A quick history of factor-based investing

And how factor-based strategies can help you protect wealth from downturns in the market and improve outcomes

In 1992, Major League Baseball’s Oakland A’s pioneered the combination of traditional scouting practices with statistical analysis of players. Like baseball, investing contains a wealth of data and metrics, which can be analyzed to inform decisions.

In investing, isolating the characteristics of a security associated with higher returns is referred to as factor investing. Factor-based approaches to investing have, in recent years, gained significant attention, however the concepts guiding these approaches have been around for some time. Many fundamental attributes of companies and securities have shown to be correlated with past stock returns and so are expected to be correlated with future returns.

The basis of Modern Portfolio Theory has long been centered around the Capital Asset Pricing Model (CAPM) originated by William Sharpe and Harry Markowitz. Sharpe and Markowitz identified beta as a factor that was instrumental to a stock’s return. Beta is arguably the best-known factor and the one every investor gains exposure to, whether intentionally or not, when allocating to equity securities.

Countless academic studies have since expounded on the ground-breaking CAPM, noting that other identifiable investment factors yielded significant premiums.

Many investment professionals have used factors to pick stocks from the very beginning. Warren Buffet isn’t thought of as a factor investor, but his focus on identifying stocks trading at a discount to their intrinsic value, based on Benjamin Graham and David Dodd’s work in 1934, makes the legendary investor one of the early adapters.

Extensive academic research has confirmed the value factor has proven to be effective in identifying stocks that are expected to outperform.

As the volume of the company data expanded, and academic research intensified, the number of factors increased as Eugene Fama and Kenneth French developed a three-factor model, which included value, beta, as well as size. Size refers to the historical precedent that small-cap stocks have outperformed large cap stocks over the long-term.



Understanding Factors – 5 examples



A stock with a market price that is below the company’s intrinsic value. Over time, stocks with a lower price relative to their intrinsic value have outperformed.



A stock that has recently trended upward tends to continue rising.



Small-capitalization stocks tend to outperform large capitalization stocks over time.



Stocks that are of a higher quality tend to outperform poorer quality stocks over time.



Stocks with a lower volatility tend to outperform higher volatility stocks over time.



The conventional wisdom with regard to timing smallcap stock investing is that U.S.small-cap stocks have historically outperformed large-cap stocks during rising rate environments. But performance is cyclical and periods of underperformance can be long.

Today the list of factors has expanded to include low volatility and momentum. In 2005, the term fundamental indexation was coined, which attempted to redefine a company’s weighting in an index based on an attribute other than market capitalization, while smart beta tilted the index to potentially improve returns and/or reduce risk through the application of rules.

Individually, each factor can provide investors with longterm performance, but research has demonstrated that individual factor performance will vary considerably based on market cycle and can lead to a volatile, uneven ride.

Why multi-factor investing?

Over time, factor-based investing has evolved from identifying individual factors to combining multiple factors in a disciplined investment process.

Multi-factor strategies can capture the opportunities provided by a factor-based approach, but also manage risk and volatility. Factor exposures can be managed to provide a smoother ride for investors across different sectors, regions and asset classes. This ongoing evolution provides investors opportunities to incorporate factor-based strategies into their portfolios.

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Multi-factor Investing

Factor-based investing is a highly effective way to invest in today’s uncertain markets. By appreciating that different factors do well at different points in the cycle, a disciplined, multi-factor approach can capture potential benefits regardless of which factor is driving returns at any given time.

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Commissions, trailing commissions, management fees and expenses all may be associated with investing in the AGFiQ ETFs. Please read the relevant prospectus before investing. The Funds are not guaranteed, their values change frequently and past performance may not be repeated. Tax, investment and all other such decisions should be made, as appropriate, only with guidance from a qualified professional. There is no guaran-tee that AGFiQ ETFs will achieve their stated objectives and there is risk involved in investing in the ETFs. The risks associated with each AGFiQ ETF are detailed in the prospectus. Before investing, consider carefully each ETF’s investment objectives, risks, charges and expenses, found in the prospectus. Please read the prospectus carefully before investing. A copy is available on AGFiQ.com. Source: MSCI. The MSCI information may only be used for your internal use, may not be reproduced or re-disseminated in any form and may not be used as a basis for, or a component or, any financial instruments or products or indices. None of the MSCI information is intended to constitute investment advice or a recommendation to make (or refrain from making) any kind of investment decision and may not be relied on as such. Historical data and analysis should not be taken as an indication or guarantee of any future performance analysis, forecast or prediction. The MSCI information is provided on an “as-is” and the user of this information assumes the entire risk of any use made of this information. MSCI, each of its affiliates and each other person involved in or related to compiling, computing or creating any MSCI information (collectively, the “MSCI Parties”) expressly disclaims all warranties (including, without limitation, any warranties of originality, accuracy, completeness, timeliness, non-infringement, merchantability and fitness for a particular purpose) with respect to this information. Without limited any of the foregoing, in no event shall any MSCI Party have any liability for any direct, indirect, special, incidental, punitive, consequential (including, without limitation, lost profits) or any other damages. (www.msci.com) Findings from Professor Ken French, of Dartmouth College, data and research were incorporated into these materials for illustrative purposes only. The content is not specific to the AGFiQ ETFs, is not a guarantee of future results and should not be considered as investment advice or an offer or solicitation to trade in AGFiQ ETFs. Investment and other similar decisions should be made with guidance from a qualified professional based on personal circumstances. Publication date: June 12, 2018

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