Optimal portfolio selection of China's green bond and stock markets: Evidence from the multi-frequency extreme risk connectedness

This paper investigates the optimal portfolio of industry stocks with China's green bond (CBGB) at different time scales, through comparing minimum connectedness portfolio (MCoP1) and modified minimum connectedness portfolio (MCoP2) under the condition of minimizing extreme risk connectedness, as well as minimum VaR portfolio. First, we examine the ability of CBGB to provide diversification benefits for industry stocks at different scales, which employs extreme risk connectedness. Then, the portfolio performing optimally at each scale is explored by comparing specific performances of various portfolio methods. The empirical results show that: (1) CBGB is weakly related to industry stocks, whether in the time or frequency domain, and is the net receiver. (2) Most industry stocks play different roles (transmitter or receiver) in different scales, with time-varying characteristics. Therefore, industry stocks benefit highly from the diversification effects of CBGB, and their portfolio should possess frequency and time-varying characteristics. (3) Based on the comparison results of weight allocations, cumulative returns, and Sharpe ratios, the short-term optimal performance is achieved by MCoP2, while in medium- to long-term, MCoP1 outperforms MCoP2 and minimum VaR portfolio. This implies that considering extreme risk connectedness in the construction of portfolios can effectively enhance returns, but in the long term, market integration should also be taken into account.

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Publication Details

Journal
Economic Analysis and Policy
Published
2024-11-20
DOI
https://doi.org/10.1016/j.eap.2024.11.015
Citations
4
Primary Topic
Market Dynamics and Volatility
Type
article
Field-Weighted Citation Impact
4.52

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article

Optimal portfolio selection of China's green bond and stock markets: Evidence from the multi-frequency extreme risk connectedness

Jing Dai, Wei‐Qiang Huang
4 citations
Economic Analysis and Policy
Market Dynamics and Volatility
4.52
article

Optimal portfolio selection of China's green bond and stock markets: Evidence from the multi-frequency extreme risk connectedness

Jing Dai, Wei‐Qiang Huang
article en
4 citations

Abstract

This paper investigates the optimal portfolio of industry stocks with China's green bond (CBGB) at different time scales, through comparing minimum connectedness portfolio (MCoP1) and modified minimum connectedness portfolio (MCoP2) under the condition of minimizing extreme risk connectedness, as well as minimum VaR portfolio. First, we examine the ability of CBGB to provide diversification benefits for industry stocks at different scales, which employs extreme risk connectedness. Then, the portfolio performing optimally at each scale is explored by comparing specific performances of various portfolio methods. The empirical results show that: (1) CBGB is weakly related to industry stocks, whether in the time or frequency domain, and is the net receiver. (2) Most industry stocks play different roles (transmitter or receiver) in different scales, with time-varying characteristics. Therefore, industry stocks benefit highly from the diversification effects of CBGB, and their portfolio should possess frequency and time-varying characteristics. (3) Based on the comparison results of weight allocations, cumulative returns, and Sharpe ratios, the short-term optimal performance is achieved by MCoP2, while in medium- to long-term, MCoP1 outperforms MCoP2 and minimum VaR portfolio. This implies that considering extreme risk connectedness in the construction of portfolios can effectively enhance returns, but in the long term, market integration should also be taken into account.

Economic Analysis and PolicyVol. 85
Northeastern University (CN)
National Natural Science Foundation of China, Fundamental Research Funds for the Central Universities
Openalex Percentile: Top 5%
Market Dynamics and Volatility
4.52
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Optimal portfolio selection of China's green bond and stock markets: Evidence from the multi-frequency extreme risk connectedness — Jing Dai, Wei‐Qiang Huang · Economic Analysis and Policy (2024) | TGRS Research Map | TGRS