Proposes an adversarial process using cosine similarity to improve robustness of models.
problem Improving robustness of models by eliminating subsidiary information.
method Adversarial process using cosine similarity to degrade subsidiary model performance.
result Cosine similarity-based adversarial process efficiently degrades subsidiary model performance.
Study examines stock price correlations between Indonesian holding companies and their subsidiaries.
problem Understanding stock price relationships between holding companies and their subsidiaries.
method Spearman correlation analysis over 2013-2022, focusing on MNC Group and Emtek Group.
result Varying degrees of correlation between holding companies and their subsidiaries, with some showing inverse relationships.
Optimal dividend strategy for insurance group with contagious default risk.
problem Optimal dividend strategy for a multi-line insurance group with default contagion.
method Analysis of recursive system of Hamilton-Jacobi-Bellman variational inequalities (HJBVIs).
result Optimal dividend strategy is still of the barrier type, and optimal barrier is modulated by default state.
Study examines how bank holding structures affect financial stress spread.
problem Financial stress spread in a network of bank holdings and subsidiaries.
method Investigates the spread of contagion in a multilayered banking network with different holding support rules.
result Holding structures can either amplify or mitigate financial stress, depending on network capitalization.
Network analysis techniques remain rarely used for understanding international management strategies. Our paper highlights their value as research tool in this field of social science using a large set of micro-data (20,000) to investigate the presence of networks of subsidiaries overseas. The research question is the …
How are economic activities linked to geographic locations? To answer this question, we use a data-driven approach that builds on the information about location, ownership and economic activities of the world's 3,000 largest firms and their almost one million subsidiaries. From this information we generate a bipartite …
This paper approaches the definition and properties of dynamic convex risk measures through the notion of a family of concave valuation operators satisfying certain simple and credible axioms. Exploring these in the simplest context of a finite time set and finite sample space, we find natural risk-transfer and time-co…
Paper proposes a method to evaluate SME credit risk using meta paths.
problem Evaluate credit risk of small and medium-sized enterprises with limited data.
method Exploits the representative power of information networks and meta paths to infer SME financial status.
result Meta path feature effectively identifies SMEs with credit risks.
New Hausdorff integrations for Lie algebroids and symplectic groupoids.
problem Integrating Lie algebroids and symplectic groupoids.
method Hausdorff versions of Lie Integration Theorems 1 and 2, Lie equivalences, and algebraic approach to holonomy.
result Generalization of integration of subalgebroids to non-wide cases and detailed exploration of foliation groupoids.
A discrete time probabilistic model, for optimal equity allocation and portfolio selection, is formulated so as to apply to (at least) reinsurance. In the context of a company with several portfolios (or subsidiaries), representing both liabilities and assets, it is proved that the model has solutions respecting constr…
The paper proves existence and behavior of Lagrangian tori in complex projective plane.
problem Existence and behavior of Lagrangian tori in complex projective plane.
method Lagrangian mean curvature flow with surgery.
result Existence of monotone Lagrangian tori under Lagrangian mean curvature flow in complex projective plane.
This paper proves cohomology invariants for differentiable stacks.
problem Understanding cohomology of differentiable stacks.
method Simplicial approach to representations up to homotopy.
result Cohomology with coefficients in a representation up to homotopy is a Morita invariant of the underlying stack.
We study cascades on a two-layer multiplex network, with asymmetric feedback that depends on the coupling strength between the layers. Based on an analytical branching process approximation, we calculate the systemic risk measured by the final fraction of failed nodes on a reference layer. The results are compared with…
This paper contains the technical foundations from stochastic differential geometry for the construction of geometrically intrinsic nonlinear recursive filters. A diffusion X on a manifold N is run for a time interval T, with a random initial condition. There is a single observation consisting of a nonlinear function o…
This paper deals with multidimensional dynamic risk measures induced by conditional g-expectations. A notion of multidimensional g-expectation is proposed to provide a multidimensional version of nonlinear expectations. By a technical result on explicit expressions for the comparison theorem, uniqueness theorem and…
Multinational corporations use highly complex structures of parents and subsidiaries to organize their operations and ownership. Offshore Financial Centers (OFCs) facilitate these structures through low taxation and lenient regulation, but are increasingly under scrutiny, for instance for enabling tax avoidance. Theref…
Geometric correspondence between spinors and horospheres in hyperbolic space.
problem Understanding the relationship between spinors and horospheres in hyperbolic geometry.
method Detailed exposition and step-by-step construction of the spinor--horosphere correspondence.
result Spinor--horosphere correspondence is a smooth, SL(2,C)-equivariant bijection. In November, 2011, the Financial Stability Board, in collaboration with the International Monetary Fund, published a list of 29 "systemically important financial institutions" (SIFIs). This designation reflects a concern that the failure of any one of them could have dramatic negative consequences for the global econom…
In this thesis, we consider the knot energy "integral Menger curvature" which is the triple integral over the inverse of the classic circumradius of three distinct points on the given knot to the power p∈[2,∞). We prove the existence of the first variation for a subset of a certain fractional Sobolev space if…
Model quantifies cyber-attacks' impact on firms and insurers.
problem Impact of cyber-attacks on firms' revenues and insurers' portfolios.
method Stochastic SIR model coupled with granular firm growth model.
result Predicts insurer needs to compensate up to two days of revenue in a 100-day incident.
We simplify information measure computation using learned features.
problem Computing information measures from raw data is computationally expensive.
method Developed a separable design for computing information measures from learned feature representations.
result A variety of information measures can be computed efficiently through learned feature representations.
A new framework for information theory considers computational constraints.
problem Understanding information in complex systems with computational limitations.
method Variational extension of Shannon's information theory with computational constraints.
result Predictive V-information can be created through computation and reliably estimated from data. An asymmetric information model is introduced for the situation in which there is a small agent who is more susceptible to the flow of information in the market than the general market participant, and who tries to implement strategies based on the additional information. In this model market participants have access t…
We study a simple model of an asset market with informed and non-informed agents. In the absence of non-informed agents, the market becomes information efficient when the number of traders with different private information is large enough. Upon introducing non-informed agents, we find that the latter contribute signif…
New method quantifies redundant information using information bottleneck.
problem Quantifying redundant information among multiple sources.
method Formulated as an information bottleneck problem, termed redundancy bottleneck.
result Extracts information that best predicts the target without revealing source identity.
This paper reviews information theory in open-world machine learning.
problem Lack of a unified theoretical foundation for open-world machine learning.
method Synthesis of information theoretic approaches.
result Established a pathway toward provable and trustworthy open world intelligence.
Generalizes information theory to evolving belief.
problem Measuring change in belief over time.
method Derives a general theory of information from first principles.
result Recover all information measures and interprets entropy as expected gain.
Paper proposes a framework to identify and obfuscate sensitive features via information density estimation.
problem Identifying and protecting sensitive attributes from leakage in obfuscation mechanisms.
method Information density estimation to identify leaking features, followed by a targeted obfuscation mechanism.
result Proven leakage guarantee in terms of Eγ-divergence for the obfuscation mechanism. Review of information plane analyses in neural networks, highlighting mixed results and methodological challenges.
problem Understanding the relationship between information-theoretic compression and neural network performance.
method Literature review and detailed analysis of information quantity estimation methods.
result Information plane compression is not necessarily information-theoretic but compatible with geometric compression.
Information geometry offers new tools for statistical analysis.
problem Statistical analysis of probability distributions.
method Geometric perspective on statistical manifolds.
result New applications in radar sensing, signal processing, etc.
In this paper, we present a new approach to interpret deep learning models. By coupling mutual information with network science, we explore how information flows through feedforward networks. We show that efficiently approximating mutual information allows us to create an information measure that quantifies how much in…
Before the massive spread of computer technology, information was far from complex. The development of technology shifted the paradigm: from individuals who faced scarce and costly information to individuals who face massive amounts of information accessible at low costs. Nowadays we are living in the era of big data a…
In financial markets valuable information is rarely circulated homogeneously, because of time required for information to spread. However, advances in communication technology means that the 'lifetime' of important information is typically short. Hence, viewed as a tradable asset, information shares the characteristics…
Introduces relative information gain for improving Gaussian process regression rates.
problem Improving the sample complexity of estimating or maximizing unknown functions.
method Introduces relative information gain, interpolates between effective dimension and information gain, and proves PAC-Bayesian bounds.
result Obtains minimax-optimal rates of convergence through the relative information gain.
This paper uses information theory to improve risk modeling in big data.
problem Insufficient application of information theory in actuarial science.
method Explores information theory to uncover performance limits of insurance big data systems.
result Guidance for risk modeling and actuarial pricing systems.
In information theory, Fisher information and Shannon information (entropy) are respectively used to quantify the uncertainty associated with the distribution modeling and the uncertainty in specifying the outcome of given variables. These two quantities are complementary and are jointly applied to information behavior…
Investors pay for additional asset information based on utility maximization.
problem Determining the optimal price for additional asset information.
method Solving a stochastic control problem with partial information and utility maximization.
result Investors choose to purchase information at a deterministic time.
New method detects information leakage using approximate Bayes predictor.
problem Unintentional exposure of sensitive information via observable data.
method Statistical learning theory and information theory framework, approximating Bayes predictor's log-loss and accuracy.
result MI can be accurately estimated to detect ILs, outperforming state-of-the-art baselines.
Market strategies minimize Fisher information to minimize risk.
problem Applying minimum Fisher information principle to market dynamics.
method Analytical extension to quantum harmonic oscillator eigenstates and Gibbs distribution.
result Minimizing Fisher information reduces information and risk.
New approach quantifies overfitting in high-dimensional regression.
problem Quantifying and avoiding overfitting in large neural networks.
method Information bottleneck theory to minimize residual information while maximizing relevant bits.
result Characterized the relative information efficiency of randomized regression compared to optimal algorithms.
Proposes a new framework for decomposing information in multivariate settings.
problem Decomposing information from multiple sources about a target variable.
method Formal analogy with set theory and Blackwell order to define PID.
result Framework can be generalized to various information theories.
Unified notation simplifies information-theoretic concepts in machine learning.
problem Opaque notation for information-theoretic quantities in machine learning.
method Proposed a practical and unified notation for information-theoretic quantities.
result Unified notation facilitates new intuitions and rederivations in machine learning.
Paper explores how to use mixed types of side information for better recommendations.
problem Challenges in using heterogeneous side information for recommender systems.
method Proposes a framework to jointly capture flat and hierarchical side information.
result Demonstrates significant performance gains over state-of-the-art methods.
Study optimal portfolios for traders with asymmetric information and delay.
problem Optimizing portfolios for traders with delayed insider information.
method Anticipating stochastic calculus and white noise approach.
result Optimal portfolios maximize expected logarithmic utility under various financial models.
Strategic brokers exploit private information in broker-mediated markets, affecting informed traders' performance.
problem Strategic interactions and information leakage in broker-mediated markets.
method Study of strategic trading behavior and information leakage in a broker-mediated market.
result Brokers hold a strategic advantage over informed traders due to information leakage in trading flows.
Proposes a new method to enhance neural learning by maximizing information gain.
problem Improving neural learning by selecting key variables to maximize information gain.
method Adaptive Ensemble Kalman Filter to quantify uncertainty and maximize information gain.
result The proposed method enables the neural network to learn more effectively from stochastic systems.
Mirror descent linked to information ratio via Bayesian regret bounds.
problem Understanding stability in mirror descent and its relation to information ratio.
method Developed a connection between mirror descent and information ratio using Bayesian regret bounds.
result Mirror descent with suitable estimators and distributions achieves bounds similar to information-directed sampling.
Study shows changes in information sharing between Bitcoin markets during 2017 crash.
problem Understanding information dynamics in Bitcoin markets during the 2017 crash.
method Analysis of high-frequency market-microstructure observables using information theoretic measures.
result Temporal changes in information sharing across markets, including predictability, memory, and synchronous coupling.