This paper studies how comparing can be used to provide information in financial markets in the presence of a hidden characteristics problem. Although an investor cannot precisely estimate the future returns of an entrepreneur’s projects, the investor can mitigate the asymmetric information problem by ranking different entrepreneurs and financing only the very best ones. Information asymmetry c...

University rankings generally present users with the problem of placing the results given for an institution in context. Only a comparison with the performance of all other institutions makes it possible to say exactly where an institution stands. In order to interpret the results of the SCImago Institutions Ranking (based on Scopus data) and the Leiden Ranking (based on Web of Science data), i...

We propose a simple network–based methodology for ranking systemically important financial institutions. We view the risks of firms –including both the financial sector and the real economy– as a network with nodes representing the volatility shocks. The metric for the connections of the nodes is the correlation between these shocks. Daily dynamic centrality measures allow us to rank firms in t...

The exchangeability assumption as defined in this paper on ranking functions seems intuitively natural, and indeed, specific ranking functions previously proposed in the literature are all exchangeable. While pointwise ranking functions are vacuously exchangeable, we now discuss two specifically listwise ranking functions previously proposed by [22] and [26] in light of our representation theor...

This paper is a continuation of the study of surprise as a base for constructing qualitative calculi for representing and reasoning about uncertain knowledge. Here, we further elaborate on κ, a qualitative ranking function which we developed in (Ibrahim, Tawfik, and Ngom 2009b) and which constructs qualitative ranks for events by obtaining the order of magnitude abstraction of the degree of sur...

In this paper, we provide an overview of the NTCIR IMine task, which is a core task of NTCIR-11 and also a succeeding work of INTENT@NTCIR-9 and INTENT2@NTCIR-10 tasks. IMine is composed of a subtopic mining (SM) task, a document ranking (DR) task and a TaskMine (TM) pilot task. 21 groups from Canada, China, Germany, France, Japan, Korea, Spain, UK and United States registered to the task, whic...

This is an overview of the NTCIR-9 INTENT task, which comprises the Subtopic Mining and the Document Ranking subtasks. The INTENT task attracted participating teams from seven different countries/regions – 16 teams for Subtopic Mining and 8 teams for Document Ranking. The Subtopic Mining subtask received 42 Chinese runs and 14 Japanese runs; the Document Ranking subtask received 24 Chinese runs...