The purpose of this paper is to explore the performance of ridge regression and the random forest model improved by genetic algorithm in predicting the Boston house price data set and conduct a comparative analysis. To achieve it, the data is divided into training set and test set according to the ratio of 70-30. The RidgeCV library is used to select the best regularization parameter for the Ridge regression model, and for the random forest model, the genetic algorithm is used to optimize the model's hyperparameters. The result shows that compared with ridge regression, the random forest model improved by genetic algorithm can perform better in the regression problem of Boston house prices.

China established pilot carbon markets in 2013. In 2020, it set targets for carbon peaking in 2030 and carbon neutrality by 2050. China’s national carbon market officially commenced operations in 2021. Based on the national market and seven pilot markets, this study established the factors influencing carbon trading prices by examining market participants, macroeconomics, energy prices, carbon prices in other markets, etc. Asymmetrical development among the seven pilot cities, for which the study employed a mixed-effects model, was the primary factor impacting carbon prices. The carbon prices in the pilot cities cannot be extrapolated to the entire country. In the national carbon market, where the study employed a multiple regression lag model, the SSE index was positively correlated with carbon prices, whereas the Dow Jones index had no significant effect on carbon prices in terms of macroeconomics. Coal and natural gas prices were negatively correlated with carbon prices, whereas oil prices were positively correlated with energy prices. The EU market prices have a positive correlation with prices in other markets. The significance of this study is that it covers the largest national Emissions Trading System (ETS) in the world and allows for comparing the characteristics of the Chinese market with those of other ETS markets. Additional studies, including more sectors, should be conducted as China’s ETS coverage increases.

Consumers’ interest in green consumption has increased rapidly in recent years with heightening concerns for environmental, social, and health risks. However, increased concerns and interest of consumers may not translate to their behavioral outcome which may be attributed to socio-economic and consumers’ internal stimuli. Furthermore, contextual differences in the marketplace may influence how consumers form their green attitudes and behavior. The purpose of this study is to assess the role of consumers’ intrinsic traits such as consumers’ personal values, their self-motivation for sustainable consumption (i.e., perceived consumer effectiveness), green skepticism, and environmental involvement in their green attitude and behavior, and to see if the country-specific contextual condition may influence consumers’ behavior. In addition, price sensitivity and environmental protection emotions are considered moderating constructs to explain the gap between green attitude and green behavior. Findings from this study provide insights into understanding Chinese and Singaporean consumers’ green behavior which is driven by their intrinsic traits and by extrinsic conditions. This understanding can help companies to develop effective green marketing communication strategies and to enhance consumer engagement in sustainable activities and consumption.

The study examines the factors shaping inflation in 2022–2023 and explores why inflation in the Hungarian economy has increased more sharply than in neighboring countries with similar structures. The research hypothesis suggests that the inflationary surge, which is notable both globally and within the European Union, is not solely due to market economy mechanisms, but also to specific circumstances in Hungary, including the state’s radical interventions aimed at curbing inflation. The study seeks to highlight these effects and provide recommendations for economic policymakers to develop a more resilient inflation policy. Additionally, it focuses on analyzing inflation in the agricultural sector. The results indicate that, alongside global inflationary pressures, several country-specific factors have driven up the inflation rate in Hungary. Energy prices have risen sharply, and some supply chains from the East have been disrupted. The country under study is less productive, and the impact of the energy price shock on the energy-intensive food industry is higher than in surrounding countries. Consequently, the exchange rate volatility in 2022–2023, combined with short- and medium-term factors, has had a significant impact on food inflation, causing substantial deviations from long-term equilibrium. The research concludes that, in addition to increasing food self-sufficiency, special attention should be given to the domestic development of the agricultural supply chain.

Climate change is forcing countries to take strategic measures to reduce the negative impact on future generations. In this context, sustainable finance has played a key role in sustainable development since the establishment of environmental, social and governance principles. The underlying market has developed rapidly since its inception, with green bonds being the most prominent instrument. This article aims to study the impact of green bond issues on the abnormal stock returns of stocks listed on the main Euronext indices. The sample includes 58 issues carried out between 2014 and 2022 by 21 different firms listed on the AEX (Netherlands), BEL 20 (Belgium), CAC 40 (France), ISEQ 20 (Ireland), OBX (Norway) and PSI (Portugal) indices. The methodology follows the procedures of the event study using the market model. The results show significant positive stock price reaction on the issue date. After the abnormal losses just before the issues, suggesting the reserves of this consolidating market, abnormal gains persisted for over a week, providing evidence against the weak efficiency Euronext’s financial markets. The findings are useful for policy makers and entrepreneurs to promote innovative initiatives that encourage the financing and development of environmentally sustainable infrastructures.

The present study attempted to assess the impact of fundamental ratios on the share prices of selected telecommunication companies in India. India has dramatically expanded over the past ten years to become the second-biggest telecoms market worldwide, with 1.17 billion users. The Indian telecom industry has proliferated thanks in part to the government of India’s liberal and reformist policies and strong customer demand. It has become a lucrative investment sector for investors due to its recent and prospective growth. Data on 13 telecom firms indexed in the S&P BSE telecommunication index from 2013 to 2022 were taken from companies’ annual reports, the BSE website (Bombay Stock Exchange), and other secondary sources. Six firm-specific fundamental factors viz. Debt to Equity ratio (D/E), Current ratio (CR), Total Assets Turnover ratio (ATR), Earnings per share (EPS), Price to earnings ratio (P/E), Return on equity (ROE), and three country-specific fundamental factors viz. Gross Domestic Product, Inflation rate, and S&P BSE Sensex return were considered. Fixed effect panel regression through Generalized Least Square (GLS) model was performed to find inferences. Debt Equity ratio and Inflation rate were found to impact share price negatively. Conversely, the Total Assets Turnover ratio (ATR), Earnings per share (EPS), Price to Earnings ratio (P/E), and Return on Equity (ROE) positively impacted selected companies’ share prices. The study results will benefit individual & institutional investors in formulating their investment and portfolio diversification strategies for gaining a high effective rate of return on their investments.