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This article focuses on the AlphaClone Hedge Fund Masters Index in the context of constructing the optimum portfolio. When building an optimum portfolio, the objective is to figure out the portfolio weights across different asset classes that achieve a specific optimization goal.

Our analysis constructs four different portfolios, each optimized for a different outcome:

Maximize Sharpe Ratio
The first optimization is to simply maximize the portfolio’s Sharpe ratio. In short, this is the portfolio that gives you the biggest return at the lowest risk. For you nerds, this is the optimal risk adjusted portfolio that lies on the efficient frontier.

Maximize Returns @ 8% Volatility Target
Optimizations that seek to solve for a specific volatility target first usually mean that the investor has certain recurring obligations they must satisfy from the proceeds of their portfolio. The goal is control risk first, then try to maximize returns without exceeding the client’s “risk budget”.

Minimize Volatility @ a 10% Return Target
Investors who seek a specific return target first and then seek to minimize volatility are usually long term buy and hold investors. As an example, an investor who has fallen behind on his or her retirement objectives may need to increase their target rate of return going forward but wants to make sure they are not taking on any extra unnecessary risk. They seek their return target but at the lowest possible risk.

Risk Parity
Risk parity is another risk first approach to portfolio optimization. By equally distributing the portfolio’s risk across the asset classes that make up the portfolio, the investor seeks to ensure they are not overexposed to any one class. Risk parity investors are primarily concerned about concentration risk in their exposures.

We compare each optimized portfolio with a “Starting Portfolio” that allocates to the funds/indexes below, each selected to represent an asset class:

Bonds: Vanguard Total Bond Market Index (VBMFX)
US Stocks (Passive): iShares Core S&P 500 ETF (IVV)
Foreign Stocks (Developed): Vanguard Developed Markets (VTMGX)
Foreign Stocks (Emerging): Vanguard Emerging Mkts Index (VEIEX)
US Stocks (alpha-seeking): AlphaClone Hedge Fund Masters (ALFMIX)
Precious Metals (Gold): Fidelity Select Gold (FSAGX)
Alternatives: DWS Global Macro (MGINX)

Methodology

We run our optimization exercise unconstrained in terms of minimum or maximum weightings for each asset class. We recognize that this may result, depending on the optimization goal, in a portfolio with a 100% weight to a single asset class – but we think for the purposes of this exercise, that outcome helps illuminate the role of each asset class in the portfolio. It also means that the optimization, with the exception of Risk Parity, is free to discard one or more asset classes (including ALFMIX).
We selected the specific funds above to maximize the analysis period which is from Aug 2001 to Dec 2019 (constrained by the inception month for ALFMIX).
We select the global macro hedge fund style for the alternatives sleeve because most investors (at least these days) allocate to alternatives to reduce the portfolio’s correlation to equities. We chose the global macro style because it has the lowest correlation to equities relative to other hedge fund styles (see this MSCI article). Ironically, the asset class with the lowest correlation to equities are not alternatives (or global macro) but bonds and gold (see correlation matrix here).

Figure 1 below summarizes allocations and portfolio metrics for each optimized portfolio.

Key Findings

Looking across the different optimized portfolios, it is obvious that investors really don’t need much more than stocks and bonds to achieve most optimization goals.
Most investors/advisors would likely opt to use the optimizations represented by P2 (maximize returns @ 8% volatility) or P3 (minimize volatility @ 10% return target) in the figure above. Because they are unconstrained, both optimizations allocate to only 3 of the 7 asset classes available.
With the exception of the Risk Parity (P4) portfolio, which must allocate to each of the 7 asset classes available, all of the optimizations favored ALFMIX exclusively over the S&P 500 for exposure to US equities. That’s not surprising given that ALFMIX has both a higher CAGR and risk-adjusted returns than the S&P 500 (see Figure 2).
For all of the optimized portfolios, every 1% in volatility yields about 1% in expected returns.

Practical Implications for Portfolio Allocation

It is instructive that unconstrained portfolio optimizations would seek to use the ALFMIX index to the exclusion of any other available equity fund. While building a portfolio or even an equity sleeve from only two or three funds may not be realistic, adding ALFMIX to whatever mix of equity exposures you have clearly adds value.

So, what’s the right allocation to ALFMIX? Of course, it depends but one way to think about your equity exposure is along a passive/active continuum. Passive sources of returns have never been easier or cheaper to access but low cost, efficient active sources of returns are a lot harder to come by – that’s where ALFMIX shines. For example, a portfolio that is 50% weighted to US equities and which seeks to achieve risk parity, might allocate 20% (40% of the total 50% equity exposure) to ALFMIX and 30% to the S&P 500. On the other hand, the same portfolio for a client who has a higher “risk budget” could increase their exposure to ALFMIX until the client’s risk budget is achieved.

© 2020, All Rights Reserved. The AlphaClone logo is a service mark of AlphaClone, Inc. The information contained herein (the “information”) may not be reproduced or re-disseminated in whole or in part without the prior written permission from AlphaClone, Inc. AlphaClone, Inc. is a registered investment advisor with the SEC. Registration of an investment advisor does not imply any level of skill or training. AlphaClone’s investment products seek capital appreciation as their investment objective. There can be no assurance that the investment objective will be achieved. Past performance is not indicative of future results. Consider the investment objectives, risks, charges, expenses and instruments used to implement a strategy before investing. This communication does not constitute an offer or a solicitation to invest with AlphaClone, Inc.

The AlphaClone Hedge Fund Masters Index (ALFMIX) is an index of high conviction equity holdings derived from hedge fund public disclosures and selected by AlphaClone. ALFMIX was launched on August 25, 2017 and is calculated by Solactive. Any performance prior to that date is hypothetical. The S&P 500 Index is an index of large capitalization US equities. It is not possible to invest in an index.

AlphaClone Index vs Peers

by Maz Jadallah

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As of August 31, 2021

Over the prior 44 months, the AlphaClone Hedge Fund Master Index (ALFMIX or “AlphaClone Index”) has outperformed its peers and the overall market. Our analysis period is as of the first full month the AlphaClone index became available as an ETF; January 1, 2018, through August 31, 2021.

The AlphaClone Index seeks to identify and access investment managers with high alpha potential by analyzing their regulatory holdings disclosures (Form 13F-HR). Other indexes use the same 13F dataset but construct their indexes very differently and, as the table above shows, generate very different results.

For example, the Goldman Sachs Hedge Industry VIP index seeks to access the 50 holdings that are most popular amongst hedge fund managers’ largest disclosed positions. As such, it yields a very different portfolio with only a 25% overlap by weight with AlphaClone’s index (see graphs below).

As always, before considering an index, please make sure to review each index’s methodology document to understand how it is constructed.

© 2021, All Rights Reserved. The AlphaClone logo is a service mark of AlphaClone, Inc. The information contained herein (the “information”) may not be reproduced or re-disseminated in whole or in part without the prior written permission from AlphaClone, Inc. AlphaClone, Inc. is a registered investment advisor with the SEC. Registration of an investment advisor does not imply any level of skill or training. AlphaClone’s investment products seek capital appreciation as their investment objective. There can be no assurance that the investment objective will be achieved. Past performance is not indicative of future results. Consider the investment objectives, risks, charges, expenses and instruments used to implement a strategy before investing. This communication does not constitute an offer or a solicitation to invest with AlphaClone, Inc.

The AlphaClone Hedge Fund Masters Index (ALFMIX) is an index of high conviction equity holdings derived from hedge fund public disclosures and selected by AlphaClone. ALFMIX was launched on August 25, 2017 and is calculated by Solactive. The Solactive Guru Index (GURU Index) tracks the price movements of the top equity holdings of a select group of hedge funds based on the quarterly regulatory filings reported to the SEC. The Index is calculated as a total return index in USD and weighted equally. The Goldman Sachs Hedge Fund VIP Index (GVIP Index) consists of hedge fund managers’ “Very-Important-Positions,” or the US-listed stocks whose performance is expected to influence the long portfolios of hedge funds. Those stocks are defined as the positions that appear most frequently among the top 10 long equity holdings within the portfolios of fundamentally-driven hedge fund managers. The Index is rebalanced on a quarterly basis to reflect changes in reported hedge fund manager holdings. The Russell 1000 Growth Index is an index composed of large- and mid-capitalization U.S. equities that exhibit growth characteristics. The S&P 500 Index is an index of large capitalization US equities. It is not possible to invest in an index.

The Fast Money Takes It Slow

by Maz Jadallah

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It’s a virtual certainty. You can bet your bottom dollar on it. Whenever we discuss our methodology with prospective investors, the first question ALWAYS relates to the delayed nature of Form 13F filings. The implication is that a hedge fund manager is likely to have already exited their position by the time the manager’s quarterly filing is published 45 days after quarter end, rendering the form useless.

After nearly six years, our response is also now very predictable. The truth is hedge funds hold their positions on average for at least a year and for high conviction holdings it can be much longer than that, therefore disclosing positions quarterly can yield valuable information about a security.

In this research note we take a definitive look at hedge fund holding periods. We analyze holding periods for all Form 13F disclosed securities as well as for those held with high conviction. We also look at whether the length of a manager’s holding period is predictive in any way to the efficacy of following their holdings.

Exhibit 1 summarizes the distribution of funds in AlphaClone’s universe by holding periods. The analysis includes every holding for every fund in our universe. Holdings that appear, disappear and then appear again later are treated as separate trades. Holding periods are presented in months.

It turns out the fast money isn’t that fast after all. The average holding period across all positions is over 17 months. It makes intuitive sense then that if managers are waiting on average a year and a half to realize their investment thesis, the fact they must file quarterly means that following them based on their disclosures can make sense …. assuming the manager has skill in selecting holdings.

Conviction matters.

Let’s dig a little deeper. When it comes to active management, conviction matters. Positions that rank among the manager’s largest will drive performance, for better or worse. Therefore, high conviction positions are where the manager must have the most confidence. High conviction holdings also tend to do better when followed than the average holding overall so it’s worth taking a look at holding periods for high conviction holdings only.

Exhibit 2, summarizes the distribution of funds in AlphaClone’s universe by holding period, for high conviction positions. For the purposes of this analysis we define high conviction positions, as any position who’s size has attained a rank of 10 or lower (a rank of 1 is the highest conviction position and the largest position) in a manager’s portfolio at any time over the course of the manager’s holding period. Like in the previous analysis, holding periods are presented in months.

Surprisingly perhaps for many, the average holding period for high conviction positions is a staggering 4 years! Perhaps the most remarkable outcome from Exhibit 2 is the contrast between reality and conventional belief around how hedge funds invest. Fed by the financial media, investor perception is that hedge funds are charlatans getting rich off of high fees, playing a game that the average investor could not hope to understand let alone profit from. Hedge funds are hot money, fast money, smarter than you money when the market is up, and the money we love to hate when the market is down. The reality of course is the opposite, hedge funds don’t play by a different set of investing rules; they buy and hold, they are patient, and yes, on average they are indeed more skilled than most investors, but that’s because they are more experienced and better equipped, not be because the laws of investing physics are somehow different for them.

Too much of a good thing.

Using 13Fs to follow experienced investors can be deceptively easy. Many investors fall in love with a manager’s stellar returns, with the manager’s brand or their cult of personality. A novice 13F follower figures they can “roll their own” and be wildly successful. Again reality does not match perception. Like any investment approach, success using 13Fs takes doing your homework, it takes discipline and it takes patience.

For example, many 13F followers, including some of our competitors, believe low turnover is a key determinant for success when selecting which managers to follow. The idea is that low turnover managers hold their positions for very long periods of time and therefore following their disclosed holdings makes the most sense, especially when they also have a great historical performance record.

Exhibit 3 correlates manager holding period with the efficacy of cloning their holdings. For the purpose of this analysis we define cloning efficacy by summing the monthly excess returns (2010-2015) of a composite made up of several “follow simulations” or “clones” (e.g. follow top 5 holdings, follow top 10 holdings, etc.) over a US market factor. All simulations account for the delay inherent in 13F disclosures and include the effects of “dead” or delisted securities, thereby avoiding survivorship bias.

The scatter plot above couldn’t more clear. There is absolutely zero correlation between a manager’s holding period and the desirability of cloning their positions. Longer holding periods are necessary to make a manager’s disclosures usable but not sufficient to determine which manager to follow. Like many of the best investment disciplines, utilizing Form 13F successfully is simple but not easy.

Active v Passive – A False Choice

by Maz Jadallah

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The active vs passive debate continues unabated in the financial media. Passive strategies continue to accumulate assets while active strategies lose them causing many to proclaim that active investing is dead. Let’s take a step back and try to separate reality from hype.

Despite passive’s impressive gains, the amount of assets being managed actively is still greater. According to the Investment Company Factbook, at the end of 2017 there was approximately $12 trillion in actively managed mutual funds vs $7 trillion in index mutual funds and ETFs combined. Add $3 trillion in hedge fund assets and you get about a 2 to 1 ratio of active over passive. So at least historically, investors have had a real need for active strategies. What was that need? Why has it changed? Will it change again in the future? The answer to all of these questions can best be explained looking through the lens of one of the most enduring traits exhibited by investors – the fact they chase performance.

Passive strategy performance has been by far better than active performance since the financial crisis (see table below). Believe it or not, investors over the past 10 years have enjoyed 4 in 5 odds that the S&P 500 returns 10% or more annually – the historical average (since 1949) is only 1 in 3, and the average during periods of increasing interest rates (like now!) is even worse at 1 in 5. So when the S&P 500 is at its historical return average (6-8%/year) or less, investors apparently want to try and do better. Conversely when returns are 10%/year or greater investors don’t see as much of a need for active. The key question then becomes – will 10%+/year US market index fund returns continue for the foreseeable future?

Perhaps recognizing the ominous signs of lower future market returns, #Vanguard (the kings of passive investing) and #Morningstar have weighted in on the need for balance between active and passive strategies in a portfolio. The prevailing wisdom is that investors should seek some exposure to active strategies making sure to select lower fee funds since low fees are a strong predictor of future performance.

But which low fee active fund should investors select? At the end of 2017 there were almost 19,000 mutual funds, 3,400 ETFs and at least 5,383 hedge funds. Screening for funds in the lowest fee quartile still leaves you with 5000 funds! Manager/fund selection is perhaps the most difficult aspects of active investing – that’s exactly where AlphaClone can help.

AlphaClone’s investment approach seeks to solve the active manager selection dilemma. Using mandated quarterly holdings disclosures by institutional investors (Form 13F-HR), we assess the stock selection skill of each manager in our universe every six months. We then select the manager’s with the highest score and build portfolios based on their disclosed high conviction holdings. Read “Clone Score – How We Pick Managers” for a deep dive into AlphaClone’s methodology.

While technically our strategies are characterized as passive because they are rules based, they can also be seen as quasi-active because we seek to identify and follow the high conviction investment holdings of the world’s most established active managers. That’s why we like to characterize our strategies as “active indexes”.

We thought it would be instructional to look at performance results for five investment regimes that span the passive/active continuum. Each approach seeks to gain exposure to US equities but in very different ways. We define the five investment approaches as follows:

Extremely passive: this approach will allocate to a single market cap weighted index that seeks to represent all US equities. We use the Fidelity Total Market Index Fund (FFSMX).

Passive: this approach divides US equities into two categories; large cap and small cap. Our analysis assumes a 50/50 allocation between the iShares S&P 500 Index ETF (IVV) and the iShares Russell 2000 ETF (IWM).

Active Index: Our analysis assumes a 100% allocation to the AlphaClone Hedge Fund Master Index (ALFMIX) which can be accessed via our ETF.

Active: taking one step further towards active management we simply take the Morningstar US Large Blend category returns which represents the average return of all active mutual funds in that category.

Extremely active: finally, for the high octane set, we include an “extremely active” category represented by the HFRI Equity Hedge Index. The index represents the average returns for hedge funds that espouse and equity investment approach.

We calculate annualized returns through August 2018 and compare each investment approach across several time horizons. The results are presented in the Exhibit 1 below – extremely passive is the left most bar (light grey), extremely active is the right most bar (dark grey).

A few things jump out from the exhibit above:

Passive strategies have performed very well, especially over the three year horizon.
Despite achieving returns that are double their historical average, the active index approach still managed to outperform the more passive approaches over the five year horizon.
No investment strategy outperforms all the time – active indexing returns lagged over the 3 year period and passive strategies are beginning to lag more recently.

Active or passive represents a false choice to investors and their advisors. A thoughtful combination of both passive and relatively low cost and efficient active investment regimes has proven itself over time to be superior to either passive or active strategies on a stand alone basis.