1/ Borrowing Fees and Expected Stock Returns (Hendrix, Crabb)
"Stocks with high borrowing fees tend to underperform their peers over the short term, but persistence of high borrowing fees is fast-decaying and not systematically predictable."
2/ "Lending data are sourced from a proprietary database maintained by DFA that contains the global lending activity of its US mutual funds.
"Fee = fed funds rate (or OBFR) – rebate rate.
"We compute a weighted average (by number of shares in each loan) fee for each security."
3/ Small caps are the 10% lowest U.S. market cap, 12.5% in developed ex-U.S., and 15% smallest in emerging markets
Small caps tend to have higher borrowing fees than large caps, more stocks on loan, and a greater dispersion in fees required to borrow the stocks.
4/ High-fee = 50+ percentile (market cap weighted fees)
For a one-day lookback window, "stocks on loan with a high fee have annualized returns that are 8.85% lower than for stocks not on loan.
"We observe the same pattern using three-day and five-day lookback periods."
5/ Again for small caps, "across all countries in every year from 2011 through 2018, high-fee stocks, on average, underperform not-on-loan stocks."
6/ For the one-day lookback window, "in all countries, small cap high-fee stocks underperform small cap stocks not on loan.
"Results for the three-day and five-day periods are consistent."
7/ Again for small caps, "high-fee stocks not only underperform stocks not on loan on the next day but also continue to meaningfully underperform in the week following portfolio sorts. The magnitude of annualized average underperformance is similar."
8/ Again for small caps, "stocks that remain high fee tend to persist in underperformance, while high-fee stocks that migrate out of that category tend to perform in line with stocks not on loan."
NOTE: "We are forming portfolios with information not known at time t."
9/ "One year after we assign small cap stocks to high- and low-fee categories, only half of high-fee stocks remain in their starting category, on average."
10/ "Small cap stocks in the top fee decile and with a high utilization are more likely to also have a high fee over the subsequent five days, one month, six months, or one year than other high-fee stocks."
11/ "High-fee stocks with lower market cap and higher P/B have a higher likelihood of staying high-fee, but this explains only 3.6% of the variation.
"The model assesses point-to-point persistence; stocks are even less likely to stay high fee consistently throughout the year."
12/ "A daily-rebalanced strategy that sells small caps when they are high-fee and buys them back when they cross the threshold would have increased turnover of 1,153%/year.
"Excluding only the top fee decile, high-utilization stocks still has 120%/year additional turnover."
13/ "It would also forgo the high lending revenue from high-fee stocks and reduce diversification.
"Given these considerations, an efficient approach may be to temporarily refrain from purchasing the most expensive-to-borrow stocks."
14/ "Among *large cap* stocks, stocks on loan with a high fee on average underperform stocks not on loan by 7.44% annualized, with a t-statistic of –2.56.
"Results are similar among *all cap* stocks, though slightly stronger due to the inclusion of small caps."
15/ Related reading:
Equity Factors: To Short Or Not To Short, That is the Question
1/ Nudge: Improving Decisions About Health, Wealth, and Happiness (Thaler, Sunstein)
"Small and apparently insignificant details (nudges) can impact people's behavior without forbidding any options or significantly changing economic incentives." (p. 6)
2/ "To count as a nudge, the intervention must be easy and cheap to avoid. Nudges are not mandates. Putting the fruit at eye level counts as a nudge. Banning junk food does not.
"The power of these small details comes from focusing people's attention in a particular direction.
3/ " “If a man sees a fly, he aims at it.” Kieboom, an economist, directs Schiphol’s building expansion. His staff conducted trials and found that etching images of house flies in urinals reduces urine spillage by 80%." (p. 4)
For the record, getting a tablet is an attempt to nudge myself into reading more papers. I'm hoping it will get me to one paper per day, but I am notoriously bad at predicting like every other member of the human race. 🤣
If you're in a disagreement with someone and he sends you links to research explaining his position and adding nuance, please don't ignore the e-mail and then continue with your original criticism.
Thanks very much!
</public service announcement>
(Although you may not realize it, criticizing and then ignoring the other person's perspective effectively makes the conversation one-sided, even though both people may appear to be continuing to talk.)
On a practical level, I think something like this happens whenever diversification-based approaches like risk parity and factors are brought up.
Those are automatically 'wrong' because there is only one valid approach (cap-weighted U.S. stocks with a sprinking of Treasuries.)
1/ Superforecasting: The Art and Science of Prediction (Tetlock, Gardner)
"Foresight isn’t a mysterious gift bestowed at birth. It is the product of particular ways of thinking, of gathering information, of updating beliefs." (p. 18)
2/ "The news delivers forecasts without asking how good the forecasters really are. Corporations and governments pay for forecasts that may be prescient, worthless, or something in between. All of us make critical decisions based on forecasts whose quality is unknown." (p. 3)
3/ "Pundits are not on the news because they possess proven skill at forecasting. Old forecasts are like old news—soon forgotten. Pundits are not asked to reconcile what they said with what happened later.
"Talking heads are skilled at telling a compelling story with conviction.
"My brother bought silver coins at a premium of 20% over face value. It was an asymmetric risk trade: you could lose a maximum of 20%, but the upside was unlimited.
"By 1974, silver had more than tripled. My brother was driving around in a Mercedes-Benz." (p. 7)
3/ "Charts have become much less reliable. In the 1970s-80s, patterns were neat. There were fewer whipsaws. There weren’t a lot of people looking at charts.
"I think high-frequency trading creates volatility around breakout points. Markets are more mature, with bigger players.