1/ Short-Selling Risk (Engelberg, Reed, Ringgenberg)

"Short sellers face unique risks, such as the risk that stock loans become expensive or are recalled. Stocks with more short-selling risk have lower returns, less price efficiency, less short selling."

papers.ssrn.com/sol3/papers.cf…
2/ "We calculate the ln of the variance of the daily Loan Fee for each stock over the past 12 months, then project this variable on a variety of lagged firm and lending market characteristics. The predicted value (ShortRisk) represents a trader’s estimate of short-selling risk."
3/ "Short-selling risk is lower for stocks with traded options and higher immediately following an IPO and for stocks with a large number of failures in the securities lending market.

"We use the predicted value from this model as a forecast of short-selling risk."
4/ "Overall, our findings suggest that higher short-selling risk is a significant limit to arbitrage.

"To start, we form simple portfolios formed by conditioning on our risk measures.

"Figure 1 shows a close connection between short-selling risk and future returns."
5/ "A strategy that buys stocks with low ShortRisk and shorts stocks with high ShortRisk earns positive and statistically significant long-short portfolio returns in each of the five short interest quintiles."
6/ "Table IV repeats the portfolio exercise with FF five-factor alphas.

"Table IV, as with Table III, is consistent with models of limits to arbitrage: we find that the returns to short selling are largest when arbitrage is riskiest."
7/ "The fact that our results are strongest among Micro/Small stocks is not surprising: there is less short-selling risk for Large stocks.

"The 99th of loan fees in the Micro (Large) sample is 1,119 (236) bps. The 90th percentile is 189 (20) bps for Micro (Large) stocks."
8/ "The negative and statistically significant coefficient on ShortRisk is consistent with the hypothesis that short-selling risk is a significant limit to arbitrage.... even after controlling for current short sale constraints and other known predictors of returns."
9/ "The risk of *future* short-selling constraints is associated with decreased price efficiency *today*, independent of short constraints that may exist at the time a short position is initiated."
10/ "Put-call parity is more likely to be violated when short-selling risk is high.

"The impact of ShortRisk increases for options with more time to expiration.

"Short sellers also trade less when short-selling risk is high; this is compounded by long holding horizons."
11/ "Loan fees increase significantly when past returns are in either the highest or the lowest quartile of returns.

"When a short seller’s position moves against her, it is likely that it will also be more difficult to borrow shares in the equity lending market."
12/ "Firms in the bottom (top) decile of past 20-day returns have loan fees that are 13 (10) bps higher. This is large compared to the unconditional mean (median) fee of 85 bps (11 bps).

"(2) and (4) include firm fixed effects so that the coefficients are estimated within-firm."
13/ Related research:

Why Do Price and Volatility Information from the Options Market Predict Stock Returns?


The Loan Fee Anomaly: A Short Seller's Best Ideas


Borrowing Fees and Expected Stock Returns

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More from @ReformedTrader

6 Dec
1/ Pandemic Tail Risk (Breugem, Corvino, Marfè, Schoenleber)

"While tail risk of the market index did not move much before the 2020 COVID-19 outbreak, we document that tail risk of less pandemic-resilient economic sectors boomed in advance."

papers.ssrn.com/sol3/papers.cf… Image
2/ "We compute a measure of [lockdown] resilience based on the capability of a company to implement work-from-home.

"Sectors from low to high resilience are Consumer Staples, Materials, Consumer Disc, Industrial, Energy, Health Care, Utilities, Technology, and Financial." ImageImageImage
3/ "In order to not over or underweight the influence of sectors with a really large or little market capitalization, we compute the equally-weighted return of the respective sectors within each specific resilience group." ImageImage
Read 8 tweets
2 Dec
For trading, policy decisions, the pandemic, and scientists' conclusions (which should almost always be tentative), there is a wide range of reasonable views.

That range reflects the many things we don't know with respect to both theory and application.
Read 5 tweets
1 Dec
New SSRN papers, December 2020
(I haven't read these yet, but they have abstracts that look interesting.)

Leveraged Loans: Is High Leverage Risk Priced in?
papers.ssrn.com/sol3/papers.cf…

Quantile Risk Premiums
papers.ssrn.com/sol3/papers.cf…

November 2020 edition
Investing in the year of Corona: The Modified Risk Parity Portfolios
papers.ssrn.com/sol3/papers.cf…

COVID-19 and Development: Lessons from Historical Pandemics
papers.ssrn.com/sol3/papers.cf…

Decoding the Pricing of Uncertainty Shocks
papers.ssrn.com/sol3/papers.cf…
Extreme Price Co-Movement of Commodity Futures and Industrial Production Growth: An Empirical Evaluation
papers.ssrn.com/sol3/papers.cf…

Smart Retail Traders, Short Sellers, and Stock Returns
papers.ssrn.com/sol3/papers.cf…
Read 11 tweets
1 Dec
1/ Asset Allocation Via Clustering: How Useful Is My Stylebox? Are Most Hedge Funds the Same? (Stock)

"We apply clustering algorithms to asset classes and HF strategies (1990-2020) to investigate cluster stability and compute the returns of risk parity."

papers.ssrn.com/sol3/papers.cf…
2/ "What can machine learning clustering algorithms tell us about which asset classes tend to move together and which have historically stayed further apart? Which hedge fund strategies provide the best diversification in portfolios?"
3/ "We find very little benefit to traditional “style box” diversification over our rolling 3-year periods. While they could make sense to access better alpha, tactical factor exposure, or portfolio beta management, they exhibited only rare opportunities for diversification.
Read 11 tweets
27 Nov
1/ Why Do Price and Volatility Information from the Options Market Predict Stock Returns? (Muravyev, Pearson, Pollet)

"Findings suggest that the IV spread [ATM puts & calls] and skew predict returns because they proxy for expected stock borrowing costs."

papers.ssrn.com/sol3/papers.cf…
2/ "The implied volatility spread is the average difference of the implied volatilities of the available calls and puts with the same strike price and expiration date.

"The IV skew is the difference between the IVs of an out-of-the-money put and an at-the-money call."
3/ "The high correlations between option-implied and
indicative fees suggest that the option-implied borrowing fees can be useful proxies for the actual stock borrowing fees faced by a marginal investor."
Read 16 tweets
26 Nov
1/ Momentum, Reversal, and Seasonality in Option Returns (Jones, Khorram, Mo)

"Option returns in individual stocks have momentum, short-term reversal, and quarterly and annual seasonality. This remains strong after controlling for other characteristics."

papers.ssrn.com/sol3/Papers.cf…
2/ Zero-delta one-month near-the-money straddles in individual stocks are formed each month and held to expiration.

Returns are excess returns calculated based on bid-ask midpoints.

IV-HV uses one-year HV
IV term stpread is calculated between 60-day and 30-day options
3/ "Straddle returns in the previous month are likely to be reversed in the following one.

"At lags 3+, there is momentum. The slope coefficients on lags 3 through 12 are all positive and all statistically significant.

"There is a complete lack of long-term reversal."
Read 20 tweets

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