Author: clsadmin

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Law on the Market? Abnormal Stock Returns and Supreme Court Decision-Making (Version 2.01 on arXiv)

clsadmin


Here is Version 2.01 of the Law on the Market Paper —
From the Abstract:  What happens when the Supreme Court of the United States decides a case impacting one or more publicly-traded firms? While many have observed anecdotal evidence linking decisions or oral arguments to abnormal stock returns, few have rigorously or systematically investigated the behavior of equities around Supreme Court actions. In this research, we present the first comprehensive, longitudinal study on the topic, spanning over 15 years and hundreds of cases and firms. Using both intra- and interday data around decisions and oral arguments, we evaluate the frequency and magnitude of statistically-significant abnormal return events after Supreme Court action. On a per-term basis, we find 5.3 cases and 7.8 stocks that exhibit abnormal returns after decision. In total, across the cases we examined, we find 79 out of the 211 cases (37%) exhibit an average abnormal return of 4.4% over a two-session window with an average |t|-statistic of 2.9. Finally, we observe that abnormal returns following Supreme Court decisions materialize over the span of hours and days, not minutes, yielding strong implications for market efficiency in this context. While we cannot causally separate substantive legal impact from mere revision of beliefs, we do find strong evidence that there is indeed a “law on the market” effect as measured by the frequency of abnormal return events, and that these abnormal returns are not immediately incorporated into prices.  

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Lexpo 2017 Amsterdam – The Legal Innovation Event

clsadmin

Legal Innovation is a global phenomena. US, UK, Canada, Australia, Continental Europe, South America, Asia, Central America, Africa, etc. (and new events in new places popping up everyday).

My view is that despite jurisdiction differences – lawyers are lawyers. No matter where I travel they are a recognizable species with similar business, technology and process improvement challenges.

Lexpo 2017 brings this conversation to the Netherlands for the second straight year.  I will be presenting on Artificial Intelligence and Law.

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Harvard Law Seeks to Attract STEM Students

clsadmin


There is an old adage which states that “Innovation is doing the obvious before it is obvious to others.”  Suffice to say – this is a totally obvious but it also very correct.  Getting at least some STEM folks to help lead law forward is really important for the future of this field.  So kudos to Harvard for doing this – particularly because as they say in the NFL — this is a ‘copycat league.’

“School officials particularly hope to lure students interested in science, technology, engineering and math to the field of law, because advanced technical knowledge and skills are in demand. “It’s incredibly valuable to have your attorney understand the underlying biology or the underlying coding systems or the underlying physics that are driving the legal questions,” said Jessica Soban, associate dean for admissions and strategic initiatives.

It is worth noting that this quote frames the effort as working to develop lawyers for technology – which is the right way to sell this idea to a conservative (intelligent but not technically inclined) faculty.

The obvious flip side of this is that some subset of these same folks will also help champion technology (and innovation) for law itself.  I would expect HLS to try to make some sort of play in this direction (but would need more folks with relevant technical skills on the core faculty) … perhaps they could consider a Joint Venture with that other academic institution in Cambridge ?

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Self-Taught Artificial Intelligence Beats Doctors at Predicting Heart Attacks (Via Science News / Plos One)

clsadmin

From Science News – “In the new study, Weng and his colleagues compared use of the ACC/AHA guidelines with four machine-learning algorithms: random forest, logistic regression, gradient boosting, and neural networks.”

We teach 3 out of 4 of these methods in our Legal Analytics Course (which is a machine learning for lawyers class).

The underlying paper was published in Plos One (one of my favorite journals) and the location where we recently published our US Supreme Court Prediction paper.  In that paper, we use a time evolving random forest (with the novel twist of a tree burning protocol).