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Most Hedge Fund Strategies Are Redundant

Abstract: Hedge fund strategies are not as unique as investors believe. We examine 18 strategy indexes and find that three factors capture more than 87% of the variation in returns. Most strategies are redundant, which has several implications for portfolio construction. Investors should focus on finding quality funds independent of strategy.

Diversification is powerful. Most investors understand that it can substantially improve portfolio performance. Too much diversification can be just as detrimental as too little, however, if it causes investors to diversify into less attractive investments.

Benartzi and Thaler (2001)1 found that investors in defined contribution plans tend to divide their assets equally among available options, even when doing so results in poor asset allocations. Institutional investors, although usually much more sophisticated than retail investors, often make a similar mistake by over-diversifying into a wide array of asset classes and investment strategies.

It makes sense for institutional portfolios to include each of the most common hedge fund strategies if each contributes something unique, but is this really the case? In this report, we analyze hedge fund indexes using four different tools—correlation, clustering, principal components, and optimization—to determine which strategies are, in fact, distinct.

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Trading off Return and Correlation

Abstract: It’s easy to evaluate a trade-off between risk and return, but much more challenging to understand a trade-off between correlation and return, particularly as the number of securities in a portfolio increases. Investors often underestimate the significance correlation plays in portfolio performance, and underweight lower return, low correlation assets as a result. Correlation can be, and often is, more important than return.

In an ideal world, we’d be able to reduce all investment decisions to a few simple variables. Unfortunately, we do not live in an ideal world. Investing can be a difficult and confusing game. Yet the goal has long been to make it as simple as practical.

In 1952, Harry Markowitz introduced an optimization method that has become the foundation of Modern Portfolio Theory. His mean-variance model, while flawed, is nevertheless useful. It relies upon three significant inputs: measures of return, risk, and correlation. Each plays a critical role in portfolio performance, yet investors often prioritize return and risk over correlation when evaluating potential investments.

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The Top 10 Factors Driving Hedge Fund Returns

Abstract: Hedge funds have the ability to exploit pricing inefficiencies across a very diverse set of asset classes and securities using a variety of techniques. It therefore shouldn’t come as a surprise that their returns draw from a greater number of risk factors than traditional investments. In this post, we look at the 10 most significant risk factors driving hedge fund returns.

Methodology

Considering the breadth of strategies in the hedge fund universe, it’s difficult to come up with a completely objective measure of significance. The list below is subjective, but we’ve done our best to keep it grounded in empirical evidence.

We’ve performed our factor-based analysis on 14 of our hedge fund strategy indexes, which together provide suitable benchmarks for the vast majority of hedge funds in existence. In doing so, we’ve used statistical and machine learning techniques to identify a factor structure for each index, then looked at the percentage of index risk explained by each factor.

Some factors contribute to many strategies. Others contribute to only a handful. Our list strives to strike a balance between factors that have modest, but widespread contributions and those that have large contributions, but only to a limited number of strategies.

We occasionally report factor returns. It’s important to note that when we do so, we provide excess returns scaled to a 10% expected annual volatility. The factor’s actual market return may have been higher or lower, depending upon its riskiness. Our risk-adjustment standardizes volatility across factors, allowing for easier comparisons.

Without further delay, here’s our list of the 10 most significant risk factors in hedge funds today.

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Contrary to Popular Opinion, Bridgewater Did Not Blow Up the Market

Abstract: In the past several weeks, risk parity funds such as Bridgewater’s All Weather have attracted substantial criticism. The attacks have clustered around two primary notions: firstly, that risk parity is a failure because it did not protect investors during August’s drawdowns and secondly, that risk parity may have caused or at least amplified the market’s sudden losses. In this post, we’ll evaluate the legitimacy of these two claims, as well as provide a deeper understanding of the motivations and behaviors of risk parity funds.

Defining Risk Parity

Most investor portfolios are heavily weighted towards equity risk. A typical 60/40 portfolio, for example, will usually derive 80-90% of its risk from equities since stocks are much more volatile that bonds.

Risk parity is an asset allocation methodology that strives to overcome this problem by creating portfolios that distribute risk roughly equally between assets. There are several ways to do this, but the most common approach is to weight assets by the inverse of their volatility. Doing so increases weights on low volatility assets and decreases weights on high volatility assets so that each asset’s levered or de-levered position has an identical expected volatility.

Most risk parity funds then lever this volatility weighted portfolio to target a specific level of risk. In Bridgewater’s case, this is a 12% annualized standard deviation. The result is a portfolio that has similar total risk to a 60/40 portfolio, but a much more equitable internal distribution of risks.

Risk Parity is a Simple, but Imperfect Solution to a Complicated Problem

The idea behind risk parity is a good one. It results in meaningfully more diversified portfolios. Risk parity is not a perfect strategy, however. It has plenty of faults, including:

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Why Do Investors Still Favor Long/Short Equity?

In its recent Investor Outlook, Preqin included the following chart describing investor preferences in the hedge fund space. It shows that more than half of the allocators interviewed intend to seek out new or additional long/short equity managers in the next 12 months.

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Long/short equity is, by far, the most desired strategy. But why?

As we noted in our Strategy Spotlight earlier this week, equity long/short performance has been lackluster for more than a decade now. Consider the following:

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Hedge Funds Reduced Net Longs Before Recent Correction

This chart of the rolling 10-day beta of the HFRX Global Hedge Fund Index relative to the S&P 500 suggests that hedge funds were reducing their net long stock exposure in advance of the recent market correction. After briefly touching 0.46 in early July, the measure fell steadily to a low of 0.16 in mid-August. It currently stands at 0.22, above its long-run mean of 0.16, but less than half of its near-term high. With only a few days remaining until funds begin reporting August returns, it will be interesting to see the extent to which hedge funds were able to sidestep losses this month.
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Relax, Hedge Funds Do Just as Well as You Thought

Abstract: A new paper argues that annualized hedge fund returns in the Lipper TASS database are 50% lower after adjusting for backfill and survivorship bias. We note that hedge fund index providers already adjust for these biases, and find that the long-term rate of return obtained using their indexes is a better estimate of actual realized returns than the authors’ lowball value. We support our claim using historical fund of funds and endowment returns, both of which are less affected by biases.

In case you missed it, a small, but vocal portion of the Twittersphere blew up on Monday when Bloomberg linked to a new research paper1 claiming that roughly half of hedge funds’ historical annualized return is an illusion caused by reporting biases.

The paper’s authors, Mila Getmansky, Peter Lee, and Andew Lo (hereafter, GLL), used data from the Lipper TASS hedge fund database to compare fund returns before and after adjusting for two well-known biases: backfill and survivorship. They found that hedge funds produced unadjusted returns of 12.6% annually between 1996 and 2014. However, they also calculated that after accounting for the biases, the actual hedge fund return realized by investors was only 6.3%.

There’s a lot of shock value in the disparity between the two calculations. So much so that Bloomberg ran its article with the headline “Hedge Funds Do Half as Well as You Think” which understandably generated a lot of buzz. If long-term hedge fund returns are truly 50% lower than previously reported, hedge fund investors should feel duped and absolutely incensed. But is this really the case?

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