Research
On-device research index

arXiv research

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.

168,695 papers · 148 categories

Trend · papers per month

6481,2961,9442,592 · Jun 202019922001200920172026
48 results for war of attrition

New findings show pure strategy equilibria are more robust in a war of attrition game.

problem Analyzing a game of war of attrition under complete information.
method Examined the stability of equilibria in pure and mixed strategies under varying payoffs.
result Pure strategy equilibria are more robust to perturbations of the canonical model.

We consider a stochastic game of contribution to the common good in which the players have continuous control over the degree of contribution, and we examine the gradualism arising from the free rider effect. This game belongs to the class of variable concession games which generalize wars of attrition. Previously know…

2019-03-31abs ↗pdf ↗

Each year, roughly 30% of first-year students at US baccalaureate institutions do not return for their second year and over $9 billion is spent educating these students. Yet, little quantitative research has analyzed the causes and possible remedies for student attrition. Here, we describe initial efforts to model stud…

2016-06-20abs ↗pdf ↗

User intended actions are widely seen in many areas. Forecasting these actions and taking proactive measures to optimize business outcome is a crucial step towards sustaining the steady business growth. In this work, we focus on pre- dicting attrition, which is one of typical user intended actions. Conventional attriti…

2018-10-11abs ↗pdf ↗

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…

2014-05-25abs ↗pdf ↗

The paper uses machine learning to predict the impact of the Ukraine crisis on financial markets.

problem Quantifying the impact of the Ukraine crisis on financial markets.
method Selected economic indexes, created datasets, and used machine learning (Linear Regression) for forecasting.
result The model accurately predicted the effects of the Ukraine crisis on financial markets.

Study reveals clusters of resilient and vulnerable Spanish agri-food firms post-Ukraine-Russia war.

problem Financial resilience of agri-food companies in Spain during the Ukraine-Russia conflict.
method Cluster analysis using centred log-ratios for compositional data of financial ratios.
result Increase in resilient firms by 2023, highlighting sectoral adaptation to economic challenges.

Study analyzes stock order transitions during US-China trade war using Markov chains.

problem Understanding order dynamics during extreme macroeconomic events.
method First-order time-homogeneous discrete-time Markov chain model.
result Active participation by different traders during high volatility days, influencing market outcomes.

We perform detrending moving average analysis (DMA) and detrended fluctuation analysis (DFA) of the WTI crude oil futures prices (1983-2012) to investigate its efficiency. We further put forward a strict statistical test in the spirit of bootstrapping to verify the weak-form market efficiency hypothesis by employing th…

2012-11-20abs ↗pdf ↗

We present a new, efficient method for automatically detecting severe conflicts `edit wars' in Wikipedia and evaluate this method on six different language WPs. We discuss how the number of edits, reverts, the length of discussions, the burstiness of edits and reverts deviate in such pages from those following the gene…

2011-07-19abs ↗pdf ↗

This paper examines how the U.S.--China trade war affects stock markets, finding evidence of financial contagion and changes in risk channels.

problem The impact of the U.S.--China trade war on stock markets and financial contagion.
method Developed a novel jump-diffusion process to account for risk contagion, using high-frequency financial data and quasi-maximum likelihood estimator.
result Evidence of financial contagion from the U.S. to China, with changes in risk contagion channels.

Noisy labels often occur in vision datasets, especially when they are obtained from crowdsourcing or Web scraping. We propose a new regularization method, which enables learning robust classifiers in presence of noisy data. To achieve this goal, we propose a new adversarial regularization scheme based on the Wasserstei…

2019-04-08abs ↗pdf ↗

DefogGAN predicts hidden RTS game information to aid strategic decision-making.

problem Predicting hidden information in real-time strategy games like StarCraft.
method Conditional Generative Adversarial Network (GAN) with pyramidal reconstruction loss.
result DefogGAN predicts enemy buildings and combat units as accurately as professional players.

It is demonstrated that the US economy has on the long-term in reality been governed by the Keynesian approach to economics independent of the current official economical policy. This is done by calculating the two-point correlation function between the fluctuations of the DJIA and the US public debt. We find that the …

2011-07-15abs ↗pdf ↗

We develop an option pricing model based on a tug-of-war game. This two-player zero-sum stochastic differential game is formulated in the context of a multi-dimensional financial market. The issuer and the holder try to manipulate asset price processes in order to minimize and maximize the expected discounted reward. W…

2014-10-07abs ↗pdf ↗

Study shows negative war news correlates with increased stock market volatility.

problem Understanding the impact of geopolitical events on financial markets.
method Used BERT model for sentiment analysis and GARCH model for volatility forecasting.
result Negative news sentiment during geopolitical crises is associated with increased stock market volatility.

Are expansions and recessions more likely to end as their magnitude increases? In this paper we apply parametric hazard models to investigate this issue in a sample of 16 countries from 1881 to 2000. For the total sample we find evidence of positive magnitude dependence for recessions, while for expansions we are not a…

2004-01-26abs ↗pdf ↗

We aim to predict whether an employee of a company will leave or not, using the k-Nearest Neighbors algorithm. We use evaluation of employee performance, average monthly hours at work and number of years spent in the company, among others, as our features. Other approaches to this problem include the use of ANNs, decis…

2018-06-19abs ↗pdf ↗

Proposes a variational autoencoder for long-term customer revenue forecasting.

problem Predicting long-term customer revenue from sparse and irregular transaction data.
method Variational Autoencoder (VAE) with flexible latent representation.
result Improves upon latest benchmarks in multiple real-world datasets.

The paper develops methods to estimate treatment effects in sample selection models.

problem Evaluation of treatments when outcomes are only observed for a subpopulation due to sample selection or attrition.
method Combines selection-on-observables and instrumental variable assumptions with double machine learning for treatment evaluation.
result Proposed estimators are asymptotically normal and root-n consistent.

The paper uses conformal prediction for forecasting conflict sequences in Markov processes.

problem Forecasting future conflict states for national policy decisions.
method Conformal prediction on Markov processes for temporally-dependent data.
result Conformal prediction provides valid uncertainty quantification and robustness to model misspecification.

Geodesic flows on certain surfaces are shown to be semi-conjugate to expansive flows.

problem Understanding geodesic flows on compact surfaces without conjugate points.
method Time-preserving semi-conjugation to a continuous expansive flow.
result Geodesic flows on compact surfaces without conjugate points of genus > 1 have a unique measure of maximal entropy.

Method estimates treatment effect bounds in sample selection models.

problem Estimating heterogeneous treatment effects in presence of sample selection.
method Debiased/double machine learning approach for non-linear and high-dimensional confounders.
result Substantially tighter effect bounds for younger users.

Study geodesic flows on hyperbolic manifolds without conjugate points, proving unique measure of maximal entropy.

problem Proving uniqueness of measure of maximal entropy for geodesic flows on specific manifolds.
method Analyzing geodesic flows on closed Riemannian manifolds without conjugate points, using properties of Gromov hyperbolic and residually finite groups.
result Proves geodesic flow has a unique measure of maximal entropy under appropriate assumptions.

Study shows OAT decomposition generates unexplained profit and loss, while SU decompositions depend on risk factor order.

problem Understanding profit and loss attribution in financial markets.
method Used financial market data from 2003 to 2022 to compare OAT, SU, and ASU decompositions.
result SU decompositions are sensitive to risk factor order and cannot identify all relevant risk factors.

In this paper we study the financial repercussions of the destruction of two fully armed and operational moon-sized battle stations ("Death Stars") in a 4-year period and the dissolution of the galactic government in Star Wars. The emphasis of this work is to calibrate and simulate a model of the banking and financial …

2015-11-29abs ↗pdf ↗

This study proposes an equal-weight portfolio strategy to reduce risk compared to traditional ETFs.

problem Risk of passive ETFs not matching optimal portfolio weights.
method Introduced an equal-weight portfolio strategy to reduce idiosyncratic risk.
result Equal-weight portfolio has lower risk than traditional ETFs, especially during idiosyncratic events.

A method to prevent image representation collapse through data-dependent augmentation.

problem Representation collapse due to image augmentations that damage information.
method Formalizing a stochastic encoding process with a tug-of-war between corruption and preserved information, using infoMax objective.
result Learning a data-dependent distribution of augmentations to avoid representation collapse.

Socio-economic inequality is measured using various indices. The Gini (gg) index, giving the overall inequality is the most commonly used, while the recently introduced Kolkata (kk) index gives a measure of 1k1-k fraction of population who possess top kk fraction of wealth in the society. This article reviews the ch…

2016-11-02abs ↗pdf ↗

New bandit model accounts for user departures in recommender systems.

problem Capturing user departures in recommender systems with multi-armed bandits.
method Proposes a novel multi-armed bandit setup with two types of users and analyzes optimal and efficient algorithms.
result Achieves optimal and efficient learning algorithms for user types and reward probabilities.

This review is about the convenience, the benefits, as well as the destructive capacities of money. It deals with various aspects of money creation, with its value, and its appropriation. All sorts of money tend to get corrupted by eventually creating too much of them. In the long run, this renders money worthless and …

2008-11-19abs ↗pdf ↗