COVID-19 has stimulated additional research interest on economic sustainability and ESG in both academia and industry. This study adopts a DEA approach to examine the efficiency of achieving ESG targets and their relationships with financial performance. Using MSCI ESG data from 2015-2019 on...

We address the problem of poor portfolio performance when a minimum-variance portfolio is constructed using the sample estimates. Estimation errors are mostly blamed for the poor portfolio performance. However, we argue that even small unbiased estimation errors can lead to significantly bad...

In recent years, manufacturing firms in the United States have faced increasing import competition from low-wage countries, especially China. Does this competition hurt or help innovation by firms? This paper studies the effect of the surge in imports from China on innovation in the US...

While Carbon Dioxide based Enhanced Oil Recovery (CO2 -EOR) is often regarded as one of the most economically viable methods of carbon capture, utilization and storage (CCUS), little is known about the existing CO2 supply contracts in the CO2 -EOR industry. By studying a sample of 103 CO2 sales...

In this paper, I reinvestigate the popular belief that the Maximum-Sharpe (MS) portfolio has terrible out-of-sample performance because of estimation errors in the expected return. I show that even without estimation error, the MS portfolio could still perform terribly under a measurement that...

The solutions to robust optimization problems are sometimes too conservative because of the focus on worst-case performance. For the least-squares (LS) problem, we describe a way to overcome this by combining the classical formulation with its robust counterpart. We focus on the issue of...

Two new two-dimensional (2D) materials known as covalent organic framework (COF) and graphene phase carbon nitride nanosheets (CNNS) have induced great interests in photocatalysis due to their highly π-conjugate structure and wide light absorption. Herein, metal-free COF-CNNS hybrids were...

We propose a new dimension reduction procedure for portfolio optimization. The vanilla principal component analysis (PCA) restricts the portfolio on the linear subspace spanned by the PCs, which often requires many PCs to performance well. In our framework, the linear subspace is based on a most...