Heterogeneity Effect of Positive and Negative Jumps on the Realized Volatility:Evidence from China

Published: 10 April 2024| Version 1 | DOI: 10.17632/mcv87wgmj9.1
, jiefei Huang, Qichao Zhang,


The folder "code" contains the code for data processing and empirical results. It includes two folders, data is used to store data, and model is used to store running python code.


Steps to reproduce

1.Empirical analysis: 1.1.''Jump decomposition.py'' is used to calculate realized volatility and decompose realized volatility. 1.2.''Quantile regression(no dummy).py''for regression analysis, you can get the regression results of the Shanghai Composite Index and different industry indexes in this article by selecting different paths of the data file. 1.3.''Quantile regression(dummy).py''to detect the impact of COVID-19. 1.4''RV_EVT_HAR.py''is used to calculate VaR. 1.5''VaR_backtest.py''is used to backtest VaR, including LR and other tests. 2.Figure: 2.1Figure 1 can be obtained through the ''correlation coefficient heat map.py'' 2.2Figure 2 can be obtained via ''jump visualization.py'' 2.3Figures 3 and 4 can be obtained through ''jump frequency and jump intensity pie chart.py'' 2.4Figure 5 requires you to choose to run ''Quantile drawing data preprocessing.py'', then run ''Quantile plotting.py'' 2.5Figure 6 requires you to choose to run ''Box plot data preprocessing.py'', then run ''Box plot.py'' 2.6Figure 7 is obtained by running ''VaR.py''


Shanghai Normal University


Financial Risk Management