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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.

169,181 papers · 148 categories

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48 results for heterogeneous price sensitivity

Estimates price sensitivity from transaction data using a novel odds ratio method.

problem Estimate price sensitivity from transaction-level data with partially observed treatment assignments.
method Recursive partitioning procedure with adversarial imputation for robust estimation.
result Validated on synthetic data and applied to three case studies, demonstrating heterogeneity in treatment effects.

A new pricing strategy maximizes revenue in high-dimensional product spaces with varying customer preferences.

problem Maximizing revenue in a high-dimensional product space with heterogeneous price sensitivity.
method Proposes M3P, a pricing policy that achieves a specific regret bound under heterogeneous price sensitivity.
result Achieves a TT-period regret of O(log(Td)(T+dlog(T)))O(\log(Td) (\sqrt{T} + d\log(T))).

The paper improves consumer preference modeling by considering multiple product categories.

problem Estimating consumer preferences across multiple product categories with varying attributes and price sensitivity.
method Extends matrix factorization techniques to account for time-varying product attributes and out-of-stock products, pooling information across categories to estimate heterogeneity in preferences.
result The model improves over traditional approaches, accurately estimating consumer preferences and price sensitivity.

Study improves stock price prediction using adaptive Mixture of Experts framework.

problem Tackles diverse volatility regimes in stock price prediction.
method Combines RNN for high-volatility stocks and linear regression for stable stocks with a gating mechanism.
result Achieves up to 33% improvement in MSE for volatile assets and 28% for stable assets.

Study shows price bubbles can exist even with heterogeneous beliefs.

problem Equilibrium price formation in markets with different belief groups.
method Analyzes continuous time asset trading with heterogeneous investors and mean reverting asset.
result Price bubbles may not form even with heterogeneous beliefs, contrary to initial expectations.

Game-theoretic model captures investor interactions for stock price forecasting.

problem Complex market dynamics driving stock price movements.
method Game-theoretic modeling of heterogeneous investor interactions in a dynamic graph structure.
result Our method outperforms state-of-the-art stock price forecasting methods.

Model shows how heterogeneity in strategies and risk tolerance affects financial market stability.

problem Understanding how heterogeneity impacts financial market dynamics.
method Agent-based model incorporating heterogeneous investment strategies and risk tolerance.
result Heterogeneity in strategies and risk tolerance suppresses price fluctuations.

Proposes ML methods for robust price-sensitivity estimation in dynamic pricing.

problem Estimating price elasticities robustly in the presence of feature-dependent sensitivity.
method Poisson semi-parametric model with two-stage estimation: first-stage ML for observed purchases, second-stage Bayesian GLM for price-sensitivity.
result Reduces estimation error in price-sensitivity parameters from 25% to 4%.

Risk management in financial derivative markets requires inevitably the calculation of the different price sensitivities. The literature contains an abundant amount of research works that have studied the computation of these important values. Most of these works consider the well-known Black and Scholes model where th…

2017-05-06abs ↗pdf ↗

Study parameter sensitivities in bond pricing models with jumps.

problem Analyzing the impact of parameters on bond pricing models with jumps.
method Theoretical analysis and MATLAB simulations of a Brownian motion and compound Poisson process.
result Explicit call price formula and verification of sensitivities.

The paper explains stock market predictability through a model of heterogeneous beliefs.

problem Understanding and predicting stock market behavior based on news and investor beliefs.
method A discrete-time model of heterogeneous beliefs where some agents receive noisy signals about asset fundamentals.
result Momentum and reversal in stock prices arise from investors' incorrect beliefs about signal accuracy and fundamental values.

The paper models asset pricing with agents having different beliefs and examines the effects of liquidity constraints.

problem Asset pricing with heterogeneous beliefs and illiquidity.
method A tractable model with quadratic costs on inventories and trading rates, characterized by a system of linear parabolic equations.
result The equilibrium price is influenced by holding and liquidity costs, and the asymptotics for small costs provide insights.

New method reduces errors in pricing and sensitivities for discontinuous payoffs.

problem Errors in pricing and sensitivities for discontinuous payoffs in digital and barrier options.
method Alternative methods for estimating sensitivities, including likelihood ratio and hybrid methods.
result New methods substantially reduce test errors in prices and sensitivities.

This study generalizes an econophysics model to account for trader heterogeneity, finding robust power-law exponents but sensitive prefactors.

problem The original Lillo-Mike-Farmer model assumed homogeneity in traders' order-splitting strategies, which this study generalizes.
method The study proposes a generalised Lillo-Mike-Farmer model and solves it exactly without heuristic assumptions.
result The power-law exponent in the order-sign ACF is robust for arbitrary heterogeneous intensity distributions, but the prefactor is sensitive to heterogeneity.

Most existing word embedding approaches do not distinguish the same words in different contexts, therefore ignoring their contextual meanings. As a result, the learned embeddings of these words are usually a mixture of multiple meanings. In this paper, we acknowledge multiple identities of the same word in different co…

2016-11-29abs ↗pdf ↗

New model explains price dynamics of Bitcoin with psychological factors.

problem Understanding price variations in cryptocurrency markets with psychological factors.
method Extended agent-based model with heterogeneous psychological parameters.
result Model shows diverse dynamics based on psychological correlation.

Paper develops methods for fair insurance pricing without direct access to sensitive attributes.

problem Fairness in insurance pricing with restricted access to sensitive attributes.
method Develops statistical methods for estimating discrimination-free premiums using privatized sensitive attributes.
result The proposed methods enable fair insurance pricing while respecting privacy and regulatory constraints.

In this paper we propose a simple and efficient method to compute the ordered default time distributions in both the homogeneous case and the two-group heterogeneous case under the interacting intensity default contagion model. We give the analytical expressions for the ordered default time distributions with recursive…

2012-04-18abs ↗pdf ↗

The paper analyzes binary option markets with exogenous information and price sensitivity.

problem Analyzing binary option markets with exogenous information and price sensitivity.
method Derive and analyze a continuous model of binary option markets with exogenous information, using Filippov surfaces and general assumptions on purchasing rules.
result Price always converges when exogenous information is constant, and price sensitivity affects price lag vs. information.

Study compares rejection policies to acceptance policies for lead-time and price-sensitive demand.

problem Optimizing firm's policy under lead time and price-dependent demand.
method Analytical comparison of M/M/1/1 and M/M/1 models with and without holding and penalty costs.
result Rejection policy can be more profitable under certain conditions.

Study local sensitivity of HDD and CDD temperature derivatives prices.

problem Understanding how temperature derivatives prices change with small temperature changes.
method Analyzes sensitivity of HDD and CDD futures and options prices to temperature perturbations using a CAR process.
result Identifies the order of the CAR process and its impact on temperature derivatives prices.

Optimizes insurance pricing by accounting for policyholders' price sensitivity.

problem Traditional insurance pricing does not consider policyholders' price sensitivity.
method Formulates insurance pricing as a decision-making problem and uses off-policy evaluation and stochastic control.
result Neural networks outperform existing techniques for policy optimization.

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…

2013-01-14abs ↗pdf ↗

Proposes Equity2Vec for cross-sectional asset pricing.

problem Sub-optimal performance due to missing cross-sectional effects and heterogeneous data.
method End-to-end deep learning framework with Equity2Vec for graph-based interactions and all alpha sources.
result Outperforms state-of-the-art approaches in real-world stock market datasets.

Study asset pricing with transaction costs, showing unique equilibrium exists.

problem Risk-sharing economies with heterogeneous agents trading under quadratic transaction costs.
method Characterizes equilibrium asset prices and strategies via nonlinear, fully-coupled equations.
result Unique solution exists when agents' preferences are sufficiently similar, and empirical liquidity premia and discounts match transaction costs and volatility.

Entropy measure assesses market volatility and price heterogeneity.

problem Quantifying short-term market heterogeneity in financial time series.
method Entropy measure based on intersecting a random sequence with its moving average.
result Entropy of volatility series varies by market, while price series is market-invariant.

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.

Revisits behavioral finance option pricing model to align with rational asset pricing theory.

problem Inconsistency between behavioral finance and rational asset pricing models in option pricing.
method Introduces arbitrage transaction costs to modify the behavioral finance option pricing formula.
result Modifies behavioral finance option pricing formula to be consistent with rational asset pricing theory.

Energy distance measures feature heterogeneity in federated learning.

problem Heterogeneity across data sources hinders model aggregation in federated learning.
method Introduced Taylor approximations of energy distance for efficient computation.
result Taylor approximations accurately capture feature discrepancies, improving convergence.

New method for learning on heterogeneous graphs without meta-paths.

problem Learning on heterogeneous graphs is sensitive to meta-paths choice, leading to poor performance.
method Decompose heterogeneous graph into homogeneous relation-type graphs, combine higher-order representations, use attention mechanisms.
result Our model outperforms state-of-the-art baselines in vertex classification tasks on heterogeneous graph datasets.

Framework for pricing waterfall structures using simulation and uncertainty modeling.

problem Pricing complex structured finance instruments under uncertainty.
method Simulation-based uncertainty modeling, calibrated probability distributions, PyTorch implementation, Adjoint Algorithmic Differentiation (AAD).
result Efficient gradient computation for risk sensitivity analysis and optimization.

Study shows how diverse investors' learning and preferences shape financial markets.

problem Understanding how diverse investor behaviors and preferences affect market dynamics.
method Developed a multi-agent reinforcement learning framework with heterogeneous preferences and learning mechanisms.
result Diverse investors develop differentiated strategies through interaction, leading to realistic market dynamics.

Study shows informed traders harm market makers but price discovery benefits outweigh costs.

problem Informed traders' impact on market makers' profitability.
method Agent-based model with heterogeneous learning agents, multi-agent reinforcement learning.
result Informed market order flow is harmful when aggregate informedness is low but beneficial as it increases.

Paper proposes a privacy-preserving DML framework using local randomization and ADMM perturbation.

problem Privacy concerns in distributed machine learning with sensitive user data.
method Local randomization and ADMM perturbation to provide differential privacy and heterogeneous privacy levels.
result The framework minimizes privacy losses and maintains model generalization.

New insights on computational limits in analyzing heterogeneous data.

problem Statistical accuracy vs computational tractability in high-dimensional heterogeneous data.
method Oracle-based computational model to establish lower bounds.
result Significant gaps between computationally feasible and classical minimax risks.

The study compares on-chain option prices with a model and finds significant differences.

problem Measuring and comparing on-chain option prices with a model-based benchmark.
method Used a two-regime MS-AR-(GJR)-GARCH model to estimate volatility and GLS to compare prices.
result On-chain option prices are significantly higher than model-based benchmarks, especially for call options.