Imagen de Portada

Forecasting the Evolving Composition of Inbound Tourism Demand: A Bayesian Compositional Time Series Approach Using Platform Booking Data

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autor principal:	Katz, Harrison
Formato:	Preprint
Publicado:	2026
Materias:	Applications Statistical Finance
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Coupled Supply and Demand Forecasting in Platform Accommodation Markets
por: Katz, Harrison
Publicado: (2026)

Directional-Shift Dirichlet ARMA Models for Compositional Time Series with Structural Break Intervention
por: Katz, Harrison
Publicado: (2026)

Distributional Fitting and Tail Analysis of Lead-Time Compositions: Nights vs. Revenue on Airbnb
por: Katz, Harrison E., et al.
Publicado: (2026)

Lead Times in Flux: Analyzing Airbnb Booking Dynamics During Global Upheavals (2018-2022)
por: Katz, Harrison, et al.
Publicado: (2025)

Bayesian Testing Of Granger Causality In Functional Time Series
por: Sen, Rituparna, et al.
Publicado: (2021)

Polyspectral Mean based Time Series Clustering of Indian Stock Market
por: Ghosh, Dhrubajyoti
Publicado: (2025)

Time Series Analysis in American Stock Market Recovering in Post COVID-19 Pandemic Period
por: Fu, Weilin, et al.
Publicado: (2022)

Pairs Trading Using a Novel Graphical Matching Approach
por: Qureshi, Khizar, et al.
Publicado: (2024)

Distributional Reference Class Forecasting of Corporate Sales Growth With Multiple Reference Variables
por: Theising, Etienne
Publicado: (2024)

Dynamic Skewness in Stochastic Volatility Models: A Penalized Prior Approach
por: Holtz, Bruno E., et al.
Publicado: (2025)

The Impact of Oil and Gold Prices Shock on Tehran Stock Exchange: A Copula Approach
por: Najafabadi, Amir T. Payandeh, et al.
Publicado: (2020)

A Nontrivial Upper Bound on the Out-of-Sample $R^2$ in Return Forecasting
por: Zhang, Cheng
Publicado: (2026)

An Accurate Discretized Approach to Parameter Estimation in the CKLS Model via the CIR Framework
por: Barick, Sourojyoti
Publicado: (2025)

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

Forecasting the U.S. Renewable-Energy Mix with an ALR-BDARMA Compositional Time-Series Framework
por: Katz, Harrison, et al.
Publicado: (2025)

Application of Machine Learning in Stock Market Forecasting: A Case Study of Disney Stock
por: Huang, Dengxin
Publicado: (2023)

Centered-Innovation MA for Bayesian Dirichlet ARMA: Theoretical Equivalence and an Application to Bank-Asset Shares
por: Katz, Harrison
Publicado: (2025)

The Evolution of Probabilistic Price Forecasting Techniques: A Review of the Day-Ahead, Intra-Day, and Balancing Markets
por: O'Connor, Ciaran, et al.
Publicado: (2025)

High-frequency lead-lag relationships in the Chinese stock index futures market: tick-by-tick dynamics of calendar spreads
por: Li, Guanlin, et al.
Publicado: (2025)

Copula estimation for nonsynchronous financial data
por: Chakrabarti, Arnab, et al.
Publicado: (2019)

Structured factor copulas for modeling the systemic risk of European and United States banks
por: Nguyen, Hoang, et al.
Publicado: (2024)

Credit scoring using neural networks and SURE posterior probability calibration
por: Garcin, Matthieu, et al.
Publicado: (2021)

Scaling and shape of financial returns distributions modeled as conditionally independent random variables
por: Larralde, Hernán, et al.
Publicado: (2025)

Predicting Value at Risk for Cryptocurrencies With Generalized Random Forests
por: Buse, Rebekka, et al.
Publicado: (2022)

The $κ$-generalised Distribution for Stock Returns
por: Forbes, Samuel
Publicado: (2024)

Regularization for electricity price forecasting
por: Uniejewski, Bartosz
Publicado: (2024)

Financial Data Analysis with Robust Federated Logistic Regression
por: Yang, Kun, et al.
Publicado: (2025)

Data-Driven Risk Measurement by SV-GARCH-EVT Model
por: Xiao, Minheng
Publicado: (2022)

Bayesian CART models for aggregate claim modeling
por: Zhang, Yaojun, et al.
Publicado: (2024)

Forecasting Electricity Prices
por: Maciejowska, Katarzyna, et al.
Publicado: (2022)

Low Volatility Stock Portfolio Through High Dimensional Bayesian Cointegration
por: Yang, Parley R, et al.
Publicado: (2024)

Clustered Network Connectedness: A New Measurement Framework with Application to Global Equity Markets
por: Buchwalter, Bastien, et al.
Publicado: (2025)

Probabilistic Forecasting for Day-ahead Electricity Prices, Battery Trading Strategies and the Economic Evaluation of Predictive Accuracy
por: Hirsch, Simon, et al.
Publicado: (2026)

High-Throughput Asset Pricing
por: Chen, Andrew Y., et al.
Publicado: (2023)

Forecasting duration in high-frequency financial data using a self-exciting flexible residual point process
por: Lee, Kyungsub
Publicado: (2026)

Stock Volume Forecasting with Advanced Information by Conditional Variational Auto-Encoder
por: Yang, Parley R, et al.
Publicado: (2024)

Peer-induced Fairness: A Causal Approach for Algorithmic Fairness Auditing
por: Fang, Shiqi, et al.
Publicado: (2024)

Student t-Lévy regression model in YUIMA
por: Masuda, Hiroki, et al.
Publicado: (2024)

Introducing shrinkage in heavy-tailed state space models to predict equity excess returns
por: Huber, Florian, et al.
Publicado: (2018)

Analysing Models for Volatility Clustering with Subordinated Processes: VGSA and Beyond
por: Barick, Sourojyoti, et al.
Publicado: (2025)