New techniques allow causal inferences from text data.
problem Making causal inferences from text data.
method Conceptual framework, latent representation learning, split-sample framework.
result Rigorous foundation for text-based causal inferences.
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.
169,341 papers · 148 categories
Trend · papers per month
48 results for “immigration attitudes”
RW populism rises in EU countries with high immigrant populations.
problem Anti-globalist sentiment increases with immigrant influx.
method Analyzed polls data from EU countries affected by recent migrant crisis.
result RW populism's rise exceeds immigration inflow.
IMMIGRATE selects features with interaction terms using margin-based weights.
problem Unclear differentiation of feature interactions from marginal effects.
method Includes and trains weights for interaction terms, applies large margin principle, considers robustness and local/global information.
result Achieves state-of-the-art results on several tasks.
This paper focuses on a class of linear Hawkes processes with general immigrants. These are counting processes with shot noise intensity, including self-excited and externally excited patterns. For such processes, we introduce the concept of age pyramid which evolves according to immigration and births. The virtue if t…
New concept of attitude towards probability introduced in risk sharing problems.
problem Risk sharing problems and attitudes towards probability.
method Generalized definition of probability premium, local approximation, rank-dependent utility model, dual theory.
result Attitude towards probability can be first-order or second-order, depending on the model.
Automates U.S. visa petition document classification and RFE response generation.
problem Manual effort in organizing visa petition documents and responding to RFEs.
method Ensemble of image and text classifiers for document categorization and text classifier for RFE evidence identification.
result Achieves considerable accuracy in automated responses while reducing processing time.
SlideVaR balances risk and prudence by considering variable investor attitudes.
problem Finding a risk measure that reflects variable investor attitudes and market changes.
method Introducing SlideVaR, a new risk measure that considers risk-tail regions and sub-additivity.
result SlideVaR outperforms traditional measures in markets with frequent state changes.
Study introduces a new method to estimate causal mediation with multiple mediators.
problem Estimating causal effects with multiple mediators and confounders.
method Simulates potential outcomes using parametric and nonparametric models.
result General approach to estimating various causal mediation quantities.
Study examines how different types of advertising impact brand attitudes.
problem Understanding how advertising types affect brand perceptions.
method Analysis of 575 brands over five years, using national, local, and digital ads, with brand/quarter and industry/week fixed effects.
result Different types of advertising have varying impacts on brand perceptions.
We compute exact values respectively bounds of "distances" - in the sense of (transforms of) power divergences and relative entropy - between two discrete-time Galton-Watson branching processes with immigration GWI for which the offspring as well as the immigration is arbitrarily Poisson-distributed (leading to arbitra…
Method selects valid IVs from a large set using clustering and test of overidentifying restrictions.
problem Selecting valid instrumental variables from a large set of candidates.
method Agglomerative hierarchical clustering combined with a test of overidentifying restrictions.
result Achieves oracle properties when the largest group of IVs is valid.
Extends decision theory to handle unlikely events and varying risk attitudes.
problem Handling preferences for unlikely events and varying risk attitudes.
method Derives a subjective lexicographic expected utility representation.
result Provides foundations for models in finance and infinite dynamic games.
ANFIS system improves satellite attitude estimation and control.
problem Improving accuracy of satellite attitude estimation and control.
method Adaptive neuro-fuzzy integrated (ANFIS) model for satellite attitude estimation and control.
result ANFIS controller outperforms optimal PID controller in time and smoothness.
Examines optimal risk sharing with realistic risk attitudes, finding risk seeking in certain subdomains.
problem Optimal risk sharing with empirically realistic risk attitudes.
method Allows for risk-seeking agents, generalizes expected utility, and uses counter-monotonic improvement theorem.
result First empirical results on optimal risk sharing with realistic risk attitudes.
Neural model incorporates metadata for better text analysis.
problem Lack of metadata in standard text modeling.
method General neural framework based on topic models.
result Achieves strong performance with metadata.
Study optimal stopping for group with diverse discount rates using an attitude function.
problem Optimal stopping for a group with diverse discount rates under an aggregation preference.
method Develop iterative approach using consistent planning for time-consistent equilibria.
result Characterize all time-consistent mild equilibria as fixed points of an operator.
Optimal risk sharing found for heterogeneous risk attitudes using distortion risk measures.
problem Risk sharing in economies with diverse risk attitudes.
method Modeling preferences with distortion risk measures, using comonotonic and counter-monotonic principles.
result Optimal risk sharing strategies identified based on risk attitudes, reducing the -agent problem to a two-agent formulation.
Neural networks outperform conventional filters in inertial sensor-based attitude estimation.
problem Limited accuracy in inertial sensor-based attitude estimation due to dynamic and static motion.
method Investigated neural networks versus conventional filters for improving accuracy.
result Neural networks outperform conventional filters only with domain-specific optimizations.
A sliding surface stabilizes rigid body attitude control.
problem Stabilizing rigid body attitude control robustly.
method Proposed sliding surface as Lie subgroup, designed sliding-mode controller.
result Closed-loop system is robust against disturbances and unwinding.
Paper proposes a deep learning method for better IMU gyroscope data.
problem Improving accuracy of IMU gyroscope data for robot orientation estimation.
method Dilated convolution neural network, proper loss function, key points identification.
result Algorithm outperforms state-of-the-art on unseen test sequences.
Understanding Gambling Behavior and Risk Attitudes Using Cryptocurrency-based Casino Blockchain Dataphysics.soc-ph
Study analyzes gambling behavior and risk attitudes using blockchain data.
problem Lack of real-life gambling data for validating predictions and experimental findings.
method Collects and analyzes betting data from a decentralized application on the Ethereum Blockchain.
result Empirical examples of gambling systems and insights into risk preferences.
Investigates how diversification preferences relate to risk attitudes.
problem Connecting diversification preferences to risk attitudes.
method Analyzes diversification preferences for various pairs of risks under different conditions.
result Diversification preferences for certain pairs of risks imply specific levels of risk aversion.
Paper introduces EnDKF for more accurate pose tracking.
problem Accurate pose tracking with directional uncertainty.
method EnDKF integrates unit-quaternion attitude representation for better directional uncertainty capture.
result Significant reduction in error compared to traditional methods.
First we provide a simple set of sufficient conditions for the weak convergence of scaled affine processes with state space . We specialize our result to one-dimensional continuous state branching processes with immigration. As an application, we study the asymptotic behavior of least squares estimators…
Higher-Order Ambiguity Attitudesq-fin.RM
Model-free preference under ambiguity defined and applied.
problem Understanding and quantifying ambiguity aversion and prudence.
method Introduces a new model-free definition of ambiguity attitudes and applies it in various contexts.
result New definition of ambiguity prudence equivalent to specific mathematical functions.
New framework learns complex AI attitudes from heterogeneous data.
problem Heterogeneous ordinal structure in AI attitudes, poorly captured by existing methods.
method Monotone Gaussian score embedding, BNP complexity discovery, confirmatory fixed-K estimation.
result Reduced holdout MSE by 25.8% over single-graph baseline.
Empirical evidence supports new financial market definitions.
problem Investor risk attitudes in financial markets.
method Developed a new method to analyze risk attitudes.
result Risk-averse behavior in equity investors, risk-loving behavior in risk-free asset investors.
New approach for optimal stopping under model ambiguity, considering agent's attitude towards ambiguity.
problem Optimal stopping under model ambiguity and varying levels of ambiguity aversion.
method Introduces a time-inconsistent stopping problem with an -maxmin nonlinear expectation and seeks subgame perfect equilibrium policies through fixed-point iterations.
result Equilibrium stopping policies can be obtained through fixed-point iteration and vary based on an agent's ambiguity attitude.
Study examines perceptions and attitudes about breast cancer on Twitter.
problem Understanding public perceptions and attitudes towards breast cancer on social media.
method Identified and collected tweets, used topic modeling and sentiment analysis.
result Identified themes and quantified users' perceptions and emotions about breast cancer.
Experiment shows cognitive biases impact human-AI collaboration, highlighting the need for diverse evaluator samples.
problem Cognitive biases affect human-AI collaboration, leading to suboptimal outcomes.
method Randomized experiment with 2,784 participants, manipulating AI suggestion quality, task burden, and financial incentives.
result Individual attitudes toward AI are the strongest predictor of performance, influencing accuracy and overcorrection.
When investors have heterogeneous attitudes towards risk, it is reasonable to assume that each investor has a pricing kernel, and that these individual pricing kernels are aggregated to form a market pricing kernel. The various investors are then buyers or sellers depending on how their individual pricing kernels compa…
LLMs can simulate human investment attitudes based on personality traits.
problem Investigating how LLMs mimic human investment behaviors.
method Simulated investment task using LLM personas with specific Big Five personality profiles.
result LLMs can produce meaningful behavioural differences in investment tasks that align with human traits.
An interacting-agent model of financial markets from the viewpoint of nonextensive statistical mechanicsphysics.soc-ph
In this paper we present an interacting-agent model of stock markets. We describe a stock market through an Ising-like model in order to formulate the tendency of traders getting to be influenced by the other traders' investment attitudes [1], and formulate the traders' decision-making regarding investment as the maxim…
The Hawkes process is a simple point process, whose intensity function depends on the entire past history and is self-exciting and has the clustering property. The Hawkes process is in general non-Markovian. The linear Hawkes process has immigration-birth representation. Based on that, Fierro et al. recently introduced…
New method identifies causal structure in count data using cumulants and path analysis.
problem Challenges in discovering causal structure from count data, especially due to non-identifiability.
method Poisson Branching Structural Causal Model (PB-SCM) with path analysis using high-order cumulants.
result Causal order is identifiable under specific conditions in PB-SCM using cumulant information.
The Frenet frame generalizes the Park transform for multi-phase circuits.
problem Generalizing the Park transform for multi-phase circuits.
method Using the Frenet frame and Cartan's moving frames.
result The Frenet frame provides a new approach to circuit analysis.
Proposes a new machine learning-based method for conjoint analysis.
problem Testing the importance of factors in conjoint analysis with interactions.
method Conditional randomization test based on machine learning algorithms.
result Validates the importance of factors in conjoint analysis without model specification.
Paper uses cross-sectional data to estimate VSL, reducing confidence intervals by a factor of 3.
problem Estimating VSL with cross-sectional data using Garen's IV approach.
method Garen's instrumental variable (IV) approach, proxy for risk attitude.
result Confidence intervals reduced by a factor of 3 using proxy.
This paper solves a financial portfolio selection problem in incomplete markets.
problem Portfolio selection in incomplete financial markets with ambiguity.
method Constructing an efficient frontier, simplifying the problem, introducing a new distorted Legendre transformation, and proving the bipolar relation and distorted duality theorem.
result The existence and uniqueness of optimal strategies are shown for different utility functions under specific conditions.
Researchers quantify risk exposure and sensitivities in financial markets under model uncertainty.
problem Optimizing investment and pricing under model uncertainty in financial markets.
method Distributionally robust optimization, Wasserstein ball, first-order sensitivity analysis.
result Sensitivities of value function, investment policy, and marginal prices to model uncertainty can be non-monotonic.
Priority to unemployed immigrants? A causal machine learning evaluation of training in Belgiumecon.EM
Study evaluates training programs for unemployed in Belgium using machine learning.
problem Determining which training programs are most effective for unemployed individuals in Belgium.
method Used Modified Causal Forests, a causal machine learning estimator, to analyze data from unemployed in Belgium.
result There is significant heterogeneity in the effectiveness of different training programs for unemployed individuals in Belgium.
This paper solves robust utility maximization with unknown claim dependencies.
problem Investor optimizes utility in the presence of an intractable contingent claim.
method Quantile optimization approach, transforming dynamic problem into static concave optimization.
result Optimal payoffs depend on ambiguity attitude, market conditions, and claim characteristics.
Two new models for forward power prices capture clustering jumps.
problem Describing forward power prices with clustering jumps.
method Continuous branching processes with immigration and Hawkes processes with exponential kernel.
result Models adequately describe forward prices evolution in French power market.
This study proves new financial market theorems breaking standard risk definitions.
problem Breaking standard risk definitions in financial markets.
method Presenting proofs for new financial market theorems.
result New definitions are richer and broader than standard ones considering shape.
Probability distribution of drawdowns in risky investmentscond-mat.stat-mech
We study the risk criterion for investments based on the drawdown from the maximal value of the capital in the past. Depending on investor's risk attitude, thus his risk exposure, we find that the distribution of these drawdowns follows a general power law. In particular, if the risk exposure is Kelly-optimal, the expo…
Dual Moments and Risk Attitudesq-fin.RM
Dual moments replace primal moments for measuring risk aversion.
problem Traditional risk aversion measures using mean and variance are insufficient in non-EU models.
method Introduced dual moments as a new measure for absolute risk aversion.
result Dual moments provide an equivalent index of absolute risk aversion in non-EU models.
Develops a new model for multiple yield curves using branching processes.
problem Reproduce empirical features of spreads between interbank rates.
method Continuous-state branching processes with immigration (CBI processes).
result Models can generate contagion effects among different spreads.
Study examines BRICS markets' vulnerability to Trump's policies.
problem Vulnerability of BRICS stock markets to Trump's election impact.
method Event-study methodology and social media, search queries, and public opinion polls integration.
result China and Brazil were hit hard, while India and South Africa suffered less.