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.
A thermodynamic theory explains EU election vote distributions.
There is bountiful evidence that political uncertainty stemming from presidential elections or doubt about the direction of future policy make financial markets significantly volatile, especially in proximity to close elections or elections that may prompt radical policy changes. Although several studies have examined …
Opinion polls have been the bridge between public opinion and politicians in elections. However, developing surveys to disclose people's feedback with respect to economic issues is limited, expensive, and time-consuming. In recent years, social media such as Twitter has enabled people to share their opinions regarding …
Study analyzes EU in variational inference for Bayesian deep learning.
Complex dynamical systems driven by the unravelling of information can be modelled effectively by treating the underlying flow of information as the model input. Complicated dynamical behaviour of the system is then derived as an output. Such an information-based approach is in sharp contrast to the conventional mathem…
Human stablecoin transactions predict political risk in cryptocurrency markets.
Improves stock market predictions on Election Day.
This paper examines how voter concentration affects election outcomes in district-based systems.
Taleb (2018) claimed a novel approach to evaluating the quality of probabilistic election forecasts via no-arbitrage pricing techniques and argued that popular forecasts of the 2016 U.S. Presidential election had violated arbitrage boundaries. We show that under mild assumptions all such political forecasts are arbitra…
Proposes using DII to identify non-linear causal relationships in EU Allowances returns.
Fuzzy Forests reduces feature space in high-dimensional survey data.
Calculates winning probability for three candidates based on support rates and information timing.
The prevalence of online media has attracted researchers from various domains to explore human behavior and make interesting predictions. In this research, we leverage heterogeneous social media data collected from various online platforms to predict Taiwan's 2016 presidential election. In contrast to most existing res…
The aim of the present article is to offer a strictly mathematical, statistical treatment of the current account balances in EU and in the Eurozone. Based on Eurostat data, an overview of the total and annual balances is first made for different collections among the EU countries. Then, using the Mathematica technical …
The 2016 United States presidential election has been characterized as a period of extreme divisiveness that was exacerbated on social media by the influence of fake news, trolls, and social bots. However, the extent to which the public became more polarized in response to these influences over the course of the electi…
Remote sensing satellites capture the cyclic dynamics of our Planet in regular time intervals recorded in satellite time series data. End-to-end trained deep learning models use this time series data to make predictions at a large scale, for instance, to produce up-to-date crop cover maps. Most time series classificati…
Study identifies clusters of EU countries with similar young mortality patterns.
Proposes a transfer learning framework to improve U.S. election prediction models.
This study analyzes EU ETS literature trends using bibliometric methods.
In accordance with "Democracy's Effect on Development: More Questions than Answers", we seek to carry out a study in following the description in the 'Questions for Further Study.' To that end, we studied 33 countries in the Sub-Saharan Africa region, who all went through an election which should signal a "step-up" for…
China and EU race to develop hydrogen for energy transition.
Study analyzes EU ETS carbon market dynamics, revealing inefficiencies and anomalies.
CreDRO learns credal ensembles via distributionally robust optimization, improving EU quantification.
Most of the analytical techniques used in the business cycle synchronisation literature rely upon the estimation of an empirical correlation matrix of time series data of macroeconomic aggregates, real GDP usually being the key variable. But the small number of available observations and small number of economies mean …
In this paper, we explore the detection of clusters of stocks that are in synergy in the Indian Stock Market and understand their behaviour in different circumstances. We have based our study on high frequency data for the year 2014. This was a year when general elections were held in India, keeping this in mind our da…
Study uses Viber and street polls to estimate Belarus election ratings and turnout.
The paper develops a test for EU portfolio efficiency in high dimensions.
The recently announced Energy Union by the European Commission is the most recent step in a series of developments aiming at integrating the EU's gas markets to increase social welfare (SW) and security of gas supply. Based on a spatial partial equilibrium model, we analyze the changes in consumption, prices, and SW up…
Study uses non-parametric method to analyze EU ETS price determinants.
The paper uses Black-Scholes model to analyze political support and coalition agreements.
Examines financial risks' impact on EU-15 economic growth.
We consider the estimation of binary election outcomes as martingales and propose an arbitrage pricing when one continuously updates estimates. We argue that the estimator needs to be priced as a binary option as the arbitrage valuation minimizes the conventionally used Brier score for tracking the accuracy of probabil…
This paper presents a data set describing the evolution of results in the Portuguese Parliamentary Elections of October 6 2019. The data spans a time interval of 4 hours and 25 minutes, in intervals of 5 minutes, concerning the results of the 27 parties involved in the electoral event. The data set is tailored f…
Unified framework for causal inference with reliable uncertainty quantification.
First European crop map created using satellite data.
The goal of this research was to find a way to extend the capabilities of computers through the processing of language in a more human way, and present applications which demonstrate the power of this method. This research presents a novel approach, Rhetorical Analysis, to solving problems in Natural Language Processin…
DDSTN improves breast cancer diagnosis by leveraging imbalanced ultrasound modalities.
Active learning suffers from biased non-response, which this paper addresses.
Study assesses sugar beet yields under EU's neonicotinoids ban and climate change.
Model predicts EU carbon prices using market and political factors.
Study examines how EU's Value at Risk constraints affect insurance oligopolies.
Among the central tenets of globalization is free migration of labor. Although much has been written about its benefits, little is known about the limitations of globalization, including how immigration affects the anti-globalist sentiment. Analyzing polls data, we find that over the last three years in a group of EU c…
Donald Trump was lagging behind in nearly all opinion polls leading up to the 2016 US presidential election, but he surprisingly won the election. This raises the following important questions: 1) why most opinion polls were not accurate in 2016? and 2) how to improve the accuracies of opinion polls? In this paper, we …
The paper examines how CoCo bonds can enhance financial stability in interconnected banking systems.
We combine fine-grained spatially referenced census data with the vote outcomes from the 2016 US presidential election. Using this dataset, we perform ecological inference using distribution regression (Flaxman et al, KDD 2015) with a multinomial-logit regression so as to model the vote outcome Trump, Clinton, Other / …
Study reveals inefficiencies in EU carbon trading market.
We report on time-varying network connectedness within three banking systems: North America, the EU, and ASEAN. The original method by Diebold and Yilmaz is improved by using exponentially weighted daily returns and ridge regularization on vector autoregression (VAR) and forecast error variance decomposition (FEVD). We…
Using the United Nations COMTRADE database we apply the reduced Google matrix (REGOMAX) algorithm to analyze the multiproduct world trade in years 2004-2016. Our approach allows to determine the trade balance sensitivity of a group of countries to a specific product price increase from a specific exporting country taki…