Cross-sector comovements and policy impact in the COVID-19 stock market: A dynamic factor approach

This study investigates the remarkable comovements in U.S. equity returns during the COVID-19 pandemic. It constructs a dynamic factor model (DFM) to illuminate the sources of the comovements and their implications. Using the Markov Chain Monte Carlo (MCMC) estimation method, the study finds that the comovements had a weak daily oscillation pattern during the pandemic. With that pattern, the study also finds significant monetary policy effects on the equity returns of several key sectors. In addition, it estimates the impact of news shocks, including monetary policy news, fiscal stimulus news, and unemployment news, on cross-sector equity returns. For any given sector, the conventional and unconventional monetary policy news shocked the sector in opposite directions. Among the positive monetary news shocks, the strongest were from interest rate policy surprises. Conversely, fiscal stimulus news had the most substantial positive impact and triggered all sectors to rebound from the bear market at the end of March 2020. Furthermore, by applying Natural Language Processing (NLP) sentiment analysis, this study sheds light on the positive correlation between comovements and news sentiment.     

The effect of settlement regimes on trading cost and market efficiency: evidence from the National Stock Exchange

Using data from 65 of the most actively traded stocks from the National Stock Exchange of India we study the relationship between impact cost and three indicators of market efficiency under different settlement regimes. Our data is uniquely suited for this study because it encompasses a transition by the National Stock Exchange of India from fixed to rolling settlement. As a by-product of our study we are able to examine inefficiencies related to the day of the week on which trades are conducted for different settlement regimes. In summary our data reveals that rolling settlement reduces aggregate impact costs, leading to greater market efficiency. Employing a fixed effects model we show that impact cost has a stronger relationship to our indicators of market efficiency under rolling settlement. However, we find evidence of two structural inefficiencies related to the day-of-the-week on which trades are conducted: 1) under rolling settlement, trades conducted earlier in the week (and settled by Thursday) have lower impact costs, and 2) there is an impact cost premium for Friday trades.     

Dynamic hedging of single and multi-dimensional options with transaction costs: a generalized utility maximization approach

We propose a new methodology for discrete time dynamic hedging with transaction costs that has three key performance features. First, the methodology can accommodate the use of a wide range of objective functions, from the use of many types of utility functions to the more traditional objectives of hedging error minimization. Second, our methodology can significantly outperform traditional dynamic hedging methodologies across a range of objective functions. Third, our methodology can be applied to both single and multi-dimensional options while analytical methods typically can only be applied to single dimensional options.