting that this factor can turn very quickly after a period of strong performance, typically as relative valuations become too high. Consider the performance of the momentum factor shown in Figure 1, for example. In the late 1990s, technology, media and telecoms stocks did well as global financial markets became caught up in the ‘dot com’ boom. Such areas of the stock

market continued to do well, up until the early 2000s, even though their valuations became increasingly stretched. The momentum factor did well as it favoured holding those stocks that had performed well in the past. But as boom turned to bust, momentum strategies did poorly. Similarly, momentum strategies did well up until the onset of the 2008 global financial crisis but poorly afterwards. Momentum strategies can therefore be cyclical, amplifying returns in a pronounced bull market, while underperforming during longer-lasting bear markets.

Quality: better quality companies expect to produce better returns than lower quality companiesThe ‘quality’ factor has been widely used in fundamental analysis for some time but is a newer phenomenon in quantitative investments.12 One issue is that it is somewhat more difficult to measure than other factors as it can partly reflect intangible factors such as a company’s brand recognition or reputation. However, some factor-based strategies address this by selecting holdings according to balance sheet measures of quality, such as return on equity and financial leverage. A 2013 study by Asness, Frazzini and Pedersen showed that when quality was measured by three financial variables — profitability, the stability of earnings growth and dividend payout ratio — the stock had significantly higher risk-adjusted returns than the overall market-capitalisation weighted index.13

A caveat with the approach is that even seemingly good-quality, well-managed companies with sound management and finances can periodically produce under-performance relative to the overall market.

Dividend yield: high dividend-yielding stocks expect to produce better returns than low dividend-yielding stocksDividends and reinvested dividends have been a major component of the total returns from stock market investments over time. On that basis, favouring companies with a higher dividend yield over those with a lower dividend yield can be expected to produce higher returns. Empirical research for higher returns from high dividend-yielding stocks came as early as 1980.14 One observation with the measure is that, to some extent, it overlaps with the ‘value’ factor. Investors also need to be wary of ‘dividend traps’ — cases in which high dividend yields may be masking a declining stock price or weak company fundamentals. Some factor-based strategies can help screen out dividend traps.

Behavioural rationales Markets are inefficient due to behavioural biases of participants

Why might an investor expect to earn a factor premium?There is evidence to suggest that factorinvesting not only has the potential to driveoutperformance in the long-run compared to a broad market-capitalisation weighted benchmark but has the ability to do so with a greater risk-adjusted trade-off. The potential outperformance is drivenby the fact that markets are inefficient whileinvestors are not rational by nature. Factorinvesting seeks to exploit these marketinefficiencies and behavioural biases. Factor investing also seeks to harness factorpremiums in return for bearing additional risk to the market. There are three generic explanations as to why this is (see figure 3). First, the factor may reflect an additional return potential for bearing an undesirable risk pattern. For example, it may be identified as doing badly when the overall market does badly. In return for bearing that risk, an additional return should be expected over time. Again: value may do well in the long-run but can perform poorly when momentum strategies are in favour; and small cap stocks may prove particularly illiquid during a market downturn.

Second, behavioural biases may make markets inefficient. ‘Anchoring’, the tendency to make investment decisions according to a key reference value means that after a market or one sector of the market falls out of favour, some investors may be unwilling to re-enter the market until it has regained its previous level. For example, many technology stocks were shunned for years after the tech bubble burst in the early 2000s. ‘Action bias’ means that some investors try to time the market rather than buy and hold for the long term and suffer as a result of higher transaction costs and potentially bad timing decisions. ‘Loss aversion’, the finding that the value placed on losses tends to be larger than that placed on equal-sized gains, shows that if a given stock performs poorly investors will typically not sell because they don’t want to realise a loss. The end result is that investors often hold on to ‘losers’ for too long. Factor investing seeks to exploit this behavioural rationale to earn a factor premium.15

Third, the structure of the equity market itself, because of restrictions or limitations, may be the source of a risk premium. For example, selling short (selling an asset without actually owning it, in the anticipation that it can be bought back later at a cheaper price) is not possible for many groups of investors. Michael Fraikin cites evidence that portfolios that are able to be short and long various factors have been shown to produce higher risk-adjusted returns than those restricted to just long positions.16

Risk premiums

For bearing additional risk over the broad equity market e.g. an undesirable return pattern

Fig 3. Why might an investor expect to earn a factor premium?

Market structure Markets may be inefficient because of restrictions and limitations

Source: Invesco. For illustrative purposes only.

Anchoring

Loss aversion

Action bias

Best

Worst

99 00 01 02 03 04 05 06 07 08 09 10 131211 14 15 16

Fig 4. Performance ranking of selected factor-based strategiesSuccessful timing has been virtually impossible

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Source: Invesco, MSCI as of 30 September 2016 (total return, in USD). Indexes: Size = MSCI World Equal Weighted, Momentum = MSCI World Momentum, Value = MSCI World Value Weighted, Yield = MSCI World High Dividend Yield, Volatility = MSCI World Min. Volatility, Quality = MSCI World Quality. All of the factor indices shown have been created comparatively recently, and therefore, contain elements of hindsight as well as selection bias. Please see MSCI disclosures at the end of this document for further information on MSCI factor indices, indexes inception dates and back-tested past performance. Past performance is no guarantee of future results.

Size Momentum Value

Yield Volatility Quality

Why now?The rationale for, and empirical under-pinnings of, factor investing are, in many cases, far from new. So why has factor investing started to attract more attention in recent years? We see four main reasons. First, although factors have been identified in the past, their importance varies over time and needs to be constantly assessed. It would be unwise to rely on the evidence of a factor producing higher returns than a broad market-capitalisation weighted benchmark index if the study supporting it was of too short a time period, out of date and maybe not corroborated by more recent work. Large amounts of data and the availability of greater computing power make the current task of monitoring the returns from various factors more feasible. Second, there is now greater understanding than there was just a decade or so ago of the nature of behavioural biases and the implications of these for factor investing. Third, the volatility and change in correlations in financial markets has led investors to look more closely at the nature of the financial market risks to which they are exposed. Factor analysis can be particularly useful in this respect. Fourth, in a generally low-return environment, the returns from factor investing may be proportionally greater than in a higher-return environment.

Using factors to explain portfolio performanceFactors are increasingly used to explain the return and risk characteristics of portfolios, although in many cases portfolio factor tilts may not initially be recognised. Although a portfolio may be appear to be balanced according to traditional style measures, that same portfolio may be unbalanced from a factor perspective. For example, a fund manager’s portfolio may be characterised by its statistical relationship to one or more of the key factors. Modern factor analysis tools make it possible to identify a fund manager as having a ‘small cap, value’ portfolio because the portfolio is exposed to these two factors. The importance of this is that the greater the extent to which an active fund manager’s performance can be explained by exposure to such factors, the weaker may be the fund manager’s claim to be truly active. That raises the hurdle for demonstrating that a fund manager can deliver truly ‘active’ performance and providing an explanation of how this is achieved: through stock selection, for example; or by exposure to a factor not identified by factor analysis.

The rise of smart betaThe growth of smart beta investing — that is, attempting to outperform market-cap-weighed indexes through factor tilts and alternative weighting — has gained widespread acceptance in recent years. Smart beta investing has become a much more feasible opportunity as ETFs representing the main equity factors have become widely available.

While many factor strategies have outperformed the MSCI World benchmark in the long run, they have underperformed strongly in the short to medium term. But not all of them at the same time. Hence the potential for diversification.

MSCI World Min. Volatility MSCI World Momentum MSCI World Eql. Weighted

MSCI World Quality MSCI World Value Weighted MSCI World High Dividend Yield

ConclusionsFactor investing has become a significant feature of the global financial markets. Broad equity factors, each supported by a fundamental rationale and empirical evidence, are a central focus of this new approach. Using MSCI World indices as examples throughout this brochure, we have shown that factor investing can outperform a market capitalisation benchmark in the long run, but can face adverse short-term performance. Rich sources of data and powerful data-handling techniques mean that factor-based investing, long supported in research findings, is now able to have a meaningful, practical and much greater role in the construction of investment portfolios.

Which factor at which time?In the short or even medium term, selected factor strategies can have quite divergent performance. It has been unusual for a factor to remain the best performing factor for more than a year or two (see figure 4). Not all factors perform well or badly at the same time, especially during periods of financial market volatility, such as during the ‘new economy’ boom and bust and the Global Financial Crisis (see figure 5). Being exposed to just one factor may, in that context, result in previous outperformance rapidly turning to underperformance of the overall market and vice versa. A direct consequence is that the different cyclical characteristics of specific factor strategies offer room for diversification. Factors that have had a low correlation with each other may provide potential diversification benefits, because the factors have tended to perform differently during the same market backdrops. For example, balancing ‘momentum’ with ‘value’ — as these will have typically exhibited negative long-term correlations — may result in more stable relative returns across a business cycle as compared to single factor strategies. A diversified factor or multi-factor approach can capture differentiated return streams which has the potential for smoother returns.

New economy Financial crisis

Invesco Expert practitioners in factor science Pushing the boundaries of portfolio construction. Invesco is an innovator in factor investing with US$145bn in AUM and 30 years’ experience.

Differentiating attributes:– Diverse, time-tested investment strategies– All vehicles designed to meet investor needs– Product specialists– Education and thought leadership support

Factor-based investment strategies

Invesco Quantitative Strategies:– US$35bn in AUM– Global presence with teams across

four continents– Factor-based active since 1983 – 43 investment professionals – Globally delivered through pooled funds

and separate accounts

PowerShares by Invesco:– US $110bn in AUM– 4th largest ETF provider* – Factor-based smart beta pioneer since 2003– 16 investment professionals – 123 ETFs globally

Source: Invesco, as of 30 September 2016. *Source: Morningstar, as of 30 September 2016. PowerShares by Invesco is ranked 4th out of 217 ETF providers globally. For illustrative purposes only. Product availability will vary by jurisdiction. Please contact your local Invesco representative for more information.

Fig 5. Relative performance of factor strategies versus the MSCI World benchmark (%)

Source: Invesco, MSCI as of 30 September 2016 (total return, in USD). All of the factor indices shown, have been created comparatively recently, and therefore, contain elements of hindsight and selection bias. Please note the x axis labelling denotes the end of each full year. Please see MSCI disclosures at the end of this document for further information on MSCI factor indices, indices inception dates and back- tested past performance. Past performance is no guarantee of future results.

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MSCI disclosureMSCI World Index was launched on 31 Mar 1986. MSCI World Value Weighted Index was launched on 07 Dec 2010. The MSCI World Momentum Index was launchedon 11 Dec 2013. The MSCI World Quality Index was launched on 18 Dec 2012. The MSCI World Minimum Volatility Index was launched on 14 Apr 2008. The MSCI World High Dividend Yield Index was launched on 31 Oct 2006. The MSCI World Equal Weighted Index was launched on 22 Jan 2008. All information presented prior to the inception dates is back-tested. Back-tested performance is not actual performance, but is hypothetical. Although back-tested data may be prepared with the benefit of hindsight, these calculations are based on the same methodology that was in effect when the index was officially launched. Index returns do not reflect payment of any sales charges or fees. Past performance cannot guarantee future results. An investment cannot be made in an index.

Sources Credit Suisse The Growth Puzzle Global Investment Returns Yearbook, 2014. Sanjoy Basu Investment Performance of Common Stocks in Relation to Their Price/Earnings Ratios: A Test of the Efficient Market Hypothesis Journal of Finance, 1977. MSCI Research Insight Foundations of Factor Investing December 2013.Source: US Value factor performance sourced by Kenneth R. French as of 30 April 2016.Rolf Banz The Relationship between Return and Market Value of Common Stocks Journal of Financial Economics, 1981.Dimson, Marsh and Staunton Triumph of the Optimists: 101 Years of Global Investment Returns Princeton University Press, 2002. Dimson, Marsh and Staunton Triumph of the Optimists: 101 Years of Global Investment Returns Princeton University Press, 2002. Dimson, Marsh and Staunton The Triumph of the Optimists Princeton 2002. The initial research period covers the period from 1975 up until the publication of the initial research of the ‘small cap phenomenon’ (1981 in the US and in all other cases during the 1980s). 19 countries were researched: Australia, Belgium, Canada, Denmark, Finland, France, Germany, Ireland, Italy, Japan, Mexico, Netherlands, New Zealand, Singapore, Spain, Sweden, Switzerland, the UK and US. The performance is based on Independence International Associates (IIA) or FTSE data. The ‘subsequent period’ is from the publication of the initial research until 2001. Robert Haugen and James Heins Risk and the Rate of Return on Financial Assets: Some Old Wine in New Bottles Journal of Financial and Quantitative Analysis, 1975 and Robert Haugen and James Heins On the Evidence Supporting the Existence of Risk Premiums in the Capital Markets Wisconsin Working Paper, December 1972. This study examines the ex post relationships between average rates of return and various measures of risk for portfolios of corporate bonds and stocks traded on the the NYSE (New York Stock Exchange) between 1927 and 1971. See, for example, John Coumarianos The Problem With ‘Low-Volatility’ Stock Funds Wall Street Journal June 5 2016. Narasimhan Jegadeesh and Sheridan Titman Returns toBuying Winners and Selling Losers: Implications for StockMarket Efficiency Journal of Finance, 1993. This study analyses the NYSE (New York Stock Exchange) and AMEX stock returns around earnings announcement dates. The sample period is from January 1965 to December 1989. MSCI Research Insight Foundations of Factor Investing December 2013. Asness, Frazzini, and Pedersen Quality Minus Junk Working paper, New York University (NYU), AQR Capital Management, LLC. 2013. This study tests the pricing of quality over a long sample of U.S. stocks from 1956 to 2012 and a broad sample of stocks from 24 developed markets from 1986 to 2012.Marshall Blume Stock Returns and Dividend Yields: Some More Evidence Review of Economics and Statistics, Nov. 1980.Credit Suisse Global Investment Returns Sourcebook.2015. This study analyses the relationship betweenthe return premiums and dividend yields for US stocks.The dataset used is that produced by CRSP (Centre forResearch in Security Prices) and includes all NYSE (NewYork Stock Exchange) common stocks from 1927, AMEXstocks from 1962, and NASDAQ from 1972. The sampleperiod is June 1927 to December 2014. Thaler, Tversky, Kahneman and Schwarz, The Effect of Myopia and Loss Aversion on Risk Taking: an Experimental Test, Quarterly Journal of Economics, May 1997.Invesco and Axioma research based on the following factors: growth, leverage, liquidity, mediumterm momentum, size, value and low-volatility, for global as well as regional universes over the period 31 December 1996 to 30 April 2016.

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Important informationThis document is intended only for Qualified Investors in Switzerland and for Professional Clients and Financial Advisers in other Continental European countries, for Professional Clients in Dubai, Jersey, Guernsey, Isle of Man, Ireland and the UK, for Institutional Investors in the United States and Australia, for Institutional Investors and/or Accredited Investors in Singapore, for Professional Investors only in Hong Kong, for Qualified Institutional Investors, pension funds and distributing companies in Japan; to wholesale investors (as defined in the Financial Markets Conduct Act) in New Zealand, for Accredited Investors as defined under National Instrument 45–106 or financial professionals in Canada, for certain specific Qualified Institutions and/ or Sophisticated Investors only in Taiwan and for one-on-one use with Institutional Investors in Bermuda, Chile, Panama and Peru. The information in this document is presented for discussion and illustrative purposes only and is not a recommendation or an offer to buy or sell any securities or investment advisory services. It should not be distributed or relied upon by members of the public or retail investors. Circulation, disclosure, or dissemination of all or any part of this document to any unauthorized person is prohibited. Where Invesco has expressed views and opinions, it is based on current market conditions and subject to change without notice. The value of investments and any income will fluctuate (this may partly be the result of exchange-rate fluctuations) and investors may not get back the full amount invested. Past performance is not a guide to a future returns. As with all investments, there are associated inherit risks and may not be suitable for an investor’s goals, objectives and risk tolerance. Please review all financial material carefully before investing. These document contains statements that are “forward-looking statements,” which are based on certain assumptions of future events and information available on the date hereof. Invesco does not assume any duty to update any forward-looking statements. Actual events may differ from those assumed. There can be no assurance that forward-looking statements, including any projected returns, will materialize or that actual market conditions and/or performance results will not be materially different or worse than those presented. While great care has been taken to ensure that the information contained herein is accurate and the data or information supplied by outside sources are reliable, no responsibility can be accepted for any errors, mistakes or omissions or for any action in reliance thereon. All trademarks and service marks included herein belong to Invesco or an affiliate, except third-party trademarks and service marks, which belong to their respective owners. The information contained herein is proprietary and confidential to Invesco and its affiliates and may not be used for any purpose other than the purpose for which it has been provided.

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