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In this article the authors will focus on the state of the art on information filtering and recommender systems based on trust. Then the authors will represent a variety of filtering and recommendation techniques studied in different literature, like basic content filtering, collaborative filtering and hybrid filtering. The authors will also examine different trust-based recommendation algorithms. It will ends with a summary of the different existing approaches and it develops the link between trust, sustainability and recommender systems.

Methodology of this study will begin with a general introduction to the different approaches of recommendation systems; then define trust and its relationship with recommender systems. At the end the authors will present their approach to “trust-based recommendation systems”.

The purpose of this study is to understand how groups of users could improve trust in a recommendation system. The authors will examine how to evaluate the performance of recommender systems to ensure their ability to meet the needs that led to its creation and to make the system sustainable with respect to the information. The authors know very well that selecting a measure must depend on the type of data to be processed and user interests. Since the recommendation domain is derived from information search paradigms, it is obvious to use the evaluation measures of information systems.

The authors presented a list of recommendations systems. They examined and compared several recommendation approaches. The authors then analyzed the dominance of collaborative filtering in the field and the emergence of Recommender Systems in social web. Then the authors presented and analyzed different trust algorithms. Finally, their proposal was to measure the impact of trust in recommendation systems.

The latest financial crisis marks a milestone in the development of financial markets. It was a period when it was possible to observe a booming development in the stock markets.

Faced with such a phenomenon, theorists have agreed on the need to resume the debate on the validity of the predictability of stock market returns, which is considered to be the cornerstone of all financial theories. The purpose of this article is to examine the predictability of the bearish stock market using a number of variables widely used in forecasting stock returns. In particular, we focus on variables related to imperfect credit markets.

We revisit the predictability of the bearish market using variables that measure the External Funding Premium (EFP), such as the Default Yield Spread.As the EFP is the key indicator of the extent of credit market imperfections, it should therefore be linked to stock market dynamics and provide useful predictive content.

The purpose of this paper is to analyze the impact of public and private information of Tunisian firms on stock liquidity.

The paper uses a sample of 41 Tunisian firms listed in Tunis Stock Exchange for the year 2007. Public information disclosed in annual reports and in web sites is measured by two self‐constructed disclosure indexes. To assess private information the authors use imbalance order flows. The stock liquidity proxy used in the study is Liu's multidimensional measure. Ordinary least squares (OLS) regression is applied to model the relationship between firm's information environment and stock liquidity.

First, the results provide evidence that public and private information are independent. Second, Tunisian investors do not trust the information disclosed in both annual reports and web sites, consequently it has no effect on stock liquidity, in contrast with private information. This result implies that Tunisian investors are overconfident and rely only on their private information.

The paper's findings indicate that Tunisian regulation efforts to enhance corporate transparency are not sufficient. Hence, Tunisian firms need more incentives to disclose more information to investors.

This paper, to the authors’ best knowledge, is the first to investigate the effect of both private and public information on stock liquidity. Moreover, the authors were not limited to annual reports as the only source of public information, as were prior papers, because public information was assessed in both annual reports and corporate web sites.