Day-of-the-Week-Effect and Month-of-the-Year-Effect on Carbon Emissions Contract Trading

Abstract

Objective: This study aims to examine whether there is a potential Day-of-the-Week-Effect and Month-of-the-Year-Effect on carbon emissions trading. Research Design & Methods: This research uses secondary data obtained through the Investing.com website. The carbon market data used is daily closing data, then the daily effect test is carried out, and monthly closing data to determine the monthly effect. Generalized Autoregressive Conditional Heteroskedasticity (GARCH) (2,1) and (3,1) method used to analyse the data. Findings: The correlogram and GARCH (2,1) and GARCH (3,1) test results show that the carbon market does not move randomly, but there are Day-of-the-Week-Effect and Month-of-the-Year-Effect phenomena. From this study, it was also found that on Wednesday in April, there was a significant increase in returns. So, it can also be concluded that the carbon market is not efficient. Implications and Recommendations: There are opportunities that can be taken from carbon trading which turns out to have a Day-of-the-Week-Effect and Month-of-the-Year-Effect so that investors who want to join carbon trading can more easily learn about it to get maximum profit in the carbon market. Contribution & Value Added: It is hoped that the results of this study can prove whether or not there is an influence on seasonal patterns so that it can be useful for speculators and business people related to carbon trading to design the right strategy in the carbon emissions market.

Keywords

• carbon emission
• carbon market
• day-of-the-week-effect
• month-of-the-year-effect
• market anomaly