This paper proposes the concepts of ESG information flows and a predictable framework of ESG flows based on AR process, and studies how ESG information flows are incorporated into and affect a dynamic portfolio with transaction costs. Two methods, called the ESG factor model and the ESG preference model, are considered to embed ESG information flows into a dynamic mean-variance model. The dynamic optimal portfolio can be expressed as a traditional optimal portfolio without ESG information and a dynamic ESG preference portfolio, and the impact of ESG information on optimal trading is explicitly analyzed. The rich numerical results show that ESG information can improve the out-of-sample performance, and ESG preference portfolio has the best out-of-sample performance including the net returns, Sharpe ratio and cumulative return of portfolios, and contribute to reducing risk and transaction costs. Our dynamic trading strategy provides valuable insights for sustainable investment both in theory and practice.

This study investigates the effectiveness of the volatility-timing strategy in the Chinese equity market. We find that the volatility-managed portfolio (VMP) consistently outperforms its original counterpart, both in individual factor analysis and mean-variance efficient multifactor assessment, and the results are robust in outof-sample setup. Notably, the outperformance is mostly driven by stocks with high arbitrage risk, short-selling constraints, relatively smaller size, and lottery preferences. Further, the multifactor portfolio constructed from the volatility-managed strategy outperforms other portfolios especially in turmoil periods such as high sentiment and low macroeconomic confidence periods. Our findings suggest that in the Chinese equity market with typical trading frictions, volatility timing strategies consistently gain profitable performance.

We extend the ex-ante mean-variance (SVIX) asset pricing models of Martin (2017) and Martin-Wagner (2019) to a mean-variance-asymmetry (AVIX) framework by incorporating higher-moment and co-moment risk in asset pricing. Our proposed AVIX model is risk-neutral with left-tail asymmetries in returns to correct the SVIX approach's downside bias. We derive an option implied market beta of a stock as the weighted average of the betas of SVIX and AVIX. Empirically, the implied beta has significant predictability of risk/return relationship We develop an investible portfolio (MKT*) that mimics realized outcomes on the implied market index adjusted for volatility asymmetry.

China commodity futures market network is constructed. Commodity is the node of the network, and the network link is defined by the price correlation matrix. We analyze the relationship between the centrality of each commodity in the commodity futures market network and the optimal weight of the commodity portfolio, empirically examine the market system factors and commodity personalized factors that affect the centrality of commodity, and evaluate the effect of network structure on the optimization of commodity portfolio selection under the mean-variance framework. It is found that the commodities with high network centrality are often related to industrial products and have high volatility. Commodities with higher centrality have lower portfolio weights. We put forward a kind of commodity futures investment strategy based on network, according to the network centricity grouping the commodities, the network centricity lower edge of the commodity structure of the portfolio, cumulative yield is better than that of centricity higher core product portfolio, the whole market portfolio yield, but due to large maximum retracement, lead to the stability and ability to resist risk compared with the other two groups of goods combination. The main contribution of this paper is to optimize portfolio selection by establishing the relationship between portfolio weight and commodity centrality by using commodity futures market network as a tool.

This paper analyzes international portfolio selection with exchange rate risk based on behavioural portfolio theory (BPT). We characterize the conditions under which the BPT problem with a single foreign market has an optimal solution, and show that the optimal portfolio contains the traditional mean–variance efficient portfolio without consideration of exchange rate risk, and an uncorrelated component constructed to hedge against exchange rate risk. We illustrate that the optimal portfolio must be mean–variance efficient with exchange rate risk, while the same is not true from the perspective of local investors unless certain conditions are satisfied. We further establish that international portfolio selection in the BPT with multiple foreign markets consists of two sequential decisions. Investors first select the optimal BPT portfolio in each market, overlooking covariances among markets, and then allocate funds across markets according to a specific rule to achieve mean–variance efficiency or to minimize the loss in efficiency.

Fund managers usually set aside certain amount of cash to pay for possible redemptions, and it is believed that this will affect overall fund performance. This paper examines the properties of efficient portfolios in the mean-variance framework in the presence of a cash account. We show that investors will retain part of funds in cash, as long as the required return is lower than the expected rerun on the portfolio corresponding to the point of intersection of the traditional efficient frontier and the straight line that passes through the minimum-variance portfolio and the origin in the mean-variance plane (portfolio q1 ). In addition, the efficient portfolios determined by our model are proportional to portfolio q1 , and are more efficient than traditional efficient portfolios. Using a simulation, we illustrate that 6% to 9% of total funds are to be retained in the cash account if no-short-selling constraint is imposed. Based on real data, our out-of-sample empirical results confirm the theoretical findings.

This paper investigates the impact of background risk on an investor’s portfolio choice in a mean–variance framework, and analyzes the properties of efficient portfolios as well as the investor’s hedging behavior in the presence of background risk. Our model implies that the efficient portfolio with background risk can be separated into two independent components: the traditional mean–variance efficient portfolio and a self-financing component constructed to hedge against background risk. Our analysis also shows that the presence of background risk shifts the efficient frontier of financial assets to the right with no changes in its shape. Moreover, both the composition of the hedge portfolio and the location of the efficient frontier are greatly affected by a number of background risk factors, including the proportion of background assets in total wealth and the correlation between background risk and financial risk.

This paper investigates the potential benefits of international diversification with short selling constraints from the perspective of Chinese investors. Based on a stream of time-rolling realized portfolios, we show that Chinese investors can gain substantially from international investments. In particular, the expected portfolio returns as well as the risk-adjusted returns can be greatly enhanced by diversifying over emerging markets, and the portfolio risk can be largely reduced by investing in developed markets in comparison with purely domestic investments. The results are robust when the out-of-sample tests are employed and when investors start with a more mean-variance efficient domestic portfolio. In addition, our analysis illustrates that optimal portfolio weights vary significantly over time due to fluctuations in the correlations among international markets, suggesting that international portfolios need to be rebalanced frequently in order to generate the greatest possible diversification benefits.

Efficient portfolio is a portfolio that yields maximum expected return given a level of risk or has minimum level of risk given a level of expected return.However,the optimal portfolios seem not being as efficient as intended.Especially during financial crisis period.optimal portfolio is not an optimal investment as it does not yield maximum return given a specific level of risk,vice and versa.One possible explanion for an unimpressive performance of the seemingly efficient portfolio is incorrectness in parameter estimates called"estimation risk in parameter estimates".Five different estimating strategies are employed to explore ex post portfolio performance when estimation risk is incorporated.These strategies are traditional mean-variance(EV),Adjusted Beta(AB) approach,Capital Asset Pricing Model(CAPM),Single Index Model(SIM), and Single Index Model incorporating shrikage Bayesian factor namely Bayesian Single Index Model(BSIM).Among the five alternative strategies,shrinkage estimators incorporating the single index model outperforms other traditional portfolio selection strategies.Allowing for asset mispricing and applying Bayesian shrinkage adjusted factor to each asset's alpha,a single factor namely excess market return is adequate in alleviating estimation uncertainty. JEL：G320

This paper investigates the impacts of background risk on investors’ portfolio choice in a mean-variance framework and analyzes the properties of the selected portfolio and investors’ hedging behaviour. Our model implies that the optimal portfolio with background risk can be separated into two independent components: the traditional mean-variance optimal portfolio and the self-financing portfolio constructed to hedge against background risk. Our results show that both the composition and risk of the optimal portfolio are greatly affected by a number of background risk factors, including the quantity and risk of the assets that are exposed to background risk, as well as the correlation between background assets and those in the portfolio.