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The Costs Of Hedge Fund Crowding In Q3 2015

Analyzing Hedge Fund Sector Crowding Our edge comes from a central thesis: the most crowded stocks are those that contribute the most to hedge fund stock-specific volatility (volatility of alpha) . Furthermore, the direction of this alpha (positive or negative) is a leading indicator. A robust analysis of the AlphaBetaWorks Statistical Equity Risk Model allows us to identify stocks that are the highest contributors to stock-specific volatility for hedge funds in each sector. These are the most crowded stocks that stand to benefit the most from accumulation and stand to lose the most from liquidation. While a static crowding analysis using our risk model provides valuable insights, we go further by identifying Hedge Fund Aggregate Sector Alpha – the alpha (stock-specific performance) of aggregated hedge fund portfolios by sector. This makes the analysis dynamic: If Hedge Fund Aggregate Sector Alpha is trending up, capital is flowing into crowded stocks. Conversely, if it is trending down, capital is flowing out of crowded stocks – often abruptly. Yes, crowding is good at some times and bad at others. Further, Hedge Fund Aggregate Sector Alpha trends persist for months and years, providing advanced notice of losses. Importantly, crowded stocks hit hard by liquidations tend to mean-revert: the worst risk-adjusted performers often become attractive long opportunities. Hedge Fund Sector Aggregates We create aggregate portfolios of hedge fund positions in each sector. Each such sector portfolio is a Hedge Fund Sector Aggregate within which we identify the highest contributors to security-specific (residual) volatility (the most crowded stocks). This follows the approach of our earlier articles on hedge fund crowding . The Hedge Fund Sector Aggregate Alpha ( α Return , residual , or security-specific return ) measures hedge fund security selection performance in a sector. It is the return HF Sector Aggregate would have generated if markets had been flat. αReturn can indicate accumulations and liquidations. The AlphaBetaWorks Statistical Equity Risk Model, a proven tool for forecasting portfolio risk and performance , estimated factor exposures and residuals . Without an effective risk model, simplistic crowding analyses ignore the systematic and idiosyncratic exposures of positions and typically merely identify companies with the largest market capitalizations. Sectors with the Largest Losses from Hedge Fund Crowding During Q3 2015, hedge funds lost $4 billion to security selection in the five sectors below. Said another way: if hedge funds had simply invested passively with the same risk, their sector long equity portfolios would have made $4 billion more. The monthly losses are listed (in $millions) below: 7/31/2015 8/31/2015 9/30/2015 Total Other Consumer Services -101.16 -113.93 -312.84 -426.77 Oil and Gas Pipelines 472.21 -465.63 -10.29 -475.93 Specialty Chemicals -155.87 196.41 -730.73 -534.32 Oil Refining and Marketing 262.69 -167.15 -388.52 -555.67 Semiconductors -240.71 -1,422.70 -660.95 -2,083.65 The Semiconductor Sector was particularly painful for hedge funds in Q3 2015, which we examined in a previous article . Below we provide our data on three of the above sectors: historical Hedge Fund Sector Alpha and the most crowded names. Specialty Chemicals – Hedge Fund Alpha and Crowding Hedge Fund Specialty Chemicals Security Selection Performance Click to enlarge Historical Return from Security Selection of Hedge Fund Specialty Chemicals Sector Aggregate Hedge Fund Specialty Chemicals Crowding Click to enlarge Crowded Hedge Fund Specialty Chemicals Sector Bets The following table contains detailed data on these crowded holdings: Exposure (%) Net Exposure Share of Risk (%) HF Sector Aggr. Sector Aggr. % $mil Days of Trading (NYSE: PAH ) Platform Specialty Products Corp. 17.59 2.52 15.07 1,351.8 14.3 44.62 (NYSE: APD ) Air Products and Chemicals, Inc. 47.46 13.89 33.57 3,010.8 13.7 22.09 (NYSE: LYB ) LyondellBasell Industries NV 3.36 23.03 -19.67 -1,764.2 -5.9 14.04 (NASDAQ: GRBK ) Green Brick Partners, Inc. 2.99 0.25 2.74 245.7 79.7 10.58 (NYSE: GRA ) W. R. Grace & Co. 11.76 3.45 8.32 745.8 11.0 2.99 (NYSE: PX ) Praxair, Inc. 0.31 16.29 -15.98 -1,433.5 -5.9 2.21 (NYSE: AXLL ) Axiall Corporation 2.79 1.20 1.59 142.8 4.5 0.74 (NYSE: TROX ) Tronox Ltd. 1.80 0.45 1.35 121.2 14.2 0.36 (NYSE: ARG ) Airgas, Inc. 0.19 3.77 -3.59 -321.8 -4.1 0.33 (NASDAQ: SIAL ) Sigma-Aldrich Corporation 3.32 7.88 -4.56 -408.6 -2.3 0.28 (NYSE: NEU ) NewMarket Corporation 0.23 2.61 -2.38 -213.4 -6.0 0.26 (NYSE: VHI ) Valhi, Inc. 0.02 0.91 -0.88 -79.2 -240.2 0.26 (NYSE: CYT ) Cytec Industries Inc. 0.07 2.04 -1.97 -176.5 -2.0 0.18 (NYSE: ASH ) Ashland Inc. 1.66 3.89 -2.23 -200.0 -2.4 0.18 (NYSE: POL ) PolyOne Corporation 0.19 1.65 -1.46 -131.2 -4.3 0.10 (NASDAQ: TANH ) Tantech Holdings Ltd. 0.00 0.19 -0.19 -17.3 -2.7 0.09 (NASDAQ: BCPC ) Balchem Corporation 0.00 0.82 -0.82 -73.4 -8.8 0.07 (NYSE: CBM ) Cambrex Corporation 0.06 0.65 -0.59 -53.2 -2.1 0.06 (NYSE: CMP ) Compass Minerals International, Inc. 0.15 1.31 -1.16 -104.0 -4.8 0.06 … Other Positions 0.29 0.51 Total 100.00 Oil Refining and Marketing – Hedge Fund Alpha and Crowding Hedge Fund Oil Refining and Marketing Security Selection Performance Click to enlarge Historical Return from Security Selection of Hedge Fund Oil Refining and Marketing Sector Aggregate Hedge Fund Oil Refining and Marketing Crowding Click to enlarge Crowded Hedge Fund Oil Refining and Marketing Sector Bets The following table contains detailed data on these crowded holdings: Exposure (%) Net Exposure Share of Risk (%) HF Sector Aggr. Sector Aggr. % $mil Days of Trading (NYSE: MWE ) MarkWest Energy Partners, L.P. 18.23 5.31 12.92 848.9 6.1 31.86 (NYSE: VLO ) Valero Energy Corporation 0.38 16.06 -15.68 -1,030.4 -2.7 23.34 (NYSE: TSO ) Tesoro Corporation 14.32 5.36 8.96 589.0 1.4 12.74 (NYSE: TRGP ) Targa Resources Corp. 8.99 2.52 6.47 425.3 8.7 7.76 (NYSE: PSX ) Phillips 66 9.21 21.86 -12.66 -831.8 -2.8 6.03 (NYSE: PBF ) PBF Energy, Inc. Class A 6.80 1.23 5.56 365.6 7.8 5.84 (NYSE: NGLS ) Targa Resources Partners LP 8.74 3.52 5.21 342.7 6.2 2.84 (NYSE: WGP ) Western Gas Equity Partners LP 3.58 6.63 -3.05 -200.5 -7.4 2.06 (NYSE: MPC ) Marathon Petroleum Corporation 9.59 14.34 -4.75 -312.0 -1.1 1.81 (NYSE: TLLP ) Tesoro Logistics LP 5.12 2.33 2.79 183.1 3.5 1.45 (NYSE: HFC ) HollyFrontier Corporation 1.29 4.22 -2.93 -192.3 -1.4 1.11 (NYSE: WNR ) Western Refining, Inc. 0.21 2.10 -1.89 -124.5 -1.4 0.61 (NYSE: IOC ) Interoil Corporation 0.66 1.50 -0.84 -55.3 -6.9 0.49 (NYSE: GEL ) Genesis Energy, L.P. 4.35 2.20 2.15 141.1 6.2 0.34 (NYSE: ENBL ) Enable Midstream Partners LP 0.39 1.73 -1.34 -88.2 -31.6 0.33 (NYSE: EMES ) Emerge Energy Services LP 0.01 0.43 -0.42 -27.6 -6.1 0.29 (NYSE: DK ) Delek US Holdings, Inc. 0.00 1.07 -1.07 -70.0 -1.2 0.26 (NYSE: WNRL ) Western Refining Logistics, LP 1.57 0.36 1.21 79.5 15.0 0.24 (NYSE: ALJ ) Alon USA Energy, Inc. 0.00 0.67 -0.67 -44.1 -2.3 0.18 (NYSE: NS ) NuStar Energy L.P. 3.50 2.33 1.17 76.9 1.4 0.15 … Other Positions 0.07 0.28 Total Semiconductors – Hedge Fund Alpha and Crowding Hedge Fund Semiconductor Security Selection Performance Click to enlarge Historical Return from Security Selection of Hedge Fund Semiconductors Sector Aggregate Given the magnitude of recent semiconductor sector liquidations and the record of mean-reversions, the following crowded hedge fund semiconductor bets may now be especially attractive: Hedge Fund Semiconductor Crowding Click to enlarge Crowded Hedge Fund Semiconductors Sector Bets The following table contains detailed data on these crowded holdings: Exposure (%) Net Exposure Share of Risk (%) HF Sector Aggr. Sector Aggr. % $mil Days of Trading (NYSE: SUNE ) SunEdison, Inc. 33.18 1.82 31.36 2,550.9 9.6 86.72 (NASDAQ: MU ) Micron Technology, Inc. 18.87 3.95 14.93 1,214.1 2.9 8.85 (NASDAQ: INTC ) Intel Corporation 3.72 27.94 -24.22 -1,970.2 -1.6 2.01 (NASDAQ: SEMI ) SunEdison Semiconductor, Inc. 3.22 0.14 3.08 250.7 52.5 0.38 (NASDAQ: SWKS ) Skyworks Solutions, Inc. 0.04 3.85 -3.82 -310.4 -0.9 0.38 (NASDAQ: TXN ) Texas Instruments Incorporated 0.09 10.38 -10.28 -836.6 -1.9 0.32 (NASDAQ: NXPI ) NXP Semiconductors NV 7.90 4.41 3.49 283.6 1.0 0.29 (NASDAQ: AVGO ) Avago Technologies Limited 3.29 6.69 -3.40 -276.3 -0.5 0.18 (NYSE: FSL ) Freescale Semiconductor Inc 0.02 2.40 -2.38 -193.5 -5.2 0.17 (NASDAQ: ON ) ON Semiconductor Corporation 3.39 0.97 2.42 196.6 4.3 0.08 (NASDAQ: MLNX ) Mellanox Technologies, Ltd. 1.89 0.43 1.45 118.3 0.7 0.08 (NASDAQ: BRCM ) Broadcom Corporation Class A 7.81 5.51 2.30 187.2 0.5 0.07 (NYSE: MX ) MagnaChip Semiconductor Corporation 0.92 0.05 0.87 70.9 31.2 0.07 (NASDAQ: ADI ) Analog Devices, Inc. 0.05 3.90 -3.85 -312.9 -1.7 0.06 (NASDAQ: QRVO ) Qorvo, Inc. 1.13 2.32 -1.19 -96.7 -1.1 0.06 (NASDAQ: NVDA ) NVIDIA Corporation 0.58 2.10 -1.51 -123.1 -0.4 0.04 (0Q19) CEVA, Inc. 1.25 0.08 1.17 95.5 30.7 0.04 (NASDAQ: MRVL ) Marvell Technology Group Ltd. 0.04 1.32 -1.28 -104.4 -0.9 0.03 (NASDAQ: MXIM ) Maxim Integrated Products, Inc. 0.34 1.90 -1.56 -126.9 -1.7 0.02 (NYSE: MXL ) MaxLinear, Inc. Class A 0.74 0.12 0.62 50.6 2.8 0.02 … Other Positions 0.36 0.13 Total Conclusions Data on the crowded names and their alpha can reduce losses and provide profitable investment opportunities. A robust and predictive equity risk model is necessary to accurately identify hedge fund crowding. Fund followers and allocators aware of crowding can gain new insights into portfolio risk, manager skill, and fund differentiation. Crowded bets tend to mean-revert following liquidation: the worst risk-adjusted performers in a sector become the best. The information herein is not represented or warranted to be accurate, correct, complete or timely. Past performance is no guarantee of future results. Copyright © 2012-2016, AlphaBetaWorks, a division of Alpha Beta Analytics, LLC. All rights reserved. Content may not be republished without express written consent.

ETF Relationships That May Tell You When The Worst Is Over

Businesses, consumers and the federal government have taken on enormous amounts of debt since the Great Recession. Optimists argue that total debt is irrelevant; that is, they believe the only thing that matters is the cost of servicing those debts. Fair enough. Then what happens when interest expense does rise? Assuming total debt remains the same, higher rates would increase the percentage of household income or the percentage of corporate/government revenue that must be allocated to debt servicing. In earlier commentary, I provided data showing how the total debt of corporations has DOUBLED since 2007. Thanks to seven years of zero percent rate policy, alongside a number of iterations of quantitative easing (QE), the average rate on corporate debt is down from eight years ago. More critically, however, average interest expense has risen substantially . That’s right. Corporations need to assign more and more of their “gross” toward paying back the interest on their loans. What about households? Well, we’re back to the 2007 record debt level of $14.1 trillion in mortgages, credit cards, auto loans, student loans and credit cards; the typical household has nearly $130,000 in total debt. The good news? Years of stimulative monetary policy has made it easier for households to service these debts. The bad news? Americans “re-leveraged” rather than “de-leveraged.” Any amount of rate hike activity would damage the ability of average Americans to borrow-n-spend. In fact, recent retail data demonstrate just how little Americans feel they have left over to spend, in spite of massive savings at the gas pump. Traditional home affordability measures like median sales price-median income illustrate just how dependent we are on ultra-low interest rates. Specifically, the historical home price-to-household income ratio is 2.6. Where are we at today? Back near the housing bubble highs of 4.0. It certainly does not get any better if one looks at U.S. government obligations. The national debt is roughly $19 trillion, excluding the country’s unfunded liabilities (e.g., Social Security, Medicare, Medicare prescription drug program, federal pensions, etc.). According to Dave Walker, the former head of the Government Accountability Office (NYSE: GAO ) under Presidents George W. Bush and Bill Clinton, the national debt is closer to $65 trillion, including unfunded liabilities. Does anyone believe that those numbers are going to get smaller? Or even, heaven forbid, remain the same? In other words, rising interest expense or rising debt levels would make it even more difficult for the government to honor its obligations. Is it any wonder, then, how schizophrenic riskier assets are? It is the direction of the Fed’s rate normalization path – no matter how gradual – that has nudged the bear out of hibernation . China? Its slowing economy adversely affects corporate profits, but it’s the Fed’s perceived reluctance to “save stocks” that has agitated market participants. Oil? Its rapid-fire descent highlights the possibility of a worldwide recession, though it is the Federal Reserve’s disinclination to “step in” that is rocking investor confidence. Fortunately, there are a number of ETF relationships that can help a cash-heavy investor identify when things may be getting better. More precisely, when “risk-off” relationships abate, one may feel more upbeat about shifting from a mode of capital preservation to a mode of wealth accumulation. Consider the relationship between gold and oil. When people prefer the precious metal to the natural resource, they are expressing a preservation preference. And vice versa. When investors speculate that oil prices will rise, they are typically expressing confidence in the growth of the global economy. It follows that the SPDR Gold Trust ETF (NYSEARCA: GLD ) : The United States Oil ETF, LP (NYSEARCA: USO ) price ratio is likely to climb in troubling times; it is likely to spike in panicky stock sell-offs. One might wish to see the slope of the GLD:USO 200-day moving average flatten out – and the GLD:USO price settle down a bit – prior to making huge commitments to riskier assets. Granted, the rapid depreciation of oil itself has had a fair amount to do with the general trend of GLD:USO. Nevertheless, all three of the most recent corrective phases in U.S. stocks – October of 2014, August-September of 2015, January of 2016 – dovetail perfectly with spikes in GLD:USO. In the same vein, the flattening of the yield curve tells market watchers that participants are concerned about recession probabilities. The difference between the 10-year Treasury bond yield and the 2-year Treasury bond yield has fallen to lows that we haven’t seen since the Fed shocked-n-awed the world with its most powerful stimulus ever, QE3. Of course, some folks prefer to remain in the world of specific ETF assets as well as rising/falling price ratio relationships. For those investors, I suggest that they track the iShares 7-10 Year Treasury Bond ETF (NYSEARCA: IEF ):iShares 1-3 Year Treasury Bond ETF (NYSEARCA: SHY ) price ratio. A rising price ratio implies that people are seeking safety in the middle of the yield curve, while others may be avoiding the short end of the yield curve due to Federal Reserve rate hike intentions. Thus, the yield curve is flattening when IEF:SHY is rising. Since the stock market highs in July, IEF:SHY has, for the most part, been on a steady path higher. A sustained reversal in this trend would be an indication that investors are growing more comfortable with the health of the domestic economy. Disclosure: Gary Gordon, MS, CFP is the president of Pacific Park Financial, Inc., a Registered Investment Adviser with the SEC. Gary Gordon, Pacific Park Financial, Inc, and/or its clients may hold positions in the ETFs, mutual funds, and/or any investment asset mentioned above. The commentary does not constitute individualized investment advice. The opinions offered herein are not personalized recommendations to buy, sell or hold securities. At times, issuers of exchange-traded products compensate Pacific Park Financial, Inc. or its subsidiaries for advertising at the ETF Expert web site. ETF Expert content is created independently of any advertising relationships.

WisdomTree Makes Early Splash In 2016

Despite market volatility, 2016 looks to be a big year for WisdomTree (NASDAQ: WETF ). The New Year’s confetti had hardly been cleared when the firm announced it had completed its acquisition of GreenHaven Commodity Funds, the managing owner of the GreenHaven Continuous Commodity Index Fund (NYSEARCA: GCC ) and GreenHaven Coal Services. The news came on January 4, the first business day of 2016, and it was quickly followed up by another big announcement: the firm’s launch of a four-fund suite of dynamic currency-hedged ETFs: WisdomTree Dynamic Currency Hedged Europe Equity Fund (BATS: DDEZ ) WisdomTree Dynamic Currency Hedged Japan Equity Fund (BATS: DDJP ) WisdomTree Dynamic Currency Hedged International Equity Fund (BATS: DDWM ) WisdomTree Dynamic Currency Hedged International SmallCap Equity Fund (BATS: DDLS ) “WisdomTree’s dynamic currency hedged strategy limits the need to make a call on currency by utilizing a data-driven, rules-based approach that assesses the picture of developed market currencies relative to the U.S. dollar on a monthly basis,” said WisdomTree Director of Research Jeremy Schwartz, in a statement. “This offers the potential for an attractive strategic and baseline exposure for long-term portfolios.” Move Into Commodities The GreenHaven acquisition also involves alternative investment funds. In addition to the GCC ETF, WisdomTree’s acquisition of GreenHaven Coal Services also includes the GreenHaven Coal Fund (NYSEARCA: TONS ), which GreenHaven Coal Services sponsors. GreenHaven has been retained by WisdomTree as the sub-advisor to both funds. “The acquisition of these ETFs represents WisdomTree’s first foray into the commodities space and exemplifies our commitment to growing an innovative, differentiated and diversified product platform,” said WisdomTree CEO Jonathan Steinberg. “Today in the U.S. alone we offer 88 ETFs across traditional equities and currency-hedged equities, domestic and international fixed income, currencies, and alternatives strategies including commodities.” GCC returned -18.99% in 2015, a very tough year for commodities, ranking in the top 12% of its Morningstar category. TONS launched in February 2015 and returned -20.90% in the final six months of 2015, but that was good enough for it to rank in the top 1% of its category. The two funds have respective net-expense ratios of 0.85% and 1.23%. Three of the new currency hedged equity ETFs – DDEZ, DDJP, and DDLS – have net-expense ratios of 0.43%. DDWM has a net-expense ratio of 0.35%. Past performance does not necessarily predict future results. Jason Seagraves contributed to this article.