Do cryptocurrencies provide better hedging? Evidence from major equity markets during COVID-19 pandemic

Using the five-minute interval price data of two cryptocurrencies and eight stock market indices, we examine the risk spillover and hedging effectiveness between these two assets. Our approach provides a comparative assessment encompassing the pre-COVID-19 and COVID-19 sample periods. We employ copula models to assess the dependence and risk spillover from Bitcoin and Ethereum to stock market returns during both the pre-COVID-19 and COVID-19 periods. Notably, the COVID-19 pandemic has increased the risk spillover from Bitcoin and Ethereum to stock market returns. The findings vis-à-vis portfolio weights and hedge effectiveness highlight hedging gains; however, optimal investments in Bitcoin and Ethereum have reduced during the COVID-19 pandemic, while the cost of hedging has increased during this period. The findings also confirm that cryptocurrencies cannot provide incremental gains by hedging stock market risk during the COVID-19 pandemic.     

It takes more than two to tango: Multiple bank lending,asset commonality and risk

Multiple-bank lending is the most prevalent form of bank-firm credit relationships in nearly all countries. It results in high asset commonality and interconnectedness, allows idiosyncratic risks to become systemic, and makes the banking system more fragile and vulnerable to shocks. Using detailed, granular-level, supervisory data on large corporate loans, we show that multiple bank lending is driven, inter alia, by regulatory limits on large credit exposures. These limits, aimed at mitigating an individual bank's concentration risk, force firms to explore alternative sources of funding, making the common borrowers' phenomenon more prominent. We find that multiple bank lending is determined endogenously, and its likelihood increases with the level of portfolio similarity between lenders. The size of the original lender and its systemic importance magnifies this effect. We argue that banks do not internalize the systemic effect of their lending decisions and that multiple bank lending constitutes an insurance mechanism related to an implicit "too-many-to-fail" guarantee. Its externalities are suboptimal and should be reinforced with better monitoring by the related authorities.     

Should investors include green bonds in their portfolios? Evidence for the USA and Europe

The green bond market has seen a rapid growth world widely in recent years. This paper explores the role of green bonds in asset allocation using the dynamic R-vine copula-based mean-CVaR approach. We compare the performance of portfolios including green bonds with that of portfolios including conventional bonds in the U.S. and European markets. Empirical results show that portfolios with green bonds outperform portfolios with conventional bonds in terms of risk-adjusted returns in the majority of cases in both markets. The benefit of green bonds comes from both the increase in the return and the decrease in the volatility for most of the cases. Overall, our findings suggest that green bonds are beneficial to investors.     

Price impact,strategic interaction and portfolio choice

This paper studies the portfolio choice of two large investors who act strategically because their trading affects interest rates. Each investor chooses her optimal portfolio conditional on the portfolio of the opponent. Equilibrium portfolios and their performance depend on the investor’s characteristics (risk aversion and return impact) and on the characteristics of the opponent (risk aversion and return impact). Depending on the interplay among these characteristics, strategic interaction can (i) increase or decrease risk taking incentives, as compared to the Merton-style portfolio, (ii) induce the more risk-averse investor to invest relatively more in the risky asset and (iii) change the role of inflation-linked bonds from hedging instrument to borrowing opportunity.     

Fund ESG performance and downside risk: Evidence from China

Whether responsible investing reduces portfolio risk remains open to discussion. We study the relationship between ESG performance and downside risk at fund level in the Chinese equity mutual fund market. We find that fund ESG performance is positively associated with fund downside risk during the period between July 2018 and March 2021, and that the positive relationship weakens during the COVID-19 pandemic. We propose three channels through which fund ESG performance could affect fund downside risk: (i) the firm channel in which the risk-mitigation effect of portfolio firms’ good ESG practices could be manifested at fund level, (ii) the diversification channel in which the portfolio concentration of high ESG-rated funds could amplify fund downside risk, and (iii) the flow channel in which funds’ better ESG performance may attract greater investor flows that could reduce fund downside risk. We show evidence that the observed time-varying relationship between fund ESG performance and downside risk is driven by the relative force of the three channels.     

Investor flow-chasing and price–performance puzzle: Evidence from global infrastructure funds

Despite the importance and peculiarity of the infrastructure fund, determinants of infrastructure fund flow and the relation between fees and fund performance were poorly understood. This paper documents two new findings using a unique dataset for global infrastructure funds from January 2005 to June 2019. First, investor flow-chasing exists at the level of infrastructure fund companies, which is intensified by the opacity of information and uncertainty of returns. Second, infrastructure funds charge higher fees even when their before-fee performance is worse, which is explained by fund characteristics and year effects. Based on these findings, we put forward countermeasures from the perspectives of investors, regulators, investor protection managers, and fund managers, with incentive mechanism reforms to alleviate the price-performance puzzle, thereby improving the efficiency of infrastructure fund portfolios.     

Forecasting gold volatility with geopolitical risk indices

This paper tries to forecast gold volatility with multiple country-specific (GPR) indices and compares the role of combined prediction models and dimension reduction methods regarding the improvement of gold volatility prediction accuracy. For this purpose, GARCH-MIDAS model’s several extensions are used. We find firstly that most country-specific GPR indices have driving effects on gold volatility, and it makes sense to take forecast information from multiple country-specific GPR indices into account when forecasting gold volatility. The out-of-sample empirical results also indicate that the dimension reduction methods yield better predictions compared to the combined prediction models. In addition, dimension reduction technologies have excellent forecasting performance mainly during low gold volatility periods. Finally, our empirical findings are robust after changing the evaluation method, model settings, in-sample length and gold market.