Abstract: The increasing popularity of factor investing has led to valuation concerns among some contrarian-minded investors, and fears of imminent mean-reversion and underperformance. In this paper, the authors find that despite their recent popularity the most common factors or styles, namely the value, momentum and defensive styles, are not, in general, markedly over-valued as measured by their value spreads. More broadly, tactical timing, whether of markets or factors, always seems to hold appeal for many. The authors look at the general efficacy of value spreads in predicting future returns to styles. At first glance, valuation-based timing of styles appears promising. This is not surprising as it is a simple consequence of the efficacy of the value strategy itself. Yet when the authors implement value timing in a multi-style framework that already includes the value style, they find somewhat disappointing results. As value timing of factors is correlated to the standard value factor, it adds further value exposure, but as compared to an explicit risk-targeted strategic allocation to value, value timing provides an intermittent and sub-optimal amount of value exposure. Thus, according to the authors, tactical value timing can reduce diversification and detract from the performance of a multi-style strategy that already includes value. Finally, the authors explore whether value timing works better at longer holding periods or at extremes, still finding fairly weak results. Contrarian value timing of factors is, generally, a weak addition for long-term investors holding well-diversified factors including value and, specifically, not sending a strong signal on stretched valuations today.

Abstract: The authors investigate two popular approaches to long-only style investing that are often considered as potential starting points for smart beta investors: the portfolio mix that combines allocations to stand-alone indexes for each style, and the integrated portfolio that integrates styles directly in the portfolio construction process. Their key finding is that integrating styles is a much more effective way to harvest long-only style premia. Compared with the portfolio mix, the integrated portfolio substantially improves returns and the information ratio by avoiding stocks with offsetting style exposures and including stocks with balanced positive style exposures.

Abstract: Using a transaction cost model and an assumption for the smart beta premium observed in data, the authors estimate the capacity of a particular implementation of momentum, quality, value, size, minimum volatility, and a multifactor combination. For a given trading horizon, they can find the fund size at which the transaction costs from flows into these strategies negate the smart beta premium. For a one-day trading horizon, momentum is the strategy with the smallest assets under management (AUM) capacity of $65 billion, and size is the largest with an AUM capacity of $5 trillion. At five days, momentum and size capacity rise to $320 billion and over $10 trillion, respectively.

Abstract: The authors investigate the biases in the backtested performance of “alternative beta” strategies using a unique sample of 215 trading strategies developed and promoted by global investment banks. Their results lend support to the cautions in the recent literature regarding backtest overfitting and lack of robustness in trading strategy performance during the “live” period (out of sample). The authors report a median 73% deterioration in Sharpe ratios between backtested and live performance periods for the strategies, and they establish a link between performance deterioration and strategy complexity, with the realized reduction in live versus backtested Sharpe ratios of the most complex strategies exceeding those of the simplest ones by over 30 percentage points. The robustness of strategy exposure to risk factors varies between asset classes and strategies; it appears reasonable in equity volatility and FX carry strategies but quite weak in the equity value strategy in particular.

Abstract: In this third of the three discussions that took place at the SASB 2016 Symposium, practitioners of a broad range of investment approaches—active as well as passive in both equities and fixed‐income—explain how and why they use ESG information when evaluating companies and making their investment decisions. There was general agreement that successful ESG investing depends on integrating ESG factors with the methods and data of traditional “fundamental” financial statement analysis. And in support of this claim, a number of the panelists noted that some of the world’s best “business value investors,” including Warren Buffett, have long incorporated environmental, social, and governance considerations into their investment decision‐making. In the analysis of such active fundamental investors, ESG concerns tend to show up as risk factors that can translate into higher costs of capital and lower values. And companies’ effectiveness in managing such factors, as reflected in high ESG scores and rankings, is viewed by many fundamental investors as an indicator of management “quality,” a reliable demonstration of the corporate commitment to investing in the company’s future. Moreover, some fixed‐income investors are equally if not more concerned than equity investors about ESG exposures. ESG factors can have pronounced effects on performance by generating “tail risks” that can materialize in both going‐concern and default scenarios. And the rating agencies have long attempted to reflect some of these risks in their analysis, though with mixed success. What is relatively new, however, is the frequency with which fixed income investors are engaging companies on ESG topics. And even large institutional investors with heavily indexed portfolios have become more aggressive in engaging their portfolio companies on ESG issues. Although the traditional ESG filters used by such investors were designed mainly just to screen out tobacco, firearms, and other “sin” shares from equity portfolios, investors’ interest in “tilting” their portfolios toward positive sustainability factors, in the form of low-carbon and gender‐balanced ETFs and other kinds of “smart beta” portfolios, has gained considerable momentum.

Abstract: Many investors are starting to explore ways to integrate environmental, social, and governance (ESG) considerations into their portfolios. Factor portfolios and indexes that integrate ESG allow investors to capture both the long-term durable factor premiums while allowing them to invest in companies with attractive ESG attributes. Traditional factors and ESG both have strong investment rationale for investors with long horizons, but how should blended ESG-factor portfolios be constructed? This article discusses several ways to integrate ESG into factor portfolios. The authors show that the approach chosen depends on the investor’s investment rationale behind integrating ESG, desired exposure, performance expectations, and preference for conceptual consistency.

Abstract: Minimum volatility (min vol) strategies are smart beta strategies that are designed to minimize risk. In the past 12 months, ending June 30, 2016, there were $7.8 billion flows into a total of 17 U.S.-equity exchange-traded fund min vol strategies. This represents just 0.04% of total equity market capitalization of the underlying securities. Capacity in these strategies is large because traditional active mutual funds tend to overweight high-volatility stocks. Were these funds to move to a neutral position in high-volatility securities, a shift of roughly $600 billion to min vol would take place. Current valuations of min vol strategies are not high relative to historical norms and are consistent with the observed outperformance of these strategies during periods of high uncertainty.

Abstract: This is the first in a series of papers we will publish in 2017 that demonstrate factor tilts generally deliver far less alpha in live portfolios than they do on paper, or put another way, investment managers generally fail to capture the returns that would be expected based on their factor tilts. We break our research into four parts. In this paper we show that the factor returns realized by fund managers differ starkly from the theoretical factor returns constructed from long–short paper portfolios. Notably, the market, value, and momentum factors are far less rewarding in live fund management than their theoretical long–short paper portfolio returns. In the second paper of the series, we challenge the idea that factor tilts — portfolios combining several theoretical factor portfolios — are the same as smart beta strategies. We show, using Fundamental Index™, equal-weight, and low-volatility strategies as illustrative examples, that factor tilts cannot successfully replicate smart beta strategies. Although the factor tilts of these strategies are easy to replicate, the resulting portfolios look very different from the originals, with the replication portfolios having far higher turnover, lower performance, and smaller capacity. In a third paper of the series, we show that the relative valuations of factor loadings can give us the courage to buy mutual funds when factor tilts are at their cheapest, hence, the most out of favor. Along with fees, turnover, and past performance — where low fees, low turnover, and low (yes, low!) past performance are predictive of better future returns — factor loadings can help us improve our forecasts of fund returns. We find the best predictor is prior three-year performance, but with the wrong sign: buying the losers is the winningest strategy. Finally, a fourth paper will take a closer look at momentum, for which we find the realized alpha in live portfolios is essentially zero compared to a theoretical alpha of around 6% a year. We show why momentum doesn’t work in live portfolios, and also show how momentum can be saved as a useful source of alpha.

Abstract: We challenge the common view that smart beta strategies and factor tilts are equivalent. Initially, the term “smart beta” referred to strategies that broke the link between the price of a stock and its weight in the portfolio or index. Capitalization weighting does not do that — neither does a portfolio that applies factor tilts to a cap-weighted starting portfolio. Some have suggested that certain smart beta strategies are essentially factor tilt strategies in disguise, which can be replicated with factor tilts applied to a cap-weighted market portfolio. We test this assertion by replicating three first-generation smart beta strategies — Fundamental Index™, equal weight, and minimum variance — with factor tilts. Creating factor-replicated portfolios that match the factor loadings of these smart beta strategies is easy, but the factor-replicated portfolios are poor substitutes for their smart beta counterparts: performance is poor, turnover is high, and capacity is terrible. Why? The simple answer is that construction details matter in achieving both lower trading costs and higher performance.

Abstract: Size factor (small minus big) is a significant and positively priced anomaly in the Chinese stock market. Retail investors in China hold more small stocks but still under-perform the market. Institutional investors in China hold more big stocks but still outperform the market. We address this puzzle by studying the size-factor-timing skill of institutional investors. First, we find that Chinese actively managed stock mutual funds possess significant size-factor-timing skill that helps generate significant alpha. Second, we find that the size-factor-timing skill is persistent among high-alpha funds. Third, we estimate fund position in different size portfolios and show that it significantly forecasts subsequent size-factor returns. We conclude that Chinese mutual funds’ timing ability on the size factor helps them beat the market at the expense of retail investors.

Abstract: It looks like exchange-traded funds (ETFs) are eating mutual funds’ lunch. Although we think this is more an index versus active story, it has not stopped mutual funds from looking to convert their active strategies into ETFs. The active ETF space is already alive and well: Active strategies already exist in the form of transparent active and smart beta funds. Although assets in these funds remain small, they are on a growth path that is consistent with that of index funds. The arbitrage mechanism helps active and smart beta ETFs track their net asset values very well, which is good for investors. Nontransparent active ETFs would help larger, active managers hide their trades from predatory traders and might also lower transaction and holding costs to investors. To date, none has been approved because of concerns over their tradeability. We think that they would likely have wider spreads than current ETFs but would trade much better than closed-end funds (which also trade on exchange intraday).

Abstract: Using a transaction cost model, and an assumption for the smart beta premium observed in data, we estimate the capacity of momentum, quality, value, size, minimum volatility, and a multi-factor combination of the first four strategies. Flows into these factor strategies incur transaction costs. For a given trading horizon, we can find the fund size where the associated transaction costs negate the smart beta premium, assuming current rebalancing trends and holding constant other market structure characteristics. With a trading horizon of one day, we find that momentum is the strategy with the smallest assets under management (AUM) capacity of $65 billion, and size is the largest with an AUM capacity of $5 trillion. Extending the trading horizon to five days increases capacity in momentum and size to $320 billion and over $10 trillion, respectively.

Abstract: A smart beta portfolio that tracks an explicit smart beta index has two performance benchmarks: the smart beta index itself and a cap-weighted index that represents the broader equity market. This dual performance objective creates a trade-off whenever the portfolio is large relative to the liquidity of the smart beta index. A portfolio that fully replicates the smart beta index, and trades all shares near the close on each rebalancing date of the smart beta index, can incur significant transaction costs and thereby adversely affect the performance of the smart beta index vis-a-vis the cap-weighted market. This article shows that sampling (by excluding the least-liquid stocks) and trading patiently (by trading over a longer interval of time) can reduce expected transaction costs and improve the performance of the smart beta index (and, by extension, the smart beta portfolio). Sampling and patient trading cause tracking error between the smart beta portfolio and the smart beta index. However, this tracking error, when modest, has very little impact on the tracking error between the smart beta portfolio and the cap-weighted performance index. The authors conclude that the optimal level of tracking error between the smart beta portfolio and the smart beta index may be much higher than the level usually chosen for a cap-weighted passive portfolio.

Abstract: Traditionally, passive portfolios are structured using an easy to implement market capitalization method albeit highly skewed towards large cap stocks. The introduction of smart beta strategies has allowed passive investors to structure equity portfolios using alternative strategies such as fundamentalweighting, equal-weighting, and low-risk weighting strategies. This paper investigates whether constrained portfolios such as Shari’ah-compliant equity portfolios (SCEPs) can benefit by adopting smart beta strategies. The sample consists of equities from the USA, Canada, Australia, Europe, Middle East, Indonesia, and Malaysia for the period January 2003 to December 2016. The empirical findings suggest that smart beta SCEPs outperform not only conventional market capitalization weighted portfolios but also SCEPs following a market capitalization-weighted strategy. Higher risk-adjusted returns and lower drawdown as a result of following smart beta strategies highlight the importance of considering smart beta portfolio weighting strategies for passive investors. The supremacy of smart beta strategies indicates the value proposition for investors and fund managers alike. We also found that geographical location affects the performance of smart beta SCEPs; countries with a Muslim majority report higher cardinality and lower drawdowns. The results remained robust with alternative Shari’ah screening guidelines and empirical estimation methodology.

Abstract: In a series of papers we published in 2016, we show that relative valuations predict subsequent returns for both factors and smart beta strategies in exactly the same way price matters in stock selection and asset allocation. To many, one surprising revelation in that series is that a number of “smart beta” strategies are expensive today relative to their historical valuations. The fact they are expensive has two uncomfortable implications. The first is that the past success of a smart beta strategy—often only a simulated past performance—is partly a consequence of “revaluation alpha” arising because many of these strategies enjoy a tailwind as they become more expensive. We, as investors, extrapolate that part of the historical alpha at our peril. The second implication is that any mean reversion toward the smart beta strategy’s historical normal relative valuation could transform lofty historical alpha into negative future alpha. As with asset allocation and stock selection, relative valuations can predict the long-term future returns of strategies and factors—not precisely, nor with any meaningful short-term timing efficacy, but well enough to add material value. These findings are robust to variations in valuation metrics, geographies, and time periods used for estimation.

Abstract: The non-existence of commercially available Islamic Equity Style Indices from index providers such as MSCI especially on small value and small growth stocks motivates us to construct our new indices. Firstly, various index construction methods are compared. Secondly, this paper describes in detail the process of index construction and finally, the new indices are tested using out-of-sample forecast and trading strategies. Notably, our results show Large Growth (LG) and Large Value (LV) indices have more efficacy compared to Small Growth (SG) and Small Value (SV) stocks. From the perspective of Islamic financial market, the creation of Islamic equity style index enables new strategies which focus on size, value, and smart beta. In addition, the out-of-sample VAR forecast indicates that LG and LV indices are the best candidates for creating a new benchmark for portfolio diversification. Furthermore, by applying simple trading strategies and selecting Islamic value and small market capitalization sto...

Abstract: Rules-based non-market cap-weighted index-based investing, also known as smart beta, advanced beta, factor investing and risk premia investing among its many names, has generated a lot of research over the past several years. As detailed, the concept of passively managed portfolios (PMF portfolios) has been around since the 1980s. Its foundations are decades long starting with Rosenberg and Marathe and Ross. PMF investing can generally be viewed as a way for investors to capture key sources of return (factors) through a rules-based cost-efficient index. Well-known factors are those such as value, size and momentum but our framework here can, in theory, apply to any targeted source of return or investment theme. Bender et al. provide a review of the foundations of factor investing.

Abstract: In this article, the authors provide a flexible and adaptive framework that allows one to construct a suite of long-only smart beta portfolios over a spectrum of risk characteristics, subject to different constraints, while preserving as much of the information in the original risk premia as possible. In their opinion, smart beta portfolios constructed according to the proposed framework represent theoretically efficient implementations of risk premia for investors who face constraints on short-selling or other restrictions on portfolio construction.

Abstract: In this paper we consider the question of how to improve the efficacy of strategies designed to capture factor premiums in equity markets and, in particular, from the value, quality, low risk and momentum factors. We consider a number of portfolio construction approaches designed to capture factor premiums with the appropriate levels of risk controls aiming at increasing information ratios. We show that information ratios can be increased by targeting constant volatility over time, hedging market beta and hedging exposures to the size factor, i.e. neutralizing biases in the market capitalization of stocks used in factor strategies. With regards to the neutralization of sector exposures, we find this to be of importance in particular for the value and low risk factors. Finally, we look at the added value of shorting stocks in factor strategies. We find that with few exceptions the contributions to performance from the short leg are inferior to those from the long leg. Thus, long-only strategies can be efficient alternatives to capture these factor premiums. Finally, we find that factor premiums tend to have fatter tails than what could be expected from a Gaussian distribution of returns, but that skewness is not significantly negative in most cases.

Abstract: Exchange Traded Funds are the fastest growing segment of investment management business. Over last eleven years ETF’s AUM grew over 2,000% This paper explores growing popularity of this investment vehicle and getting to the genesis of index tracking funds and to the roots of indexing, bares shortcomings of most common weighting scheme – capitalization weighting. Those flaws caused the rise of quantitative investing. The author reviews the literature in search of the most relevant Smart Beta definition and the reasons why this new investment concept is blooming nowadays. The substance of this paper is presentation of most popular alternative weighting schemes and exploration of their pros and cons by implementing those solutions to polish index WIG20. The impact of alternative weighting on performance of the index and its features has been synthesized and evaluated. In the result of this analyses and comparison cap-weighted WIG20 turned out to be the less effective weighting scheme.

Abstract: This article shows that it can take a long period of time until research knowledge finds its application in practice and get disseminated as innovation trend. Factor-based investing is such an example. Having its developing roots in the nineties, it took more than two decades until this approach was detected by the by investment community. The goal of this article is to recall the definition of factor investing, present its historical evolvement and motivate its recent break-through and current trend among investment practitioners (known also under the notion smart beta). It aims at familiarizing with this investment approach from a practical perspective and highlighting its diversifying benefits in a portfolio context with the potential to outperform the market on risk-adjusted basis.

Abstract: In traditional life-cycle models, the equity-bond glide path shifts investment allocation from riskier assets to relatively safer assets as investors approach retirement. In this article, we develop a smart beta glide path that seeks to take advantage of broad, persistent patterns within asset classes to identify securities with higher risk-adjusted returns than the market. Within equities, investors can shift from return-enhancing strategies—like value, momentum, size, and quality—to risk-reducing strategies like minimum volatility as they move through the life cycle. Adopting smart beta glide paths may improve Sharpe ratios by up to 20% over a standard equity-bond glide path.

Abstract: The most common strategies using risk factor approaches are found on the opposite ends of the complexity spectrum: simple, long-only equity factor strategies (i.e., smart beta) and multiasset class long/short risk premia approaches that often employ leverage and derivatives. The space between these two poles is just starting to be explored, as risk factors become a more common feature of both portfolio attribution and portfolio construction. Today’s simple factor smart beta portfolios can be extended across multiple asset classes, coupled with shorting, in order to approach a diluted risk premia approach.

Abstract: Smart beta has been an important investment phenomenon in the past several years. However, some researchers have reservations about the future prospects of smart beta strategies and their application in retirement investing. This article argues that one smart beta factor, the low-volatility premium, may be uniquely suitable for retirement investing because retirement investors’ main concern is the certainty of investment outcomes. This article compares simple portfolios that use both regular equities and low-volatility assets via scenario analysis and Monte Carlo simulations. The study shows that low-volatility assets may indeed deliver better outcomes in both the accumulation and distribution stages of a retirement investor’s life cycle. Investors need to understand the return assumptions of various assets and make investment choices that are consistent with their views. The study also suggests that investors in the distribution stage may benefit significantly from fixed-income annuities. The article concludes by suggesting that both institutional sponsors of defined contribution plans and individual investors consider low-volatility assets as key components of their retirement plans.

Abstract: Although the proliferation of “smart beta” products using various style factors makes them seem new, many of these factors have been used in portfolio construction and risk management for decades. This article examines the historical performance of style risk factors to show that 1) their returns vary widely through time, and even those with no long-term return association can have unexpected, outsized returns at times; 2) across geographical regions, the same factor can exhibit quite different returns at the same time; and 3) an investor’s goals need to be considered when deciding which factors are appropriate to use to generate portfolio alpha.

Abstract: We propose a new framework for alternative risk premia investing to facilitate the construction of balanced portfolios of commonly known strategies across asset classes. The categories of the framework, fundamental, behavioral, and structural premia, describe the nature and the robustness of the premia within the category. Each of the categories is further divided into a defensive and offensive compartment depending on the risk characteristics of the premia.