Quantitative Description of V2O3V_2O_3 by the Hubbard Model in Infinite Dimensions

We show that the analytic single-particle density of states and the optical conductivity for the half-filled Hubbard model on the Bethe lattice in infinite dimensions describe quantitatively the behavior of the gap and the kinetic energy ratio of the correlated insulator $V_2O_3$. The form of the optical conductivity shows $\omega^{3/2}$ rising and is quite similar to the experimental data, and the density of states shows $\omega^{1/2}$ behavior near the band edges.Comment: 9 pages, revtex, 4 figures upon reques

The effects of domestic climate change measures on international competitiveness

Under the Kyoto Protocol, industrialized countries (called Annex I countries) have to reduce their combined emissions to 5 percent below 1990 levels in the first commitment period of 2008-12. Efforts to reduce emissions to meet Kyoto targets and beyond have raised issues of competitiveness in countries that are implementing these policies,as well as fear of leakage of carbon-intensive industries to non-implementing countries. This has also led to proposals for tariff or border tax adjustments to offset any adverse impact of capping carbon dioxide emissions. This paper examines the implications of climate change policies such as carbon tax and energy efficiency standards on competitiveness across industries, as well as issues related to leakage, if any, of carbon-intensive industries to developing countries. Although competitiveness issues have been much debated in the context of carbon taxation policies, the study finds no evidence that the energy intensive industries’ competitiveness is affected by carbon taxes. In fact, the analysis suggests that exports of most energy-intensive industries increase when a carbon tax is imposed by the exporting countries, or by both importing and exporting countries. This finding gives credence to the initial assumption that recycling the taxes back to the energy-intensive industries by means of subsidies and exemptions may be overcompensating for the disadvantage to those industries. There is, however, no conclusive evidence that supports relocation (leakage) of carbon-intensive industries to developing countries due to stringent climate change policies.Climate Change Mitigation and Green House Gases,Climate Change Economics,Energy and Environment,Environment and Energy Efficiency,Transport Economics Policy&Planning

Do Local Analysts Know More? A Cross-Country Study of the Performance of Local Analysts and Foreign Analysts

This paper examines whether analysts resident in a country make more precise earnings forecasts for firms in that country than analysts who are not resident in that country. Using a sample of 32 countries, we find that there is an economically and statistically significant analyst local advantage even after controlling for firm and analyst characteristics. The importance of the local advantage is inversely related to the quality of the information provided by firms. In particular, the local advantage is high in countries where earnings are smoothed more, less information is disclosed by firms, and firm idiosyncratic information explains a smaller fraction of stock returns. The local advantage is also negatively related to market participation by foreign investors and by institutions and positively related to holdings by insiders. U.S. investors underweight a country's stocks more in their portfolios if that country has a higher analyst local advantage.

Does Corporate Social Responsibility Reduce the Costs of High Leverage? Evidence from Capital Structure and Product Market Interactions

Research on capital structure and product market interactions shows that high leverage is associated with substantial losses in market share due to unfavorable actions by customers and competitors. We examine whether corporate social responsibility (CSR) affects firms’ interactions with customers and competitors, and whether it can reduce the costs of high leverage. We find that CSR reduces losses in market share when firms are highly leveraged. By reducing adverse behavior by customers and competitors, CSR helps highly leveraged firms keep customers and guard against rivals’ predation. Our results support the stakeholder value maximization view of CSR

An Adaptive Dual-level Reinforcement Learning Approach for Optimal Trade Execution

The purpose of this research is to devise a tactic that can closely track the daily cumulative volume-weighted average price (VWAP) using reinforcement learning. Previous studies often choose a relatively short trading horizon to implement their models, making it difficult to accurately track the daily cumulative VWAP since the variations of financial data are often insignificant within the short trading horizon. In this paper, we aim to develop a strategy that can accurately track the daily cumulative VWAP while minimizing the deviation from the VWAP. We propose a method that leverages the U-shaped pattern of intraday stock trade volumes and use Proximal Policy Optimization (PPO) as the learning algorithm. Our method follows a dual-level approach: a Transformer model that captures the overall(global) distribution of daily volumes in a U-shape, and a LSTM model that handles the distribution of orders within smaller(local) time intervals. The results from our experiments suggest that this dual-level architecture improves the accuracy of approximating the cumulative VWAP, when compared to previous reinforcement learning-based models.Comment: Submitted to Expert Systems with Applications (Under 2nd review