Mina Glambosky

We utilize a sample of 44,344 firm-years (1990–2019) to examine the association between operational hedging and stock price crash risk. We examine the association between operational hedging and crash risk. Our operational hedge measure (OPERHEDGE), based on Kogan et al. (2023), indicates a rise in revenue leads to a nearly proportional increase in the cost of goods sold. We address endogeneity concerns through multiple methods and alternative measurements and find consistently negative and significant coefficients for OPERHEDGE. Robustness checks using alternative crash risk measures, time horizons and subsamples confirm the negative association between operational hedging and crash risk. Regression results support variable costs acting as a natural hedge against revenue fluctuations, leading to lower future crash risk for firms with stronger operational hedging. Notably, the negative relationship is stronger for firms experiencing declining earnings and with higher accruals management. The ability of an operational hedge to mitigate stock price crash risk remains an open question and is the focus of our research. The findings have important implications for corporate risk management, highlighting that operational decisions can play a crucial role in mitigating crash risk.

This study applies machine learning methods to develop a sustainable pairs trading market-neutral investment strategy across multiple futures markets. Cointegrated pairs with similar price trends are identified, and a hedge ratio is determined using an Error Correction Model (ECM) framework and support vector machine algorithm based upon the two-step Engle–Granger method. The study shows that normal backwardation and contango do not consistently characterize futures markets, and an algorithmic pairs trading strategy is effective, given the unique predominant price trends of each futures market. Across multiple futures markets, the pairs trading strategy results in larger risk-adjusted returns and lower exposure to market risk, relative to an appropriate benchmark. Backtesting is employed and results show that the pairs trading strategy may hedge against unexpected negative systemic events, specifically the COVID-19 pandemic, remaining profitable over the period examined.

This study aims to examine the relationship between the Korean and Chinese game industries, and more broadly, the Chinese stock market. Chinese firms are the most important partners and investors in the Korean game industry, which has emerged as a significant component of a thriving Korean economy. The paper examines the impact of growth in the Chinese game industry on the Korean market and the correlation and cointegration between the stock returns of nineteen Korean game companies, the Chinese stock market, and Chinese game companies. A portfolio constructed from Korean game companies listed on the KOSPI and KOSDAQ is analyzed. Variation in the Shanghai Composite Index is shown to significantly influence the performance of Korean game companies. Further, the Korean game industry is sensitive to changes in the stock price of leading Chinese game publishers. The Korean game industry returns more closely mirror the returns of the Chinese stock markets rather than the Korean markets, evidence of the influence of China. As growth and returns in the Korean game industry are closely related to the performance of the Chinese market, future performance is subject to political and economic changes in China.

The authors decompose a simple cross-country interest rate differential into three cross-country differential factors, originated from the Nelson–Siegel model. Results suggest that return premiums for carry trades are highly associated with parallel yield curve shifts in investment currencies against the US yield curve. Currency portfolios based on cross-country yield curve gap can be profitable, with lowest tercile portfolios yielding sizable risk-adjusted returns adjusted for transaction costs. The authors’ model identifies higher currency carry returns for hedge funds when cross-country yield curves exhibit a wide interest gap over all maturities and finds that investment currency yields have greater curvature relative to funding currency yields. TOPICS:Currency, performance measurement, global markets

Academic literature struggles to explain investors’ attitude towards fees and expenses charged by mutual funds. In general, investors have been found to exhibit a puzzling lack of interest in this non-trivial component of their total return, raising questions of rationality of real-world investor behavior. An emergence of exchange-traded funds (ETFs), their rapid proliferation in the past decades and distinct features, such as more simple expense structure, present a valuable opportunity to contribute to the debate surrounding the pricing of funds. To better understand the expense policy/fund flows dynamics, the authors first test a conjecture that later entrants in the ETF markets face a disadvantage in competition for fund flows. Then, they test whether competitive pressure can be successfully overcome by lowering expenses charged to ETF investors. The results suggest that, though it is not necessary to be a first entrant in a fund category to enjoy competitive advantage, an earlier market entry is beneficial for attracting fund flows. It is also found that later entrants’ to the ETF market successfully use the strategy of reducing their expense ratios. Firms with lower net expense ratios obtain greater investment, as evidenced by greater capitalization and market share, supporting our intuition that investors may acknowledge the merits of low-cost ETFs.