A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.
New findings show that some knotted surfaces remain distinct even after many stabilizations.
Oil prices affect Russian banks' stability, with negative impacts from decreases.
PenduMAV is a 6-input omnidirectional MAV without internal forces.
New stabilization methods for exotic surfaces in 4-manifolds.
New findings show stabilization isn't enough for certain knotted surfaces.
We investigate the role of networks of alliances in preventing (multilateral) interstate wars. We first show that, in the absence of international trade, no network of alliances is peaceful and stable. We then show that international trade induces peaceful and stable networks: trade increases the density of alliances s…
Unfulfilled expectations from macro-economic initiatives during the Great Recession and the massive shift into globalization echo today with political upheaval, anti-establishment propaganda, and looming trade/currency wars that threaten domestic and international value chains. Once stable entities like the EU now look…
MuZero visualizes its internal representations to stabilize planning.
We analyse the importance of international relations between countries on the financial stability. The contagion effect in the network is tested by implementing an epidemiological model, comprising a number of European countries and using bilateral data on foreign claims between them. Banking statistics of consolidated…
reval package selects best clustering solutions via stability-based validation.
Single stabilization is not always enough to make exotic surfaces isotopic.
New study on replicability and stability in machine learning algorithms.
The paper presents a new method to create exotic 4-manifolds and surfaces that remain exotic after stabilization.
New insights on stability in reservoir computing for better performance.
New module constructs exotic surfaces in 4-manifolds.
Recurring international financial crises have adverse socioeconomic effects and demand novel regulatory instruments or strategies for risk management and market stabilization. However, the complex web of market interactions often impedes rational decisions that would absolutely minimize the risk. Here we show that, for…
Proposes a framework to predict stock movements by integrating multi-order and internal dynamics.
Geometric stability predicts steerability and detects drift in language models.
Emerging economies use countercyclical policies to manage crises and dominant currencies.
New criterion selects optimal number of clusters based on stability.
The search for universal laws that help establish a relationship between dynamics and computation is driven by recent expansionist initiatives in biologically inspired computing. A general setting to understand both such dynamics and computation is a driven dynamical system that responds to a temporal input. Surprising…
Geometric stability measures neural network robustness, distinguishing from similarity metrics.
The aim of this paper is to identify the determinants of international stock markets integration. Intuitively we selected a great number of factors linked to financial integration. Then, we developed an international asset-pricing model with time-varying degree of integration. This model is estimated for 30 countries (…
Recurrent neural networks trained on regular languages exhibit stable states that can recover from noise.
Bayesian explanations are more resilient to adversarial attacks than deterministic ones.
Financial system being the place of metting capital flows (equality between saving and investment), a volatility of capital flows can destroy the robustness and good working of financial system, it means subvert financial stability. The same a weak financial system, few regulated and bad manage can exacerbate volatilit…
The study improves stock market valuation using volatility and earnings data.
Internal Lagrangians derived from variational principles.
This paper introduces hierarchical quasi-clustering methods, a generalization of hierarchical clustering for asymmetric networks where the output structure preserves the asymmetry of the input data. We show that this output structure is equivalent to a finite quasi-ultrametric space and study admissibility with respect…
This paper develops a dynamic internal fraud model for operational losses in retail banking. It considers public operational losses arising from internal fraud in retail banking within a group of international banks. Additionally, the model takes into account internal factors such as the ethical quality of workers and …
The structure of the control network of transnational corporations affects global market competition and financial stability. So far, only small national samples were studied and there was no appropriate methodology to assess control globally. We present the first investigation of the architecture of the international …
The paper explores slice disks and their properties using satellite operations and knot Floer homology.
Examines international taxation's impact on Georgian businesses.
We propose a novel {\it Equilibrated Recurrent Neural Network} (ERNN) to combat the issues of inaccuracy and instability in conventional RNNs. Drawing upon the concept of autapse in neuroscience, we propose augmenting an RNN with a time-delayed self-feedback loop. Our sole purpose is to modify the dynamics of each inte…
Optimized execution model using interbank and internal liquidity.
Paper improves generalization bounds for structured output prediction problems.
We study warped compactifications of string/M theory with the help of effective potentials, continuing previous work of the last two authors and Michael R. Douglas presented in arXiv:1206.1885. The dynamics of the conformal factor of the internal metric, which is responsible for instabilities in these constructions, is…
This study assesses how economic shocks affect the efficiency and robustness of international pesticide trade networks.
Batch Normalization (BatchNorm) is a widely adopted technique that enables faster and more stable training of deep neural networks (DNNs). Despite its pervasiveness, the exact reasons for BatchNorm's effectiveness are still poorly understood. The popular belief is that this effectiveness stems from controlling the chan…
We educe a perspective on how best to regulate the bank of tomorrow in frames of debate launched by the International Centre for Financial Regulation and Financial Times. Our goal is to create a conceptual framework for policymakers and regulators to shape the international financial system in century of globalization …
Generative Adversarial Networks (GANs) have achieved impressive results for many real-world applications. As an active research topic, many GAN variants have emerged with improvements in sample quality and training stability. However, visualization and understanding of GANs is largely missing. How does a GAN represent …
On June 26th, 2004, Central bank governors and the heads of bank supervisory authorities in the Group of Ten (G10) countries issued a press release and endorsed the publication of "International Convergence of Capital Measurement and Capital Standards: a Revised Framework", the new capital adequacy framework commonly k…
We consider a structural default model in an interconnected banking network as in Lipton [International Journal of Theoretical and Applied Finance, 19(6), 2016], with mutual obligations between each pair of banks. We analyse the model numerically for two banks with jumps in their asset value processes. Specifically, we…
There are few papers about the international trade of flowers, so it is believed that this paper, with this topic, could be an important contribution to the international scientific community. It is intended to analyze if the international trade flowers tendencies and policies are adapted to the actual world global con…
Spain uses DEA to select international markets for exports.
Improved speech recognition model with better performance.
Introduces internal Lagrangians for differential equations and connects them to presymplectic structures.
Develops a tool to identify abnormal blood smear results based on CBC tests.