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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.

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.