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Realistic Long-short Strategy Performance

| | Posted in: Short Selling, Strategic Allocation

How well do long-short stock strategies work, after accounting for all costs? In their February 2014 paper entitled “Assessing the Cost of Accounting-Based Long-Short Trades: Should You Invest a Billion Dollars in an Academic Strategy?”, William Beaver, Maureen McNichols and Richard Price examine the net attractiveness of several long-short strategies as stand-alone investments (as for a hedge fund) and as diversifiers of the market portfolio. They also consider long-only versions of these strategies. Specifically, they consider five anomalies exposed by the extreme tenths (deciles) of stocks sorted by:

  1. Book-to-Market ratio (BM) measured annually.
  2. Operating Cash Flow (CF) measured annually as a percentage of average assets.
  3. Accruals (AC) measured annually as earnings minus cash flow as a percentage of average assets.
  4. Unexpected Earnings (UE) measured as year-over-year percentage change in quarterly earnings.
  5. Change in Net Operating Assets (ΔNOA) measured annually as a percentage of average assets.

For strategies other than UE, they reform strategy portfolios (long the “good” decile and short the “bad” decile) annually at the end of April using accounting data from the prior fiscal year. For UE, they reform the portfolio at the ends of March, June, September and December using prior-quarter data. They highlight cost of capital, financing costs and rebates received on short positions, downside risk and short-side contribution to performance. They assume that the same amount of capital supports either a long-only portfolio, or a portfolio with equal long and short sides (with the long side satisfying Federal Reserve Regulation T collateral requirements for the short side). They account for shorting costs as fees for initiating short positions plus an ongoing collateral rate set at least as high as the federal funds rate, offset by a rebate of 0.25% per year interest on short sale proceeds. They estimate stock trading costs as the stock-by-stock percentage bid-ask spread. They consider two samples (including delistings): (1) all U.S. listed stocks; and, (2) the 20% of stocks with the largest market capitalizations. Using accounting data as described above for all non-ADR firms listed on NYSE, AMEX and NASDAQ for fiscal years 1992 through 2011, and associated monthly stock returns during May 1993 through April 2013, they find that:

  • Regarding hard-to-borrow/costly-to-short stocks:
    • For the sample of all stocks, those under $1 ($5) comprise 2% to 21% (14% to 65%) of extreme anomaly deciles
    • For the sample of large stocks, those under $1 ($5) comprise 0% (no more than 4%) of extreme anomaly deciles.
  • Regarding trading frictions:
    • Average bid-ask spreads for extreme anomaly deciles for the sample of all stocks (large stocks) range from 4.2% to 8.5% (0.7% to 1.5%).
    • Annual turnover of extreme deciles is relatively low for BM and CF anomalies (45% to 63%) and high for AC, UE, and ΔNOA anomalies (70% or higher).
  • Regarding gross raw performance of the short and long sides of hedge portfolios:
    • Average gross raw annualized returns for stocks in the short sides of hedge portfolios range from 5% to 14.1% across anomalies and stock samples. In other words, the short sides do not decrease in value, and short sides reduce respective hedge portfolio returns.
    • For the sample of all stocks (large stocks), percentages of years with positive returns for short-side stocks across anomalies range from 37% to 63% (58% to 71%). Percentages of years with negative long-side returns range from 21% to 47% for both samples.
    • For the sample of all stocks (large stocks), the worst intra-year return for the short side is -298% for CF (-103% for BM). For three of ten sample-anomaly combinations, the worst intra-year hedge portfolio drawdowns exceed 100% (CF for all stocks, and BM for all stocks and large stocks).
  • Based on net Sharpe ratio, accounting for shorting and trading frictions, the hedge strategies generally do not beat the market. Their volatility reductions do not overcome the combined performance losses from the positive returns of short-side stocks and implementation costs. Leverage does not improve net Sharpe ratios, and elevates downside risks.
  • However, correlations between monthly hedge portfolio and market returns are no higher than 0.39 (and are negative for seven of ten sample-anomaly combinations), such that the hedge portfolios effectively diversify a market position.
    • The market portfolio generates an annualized Sharpe ratio of 0.37.
    • For the sample of all stocks, the highest net annualized Sharpe ratio of 0.75 derives from allocations of 40% to the market, 30% to CF and 30% to ΔNOA. Maximum portfolio drawdown is -42%, and 11% of annual returns are negative.
    • For large stocks, the highest net annualized Sharpe ratio of 0.95 derives from allocations of 40% to the market, 42% to CF and 18% to ΔNOA). Maximum portfolio drawdown is just -12%, and 11% of annual returns are negative.
  • Among long-only strategies, CF has the highest net annualized Sharpe ratio at 0.53. There is very little benefit from diversifying with long-only strategies because return correlations with the market and among the strategies are high.

In summary, evidence indicates that long-short strategies based on widely accepted stock return anomalies do not outperform the market as standalone strategies, but do effectively diversify a market position.

Cautions regarding findings include:

  • Some stocks may not be available for borrowing at all, or available only at collateral rates much higher than assumed.
  • Regarding trading frictions, the study accounts for bid-ask spreads but apparently ignores impact of trading and broker fees. Impact of trading may be substantial for some stocks, and broker fees may be material when position sizes are relatively small.
  • Many investors may not be able to achieve the stock borrowing costs/rebate terms assumed.
  • Using combinations of two related samples and five basic strategies introduces data snooping bias, such that the best performance likely overstates reasonable expectations.
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