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An index based on the carbon-neutral concept stock pool is built, and GARCH-dynamic Copula-CoVaR is used to study the risk spillover effect between the carbon market and the carbon-neutral index. The results show as follows. 1) There is a bi-directional risk spillover between the national carbon emission allowance market and the carbon-neutral index, and the positive correlation is becoming increasingly significant. 2) The correlation between the local carbon market and the carbon-neutral index is weak, and there is an asymmetric risk spillover relationship between them: the former can have a one-way risk impact on the latter. 3) In general, the carbon-neutral index is a net risk receiver, and carbon-neutral concept enterprises face the risk of carbon emission allowance price fluctuation in the process of green transformation. In addition, drawing on the research ideas existed, appropriate "brown assets" and "green assets" in the carbon market and stock market are found, and trading strategies including hedging and pair trading are designed, providing new ideas for investors' asset allocation.

Based on the Lasso algorithm and a bidirectional fixed multiple linear regression model, this study comprehensively investigates the impact of macro and micro factors on the credit spread of ESG bonds in China. Research has shown that the credit spread of ESG bonds is negatively correlated with macro factors such as regional per capita GDP, local fiscal revenue, money supply, stock market returns, as well as micro factors such as total issuance amount, entity rating, debt rating, guaranteed delivery, state-owned equity certification, and green certification. Meanwhile, the credit spread is positively correlated with factors such as RMB exchange rate, fuel oil price, and urban investment bond certification. Further heterogeneity analysis indicates that ESG bonds are more significantly impacted by external factors after the epidemic, and the safety of state-owned bonds is further highlighted. The default rate of ESG urban investment bonds in the southwest region is relatively high, and the key to reducing their credit spread is to obtain green certification for establishing a positive market image. The above research conclusions provide important references for optimizing the bond pricing mechanism and reasonably evaluating the risks of ESG concept financing projects.

Due to the defects of Merrill Lynch Clock, this paper aims to put forward Pringle Clock for theoretical improvement. In addition, strategic optimization for Pringle from perspectives including indicators, assets and timing is made, and finally its effectiveness in domestic market is tested. The results show as follows. 1) Stages of the Pringle cycle divided by three indexes (leading, consistent and lagging) can accurately grasp allocation opportunities of assets in different categories. 2) Researches and investments in the subdivided industries of the equity market are conducive to improving portfolio returns, and Markowitz mean-variance model can be used for portfolio optimization.3) Selecting appropriate leading interest rate indicators (by using wavelet cross analysis) and predicting the characteristics of the next stage in advance (by using VAR model) are of great help to improve the flexible timing ability of the asset allocation strategies.