Spillover Network Features from the Industry Chain View in Multi-Time Scales
Sida Feng1, Qingru Sun2, Xueyong Liu3
1The College of Economics and Management, Beijing University of Chemical Technology, Beijing 100029, China.
Entropy (Basel, Switzerland)
|August 26, 2022
Summary
This study reveals optimal investment horizons for financial stocks based on risk tolerance. Short-term investments suit risk-takers, while long-term strategies benefit conservative investors, highlighting dynamic industry chain relationships.
Area of Science:
- * Financial markets
- * Econometrics
- * Network analysis
Background:
- * Financial stocks exhibit intricate economic and technical interdependencies within industry chains.
- * Market participants often focus on specific industry chains with varying investment horizons.
- * Understanding these dynamics is crucial for targeted investment strategies.
Purpose of the Study:
- * To provide targeted information for market participants with different investment time scales within a single industry chain.
- * To systematically analyze stock interactions and risk transmission across multiple time scales.
- * To enhance market monitoring and stock selection through a multi-faceted analytical approach.
Main Methods:
- * Generalized Autoregressive Conditional Heteroskedasticity-Backward Expectation (GARCH-BEKK) model for volatility clustering.
- * Heterogeneous network analysis to map inter-stock relationships.
- * Wavelet analysis to explore time-frequency dynamics and cross-correlations.
Main Results:
- * Investment scales of 4-8 days are optimal for high-risk, high-return investors, while 32-128 days suit conservative investors.
- * Specific links within industry chains demonstrate significant sensitivity to stock changes in other segments.
- * Stock influence, sensitivity, and intermediacy vary across different time scales, offering insights for market monitoring and stock selection.
- * Key transmission paths, their structures, and attributes differ significantly across multi-time scales.
Conclusions:
- * Investment strategies should align with risk tolerance and chosen time scales, leveraging identified industry chain sensitivities.
- * Understanding multi-time scale dynamics is essential for effective risk management and control within financial industry chains.
- * The study provides a framework for participants to navigate complex stock interdependencies and optimize investment decisions.
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