Copertina

Prediction Markets as Bayesian Inverse Problems: Uncertainty Quantification, Identifiability, and Information Gain from Price-Volume Histories under Latent Types

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Madrigal-Cianci, Juan Pablo, Maya, Camilo Monsalve, Breakey, Lachlan
Natura:	Preprint
Pubblicazione:	2026
Soggetti:	Mathematical Finance Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Sensor Informativeness, Identifiability, and Uncertainty in Bayesian Inverse Problems for Structural Health Monitoring
di: Bakeer, Tammam, et al.
Pubblicazione: (2025)

An Efficient Bayesian Framework for Inverse Problems via Optimization and Inversion: Surrogate Modeling, Parameter Inference, and Uncertainty Quantification
di: Chiappetta, Mihaela, et al.
Pubblicazione: (2026)

Multi-Physics-Enhanced Bayesian Inverse Analysis: Information Gain from Additional Fields
di: Haeusel, Lea J., et al.
Pubblicazione: (2025)

Options Pricing under Bayesian MS-VAR Process
di: Gankhuu, Battulga
Pubblicazione: (2021)

Local Information Operators for Spatial Identifiability in Distributed-Parameter Inverse Problems in Computational Mechanics
di: Bakeer, Tammam
Pubblicazione: (2026)

Multimodal Stock Price Prediction: A Case Study of the Russian Securities Market
di: Khubiev, Kasymkhan, et al.
Pubblicazione: (2025)

A Prior-Predictive Monte Carlo Framework for Pricing Complex Data Products in Data-Poor Markets
di: Siemiatkowski, Adam L., et al.
Pubblicazione: (2026)

Market-Based Price Autocorrelation
di: Olkhov, Victor
Pubblicazione: (2022)

Forecasting Intraday Volume in Equity Markets with Machine Learning
di: Cucuringu, Mihai, et al.
Pubblicazione: (2025)

Beyond the Traditional VIX: A Novel Approach to Identifying Uncertainty Shocks in Financial Markets
di: Jha, Ayush, et al.
Pubblicazione: (2024)

Predicting Stock Price Movement as an Image Classification Problem
di: Steinbacher, Matej
Pubblicazione: (2023)

Inverse Portfolio Optimization with Synthetic Investor Data: Recovering Risk Preferences under Uncertainty
di: Cha, Jinho, et al.
Pubblicazione: (2025)

Probabilistic Predictions of Option Prices with Modular Approximate Bayesian Inference
di: Maneesoonthorn, Worapree, et al.
Pubblicazione: (2024)

Multi-Fidelity Bayesian Neural Network for Uncertainty Quantification in Transonic Aerodynamic Loads
di: Vaiuso, Andrea, et al.
Pubblicazione: (2024)

Embedded Model Form Uncertainty Quantification with Measurement Noise for Bayesian Model Calibration
di: Arcones, Daniel Andrés, et al.
Pubblicazione: (2024)

Semantic Non-Fungibility and Violations of the Law of One Price in Prediction Markets
di: Gebele, Jonas, et al.
Pubblicazione: (2026)

Directional Price Forecasting in the Continuous Intraday Market under Consideration of Neighboring Products and Limit Order Books
di: Hornek, Timothée, et al.
Pubblicazione: (2025)

UAMM: Price-oracle based Automated Market Maker
di: Im, Daniel Jiwoong, et al.
Pubblicazione: (2023)

Conditionally Identifiable Latent Representation for Multivariate Time Series with Structural Dynamics
di: Chang, Minkey, et al.
Pubblicazione: (2026)

The Risk-Neutral Equivalent Pricing of Model-Uncertainty
di: Wren, Ken Kangda
Pubblicazione: (2025)

The Deep Latent Space Particle Filter for Real-Time Data Assimilation with Uncertainty Quantification
di: Mücke, Nikolaj T., et al.
Pubblicazione: (2024)

Mamba Meets Financial Markets: A Graph-Mamba Approach for Stock Price Prediction
di: Mehrabian, Ali, et al.
Pubblicazione: (2024)

Marketron Through the Looking Glass: From Equity Dynamics to Option Pricing in Incomplete Markets
di: Halperin, Igor, et al.
Pubblicazione: (2025)

Pricing Poseidon: Extreme Weather Uncertainty and Firm Return Dynamics
di: MATHIAS S. KRUTTLI, et al.
Pubblicazione: (2025)

Deep Learning Option Pricing with Market Implied Volatility Surfaces
di: Ding, Lijie, et al.
Pubblicazione: (2025)

The Price of Liquidity: Implied Volatility of Automated Market Maker Fees
di: Bichuch, Maxim, et al.
Pubblicazione: (2025)

Multivariate Simulation-based Forecasting for Intraday Power Markets: Modelling Cross-Product Price Effects
di: Hirsch, Simon, et al.
Pubblicazione: (2023)

Optimal Experimental Design of a Moving Sensor for Linear Bayesian Inverse Problems
di: Aretz, Nicole, et al.
Pubblicazione: (2025)

Why Regression? Binary Encoding Classification Brings Confidence to Stock Market Index Price Prediction
di: Jiang, Junzhe, et al.
Pubblicazione: (2025)

Stock Price Informativeness and the Sensitivity of Advertising Expenditures to Stock Price
di: Zhimin Xie, et al.
Pubblicazione: (2026)

Tokenizing Stock Prices for Enhanced Multi-Step Forecast and Prediction
di: Zhu, Zhuohang, et al.
Pubblicazione: (2025)

On the Co-movement of Crude, Gold Prices and Stock Index in Indian Market
di: Sen, Abhibasu, et al.
Pubblicazione: (2019)

Unifying Market Microstructure and Dynamic Asset Pricing
di: Lauria, Davide, et al.
Pubblicazione: (2023)

Stochastic Path-Dependent Volatility Models for Price-Storage Dynamics in Natural Gas Markets and Discrete-Time Swing Option Pricing
di: Qiu, Jinniao, et al.
Pubblicazione: (2024)

On Bitcoin Price Prediction
di: Bournassenko, Grégory
Pubblicazione: (2025)

Adaptive Temporal Fusion Transformers for Cryptocurrency Price Prediction
di: Peik, Arash, et al.
Pubblicazione: (2025)

Dynamic Bayesian Networks for Predicting Cryptocurrency Price Directions: Uncovering Causal Relationships
di: Amirzadeh, Rasoul, et al.
Pubblicazione: (2023)

Bayesian Parameter Inference and Uncertainty Quantification for a Computational Pulmonary Hemodynamics Model Using Gaussian Processes
di: Kachabi, Amirreza, et al.
Pubblicazione: (2025)

Toward Black Scholes for Prediction Markets: A Unified Kernel and Market Maker's Handbook
di: Dalen, Shaw
Pubblicazione: (2025)

Price Limits and Financial Reporting Quality: Evidence From the ChiNext Market
di: Jie Zhang, et al.
Pubblicazione: (2026)