2 resultados para Simple linear regression
em Repositório Institucional da Universidade Federal do Rio Grande do Norte
Resumo:
The objective is to analyze the relationship between risk and number of stocks of a portfolio for an individual investor when stocks are chosen by "naive strategy". For this, we carried out an experiment in which individuals select actions to reproduce this relationship. 126 participants were informed that the risk of first choice would be an asset average of all standard deviations of the portfolios consist of a single asset, and the same procedure should be used for portfolios composed of two, three and so on, up to 30 actions . They selected the assets they want in their portfolios without the support of a financial analysis. For comparison we also tested a hypothetical simulation of 126 investors who selected shares the same universe, through a random number generator. Thus, each real participant is compensated for random hypothetical investor facing the same opportunity. Patterns were observed in the portfolios of individual participants, characterizing the curves for the components of the samples. Because these groupings are somewhat arbitrary, it was used a more objective measure of behavior: a simple linear regression for each participant, in order to predict the variance of the portfolio depending on the number of assets. In addition, we conducted a pooled regression on all observations by analyzing cross-section. The result of pattern occurs on average but not for most individuals, many of which effectively "de-diversify" when adding seemingly random bonds. Furthermore, the results are slightly worse using a random number generator. This finding challenges the belief that only a small number of titles is necessary for diversification and shows that there is only applicable to a large sample. The implications are important since many individual investors holding few stocks in their portfolios
Resumo:
This research aims to understand the factors that influence intention to online purchase of consumers, and to identify between these factors those that influence the users and the nonusers of electronic commerce. Thus, it is an applied, exploratory and descriptive research, developed in a quantitative model. Data collection was done through a questionnaire administered to a sample of 194 graduate students from the Centre for Applied Social Sciences of UFRN and data analysis was performed using descriptive statistics, confirmatory factorial analysis and simple and multiple linear regression analysis. The results of descriptive statistics revealed that respondents in general and users of electronic commerce have positive perceptions of ease of use, usefulness and social influence about buying online, and intend to make purchases on Internet over the next six months. As for the non-users of electronic commerce, they do not trust the Internet to transact business, have negative perceptions of risk and social influence over purchasing online, and does not intend to make purchases on Internet over the next six months. Through confirmatory factorial analysis six factors were set up: behavioral intention, perceived ease of use, perceived usefulness, perceived risk, trust and social influence. Through multiple regression analysis, was observed that all these factors influence online purchase intentions of respondents in general, that only the social influence does not influence the intention to continue buying on the Internet from users of electronic commerce, and that only trust and social influence affect the intention to purchase online from non-users of electronic commerce. Through simple regression analysis, was found that trust influences perceptions of ease of use, usefulness and risk of respondents in general and users of electronic commerce, and that trust does not influence the perceptions of risk of non-users of electronic commerce. Finally, it was also found that the perceived ease of use influences perceived usefulness of the three groups. Given this scenario, it was concluded that it is extremely important that organizations that work with online sales know the factors that influence consumers purchasing intentions in order to gain space in their market