The shift in recent years from actively managed to passively managed funds is among the most notable trends in the $47 trillion investment management industry. This year, for the first time, passive fund assets are larger than those of active funds. Passive funds typically strive to mimic an index or benchmark using a fixed procedure (without discretion by the fund managers) to determine the funds’ asset allocation. Funds that use factor based/smart beta strategies have been among the fastest growing passively managed investment vehicles and now manage nearly two trillion dollars in 1,000 mutual funds and ETFs. The present and subsequent articles provide an overview of factor investing from its origin with the Capital Asset Pricing Model culminating in today’s methods and controversies. We first describe CAPM, the dominant model used to explain and forecast asset returns. CAPM only uses one factor in its calculation  risk, which is defined as a security’s volatility and measured by beta, the security’s volatility compared to that of the overall market’s. Over time, CAPM has been revised by adding additional factors to the calculation of asset returns. The proliferation of factors has led one author to find what he labelled a “zoo of factors.” The second article examines a recently published book, Popularity: A Bridge Between Classical and Behavioral Finance, which describes a model for asset pricing based on the concept of popularity, which is essentially investors’ demand or aversion to factor characteristics, whether financial, behavioral, or economic. The model expands the CAPM by incorporating behavioral and nonpecuniary factors with the classical risk factors. The result is a model that provides markedly better explanations and forecasts of asset pricing than CAPM yet remains within the CAPM equilibrium model. The third paper, Hedge Funds and Factor Investing, examines how many hedge funds have adapted factor investing into their strategies with case studies of several hedge funds and evaluates the success of these strategies. A word on nomenclature. “Factor investing” is the descriptive term that refers to a technique of analyzing asset prices using factors as explanatory variables and using statistical analysis of historical data. “Smart Beta,” is a product label used to identify mutual funds or ETFs that use the factor investing approach. Factor Investing and Valuation of Assets Factors are the “drivers” of asset returns that help explain and predict the return of a security, index or fund by statistical analysis of historical data. The term is used in regression or factor analysis and whose formula in the linear case is: Y = a + b (factor 1) + c (factor 2) +d (factor 3) … where the size of the betas (b, c, and d) of each factor measures the statistical relationship between that factor and the price of asset Y. (Regression analysis measures correlation between variables but does not indicate causality.) The larger the relative beta of a given factor the more it drives the assets’ price: the lower the accompanying pstatistic of a given factor, the more statistically significant is the factor. A pstatistic lower than 0.05 indicates causality. From Investment Alpha to Beta Until recently, “alpha” was widely used by investors to select securities or funds. Alpha is the residual in a factor analysis compared to an index or the performance of peers that is taken to measure the portion of a fund’s return that is attributed to manager skill. Over time, academic research showed that alpha (and hence the manager’s contribution to return) could be decomposed into factors such as company size and the liquidity of a security). As factors were shown to influence returns the size of alpha diminished along with its explanatory power. The critical analysis that catapulted factors into prominence occurred in 2009 with the publication of a research report Evaluation of Active Management of the Norwegian Government Pension Fund –Global by professors Andrew Ang, William Goetzmann and Stephen Schaefer. The authors showed that the added value of the fund’s active management did not reflect true manager skill but could in fact be explained by implicit exposure to several systematic factors. They recommended the adoption of a factor investing approach as a solution. The result of this analysis has been the launch of hundreds of investment vehicles based on factor investing (or “smart beta”) with the stated goal of providing investors with increased portfolio diversification and/or improved risk adjusted returns. Zoo of Factors and Multifactor Models The Capital Asset Pricing Model (CAPM), the most widely used asset pricing model, uses risk, as measured by an asset’s market volatility or beta, as the only factor that determines an asset price. This model, known as risk/return, became overly restrictive as other factors were found to participate in determining asset returns. Once the floodgates were opened, over 400 factors have been put forth by academics and money managers, leading one researcher to describe the field as a “Zoo of Factors.” However, as shown below, relatively few factors that survived rigorous analysis now form the skeleton of factor investing. The first popular multifactor model, the FamaFrench threefactor model, contained three factors: the major market (i.e., the S&P 500), value vs. growth, and size (market capitalization). They later added two additional factors (investment in the company and profitability) to develop a 5factor model. Andrew Lo then introduced momentum as additional factor in explaining hedge fund and mutual fund returns. A study by Hansanhodzik & Lo, “Can Hedge Fund Returns be Replicated: The Linear Case,” identifies five factors that are correlated, and presumed to determine hedge fund performance; equity markets; US Dollar; Credit spreads; bonds; and Commodities. Cliff Assness, founder of AQR, the largest hedge fund that uses factor investing, identifies six factors as drivers of investment returns: value, momentum, profitability, low volatility, interest rate carry, and defensive company stock. S&P has developed factor indices for the following factors: Volatility, high beta, size, style, quality, momentum, enhanced value, dividends, capital expenditures, and multifactor funds. Finally, Invesco uses six factors in constructing investor portfolios: Value, Size, Momentum, Low Volatility, Quality and Dividend Yield. One continuing problem with factor selection is the use of “data mining.” In data mining, a statistical program is allowed run rampant over a database of asset return and factor statistics to find correlations between asset returns and the factors. The result is often statistical correlations that have no economic or financial explanation. The antidote to data mining is to ensure that a factor is only used in a model if there is a credible financial or economic explanation for its inclusion. What is “Smart Beta?” Traditional asset allocation uses either the market capweighted or equally weighted approach to construct portfolios. In capweighed portfolios, a stock whose market capital (measured by the number of shares outstanding times the stock’s market price) is 5% of the S&P 500 index would have an allocation of 5% of the assets of an S&P 500 index fund. In the equally weighted approach, each stock is given an equal allocation in the portfolio. "Smart" refers to the use of an alternative methodology to sizebased (marketcap) allocations in which a security’s price determines its portfolio allocation. A smart beta investment strategy is designed to add value by strategically choosing, weighting and rebalancing the companies in an index based upon factors – listed above  other than market capitalization. These factors are considered “smart” because they were selected based on the result of economic and financial research.
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