Spatial and Spatiotemporal Volatility Models: A Review

ArXiv ID: 2308.13061 “View on arXiv”

Authors: Unknown

Abstract

Spatial and spatiotemporal volatility models are a class of models designed to capture spatial dependence in the volatility of spatial and spatiotemporal data. Spatial dependence in the volatility may arise due to spatial spillovers among locations; that is, if two locations are in close proximity, they can exhibit similar volatilities. In this paper, we aim to provide a comprehensive review of the recent literature on spatial and spatiotemporal volatility models. We first briefly review time series volatility models and their multivariate extensions to motivate their spatial and spatiotemporal counterparts. We then review various spatial and spatiotemporal volatility specifications proposed in the literature along with their underlying motivations and estimation strategies. Through this analysis, we effectively compare all models and provide practical recommendations for their appropriate usage. We highlight possible extensions and conclude by outlining directions for future research.

Keywords: Spatial Volatility Models, Spatiotemporal Volatility, Spatial Dependence, Multivariate Volatility, Time Series Analysis

Complexity vs Empirical Score

• Math Complexity: 7.5/10
• Empirical Rigor: 3.0/10
• Quadrant: Lab Rats
• Why: The paper is a theoretical review heavy with advanced statistical derivations and spatial econometrics formalism, but it presents no original backtesting, code, or implementation details, focusing instead on model specifications and estimation strategies.

  flowchart TD
    A["Research Goal:<br>Spatiotemporal Volatility Review"] --> B["Methodology: Literature Review & Analysis"]
    B --> C["Key Input: Time Series &<br>Multivariate Volatility Models"]
    B --> D["Key Input: Spatial &<br>Spatiotemporal Specifications"]
    
    C --> E["Computational Process:<br>Comparative Analysis &<br>Model Evaluation"]
    D --> E
    
    E --> F["Outcome 1: Practical<br>Recommendations for Model Usage"]
    E --> G["Outcome 2: Future Research<br>Directions & Extensions"]