The Development of Structure in the Citation Network of the United States Supreme Court

This is one of our all time best efforts from a scientific perspective (and it is now 7 years old).  We did a rehash of it in our recent paper in the March 31, 2017 edition of Science magazine.

What are some of the key takeaway points?

(1) The Supreme Court’s increasing reliance upon its own decisions over the 1800-1830 window.

(2) The important role of maritime/admiralty law in the early years of the Supreme Court’s citation network. At least with respect to the Supreme Court’s citation network, these maritime decisions are the root of the Supreme Court’s jurisprudence.

(3) The increasing centrality of decisions such as Marbury v. Madison, Martin v. Hunter’s Lessee to the overall network.

The Development of Structure in the SCOTUS Citation Network

The visualization offered above is the largest weakly connected component of the citation network of the United States Supreme Court (1800-1829). Each time slice visualizes the aggregate network as of the year in question.

In our paper entitled Distance Measures for Dynamic Citation Networks, we offer some thoughts on the early SCOTUS citation network. In reviewing the visual above note ….“[T]he Court’s early citation practices indicate a general absence of references to its own prior decisions. While the court did invoke well-established legal concepts, those concepts were often originally developed in alternative domains or jurisdictions. At some level, the lack of self-reference and corresponding reliance upon external sources is not terribly surprising. Namely, there often did not exist a set of established Supreme Court precedents for the class of disputes which reached the high court. Thus, it was necessary for the jurisprudence of the United States Supreme Court, seen through the prism of its case-to-case citation network, to transition through a loading phase. During this loading phase, the largest weakly connected component of the graph generally lacked any meaningful clustering. However, this sparsely connected graph would soon give way, and by the early 1820’s, the largest weakly connected component displayed detectable structure.”

We also explore this network in our 2010 paper — Michael Bommarito, Daniel Martin Katz, Jonathan Zelner & James Fowler, Distance Measures for Dynamic Citation Networks 389 Physica A 4201 (2010) < SSRN > < arXiv >

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

Here is Version 2.01 of the Law on the Market Paper
From the AbstractWhat 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.  

A General Approach for Predicting the Behavior of the Supreme Court of the United States (PLOS One) – Final Version April 2017

Our SCOTUS Prediction Paper is now live in Plos One (one of my favorite journals) — very happy about this (thanks to Luís A. Nunes Amaral of Northwestern University for serving as our Editor).  #OpenSourceScience #SCOTUS #LegalAnalytics #LegalData #QuantitativeLegalPrediction

The Three Forms of (Legal) Prediction: Experts, Crowds + Algorithms (Updated Version of Presentation)

Law on the Market? Evaluating the Securities Market Impact Of Supreme Court Decisions (Katz, Bommarito, Soellinger & Chen)

Screen Shot 2015-08-24 at 5.01.07 PM
: Do judicial decisions affect the securities markets in discernible and perhaps predictable ways? In other words, is there “law on the market” (LOTM)? This is a question that has been raised by commentators, but answered by very few in a systematic and financially rigorous manner. Using intraday data and a multiday event window, this large scale event study seeks to determine the existence, frequency and magnitude of equity market impacts flowing from Supreme Court decisions.

We demonstrate that, while certainly not present in every case, “law on the market” events are fairly common. Across all cases decided by the Supreme Court of the United States between the 1999-2013 terms, we identify 79 cases where the share price of one or more publicly traded company moved in direct response to a Supreme Court decision. In the aggregate, over fifteen years, Supreme Court decisions were responsible for more than 140 billion dollars in absolute changes in wealth. Our analysis not only contributes to our understanding of the political economy of judicial decision making, but also links to the broader set of research exploring the performance in financial markets using event study methods.

We conclude by exploring the informational efficiency of law as a market by highlighting the speed at which information from Supreme Court decisions is assimilated by the market. Relatively speaking, LOTM events have historically exhibited slow rates of information incorporation for affected securities. This implies a market ripe for arbitrage where an event-based trading strategy could be successful.

Available on SSRN and arXiv

The Three Forms of (Legal) Prediction: Experts, Crowds and Algorithms (Presentation at the Chicago Legal Innovation and Technology MEETUP)

Why The Best Supreme Court Predictor In The World Is Some Random Guy In Queens (via

SCOTUS_538Nice coverage of the research in this area and our multi year research agenda attached to forecasting using the three known streams of intelligence (experts, crowds & algorithms).

Announcing the All New LexPredict FantasySCOTUS – (Sponsored By Thomson Reuters)

LexPredictToday I am excited to announce that LexPredict has now launched the all new FantasySCOTUS under the direction of Michael J. Bommarito II, Daniel Martin Katz and Josh Blackman.

FantasySCOTUS is the leading Supreme Court Fantasy League. Thousands of attorneys, law students, and other avid Supreme Court followers make predictions about cases before the Supreme Court. Participation is FREE and Supreme Court geeks can win cash prizes up to $10,000 (many other prizes as well — thanks to the generous support of Thomson Reuters).

We hope to launch additional functionality soon but we are now live and ready to accept your predictions for the 2014-2015 Supreme Court Term!

10 Predictions About How IBM’s Watson Will Impact the Legal Profession


I enjoyed collaborating with Paul Lippe for this short article in the ABA Journal New Normal column. We make 10 predictions about Watson’s application into the legal industry (some short term and some longer term) and preview some of our specific collaboration applying IBM Watson in the legal industry. Suffice to say there is much more to come …