19 resultados para Brazilian start ups
Resumo:
No presente artigo apresentamos processos de Levy usados na literatura para modelar os retornos dos ativos financeiros, estes processos sao gerados pelas distribuições Pareto-Estaveis e Hiperbolicas. Estudamos algumas propriedades destas distribui<;oes, em particular a propriedade da invariancia da escala temporal. Por ultimo apresentamos evidencias empiricas da aplicabilidade destes processos para modelar retornos de ativos Brasileiros, para isto usamos 0 Ibovespa, o recibo da Telebras e Petrobras, na amostra usamos dados dos periodos de 1 de janeiro de 1995 a 31 de dezembro de 1998 (Gl) e de 12 de janeiro de 1996 a 31 de dezembro de 1997(G2).
Resumo:
Generating personalized movie recommendations to users is a problem that most commonly relies on user-movie ratings. These ratings are generally used either to understand the user preferences or to recommend movies that users with similar rating patterns have rated highly. However, movie recommenders are often subject to the Cold-Start problem: new movies have not been rated by anyone, so, they will not be recommended to anyone; likewise, the preferences of new users who have not rated any movie cannot be learned. In parallel, Social-Media platforms, such as Twitter, collect great amounts of user feedback on movies, as these are very popular nowadays. This thesis proposes to explore feedback shared on Twitter to predict the popularity of new movies and show how it can be used to tackle the Cold-Start problem. It also proposes, at a finer grain, to explore the reputation of directors and actors on IMDb to tackle the Cold-Start problem. To assess these aspects, a Reputation-enhanced Recommendation Algorithm is implemented and evaluated on a crawled IMDb dataset with previous user ratings of old movies,together with Twitter data crawled from January 2014 to March 2014, to recommend 60 movies affected by the Cold-Start problem. Twitter revealed to be a strong reputation predictor, and the Reputation-enhanced Recommendation Algorithm improved over several baseline methods. Additionally, the algorithm also proved to be useful when recommending movies in an extreme Cold-Start scenario, where both new movies and users are affected by the Cold-Start problem.
Resumo:
Double Degree Masters in Economics Program from Insper and NOVA School of Business and Economics
Resumo:
This work project studies the effect of variations in the proportion of female candidates on the quality of politicians. This effect was divided between nominated and elected body. Cross-sectional data was used for two elections, and an OLS as an IV approach. Results show that the existence of female candidates on parties’ list increases the quality of the nominated body. Moreover, contrary to what many advocate, increasing the presence of female candidates either increases or has no effect on the quality of the elected body. Results that were confirmed for the overall data and controlling for region factors only.