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

Published: 25 November 2024| Version 1 | DOI: 10.17632/4yjzw8mgr9.1
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Description

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.

Files

Steps to reproduce

See the readme.txt file for details.

Categories

Financial Forecasting, Volatility, Cryptocurrency

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