Category Archives: Risk

Hedge Fund Industrials Factor Timing

In an earlier post, we discussed the largest bets hedge fund long portfolios were making in Q1 2015. The third largest was on the Industrials Factor. This is the risk specific to the industrials sector after controlling for market exposure. It captures capital allocation to industrials and sensitivity (beta) to the sector. There is weak statistical evidence of poor industrials factor timing by hedge funds – investors who follow hedge funds should either ignore this bet or treat it as a negative indicator.

At the end of Q1 2015, high industrials sector factor exposure was the third largest source of U.S. hedge funds’ long portfolio crowding. HF Aggregate, a portfolio consisting of popular long U.S. equity holdings of all hedge funds tractable from quarterly filings, had over 25% industrials factor exposure – a 9% overweight relative to Market. This exposure was at an all-time high:

Chart of the historical industrials factor exposure of U.S. Hedge Fund Aggregate

U.S. Hedge Fund Aggregate’s Industrials Sector Factor Exposure History

This industrials factor exposure captures sector risk after controlling for market exposure. For example, a fund with 10% allocated to a broad industrials index will have approximately 10% industrials factor exposure. A fund with 10% allocated to a 2x-levered broad industrials ETF will have approximately 20% industrials factor exposure.

Here we analyze the hedge fund industry’s skill in timing the U.S. Industrials Factor by varying this exposure. The AlphaBetaWorks Performance Analytics Platform evaluates market timing skills and performance using two related tests:

  • Statistical test for the relationship between factor exposure and subsequent factor returns,
  • Statistical test for the size and consistency of returns generated by varying factor exposures.

Hedge Fund Industrials Factor Exposure and Industrials Factor Return

We calculated the Spearman’s rank correlation coefficient of HF Aggregate’s industrials factor exposure and subsequent industrials factor return for the past 10 years and tested it for significance. The chart below illustrates the correlation between the two series and the test results:

Chart of the correlation between historical industrials factor exposure of U.S. Hedge Fund Aggregate and subsequent factor return

U.S. Hedge Fund Aggregate’s Industrials Factor Exposure and Return

There is a statistically weak negative relationship between HF Aggregate’s industrials factor exposure and subsequent factor performance. Hedge fund industrials factor exposure is a weak predictor of future industrials returns.

Hedge Fund Industrials Factor Timing Returns

Over the past 10 years, HF Aggregate (USHFS in red) made approximately 0.9% less than it would have with constant industrials factor exposure, as illustrated below. The performance of HF Aggregate is compared to all tractable 13F filers (Group in gray). The AlphaBetaWorks Performance Analytics Platform identifies this performance due to industrials factor timing as industrials βReturn:

Chart of the cumulative historical contribution of variation in industrials factor exposure of U.S. Hedge Fund Aggregate to the Aggregate’s performance

U.S. Hedge Fund Aggregate’s Industrials Factor Timing Return

The weak evidence of poor industrials factor timing by the industry, combined with the high recent industrials factor exposure, is a weak bearish indicator for the sector.

Summary

  • The industrials factor exposure of U.S. hedge funds’ long portfolios is weakly predictive of subsequent sector performance.
  • Current hedge fund industrials factor exposure, at 10-year highs, is a weak bearish indicator for the Industrials Sector.
  • Investors who track hedge fund holdings should either ignore this bet or treat is as a negative indicator.
The information herein is not represented or warranted to be accurate, correct, complete or timely.
Past performance is no guarantee of future results.
Copyright © 2012-2015, 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 Oil Factor Timing

In an earlier post, we discussed the largest bets hedge fund long portfolios were making in Q1 2015. The second largest was on the oil price. This exposure is the residual oil price risk after controlling for market and sector exposures. It captures overweighting within various sectors of companies that out- or underperform under rising oil price. There is weak statistical evidence of skilled oil factor timing by hedge funds – the current bet is a weak bullish indicator for oil prices.

At the end of Q1 2015, high oil price factor exposure was the second largest source of U.S. hedge funds’ long portfolio crowding. HF Aggregate, a portfolio consisting of popular long U.S. equity holdings of all hedge funds tractable from quarterly filings, had approximately 2.5% oil price factor exposure. This exposure was approaching the 10-year highs reached in 2007-2009:

Chart of the exposure of oil price factor of the U.S. Hedge Fund Aggregate

U.S. Hedge Fund Aggregate’s Oil Factor Exposure History

This oil price exposure captures residual oil risk after controlling for sector exposures. For examples, airlines with higher operational or financial leverage than peers have negative oil price factor exposure – they will underperform peers when oil price increases; airlines with lower operational or financial leverage than peers have positive oil price factor exposure –they will outperform peers when oil price increases.

Here we analyze the hedge fund industry’s skill in timing the oil price by varying this intra-sector oil price risk. The AlphaBetaWorks Performance Analytics Platform evaluates market timing skills and performance using two related tests:

  • Statistical test for the relationship between factor exposure and subsequent factor returns,
  • Statistical test for the size and consistency of returns generated by varying factor exposures.

Hedge Fund Oil Factor Exposure and Oil Return

We calculated the Spearman’s rank correlation coefficient of HF Aggregate’s oil price factor exposure and subsequent oil price return and tested it for significance. The chart below illustrates the correlation between the two series and the test results:

Chart of the correlation between oil price factor exposure of the U.S. Hedge Fund Aggregate and subsequent oil price return

U.S. Hedge Fund Aggregate’s Oil Factor Exposure and Return

There is a statistically weak positive relationship between HF Aggregate’s oil factor exposure and subsequent oil performance. Hedge fund oil factor exposure is a weak indicator of future oil price direction.

Hedge Fund Oil Factor Timing Returns

Over the past 10 years, HF Aggregate (USHFS in red) made approximately 1.5% more than it would have with constant oil factor exposure, as illustrated below. The performance of HF Aggregate is compared to all tractable 13F filers (Group in gray). The AlphaBetaWorks Performance Analytics Platform identifies this performance due to oil price factor timing as oil price βReturn:

Chart of the return due to variation in oil price factor exposure of the U.S. Hedge Fund Aggregate

U.S. Hedge Fund Aggregate’s Oil Factor Timing Return

The weak evidence of oil factor timing skill by the industry, combined with the high recent oil factor exposure, is a weak bullish indicator for oil prices.

Summary

  • The oil price factor exposure of U.S. hedge funds’ long portfolios is weakly predictive of subsequent oil performance.
  • Current hedge fund oil factor exposure, near 10-year highs, is a weak bullish indicator for oil prices.
The information herein is not represented or warranted to be accurate, correct, complete or timely.
Past performance is no guarantee of future results.
Copyright © 2012-2015, 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 U.S. Market Timing

The single largest bet hedge fund long portfolios were making in Q1 2015 was on the U.S. market (high beta). While the bet is exceptionally large, it is not predictive of market direction. Allocators should pay attention to this risk aggregation.

At the end of Q1 2015, high market factor exposure (high beta) was the primary source of U.S. hedge funds’ long portfolio crowding. HF Aggregate, a portfolio consisting of popular long U.S. equity holdings of all hedge funds tractable from quarterly filings, had approximately 115% U.S. market factor exposure (1.15 U.S. market beta). This exposure was at 10-year highs – the level last seen in mid-2006:

Chart of the historical U.S. Market Factor exposure of U.S. Hedge Fund Aggregate

U.S. Hedge Fund Aggregate’s U.S. Market Factor Exposure History

Our work on hedge fund crowding has so far not addressed hedge fund factor timing and hedge fund U.S. market timing specifically. We dive into this performance here.

The AlphaBetaWorks Performance Analytics Platform evaluates market timing skills and performance using two related tests:

  • Statistical test for the relationship between factor exposure and subsequent factor returns,
  • Statistical test for the size and consistency of returns generated by varying factor exposures.

Hedge Fund Market Exposure and Market Return

We calculated the Spearman’s rank correlation coefficient of HF Aggregate’s market exposure and subsequent market return and tested it for significance. The chart below illustrates the correlation between the two series and the test results:

Chart of the correlation between the U.S. market exposure of long U.S. hedge fund equity portfolios and U.S. market return

U.S. Hedge Fund Aggregate’s U.S. Market Exposure and Return

The chart shows that there is a positive relationship between HF Aggregate’s U.S. market exposure and subsequent U.S. market return, but it is weak and statistically insignificant. In other words, hedge funds’ variation in U.S. market exposure has done little to help their performance.

Hedge Fund U.S. Market Timing Returns

Over the past 10 years, HF Aggregate (USHFS in red) made approximately 1% more than it would have with constant factor exposures, as illustrated below. The performance of HF Aggregate is compared to all tractable 13F filers (Group in gray). The AlphaBetaWorks Performance Analytics Platform identifies this performance due to U.S. market factor timing as U.S. market βReturn:

Chart of the historical return due to variation in U.S. market exposure of long U.S. hedge fund equity portfolios

U.S. Hedge Fund Aggregate’s U.S. Market Timing Return

The performance impact of this variation in beta within U.S. hedge fund long portfolios is also minor. However, the group of all 13F filers was a poor market timer, particularly during the volatility of 2008-2009. During the crisis, non-filers were the smart money and took advantage of U.S. market volatility, at the expense of 13F filers. 13F filers were a contrarian indicator.

Summary

  • Hedge fund long equity portfolios consistently take 5-15% more market risk than S&P500 and other broad market benchmarks.
  • There has been no statistically significant relationship between U.S. market exposure (market beta) of U.S. hedge funds’ long portfolios and subsequent market return.
  • The high market factor exposure of U.S. hedge funds’ long portfolios is not predictive of subsequent market returns.
  • The broader group of all 13F filers generated significant negative returns by varying market exposure, particularly during the 2008-2009 volatility.
The information herein is not represented or warranted to be accurate, correct, complete or timely.
Past performance is no guarantee of future results.
Copyright © 2012-2015, 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 Toll: January 2015

Several of our articles discussed the vulnerability of crowded hedge fund positions to volatilitymass liquidation, and losses. We illustrated specific blow-ups (SanDisk (SNDK) and eHealth (EHTH)), as well as sectors with persistently poor hedge fund performance (Oil and Gas Production and Miscellaneous Mining). However, we have not showed how representative these examples are. This piece illustrates the performance toll of hedge fund crowding in a single (especially damaging) month – January 2015.

Identifying Crowding

We analyze hedge fund holdings (HF Aggregate) relative to the market portfolio (Market Aggregate). HF Aggregate is position-weighted while Market Aggregate is capitalization-weighted. We follow the approach of our earlier articles on aggregate and sector-specific hedge fund crowding.

January 2015 Hedge Fund Crowding Toll

January 2015 is a convenient month to consider: Due to intra-month volatility, the market was approximately flat at several dates. Hence, relative performance at these points gives a good picture of risk-adjusted performance. Whereas Russell 3000 was down about 2.7%, the portfolio of equal-weighted crowded hedge fund longs (in red on the chart below) declined twice as much:

Chart of the January 2015 performance of crowded long hedge fund bets

January 2015 Performance of Crowded Hedge Fund Long Bets

The crowded hedge fund longs in the above chart consist of HF Aggregate’s illiquid long bets relative to the Market Aggregate. Illiquid longs are overweight exposures of HF Aggregate valued at over 10 days of trading volume. We have discussed earlier that illiquidity is a key source of crowding risk since funds have difficulty exiting these positions. The specific 10 day limit was chosen arbitrarily. Below we show that results are consistent across a broad range of liquidity limits. The portfolio was constructed using AlphaBetaWorks’ Q3 2014 hedge fund crowding dataset, available to subscribers in late November.

Crowded hedge fund shorts are defined similarly: They consist of illiquid underweights relative to the Market Aggregate valued at over 10 days of trading volume. Crowded shorts (in green on the chart below) slightly outperformed the market in January:

Chart of he January 2015 performance of the crowded hedge fund long and short bets

January 2015 Performance of Crowded Hedge Fund Long and Short Bets

The performance of crowded hedge fund bets was roughly proportional to their crowding and liquidity. In the following chart, each line represents the performance of crowded hedge fund bets with a given level of crowding. Crowded and illiquid longs sized at 100 days of volume (red), underperformed crowded longs sized at 50 days (orange), etc. Meanwhile, illiquid shors (in shades of green) outperformed dramatically:

Chart of the January 2015 performance of crowded hedge fund bets as a function of liquidity

January 2015 Crowded Hedge Fund Bet Performance and Liquidity

In general, the larger and more illiquid a crowded hedge fund long bet was, the worse it fared. Even when a positive catalyst ought to lift a crowded long, impatient hedge fund holders may sell on the news, muting any upside. On the other hand, even when a negative catalyst ought to sink a crowded short, managers may buy on the news, muting any downside.

The damage covered a variety of industries and company sizes. Some of the notable losses in the crowded and illiquid long group were the following:

HF Aggregate Exposure

Symbol Name Value ($ mil) Liquidity (days) Performance (%)
NOR Noranda Aluminum Holding Corporation 103.80 40.19 -16.68
NMIH NMI Holdings, Inc. Class A 127.93 43.41 -16.71
AGYS Agilysys, Inc. 100.22 114.63 -18.42
RP RealPage, Inc. 112.04 10.96 -18.73
LPG Dorian LPG Ltd. 107.44 28.71 -19.01
TWI Titan International, Inc. 125.13 16.29 -19.09
HTZ Hertz Global Holdings, Inc. 2778.20 10.77 -20.46
DPM DCP Midstream Partners, LP 377.28 15.00 -20.85
HLF Herbalife Ltd. 982.00 10.42 -22.16
THRX Theravance, Inc. 321.32 19.18 -24.92
SALT Scorpio Bulkers, Inc. 139.66 32.25 -25.35
SXC SunCoke Energy, Inc. 161.15 16.09 -25.73
CACQ Caesars Acquisition Co. Class A 110.62 83.10 -29.25
SD SandRidge Energy, Inc. 317.85 11.38 -29.83
YRCW YRC Worldwide Inc. 280.23 15.99 -36.12
CZR Caesars Entertainment Corporation 245.84 10.74 -39.47
LE Lands’ End, Inc. 321.92 12.10 -46.47
ASPS Altisource Portfolio Solutions S.A. 245.55 10.77 -52.17
ADES Advanced Emissions Solutions, Inc. 107.92 41.21 -77.55
OCN Ocwen Financial Corporation 910.00 12.37 -87.76

Some of the notable gains in the crowded short group were the following:

HF Aggregate Exposure

Symbol Name Value ($ mil) Liquidity (days) Performance (%)
SBUX Starbucks Corporation -766.74 -2.02 6.78
KR Kroger Co. -390.36 -1.81 6.80
SPG Simon Property Group, Inc. -508.85 -1.90 6.83
LUV Southwest Airlines Co. -767.17 -1.88 6.89
NS NuStar Energy L.P. -141.06 -3.79 6.97
PRXL PAREXEL International Corporation -277.74 -6.47 7.09
BAH Booz Allen Hamilton Holding Corporation Class A -140.18 -7.13 7.60
ICLR ICON Plc -281.30 -9.46 8.28
GILD Gilead Sciences, Inc. -2122.35 -1.29 9.56
BA Boeing Company -2372.83 -4.29 9.78
NEU NewMarket Corporation -178.11 -10.24 10.35
PBYI Puma Biotechnology, Inc. -109.17 -1.57 10.75
ATK Alliant Techsystems Inc. -108.27 -2.90 11.02
TMUS T-Mobile US, Inc. -149.48 -1.11 11.13
BIIB Biogen Idec Inc. -1221.11 -2.01 12.86
SLXP Salix Pharmaceuticals, Ltd. -695.73 -2.19 14.75
PCRX Pacira Pharmaceuticals, Inc. -249.52 -4.43 16.82
CLR Continental Resources, Inc. -535.76 -3.54 17.56
HAR Harman International Industries, Incorporated -111.76 -1.31 19.27
ICPT Intercept Pharmaceuticals, Inc. -378.15 -4.27 25.29

January 2015 was an especially costly month for crowded hedge fund ideas, but it illustrated a broad and consistent effect. Crowding takes a heavy toll on performance and warrants close scrutiny from portfolio managers, analysts, and allocators.

The information herein is not represented or warranted to be accurate, correct, complete or timely.
Past performance is no guarantee of future results.
Copyright © 2012-2015, 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 Costs – eHealth

EHTH (eHealth, Inc.), an Internet health insurance agency, was down over 50% following disappointing revenue and EPS guidance. The events were yet another example of the mass sell-offs in crowded hedge fund bets after disappointing news. This once again demonstrates that investors must monitor their portfolios for crowding.

EHTH was not the largest stock-specific hedge fund insurance sector bet, but it was one of the least liquid. The aggregate crowded position constituted about nine days’ trading volume. As funds struggled to exit, more shares traded in one day than in the prior week, knocking the price down 54%. We illustrate how investors aware of this crowding could have avoided the losses.

To explore crowding we analyze hedge fund Life and Health Insurance Sector holdings (HF Sector Aggregate) relative to the Sector Market Portfolio (Sector Aggregate). HF Sector Aggregate is position-weighted while Sector Aggregate is capitalization-weighted. This follows the approach of our earlier articles on aggregate and sector-specific hedge fund crowding. Crowded positions are vulnerable to volatility, mass liquidation, and losses; they persistently underperform in some sectors.

Hedge Fund Life and Health Insurance Performance

The figure below plots historical return of HF Life and Health Insurance Aggregate. Factor return is due to systematic (market) risk. Blue area represents positive and gray area represents negative risk-adjusted returns from security selection (αReturn). Crowded bets underperformed the factor portfolio by over 35%:

Chart of the historical factor and idiosyncratic performance of the Hedge Fund Life and Health Insurance Sector Aggregate

Hedge Fund Life and Health Insurance Sector Aggregate Historical Performance

Hedge Fund Life and Health Insurance Risk-Adjusted Performance

The risk-adjusted return from security selection (αReturn) of HF Sector Aggregate is the return it would have generated if markets were flat – all market effects on performance have been eliminated. This is the idiosyncratic performance of the crowded portfolio. Crowded bets in this sector are especially dangerous, given their propensity to disappoint:

Chart of the historical security selection (stock picking) performance of the Hedge Fund Life and Health Insurance Sector Aggregate

Hedge Fund Life and Health Insurance Sector Aggregate Historical Security Selection Performance

Crowded Hedge Fund Life and Health Insurance Ideas

The following stocks contributed most to the relative residual (security-specific) risk of the HF Sector Aggregate as of Q3 2014. Blue bars represent long (overweight) exposures relative to Sector Aggregate. White bars represent short (underweight) exposures. Bar height represents contribution to relative stock-specific risk:

Chart of the contribution to the residual (stock-specific) risk of the crowded hedge fund Life and Health Insurance Sector bets

Crowded Hedge Fund Life and Health Insurance Sector Bets

The following table contains detailed data on these crowded ideas:

Exposure (%) Net Exposure Share of Risk (%)
HF Sector Aggr. Sector Aggr. % $mil Days of Trading
VOYA Voya Financial, Inc. 29.79 5.83 23.96 375.4 4.5 39.08
UAM Universal American Corp. 8.73 0.39 8.34 130.7 123.5 18.76
LNC Lincoln National Corporation 23.20 8.45 14.75 231.2 1.9 11.48
EHTH eHealth, Inc. 3.55 0.26 3.29 51.6 8.9 8.98
AFL Aflac Incorporated 1.05 15.94 -14.88 -233.2 -1.6 8.52
MET MetLife, Inc. 12.56 36.31 -23.75 -372.1 -1.1 8.15
GNW Genworth Financial, Inc. Class A 5.55 3.93 1.62 25.4 0.3 1.04
UNM Unum Group 0.92 5.29 -4.37 -68.5 -1.0 0.97
PNX Phoenix Companies, Inc. 1.59 0.19 1.39 21.9 9.5 0.87
SYA Symetra Financial Corporation 3.75 1.63 2.12 33.1 3.6 0.42
RGA Reinsurance Group of America, Incorporat 0.55 3.32 -2.76 -43.3 -1.4 0.28
TMK Torchmark Corporation 0.00 4.13 -4.13 -64.7 -1.5 0.27
ANAT American National Insurance Company 0.00 1.82 -1.82 -28.6 -17.4 0.27
SFG StanCorp Financial Group, Inc. 0.00 1.64 -1.64 -25.6 -1.8 0.24
PRI Primerica, Inc. 0.00 1.58 -1.58 -24.8 -1.7 0.16
EIG Employers Holdings, Inc. 1.06 0.37 0.69 10.8 4.1 0.10
AEL American Equity Investment Life Holding 0.13 1.03 -0.91 -14.2 -0.7 0.09
PL Protective Life Corporation 2.41 3.32 -0.91 -14.2 -0.3 0.08
CNO CNO Financial Group, Inc. 3.11 2.13 0.98 15.4 0.6 0.07
IHC Independence Holding Company 0.60 0.14 0.46 7.2 42.1 0.05
Other Positions 0.03 0.11
Total 100.00

The table above shows that, while EHTH was neither the highest contributor to risk nor the most illiquid, it was one of the top bets in each category. When the bad news came, its value halved. VOYA, UAM, and LNC, the other large and illiquid bets, are also at risk. Even when a positive catalyst arrives, impatient hedge fund holders may sell on the news, muting any upside. Whether or not investors choose to steer clear of crowded names, they must monitor them. With proper data, this attention to crowding can prevent “unexpected” volatility.

Conclusion

eHealth illustrates the vulnerability of crowded and illiquid positions to disorderly liquidation. eHealth was especially dangerous, given the tendency of crowded hedge fund life and health insurance ideas to disappoint. Investors armed with hedge fund crowding insights could have avoided these losses.

The information herein is not represented or warranted to be accurate, correct, complete or timely.
Past performance is no guarantee of future results.
Copyright © 2012-2015, 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 Costs – SanDisk

SanDisk (SNDK) was down 14% following a disappointing pre-announcement. This is a common occurrence for crowded ideas: SanDisk is the most crowded hedge fund bet in its sector, and crowded hedge fund Electronic Components picks tend to do poorly. These events illustrate crowding costs, particularly in the areas where hedge funds display a persistent lack of skill.

This piece analyzes hedge fund Electronic Components sector holdings (HF Sector Aggregate) relative to the sector market portfolio (Sector Aggregate). HF Sector Aggregate is position-weighted while Sector Aggregate is capitalization-weighted. We follow the approach of our earlier articles on aggregate and sector-specific hedge fund crowding. Crowded positions are vulnerable to volatility, mass liquidation, and losses. In some sectors crowded positions persistently underperform.

Hedge Fund Electronic Components Performance

The figure below plots historical return of HF Sector Aggregate. Factor return is due to systematic (market) risk. Blue area represents positive and gray area represents negative risk-adjusted returns from security selection (αReturn):

Chart of the components of Hedge Fund Electronic Components Sector Aggregate historical performance

Hedge Fund Electronic Components Sector Aggregate Historical Performance

Hedge Fund Electronic Components Risk-Adjusted Performance

The risk-adjusted return from security selection (αReturn) of HF Sector Aggregate is the return it would have generated if markets were flat. This is the idiosyncratic performance of the crowded portfolio. Adjusted for market returns, crowded bets have lost 24% since 2004:

Chart of the risk-adjusted return from security selection of the Hedge Fund Electronic Components Sector Aggregate

Hedge Fund Electronic Components Sector Aggregate Historical Risk-Adjusted Performance

Crowded Hedge Fund Electronic Components Bets

The following stocks contributed most to the relative residual (security-specific) risk of the HF Sector Aggregate as of 2014-09-30. Blue bars represent long (overweight) exposures relative to Sector Aggregate. White bars represent short (underweight) exposures. Bar height represents contribution to relative stock-specific risk:

Chart of the recent crowded stock-specific (idiosyncratic) Hedge Fund Electronic Components Sector bets

Crowded Hedge Fund Electronic Components Sector Bets

The following table contains detailed data on these crowded bets:

Exposure (%) Net Exposure Share of Risk (%)
HF Sector Aggr. Sector Aggr. % $mil Days of Trading
SNDK SanDisk Corporation 40.46 16.60 23.87 584.0 1.7 43.86
FLEX Flextronics International Ltd. 35.31 4.59 30.73 751.9 13.7 37.92
GLW Corning Incorporated 2.68 18.87 -16.19 -396.1 -2.0 5.73
TEL TE Connectivity Ltd. 0.02 17.10 -17.07 -417.9 -3.0 4.84
FSLR First Solar, Inc. 1.38 4.98 -3.60 -88.1 -0.7 3.00
APH Amphenol Corporation Class A 1.31 11.86 -10.55 -258.3 -3.4 1.30
CREE Cree, Inc. 0.82 3.70 -2.88 -70.5 -0.8 1.02
KN Knowles Corp. 3.51 1.70 1.81 44.3 1.1 0.58
PLUG Plug Power Inc. 0.03 0.58 -0.55 -13.5 -0.6 0.47
SANM Sanmina-SCI Corporation 0.00 1.30 -1.30 -31.9 -1.9 0.23
OLED Universal Display Corporation 0.27 1.15 -0.88 -21.5 -1.3 0.17
JBL Jabil Circuit, Inc. 1.67 3.05 -1.38 -33.7 -0.5 0.12
RSYS RadiSys Corporation 0.75 0.07 0.67 16.5 60.7 0.11
IMI Intermolecular, Inc. 0.91 0.08 0.82 20.1 145.2 0.10
RELL Richardson Electronics, Ltd. 1.62 0.09 1.53 37.5 162.9 0.08
CODE Spansion Inc. Class A 0.21 1.05 -0.84 -20.7 -0.3 0.06
PLXS Plexus Corp. 0.00 0.94 -0.94 -23.0 -2.9 0.05
AVX AVX Corporation 0.00 1.69 -1.69 -41.3 -13.2 0.04
VICR Vicor Corporation 0.70 0.19 0.51 12.5 9.9 0.04
FN Fabrinet 0.00 0.39 -0.39 -9.5 -2.8 0.04
Other Positions 0.19 0.23
Total 100.00

Conclusion

SanDisk illustrates the vulnerability to crowded names to mass liquidation by impatient investors. In general, crowded Electronic Component stocks tend to disappoint and hedge funds do even worse in other sectors.

Instead of blindly following hedge funds into popular technology names, investors should be wary of these ideas. Even excellent managers are seldom skilled in all areas and tend to generate the bulk of their active returns from a few specific skills.

The information herein is not represented or warranted to be accurate, correct, complete or timely.
Past performance is no guarantee of future results.
Copyright © 2012-2015, 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 Internet Software Crowding

Hedge funds tend to pile into the same few stocks. In most sectors these crowded bets underperform. In previous articles we discussed the crowding of hedge fund energy as well as exploration and production bets. Internet software stocks show similar underperformance.

Hedge Fund Internet Software Aggregate

If markets were flat since 2004, the aggregate position-weighted hedge fund internet software portfolio (HF Aggregate) would have lost 25%. This is HF Aggregate’s risk adjust return from security selection (αReturn):

Chart of the cumulative risk-adjusted returns from security selection of the HF Internet Software Aggregate

Hedge Fund Internet Software Aggregate’s Residual Returns (αReturns)

Given the compounding of αReturns and internet software sector returns, the cumulative underperformance is even larger: Since 2004 HF Aggregate returned 200%. A portfolio with the same systematic risk as HF Aggregate (Factor Portfolio) returned 300%. Investors in crowded bets missed out on 100% in gains:

Chart of the cumulative total and factor (systematic) returns of the HF Internet Software Aggregate

Hedge Fund Internet Software Aggregate’s Total and Factor Returns

Hedge Fund Internet Software Crowding History

The following video shows the history of crowded hedge fund internet software bets. These are the stocks behind the record:

Current Hedge Fund Internet Software Crowding

The following are the currently crowded hedge fund internet software bets. Just two (long EQIX, short/underweight GOOGL) are responsible for over three quarters of the risk of HF Internet Software Aggregate:

Position (%)
Symbol Name HF Aggregate Market Aggregate Relative Share of Risk (%)
EQIX Equinix, Inc. 23.77 1.63 22.14 53.73
GOOGL Google Inc. Class A 10.51 44.39 -33.88 25.65
TWTR Twitter, Inc. 0.49 3.46 -2.97 4.65
ZNGA Zynga Inc. Class A 2.89 0.26 2.63 3.52
RBDC RBID.com, Inc. 0.00 0.17 -0.17 2.07
P Pandora Media, Inc. 2.41 0.53 1.88 1.87
RAX Rackspace Hosting, Inc. 3.13 0.86 2.27 1.76
SFLY Shutterfly, Inc. 2.32 0.22 2.10 1.38
WBMD WebMD Health Corp. 1.84 0.18 1.66 0.93
NERO NeuroMama Ltd. 0.00 0.74 -0.74 0.75
AKAM Akamai Technologies, Inc. 3.04 1.50 1.54 0.61
TRLA Trulia, Inc. 1.01 0.25 0.76 0.36
IACI IAC/InterActiveCorp. 2.83 0.66 2.16 0.34
YNDX Yandex NV Class A 2.32 0.81 1.51 0.33
MSTR MicroStrategy Incorporated Class A 1.54 0.20 1.34 0.31
LNKD LinkedIn Corporation Class A 2.20 3.20 -1.00 0.27
FB Facebook, Inc. Class A 21.76 22.54 -0.78 0.21
MELI MercadoLibre SA 0.00 0.81 -0.81 0.15
KING King Digital Entertainment Plc 1.05 0.63 0.42 0.13
ECOM Channeladvisor Corporation 0.42 0.06 0.37 0.11

The information herein is not represented or warranted to be accurate, correct, complete or timely.
Past performance is no guarantee of future results.
Copyright © 2012-2014, 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 E&P Crowding History

As we have discussed in earlier articles on hedge fund energy as well as exploration and production crowding, funds pile into the same few stocks. Over time these crowded stocks tend to underperform.

The following video shows the most crowded hedge fund E&P stocks over history, and their historical risk-adjusted performance:

The information herein is not represented or warranted to be accurate, correct, complete or timely.
Past performance is no guarantee of future results.
Copyright © 2012-2014, 
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 Costs – Energy

In recent articles we discussed shared long bets among U.S. hedge funds – a phenomenon called “crowding” – without quantifying its consequences. Crowding is costly to investors, fund managers, and allocators. A prime example of this is the Energy Sector:

  • Over the past 10 years the aggregate hedge fund long energy portfolio (HF Energy Aggregate) delivered negative risk-adjusted returns.
  • Since the energy cycle peaked in mid-2008, HF Energy Aggregate took more risk than the market energy portfolio (Market Energy Aggregate), yet it underperformed.
  • Since mid-2008, HF Energy Aggregate has lost 20% on a risk-adjusted basis.

Hedge Fund Energy Crowding

Our previous article discussed hedge fund (HF) energy herding, We created an aggregate position-weighted portfolio (HF Energy Aggregate) consisting of all long energy equity positions reported by over 400 U.S. hedge funds with medium to low turnover. We then evaluated HF Energy Aggregate’s risk relative to the capitalization-weighted portfolio of energy equities (Market Energy Aggregate) using AlphaBetaWorks’ Statistical Equity Risk Model. The exercise revealed factor (systematic/market) and residual (idiosyncratic/security-specific) crowding.

We mentioned that consensus hedge fund long energy bets tend to disappoint and carry higher risk, but we did not quantify these costs.

Crowded Energy Stocks Underperform

Hedge fund crowding hurts performance. HF Energy Aggregate had poor returns following the peak of the last energy cycle in 2008, even without taking into account its higher risk:

Chart of the historical cumulative returns of Hedge Fund Energy Aggregate  and Market Energy Aggregate

Historical Return for Hedge Fund Energy Aggregate vs. Market Energy Aggregate

The spectacular relative performance of HF Energy Aggregate during the commodity boom and the disastrous relative performance in the subsequent commodity crash suggest herding into higher-risk stocks. This is consistent with the aggregate systematic crowding of hedge funds towards higher market beta.

Crowded Energy Stocks Are Riskier

HF Energy Aggregate tends to carry approximately 20% more market exposure than Market Energy Aggregate:

Chart of the exposure of Hedge Fund Energy Aggregate’ to most significant risk factors

Hedge Fund Energy Aggregate’s Exposure to Significant Risk Factors

Crowded Energy Stocks Have Poor Risk-Adjusted Returns

Due to the higher risk of HF Energy Aggregate, its residual return (risk-adjusted performance due to security selection) is even worse. Investors would have made approximately 20% more over the past 10 years holding an ETF portfolio with similar factor risk (factor portfolio):

Chart of the historical cumulative returns, factor returns, and risk-adjusted returns from security selection of  Hedge Fund Energy Aggregate

Historical Hedge Fund Energy Aggregate Factor and Residual Returns

Investors would have also made approximately 20% more since the mid-2008 energy cycle peak with this factor portfolio:

Chart of the historical cumulative returns, factor returns, and risk-adjusted returns from security selection of Hedge Fund Energy Aggregate  since the 2008 energy cycle peak

Historical Hedge Fund Energy Aggregate Factor and Residual Returns since Cycle Peak

Summary

  • Hedge Fund Energy Aggregate tends to have higher risk than Market Energy Aggregate.
  • Crowded Hedge Fund Energy stocks tend to generate negative risk-adjusted returns.
  • Crowded Hedge Fund Energy stocks tend to outperform in a boom and underperform in a bust: Since mid-2008 energy cycle peak, HF Energy Aggregate underperformed nominally and lost 20% on a risk-adjusted basis.
The information herein is not represented or warranted to be accurate, correct, complete or timely.
Past performance is no guarantee of future results.
Copyright © 2012-2014, 
AlphaBetaWorks, a division of Alpha Beta Analytics, LLC. All rights reserved.
Content may not be republished without express written consent.
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Pure Sector Factors and the Energy Cycle

Separating the Signal from the Noise in the Energy Sector

In an article introducing pure sector factors, we illustrated how market noise obscures relationships among individual sectors, concealing industry-specific performance. As a result, most investors are oblivious of the underlying secular trends and are frequently blindsided by them. This obliviousness can be costly. For example, investors aware of the pure oil and gas producer performance would have been forewarned of the recent energy sector selloff.

Oil and Gas Producer Sector Performance

The selloff in oil and gas producer equities in September and October of 2014 caught some by surprise. It should not have.

A superficial analysis of oil and gas producers’ performance would simply consider historical returns. The sector roughly tracked the broad market, increasing over 200% since 2009 lows:

Chart of the cumulative return of the oil and gas producer sector index

Oil and Gas Producers Sector Index Return

This simple chart conceals powerful secular trends. Obscured by market noise, the underlying energy sector cycle is concealed.

Oil and Gas Producer Pure Sector Factor

We reveal the underlying trends by removing market and macroeconomic effects from security returns and calculating the performance of pure oil and gas producer sector factor. Contrary to the chart above, the sector’s pure performance since 2009 lows was -20%:

Chart of the cumulative historical return  of the oil and gas producers pure sector factor

Oil and Gas Producers Pure Sector Factor Return

The pure sector factor tracks the energy cycle, revealing a story of broad economic and geopolitical trends:

  • Overcapacity and crash of the late-90s;
  • Supply shortages, emerging-market commodity boom, and unconventional revolution of 2000-2008;
  • Low-cost production growth, over-investment, and a return to overcapacity post-2008.

Since the energy cycle peaked in 2008, the oil and gas producer sector has lagged the market, on a risk-adjusted basis, by over 35%. Investors in the sector have missed out on over 35% in gains. This deterioration has been concealed by the broad market rally.

Deterioration in sector-specific performance began around the same time as rapid growth in natural gas supply from Haynesville and Marcellus and oil supply from Bakken. The pure return of producer equities, free from market noise, has been negative even as oil prices advanced. Consequently, pure oil and gas producer performance has been a powerful leading indicator.

Oil and Gas Pipelines Pure Sector Factor

The flip-side of the growth in supply has been the shortage of pipeline capacity. The following are the pure returns for oil and gas pipelines, with market effects removed. This boom in pipelines is a direct consequence of the glut of hydrocarbon production evident in the pure producer performance:

Chart of the pure sector factor return for the oil and gas pipelines sector

Oil and Gas Pipelines Pure Sector Factor Return

Recent Pure Oil and Gas Producer Performance

The poor performance of oil and gas producers in October 2014 was a continuation of a long trend. When the broad market experienced hiccups, the underlying trends became evident:

Chart of the daily return of oil and gas producers pure sector factor

Oil and Gas Producers Pure Sector Factor Daily Return

Conclusions

  • By stripping away the effects of market and macroeconomic variables, we can calculate the returns of pure sector factors.
  • Pure oil and gas producer performance has been a powerful leading indicator of the energy sector selloff.
  • The energy cycle peaked in mid-2008 and producers have been in decline since.
  • Despite sector index return of over 200% since 2009 lows, sector investors missed out on 35% in returns since 2008 – pure sector performance was a decline of over 35%.
  • Failure to isolate pure sector factors left many energy investors complacent and ignorant of the underlying trends as the broad market advanced.

 

The information herein is not represented or warranted to be accurate, correct, complete or timely.
Past performance is no guarantee of future results.
Copyright © 2012-2014, AlphaBetaWorks, a division of Alpha Beta Analytics, LLC. All rights reserved.
Content may not be republished without express written consent.
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