Coastal wetlands can have exceptionally large carbon (C) stocks and their protection and restoration would constitute an effective mitigation strategy to climate change. Inclusion of coastal ecosystems in mitigation strategies requires quantification of carbon stocks in order to calculate emissions or sequestration through time. In this study, we quantified the ecosystem C stocks of coastal wet...

Using a unique sample of matching stocks in China, this paper investigates the comovement between different stocks and its driving factors. Major findings include: (1) There exists a high positive correlation between returns on two matching stocks with similar ticker symbols; (2) By analyzing changes in correlation that took place after stocks changed their ticker symbols, we find that changes ...

Arti cial Neural Networks can be used to predict future returns of stocks in order to take nancial decisions Should one build a separate network for each stock or share the same network for all the stocks In this paper we also explore other alternatives in which some layers are shared and others are not shared When the prediction of future returns for di erent stocks are viewed as di erent task...

In this paper we propose a generalised autoregressive conditional heteroskedasticity (GARCH) model-based test for a unit root. The model allows for two endogenous structural breaks. We test for unit roots in 156 US stocks listed on the NYSE over the period 1980 to 2007. We find that the unit root null hypothesis is rejected in 40% of the stocks, and only in four out of the nine sectors the null...

This paper tests whether information advantages help explain why some individual investors concentrate their stock portfolios in a few stocks. Slock investments made by households that choose lo concentrate their brokerage accounts in a few stocks outperform those made by households with more diversified accounts (especially among those with large portfolios). Excess returns of concentrated rel...

In this study, we utilize the genetic algorithm (GA) to select high quality stocks with investment value. Given the fundamental financial and price information of stocks trading, we attempt to use GA to identify stocks that are likely to outperform the market by having excess returns. To evaluate the efficiency of the GA for stock selection, the return of equally weighted portfolio formed by th...

the stock selection problem is one of the major issues in the investment industry, which is mainlysolved by analyzing financial ratios. however, considering the complexity and imprecise patterns ofthe stock market, obvious and easy-to-understand investment rules, based on fundamental analysis,are difficult to obtain. fundamental and technical analyses are two common methods for predictingthe fu...

in this paper, a model has been provided for selecting right portfolio in stock exchange. the ranking of financial industries and companies has been applied for the selection of the right stock in this model. these rankings have been done through promethee decision- making method. technical analysis aims to determine the right time to buy and sell the superior stocks. a survey study is also don...

This research was conducted to determine the influence of oil price, stocks and exchange rates in Indonesia. The data used this is secondary form time series stretching from November 2014 2022. Quantitative method, which VAR (Vector Autoregressive) test analyze hypotheses with measurable obtain parameters variables’ influence. study’s results found that prices significantly influenced Indonesia...