Stock-Borrow Costs as Signals of Limits to Arbitrage

# "Dusty Corners of the Market" and Limits-to-Arbitrage


# "Dusty Corners of the Market" and Limits-to-Arbitrage












In his 21 November 2014 blog post, Dusty Corners of the Market, John Cochrane seems to imply that certain areas of the market tend to be more resilient to the forces of arbitrage and efficiency.

The paper he provides as an example discusses the cross-section of asset pricing anomalies with respect to sorts performed on the cost to short. The intuition is that asset pricing anomalies should be more pronounced for expensive-to-short securities because would-be shorts-sellers are discouraged and/or prohibited from taking positions which might counterbalance the bullish stances of longs. The evidence supports this intuition; many anomalies appear to be dependent on the hard-to-short anomaly.

I indeed interpret this as evidence for the broader intuition that pricing inefficiencies should be more pronounced and resilient within the market's dusty corners (e.g., under-covered securities and/or securities where barriers to arbitrage forces inhibit market efficiency mechanisms). The 2008 Fama-French paper, Dissecting Anomalies also (indirectly) alludes to this premise by sorting anomalies based on market cap size (i.e., SmB), noting that the strength of some anomalies can be expressed as a function of size.

- What are some indicators that a given security might be inefficiently priced?

- What about efficiently priced (i.e., how can we estimate the degree of information already baked into price)?

- Other than anomalies which can be explained by long/short information asymmetry, what are some are other examples of limits-to-arbitrage?

## Answer by amdopt (score 3)

https://quant.stackexchange.com/a/41353

> What are some indicators that a given security might be inefficiently priced? What about efficiently priced (i.e., how can we estimate the degree of information already baked into price)?

You would need to get lower level data than what was used in this paper that was referenced here. The MSF data is probably fine for the paper, but if you were to drill into it, you would find the information that you are seeking that can be made into an indicator.

Specifically, borrowing rates at different brokers that are meaningfully different would be an obvious indicator of information asymmetry. For example, broker 1 has stock XYZ available at a 2% fee, and broker 2 has the same stock available at a 5% fee. Customers of broker 2 may be borrowing their inventory rapidly, and this information has yet to spread. It will spread as soon as broker 2 is out of stock to lend and broker 2's stock loan desk has to start calling other stock loan desks at other brokers to borrow for its clients.

This is just one example of how borrowing rates could diverge. There are others ways it could happen, but they all point to information asymmetry. The liquidity of the stock, your interpretation of the information, and how quickly you can act will determine if this information can be reliably traded upon--it can't always! You will also need relationships with a few brokers and specifically their stock loan desk to be able to obtain this information, however, it is possible to obtain.

In my experience, these divergences happen often and always due to the decentralized nature of stock lending, but the stocks that they happen to are usually small in market cap and may not be very actively traded.

I'm happy to elaborate on anything above. I hope this helps.