Data and Codes for "Predicting Cryptocurrency Volatility: The Power of Model Clustering"

These codes replicate all the empirical results presented in the paper "Predicting Cryptocurrency Volatility: The Power of Model Clustering" by Yue Qiu, Shaoguang Qu, Zhentao Shi, and Tian Xie. 1. Input Data: crvg_data.mat This file contains the primary dataset used for the empirical analyses in the paper. 2. Main Script File: crvg_main.m - This script performs all the empirical exercises described in the paper. - It reproduces Figures 1, 3, 4, and 5 in the main manuscript (excluding Figure 2, which is a flowchart), as well as Figure A.1 in the appendix. - It also replicates Tables 1 to 10 in the main manuscript and Tables A.2 and A.3 in the appendix (Table A.1 lists selected representative cryptocurrencies). 3. Function Folder: \functions\ This folder contains 17 essential function files required to replicate the empirical results. 4. Result Files: result_main.mat, result_robust1.mat, result_robust2.mat, result_robust3.mat - Forecasting exercises can be time-intensive, so saving intermediate results is recommended before conducting further analysis. - Pre-saved result files are provided for the main analysis and three robustness checks. - While the provided codes can generate these result files, the process may take some time. - The forecasting and testing procedures involve inherent randomness, which may lead to slight variations in quantitative results. However, the qualitative conclusions remain consistent.