75% of investors are aware of risks in investing in Bitcoin, according to Gallup poll. However, a majority of your investors have some understanding of Bitcoin, forming a potential pool of investors in the future.
The Turkish economic situation is threatening a global contagion crisis. These crises seem to come about every 10 years:
1978 - Oil Shock Crisis
1987 - Stock Market Crash
1998 - Asian Financial Crisis
2008 - 2008 Financial Crisis
2018 - Turkish Financial Crisis?
Hedge funds (along with liquid alternative investments) and smart beta funds have been among the fastest growing investment vehicles over the past few years. I believe that the reason for this growth is that they both appeal to the investors’ focus on factors or performance drivers rather than alpha or labels. More and more, investors view investments as a bundle of factors that are evaluated for their impact on the overall portfolio.
Major market factors (i.e., stocks and bonds) are gained through index funds and ETFs. Once these are included in a portfolio, investors seek investments with factors that either add diversification to their portfolio or produce better risk adjusted returns that existing portfolio assets. Because hedge funds and smart beta funds are driven by similar factors and play similar roles in investment portfolios, it is inevitable that they will compete for the same investors.
Factors in this context are economic or financial variables that act as drivers in the risks and returns of an investment. The term is grounded in regression analysis where independent variables (factors) are correlated to (and presumed to determine) the dependent variable (here the investment return). The general formula for the linear case is as follows: Y = a + b(factor 1) + c(factor 2) +d (factor 3)…… Were Y is the performance of a security, index or fund, a is the alpha and b, c, and d are the betas that measure the degree to which each factor impacts Y. The Fama-French three-factor model was the first popular framework for factor investing. According to the model, stock returns are a function of not only the major market (i.e., the S&P 500), but also of two additional factors: value vs. growth and size (market capitalization) of the stock. Since then, literally dozens of factors have been found to help explain the returns of not only stocks, but also mutual funds, ETFs and hedge funds. Fung and Hsieh for example developed a 9-factor model to explain hedge fund index returns. Fama and French themselves added two additional factors to develop the 5-factor model. Andrew Lo introduced momentum as an important factor in explaining hedge fund and mutual fund returns. In a famous study by Jasmina Hansanhodzik & Andrew Lo, “Can hedge fund returns be replicated: the linear case,” ((Journal of Investment Management, Vol. 5, No. 2, (2007), pp. 5–45) the authors identify five factors that are correlated with hedge fund performance: 1) equity markets; 2) US Dollar; 3) Credit spreads; 4) bonds and 5) Commodities. One of the leading practitioners of the factor approach to investing is AQR, headed by Cliff Assness. Assness identifies a number of factors that drive investment returns including value, momentum, profitability, low volatility, interest rate carry, and defernsive company stock. One of the unique features of the AQR funds is their willingness to take both long and short positions in these factors, effectively doing away with the distinction between hedge funds, liquid alternative investments and smart beta.
One of the major fall-outs of factor investing is the dramatic shrinking of investment alpha as returns that were originally attributed to manager skill turn out to be correlated with various factors. Increasingly, what was once described as alpha generation by investors is shown to be a result of a factor which explains the return. With a shrinking alpha, investors are focused on factors in building their portfolios. Factors influence investment return independent of the skill of the investment manager. The idea is to let a statistical model determine the optimal number of factors and their relative size in order to maximize performance. (Of course, there is manager input in the initial factors that are included in the model as well as the manner in which the factors are measured). Any return on an investment in excess of the influence of factors is said to be “alpha,” a measure of investor manager skill.
Types of Factors
There are three types of factors that are used in factor models. although some factors are more than one type: Market Exposure Factors – these factors provide non-correlated exposure to various betas in order to provide diversification in investment portfolios Risk Premium Factors – these factors are riskier than risk-free assets and therefore provide investors with a risk premium Market Anomoly Factors – these factors take advantage of market anomolies, such as those caused by emotional behavior of market participants.
Smart Beta Products
Smart beta strategies, which are frequently referred to as multi-factor products or strategic beta, use one or more factors to construct portfolios that either outperform, have a lower correlation or provide a different risk/return profile than the traditional fund weighted indices. The most common factors and anomalies include carry trades, momentum, volatility, value, size, liquidity and quality. Smart beta has been applied to both equities and fixed income. Smart beta funds now number over 600 and represent almost 20% of ETFs, with $400 billion under management. Whereas hedge fund strategies are presented as being either diversifiers or replacements, common portfolio goals for various smart beta include risk parity, maximum diversification, defensive, high dividend, quality and fundamental. (It is noteworthy that smart beta provides a much wider range of roles than hedge funds.) You will note that there is an overlap in some of the factors listed above, notably credit spread, equity markets, bonds, and momentum. However, smart beta exposure costs under 40 basis points and comes in ’40 Act funds that have complete transparency and liquidity and extensive government supervision, while hedge funds’ baggage includes high management fees and incentive compensation; lock-ups and redemption restrictions; lack of government supervision; little transparency; and legal and administrative hassles.
Active Factor Fund
A group of funds recently launched by Unigestian with seed money from the U.K. pension fund RPMI Railpen is an example of a cross over fund that seeks to incorporate factors typically associated with smart beta funds in a liquid alternative investment. The funds are described as follows: “The funds being launched are a long-only active factor fund combining a number of identified factors and a long/short factor fund which follows a market neutral, pure alpha strategy aiming to profit from both positive and negative factor exposure. The factors included in the funds are value (Price/Book, Price/Earnings, Price/Sales, Price/FFO), Momentum (one year return), quality (profitability and leverage), and size (market cap).” We will undoubtedly see many examples of this type of crossover fund in the future.
The Department of Labor put in place a fiduciary rule in 2016 to regulate the behavior of brokers when dealing with retirement accounts. The rule embodied the "strong form" of retirement regulation calling for brokers to place their clients' interest ahead of their own. However, the federal appeals court struck down the regulation in March, 2018 and the Trump Administration has indicated it will not challenge the ruling, leaving the obligations of brokers to their retirement accounts in limbo. The Securities and Exchange Commission has released an ambiguous proposal that would require brokers "to act in the best interest of the retail client." To make matters worst, the SEC states "we are not proposing to define best interest at this time." We will continue to track this important issue in subsequent blogs.
Ezra Zask, President, Ezra Zask Research Associates
One of the most controversial questions in the investment world is: why do hedge funds keep gaining assets when their performance over the past decade has been relatively poor compared to stocks? After all, hedge fund returns have lagged the S&P for the past 7 years; a period that covers a full business cycle.
One way they have accomplished this feat is by changing the definition of “performance” over time to overcome the inability to live up to the preceding definition. Thus, high return was replaced by downside protection, alpha and, most recently, diversification and risk reduction.
Hedge funds have faced a number of challenges over the past three decades that have led to fundamental changes in their objectives and operations. A short list of these challenges includes the proliferation of hedge funds and hedge fund strategies; the institutionalization of hedge fund investors; economic crises in 1987, 1994, 1998, 2001 and 2008; sustained stock bull market, and increased criticism of hedge fund performance and fees.
As with any evolution, some hedge funds thrived -- at least in terms of increasing assets under management and generating income for their managers --while others either became extinct or are an endangered species. In the course of this evolution, the surviving hedge funds would not be recognized by investors of 20 years ago.
The performance criteria that hedge funds are expected to meet has changed dramatically over the years. We can broadly identify three hedge fund performance regimes.
In broad strokes, Hedge Fund 1.0, which was dominant in the 1980’s and 1990’s, touted the outsized return that were available through hedge fund investments. George Soros and Julian Robertson were the models for these managers. However, as the hedge fund field became crowded, hedge funds were forced to compete in well-arbitraged markets and these outsized returns became more and more rare. The process was accelerated by the larger scale of funds who were unable to meaningfully invest in small markets.
Hedge Fund 2.0 focused on the downside protection and absolute return measure of hedge fund performance as proven by their relatively small losses compared to other investments during the Asian crisis of 1998, and the Internet bubble of 2001. This hedge fund meme exploded during the Credit Crisis in 2008 when hedge funds as a group lost over 20%. (While still lower than the S&P loss of over 40%, the loss was not supposed to occur under hedge fund 2.0)
Hedge fund 2.0 also included the notion that hedge funds added the elusive and much sought after investment alpha (returns above market returns) which ostensibly resulted from manager skill or unexploited market opportunities. This alleged benefit was also whittled away as new sources of beta were identified (specific to hedge fund strategies and markets) and reduced the size of available alpha.
In hedge fund 3.0 performance no longer holds hedge funds to a benchmark or, indeed, any return criteria. The performance criteria of hedge fund 3.0 is summarized in a paper published by the Alternative Investment Management Association (AIMA), a hedge fund industry group, and the Chartered Alternative Investment Association (CAIA), which provides certification for alternative investments. The paper is titled “Portfolio Transformers: Examining the Role of Hedge Funds and Diversifiers in an Investor Portfolio.” In this paper, hedge funds are touted as either portfolio diversifiers or investment substitutes (for traditional stocks and bonds). The benefits for investors that result from including hedge funds in their portfolios include the following:
Employing this approach (where hedge funds take on the role of a substitute or complement the equity or fixed income portfolio) offers an investor a way of reducing the volatility (risk) within their public equity allocation, with little if any reduction in the portfolio’s total performance.
One of the interesting aspects of Hedge Funds 3.0 is that performance defined as beating a benchmark (whether S&P or any other benchmark) is no longer required for a hedge fund to be successful. The most that is held out to investors is that hedge funds “offer a higher probability of generating-outsized returns (albeit by taking on a higher level or risk,” which is true of any risky investment.) The second crumb offered to investors is that diversification via hedge funds results in “little if any reduction in the portfolio’s total performance.”
Both of these measures of “success” may come back to haunt hedge funds because it places them squarely in competition with other “substitutes” and “diversifiers” such as smart beta, commodities, and index funds.
Ezra Zask has been actively managing, consulting, teaching, advising, writing and speaking on hedge fund and investment management issues for over three decades.