Tag Archives: alpha

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.

Alpha Wounds: Passive Management Is Not Passive

By Jason Voss, CFA Alpha wounds are decisions made by the investment industry that hurt active investment managers. It is my belief that there is still plenty of alpha left to be harvested by discerning research analysts and portfolio managers. So far, I have discussed the deleterious effects of managing to, rather than from, a benchmark ; poor evaluative methodologies by investment industry adjuncts; and the poor diversification of the human resources portfolio at active management houses. This month I point out a fact hiding in plain sight: Passive management is not passive. One of the tremendous and rarely discussed ironies in the active vs. passive debate is that passive management is thought of as the opposite of active management. That is, it is perceived as a ship set adrift in an ocean with no compass heading and no crew. Passengers are on board and left to fend for themselves. I politely disagree. Passive management is not blind, deaf, or dumb. In fact, for every index and for every fund or exchange-traded fund (ETF) designed to track it, human choice is involved. As I have discussed before in an entirely different context, choices are actions , that is, activity. That is, we are talking about active investing. To be fair, passive investing is not exactly “active” investing. It is really more like “less active” investing. Given a) the consistent inability of active managers to beat benchmarks, and b) the fact that passive investing actually involves active choices, maybe it makes sense to see what the indices are doing, right? . . . Right? Case Study: The S&P 500 Let’s consider one very famous index, the Standard & Poor’s 500. I hope it is indisputable that the S&P 500 is among the best-known indices and hence a proxy for stock market activity in the United States. Is an index fund or ETF that tracks the storied S&P 500 truly passive? Absolutely not. Many do not realize that a small committee at Standard & Poor’s oversees and makes decisions about the index. Specifically: “S&P Dow Jones U.S. indices are maintained by the U.S. Index Committee. All committee members are full-time professional members of S&P Dow Jones Indices’ staff. The committee meets monthly. At each meeting, the Index Committee reviews pending corporate actions that may affect index constituents, statistics comparing the composition of the indices to the market, companies that are being considered as candidates for addition to an index, and any significant market events. In addition, the Index Committee may revise index policy covering rules for selecting companies, treatment of dividends, share counts or other matters.” To me this sounds very similar to a description of the activities of an investment committee at an actively managed mutual fund. Yes, there is certainly a demure, passive tone. No doubt. But there are decisions being made here. Which brings me to my next point. Perhaps active managers would be wise to examine the nature of the decision criteria made by this committee in order to improve their own results. This is especially true if, like many funds, the S&P 500 is their benchmark. Put another way: What is this committee doing so incredibly right so as to best a majority of those competing against it? Here are the criteria that the US Index Committee consider: Market capitalization Liquidity Domicile Public float Sector classification Financial viability Treatment of IPOs A list of eligible securities Additionally, there are criteria for deleting an issue. Some of the above may seem simple on the face of things, but let’s drill a little deeper. The Hidden Story Inside Market Capitalization Market capitalization is indicative of some unique characteristics of a business. For example, a large market capitalization is likely the result of a highly successful business with in-demand products, well-established markets, a strong competitive position, that is professionally managed, well capitalized financially, and for which all of these things have been true over a long period of time. Heck, it is also more likely than not that the business pays its shareholders back with share buybacks, or – gasp! – dividends. In other words, large market capitalization is a natural outcome of running a successful business. The Remedy for the Alpha Wound: Could “active” managers also consider such criteria in conducting fundamental analysis? Could active managers actually roll up their sleeves and engage in some good old-fashioned fundamental analysis? Low Turnover Like most indices, the components of the S&P 500 do not change very frequently . A review of the historical data from 2002 through November 2015 shows 69 additions (and, hence, deletions) from the index. That works out to a turnover ratio of just 1.06% [(69 changes ÷ 13 years = 5.31 changes per year on average) ÷ 500]. Compare that with the average turnover ratio of 124.6% in the United States in 2012 (the last year for which data is available), and an average of the major global equity markets of 89%. Is there any possibility of actually understanding the companies in which you have placed your investors’ cash in these circumstances? Said differently, US investors have 117.5 times the turnover of the S&P 500. Given that most of the trading is likely in S&P 500 stocks, that the turnover of the index is so low, and that active managers have underperformed, does it seem like a possible self-inflicted alpha wound? In the most positive light, this is a trading desk enrichment program. The Remedy for the Alpha Wound: Could an “active” manager perform better by reducing its turnover? Diversification Another possible lesson to be learned from looking at indices is that each of them represents a diversified portfolio within a given context. For the record, I am personally against what I and many others call “deworsification”. Forthcoming research from C. Thomas Howard, CIO of Athena Investment Management, and a brokerage firm I cannot mention quite yet, entitled Why Most Equity Mutual Funds Underperform and How to Identify Those That Outperform, demonstrates that most fund managers are horribly diversified – as in overly so. The researchers estimate that for every one-decile increase, that over-diversification subtracts 13.5 basis points (bps). Also, they estimate that for every one-decile increase in closet-indexing, that performance is negatively affected by a whopping 31.6 bps. So as managers r-squared relative to their benchmark increases, performance decreases. It is important to remember that originally indices were created not as investment vehicles, but as a way of summarizing the performance of an entire market in one number. No one is likely to have originated the idea of investing in 500 companies. One benefit of being fully invested in each component of the S&P 500 is you end up buying every winner. But you also end up buying every loser. One simple strategy, and I am surprised that it is not deployed more frequently, is to buy the S&P 500 but to conduct fundamental analysis of its components and identify the handful of firms you believe have the highest probability of performing poorly. Then either exclude these from your index-like fund or short them. The Remedy for the Alpha Wound: Could it be that active managers are hurting alpha by over-diversifying and closet-indexing? “Passive” Investing Free Passes Passive investing gets three massive free passes. First, frequently risk-adjusted returns are calculated relative to the benchmark. This means that because benchmarks are both the numerator and the denominator in such calculations, their risk is always cancelled out. This implies that benchmarks have no risk. Clearly this is bogus. What is needed is a neutral way of evaluating risk to which both the benchmark and the active manager are compared. Second, benchmark returns are always gross of fees. Yet, if you read through the S&P Dow Jones report I referenced above, you get the sense that there is a large team making these decisions. What is the expense of creating and maintaining these indices? Also, the expense of buying and selling the securities from the benchmark is excluded. Yes, the turnover is low, but for a true apples-to-apples comparison, shouldn’t these be included? As a proxy, many investment industry adjuncts evaluate index funds tracking a particular benchmark in order to estimate these expenses. This is clearly fairer to active managers. The third and likely largest of the free passes handed to passive investors is the massive momentum effects of their “buy lists.” Indices are effectively “buy” lists. For the larger indices this means that there are huge momentum effects embedded into the strategies. So passive investors benefit considerably from non-fundamental factors when their performance is evaluated. To my knowledge, there is no agreed-upon method for how to back these factors out. In conclusion, passive investing is not truly passive. It is more like less active management. Looked at in this way, it makes obvious certain innate characteristics of smart investing that “passive” investors take advantage of. Maybe active managers could learn a thing or two from these strategies. Disclaimer: Please note that the content of this site should not be construed as investment advice, nor do the opinions expressed necessarily reflect the views of CFA Institute.