Tag Archives: factor timing

Hedge Fund Crowding Update – Q2 2017

Whereas hedge fund crowding primarily consists of systematic factor bets, most analysis of hedge fund crowding focuses solely on popular positions. Moreover, such analysis usually assumes that hedge fund crowding in individual stocks is a bullish indicator. This article illustrates the flaws of these common assumptions, identifies the principal sources of hedge fund crowding, and discusses the opportunities that this crowding presents:

  • Factor (systematic) exposures, rather than individual stocks, account for 70% of the crowding.
  • Residual (idiosyncratic, or stock-specific) bets account for just 30% of hedge fund crowding.
  • Simplistic analysis of crowding in individual stocks overlooks the majority of crowding risk.
  • Crowded hedge fund factor bets have been experiencing steep losses since 2015 and have been attractive shorts.
  • Crowded hedge fund stock-specific bets have been attractive longs following the 2014-2015 liquidations and the subsequent recovery, but the trend appears to have ended.

Identifying Hedge Fund Crowding

The analysis of hedge fund crowding in this article follows the approach of our earlier studies: We started with a decade of hedge fund Form 13F filings. Form 13F discloses positions of firms with long U.S. assets over $100 million. We only considered funds with a sufficiently low turnover to be analyzable from filings, and our database is free of survivorship bias. This sample included approximately 1,000 firms. We combined all portfolios into a single position-weighted portfolio – HF Aggregate. We then used the AlphaBetaWorks (ABW) Statistical Equity Risk Model an effective predictor of future risk – to analyze HF Aggregate’s risk relative to the U.S. Market (represented by the iShares Russell 3000 ETF (IWV) benchmark), identify the crowded exposures, and analyze their performance trends.

Factor and Residual Components of Hedge Fund Crowding

Virtually all of HF Aggregate’s absolute risk is systematic. Thus, the aggregate long U.S. equity holdings of hedge funds will very nearly track a passive factor portfolio with similar risk:

Chart of the factor (systematic) and residual (idiosyncratic) components of absolute U.S. long equity hedge fund crowding on 6/30/2017

Components of U.S. Hedge Fund Aggregate’s Absolute Risk in Q2 2017

Source Volatility (ann. %) Share of Variance (%)
Factor 11.80 97.78
Residual 1.78 2.22
Total 11.93 100.00

HF Aggregate has 2.8% estimated future volatility (tracking error) relative to the Market. Approximately 70% of this relative risk is due to factor crowding:

Chart of the factor (systematic) and residual (idiosyncratic) components of U.S. long equity hedge fund crowding relative to the Market on 6/30/2017

Components of U.S. Hedge Fund Aggregate’s Relative Risk in Q2 2017

Source Volatility (ann. %) Share of Variance (%)
Factor 2.37 69.90
Residual 1.55 30.10
Total 2.83 100.00

Consequently, simplistic analysis of hedge fund crowding that focuses on the popular holdings and position overlap is fatally flawed. It will capture less than a third of the crowding risk that is stock-specific and will overlook the bulk that is systematic.

Stock Picking and Market Timing Returns from Crowding

Crowded factor and residual bets go through cycles of outperformance and underperformance, depending on capital flows. These trends can provide attractive investment opportunities: short during liquidation, and long during expansion.

The following chart shows HF Aggregate’s cumulative βReturn (risk-adjusted returns from factor timing). Crowded hedge fund factor bets have experienced steep and accelerating losses since 2015. We identified these factors in earlier research as attractive short candidates, and the downtrend has persisted:

Chart of the cumulative risk-adjusted return from factor timing (variation in factor exposures) of the U.S. Hedge Fund Aggregate portfolio

Historical Risk-Adjusted Return from Factor Timing of U.S. Hedge Fund Aggregate

The following chart shows HF Aggregate’s cumulative αReturn (risk-adjusted returns from security selection). Following the unprecedented losses on crowded residual bets during 2011-2015, we advised long exposures to these beaten-down stocks in late-2015. The subsequent recovery has been spectacular but now appears over. Thus, the crowded hedge fund residual bets no longer seem to offer clear long or short opportunities:

Chart of the cumulative risk-adjusted return from security selection (stock picking) of the U.S. Hedge Fund Aggregate portfolio

Historical Risk-Adjusted Return from Security Selection of U.S. Hedge Fund Aggregate

The rest of this article considers the crowded factor and residual bets responsible for the above trends.

Hedge Fund Factor (Systematic) Crowding

The following chart shows the main sources of hedge fund factor crowding as of 6/30/2017 in red relative to U.S. Market’s exposures in gray:

Chart of the factor exposures contributing most to the factor variance of U.S. Hedge Fund Aggregate Portfolio relative to U.S. Market on 6/30/2017

Significant Absolute and Relative Factor Exposures of U.S. Hedge Fund Aggregate in Q2 2017

The dominant hedge fund long equity bet is Market (high Beta). Thus, the most crowded bet is high overall market risk, rather than a specific stock. Like a leveraged ETF, HF Aggregate outperforms when the Market is up and underperforms when it is down.

Chart of the main contributions to the factor variance of U.S. Hedge Fund Aggregate Portfolio relative to U.S. Market on 6/30/2017

Factors Contributing Most to Relative Factor Variance of U.S. Hedge Fund Aggregate in Q2 2017

Factor Relative Exposure Factor Volatility Share of Relative Factor Variance Share of Relative Total Variance
Market 14.05 9.80 47.63 33.29
Health Care 8.72 7.75 13.41 9.37
FX -8.49 6.77 11.35 7.93
Real Estate -2.54 12.40 6.11 4.27
Oil Price 1.11 29.50 5.30 3.71
Utilities -3.17 12.72 4.89 3.42
Bond Index -8.12 3.41 3.86 2.70
Financials -5.29 7.90 2.23 1.56
Industrials -4.15 4.72 2.17 1.51
Consumer Discretionary 8.11 4.31 1.51 1.06

(Relative exposures and relative variance contribution. All values are in %. Volatility is annualized.)

In fact, crowding in the simple Market Factor alone accounts for more risk than all the stock-specific crowding combined.

Despite recent losses, HF Aggregate’s Health Care Factor exposure remains near the recent record levels.

Hedge Fund Residual (Idiosyncratic) Crowding

The remaining 30% of hedge fund crowding as of 6/30/2017 was due to residual (idiosyncratic, stock-specific) risk:

Chart of the main contributors to the residual variance of U.S. Hedge Fund Aggregate Portfolio relative to U.S. Market on 6/30/2017

Stocks Contributing Most to Relative Residual Variance of U.S. Hedge Fund Aggregate in Q2 2017

Symbol Name Relative Exposure Residual Volatility Share of Relative Residual Variance Share of Relative Total Variance
BABA Alibaba Group Holding ADR 2.23 23.93 11.82 3.56
LNG Cheniere Energy, Inc. 1.44 27.51 6.54 1.97
HLF Herbalife Ltd. 0.92 36.18 4.59 1.38
CHTR Charter Communications, Inc. 1.66 19.10 4.15 1.25
AVGO Broadcom Limited 1.32 21.20 3.24 0.98
AAPL Apple Inc. -1.96 13.37 2.84 0.86
ALXN Alexion Pharmaceuticals, Inc. 0.85 29.14 2.52 0.76
FB Facebook, Inc. Class A 1.01 24.17 2.47 0.74
EXPE Expedia, Inc. 1.08 21.31 2.21 0.66
FWONK Liberty Media Corporation Formula One 0.91 24.90 2.11 0.64

(Relative exposures and relative variance contribution. All values are in %. Volatility is annualized.)

Following the 2011-2015 losses and the subsequent gains, these crowded bets do not offer clear long or short opportunities. Moreover, residual crowding accounts for a small fraction of the industry’s risk. While systematic hedge fund crowding continues to dominate, investors and allocators should focus on managing the crowded factor exposures. Without a firm grasp of factor crowding, investors and fund followers may blindly follow losing bets.

Summary

  • Factor (systematic) exposures that capture risks shared by many stocks, rather than individual stocks, are responsible for the majority of hedge fund crowding.
  • The main sources of Q2 2017 hedge fund crowding were long U.S. Market (high Beta), long Health Care, and short USD (preference for exporters over importers).
  • The crowded factor bets have been in a multi-year bearish trend.
  • The crowded residual bets have recovered from steep losses and no longer offer clear opportunities.
  • Without a robust analysis of the factor and residual components of crowding, a hedge fund investor, follower, or allocator may be missing the bulk of crowding risk and investing in a generic passive factor portfolio.
The information herein is not represented or warranted to be accurate, correct, complete or timely.
Past performance is no guarantee of future results.
Copyright © 2012-2017, AlphaBetaWorks, a division of Alpha Beta Analytics, LLC. All rights reserved.
Content may not be republished without express written consent.

 

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Hedge Fund Crowding Update – Q1 2017

A typical analysis of hedge fund crowding considers large, popular, and concentrated hedge fund long equity holdings. Such analysis usually assumes that crowding comes from stock-specific bets and that it is a bullish indicator. These assumptions are incorrect and have cost investors dearly:

  • Residual, idiosyncratic, or stock-specific bets now account for less than a third of hedge fund crowding. Factor (systematic) risk, rather than the risk from individual stocks, is driving hedge funds’ active returns. Consequently, simplistic analysis of hedge fund crowding that focuses on specific stocks misses the bulk of funds’ active risk and return.
  • The returns of crowded hedge fund factor and residual bets vary over time as the funds go through cycles of capital inflows and outflows. Consequently, generic analysis of hedge fund crowding can herd investors into losing bets on the wrong side of a cycle. For instance, depending on the trend, investors may desire long exposure to the crowded factor exposures in one year and short exposure in another.

This article reviews hedge fund long equity crowding at the end of Q1 2017. We identify the dominant systematic exposures and the top residual bets that will have the largest impact on investor performance. We also explore the current trends in returns from crowding that indicate profitable positioning.

Identifying Hedge Fund Crowding

This article follows the approach of our earlier studies of hedge fund crowding: We start with a survivorship-free database of SEC filings by over 1,000 U.S. hedge funds spanning over a decade. This database contains all funds that had ever filed 13F Reports (which disclose long U.S. assets over $100 million). We only consider funds with a sufficiently low turnover to be analyzable from filings. We combine all fund portfolios into a single position-weighted portfolio (HF Aggregate). The analysis of HF Aggregate’s risk relative to the U.S. Market reveals its active bets and the industry’s crowding. The AlphaBetaWorks (ABW) Statistical Equity Risk Model an effective predictor of future risk – identifies and quantifies the crowded exposures driving HF Aggregate’s performance.

Factor and Residual Components of Hedge Fund Crowding

The 3/31/2017 HF Aggregate had 2.6% estimated future volatility (tracking error) relative to the U.S. Market (represented by the iShares Russell 3000 ETF (IWV) benchmark). Approximately 30% of this was due to residual crowding, and approximately 70% was due to factor crowding:

Chart of the factor (systematic) and residual (idiosyncratic) components of US hedge fund crowding on 03/31/2017

Components of the Relative Risk for U.S. Hedge Fund Aggregate in Q1 2017

Source Volatility (ann. %) Share of Variance (%)
Factor 2.19 69.01
Residual 1.47 30.99
Total 2.64 100.00

Hedge fund crowding analysis that focuses on the popular holdings and position overlap thus captures less than a third of the total risk and overlooks over two-thirds of crowding that is due to factors – a fatal flaw. Since similar factor exposures can cause funds with no shared positions to correlate closely, a simplistic analysis of holdings and position overlap fosters dangerous complacency.

Stock Picking and Market Timing Returns from Crowding

A precise understanding of crowding is critical to investors and allocators since, depending on the capital flows, crowded bets can generate large and unexpected gains or losses.

The following chart shows cumulative βReturn (risk-adjusted returns from factor timing, or from the variation of factor exposures) of HF Aggregate. Crowded hedge fund factor bets have underperformed since 2011, and losses from hedge fund factor crowding have accelerated since 2015. The crowded factor bets below could have been attractive short candidates. In aggregate, hedge funds’ long equity portfolios would have made approximately 10% more since 2015 had they kept their factor exposures constant:

Chart of the cumulative risk-adjusted return from factor timing (variation in systematic exposures) due to U.S. long equity hedge fund crowding

Historical Risk-Adjusted Return from Factor Timing of U.S. Hedge Fund Aggregate

Crowded hedge fund residual bets have also underperformed since 2011. The following chart shows cumulative αReturn (risk-adjusted returns from security selection) of HF Aggregate. HF Aggregate experienced massive losses from security selection during 2011-2015. Given the unprecedented losses, we advised long exposures to the crowded residual bets in late-2015, and these have indeed recovered:

Chart of the cumulative risk-adjusted return from security selection (stock picking) due to U.S. long equity hedge fund crowding

Historical Risk-Adjusted Return from Security Selection of U.S. Hedge Fund Aggregate

We now turn to the specific crowded factor and residual bets behind the trends above.

Hedge Fund Factor (Systematic) Crowding

The following chart illustrates the main sources of factor crowding. HF Aggregate’s factor exposures are in red. The U.S. Market’s (defined as the iShares Russell 3000 ETF (IWV) benchmark) is in gray:

Chart of the factor exposures contributing most to the factor variance of U.S. Hedge Fund Aggregate Portfolio relative to U.S. Market on 03/31/2017

Significant Absolute and Residual Factor Exposures of U.S. Hedge Fund Aggregate in Q1 2017

The dominant bet of hedge funds’ long equity portfolios is Market (high Beta). The most crowded hedge fund bet is thus not a particular stock, but high overall market risk. HF Aggregate partially behaves like a leveraged market ETF, outperforming during bullish regimes and underperforming during bearish ones.

Chart of the main factors and their cumulative contribution to the factor variance of U.S. Hedge Fund Aggregate Portfolio relative to U.S. Market on 03/31/2017

Factors Contributing Most to Relative Factor Variance of U.S. Hedge Fund Aggregate in Q1 2017

Factor Relative Exposure Factor Volatility Share of Relative Factor Variance Share of Relative Total Variance
Market 13.25 10.67 54.00 37.26
Health Care 8.55 7.62 15.93 10.99
Utilities -3.05 12.86 8.16 5.63
Real Estate -2.69 12.87 7.91 5.46
Bond Index -7.33 3.59 6.02 4.15
Consumer Staples -5.04 8.04 4.64 3.20
Size -2.02 9.35 2.45 1.69
Oil Price 0.53 30.36 2.38 1.64
Industrials -4.28 4.96 1.85 1.27
FX 2.59 6.77 -1.83 -1.26

(Relative exposures and relative variance contribution. All values are in %. Volatility is annualized.)

Crowding into a single factor (Market) accounts for more hedge fund risk than all their stock-specific and other factor bets combined. The three top sector bets are long Health Care, short Utilities, and short Real Estate.

HF Aggregate’s exposures to Market, Health Care, and Bond Factors remained near record levels reached recently.

Hedge Fund Residual (Idiosyncratic) Crowding

The remaining third of hedge fund crowding as of 3/31/2017 was due to residual (idiosyncratic, stock-specific) risk:

Chart of the main stock-specific bets and their cumulative contribution to the residual variance of U.S. Hedge Fund Aggregate Portfolio relative to U.S. Market on 03/31/2017

Stocks Contributing Most to Relative Residual Variance of U.S. Hedge Fund Aggregate in Q1 2017

Symbol Name Relative Exposure Residual Volatility Share of Relative Residual Variance Share of Relative Total Variance
CHTR Charter Communications, Inc. Class A 2.53 18.64 10.31 3.19
LNG Cheniere Energy, Inc. 1.41 29.37 7.96 2.47
BABA Alibaba Group Holding Ltd. Sponsored ADR 1.17 26.26 4.40 1.36
FB Facebook, Inc. Class A 1.02 28.05 3.76 1.17
FLT FleetCor Technologies, Inc. 1.19 22.02 3.19 0.99
HCA HCA Holdings, Inc. 1.12 21.36 2.66 0.82
AAPL Apple Inc. -1.72 13.87 2.63 0.81
NXPI NXP Semiconductors NV 0.78 28.62 2.31 0.71
PYPL PayPal Holdings Inc 1.26 17.48 2.26 0.70
ATVI Activision Blizzard, Inc. 0.98 21.53 2.05 0.64

(Relative exposures and relative variance contribution. All values are in %. Volatility is annualized.)

While systematic hedge fund crowding continues to dominate, investors and allocators should focus on the factor exposures. Without a firm grasp of factor crowding, allocators to a supposedly diversified hedge fund portfolio may be paying high active management fees for what is effectively a leveraged ETF book. Also, investors and fund followers may blindly follow losing factor bets.

Nevertheless, residual hedge fund crowding can be a profitable long and short indicator. The 25% decline in 2010-2015 was followed by a 15% gain.

Summary

  • Factor (systematic) exposures and risks shared across stocks, rather than individual positions, are the primary drivers of hedge fund industry’s long equity risk.
  • The main sources of Q1 2017 hedge fund crowding were long U.S. Market (high Beta), long Health Care, short Utilities, and short Real Estate Factor exposures.
  • Without a robust analysis of factor and residual crowding, a hedge fund investor, follower, or allocator may be investing in a generic passive factor portfolio, likely with leverage.
  • The crowded factor bets have been in a bearish trend and may represent attractive short candidates.
  • The crowded residual bets have been recovering from steep losses and may continue to represent attractive long candidates, though less so than in 2016.
The information herein is not represented or warranted to be accurate, correct, complete or timely.
Past performance is no guarantee of future results.
Copyright © 2012-2017, AlphaBetaWorks, a division of Alpha Beta Analytics, LLC. All rights reserved.
Content may not be republished without express written consent.
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