The regulation of short selling: A transatlantic discussion on policy issues and instruments
Bibliographic record
Abstract
While it is by no means a new trading strategy, short selling has attracted considerable attention on the part of regulators and the public over the last decade. In the midst of the financial crisis, securities markets regulators across the world imposed temporary bans or constraints on short selling. The regulators’ interventions sought “to restore the orderly functioning of securities markets and limit unwarranted drops in securities prices capable of exacerbating the crisis”. Following the crisis, the success of Michael Lewis’ book The Big Short – and subsequent movie – heightened the interest of the public towards this controversial trading strategy. Although regulators have lifted rapidly the temporary bans, the issues raised by short selling have continued to elicit debate in the academic, business and policy-making communities. If short selling attracts such attention, it is arguably because it poses challenges for the goals of financial markets regulation. Indeed, short selling involves market efficiency, stability and integrity. More troubling, it can both support and disrupt these goals, as underscore the mixed empirical record and the anecdotal evidence. Likewise, as commentators have more recently pointed out, short selling has implications for corporate governance. In particular, it can be a powerful tool to uncover fraud, but at the same time unsettle shareholder democracy. Given the breadth of the issues associated with short selling, the academic literature, in both law and financial economics, is vast. Against this rich theoretical and empirical backdrop, the purpose of this paper, which flows from a panel discussion between its three authors, is modest. At a general level, the paper seeks to foster the Trans-Atlantic dialogue on financial markets regulation, taking short selling as a case study. Specifically, it aims at providing a critical perspective on the regulatory choices and techniques used in Europe and Canada for dealing with the issues raised by short selling.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.020 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.006 | 0.021 |
| Scholarly communication | 0.017 | 0.022 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.035 | 0.020 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".