Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Competition analysis on the over-the-counter credit default swap market   We study two questions related to competition on the OTC CDS market using
data collected as part of the EMIR regulation.
  First, we study the competition between central counterparties through
collateral requirements. We present models that successfully estimate the
initial margin requirements. However, our estimations are not precise enough to
use them as input to a predictive model for CCP choice by counterparties in the
OTC market.
  Second, we model counterpart choice on the interdealer market using a novel
semi-supervised predictive task. We present our methodology as part of the
literature on model interpretability before arguing for the use of conditional
entropy as the metric of interest to derive knowledge from data through a
model-agnostic approach. In particular, we justify the use of deep neural
networks to measure conditional entropy on real-world datasets. We create the
$\textit{Razor entropy}$ using the framework of algorithmic information theory
and derive an explicit formula that is identical to our semi-supervised
training objective. Finally, we borrow concepts from game theory to define
$\textit{top-k Shapley values}$. This novel method of payoff distribution
satisfies most of the properties of Shapley values, and is of particular
interest when the value function is monotone submodular. Unlike classical
Shapley values, top-k Shapley values can be computed in quadratic time of the
number of features instead of exponential. We implement our methodology and
report the results on our particular task of counterpart choice.
  Finally, we present an improvement to the $\textit{node2vec}$ algorithm that
could for example be used to further study intermediation. We show that the
neighbor sampling used in the generation of biased walks can be performed in
logarithmic time with a quasilinear time pre-computation, unlike the current
implementations that do not scale well.

2
The categories of this paper are: math
6
The categories of this paper are: astro-ph
13
The categories of this paper are: quant-ph
31
The categories of this paper are: ao-sci
4
The categories of this paper are: cond-mat
15
The categories of this paper are: nucl-ex
22
The categories of this paper are: chao-dyn
21
The categories of this paper are: adap-org
27
The categories of this paper are: comp-gas
10
The categories of this paper are: q-bio
32
The categories of this paper are: atom-ph
14
The categories of this paper are: math-ph
28
The categories of this paper are: alg-geom
34
The categories of this paper are: chem-ph
29
The categories of this paper are: funct-an
20
The categories of this paper are: acc-phys