BUSCADOR RECOLECTA

This paper studies P2P lending and the factors explaining loan default. This is an important issue because in P2P lending individual investors bear the credit risk, instead of financial institutions, which are experts in dealing with this risk. P2P lenders suffer a severe problem of information asymmetry, because they are at a disadvantage facing the borrower. For this reason, P2P lending sites provide potential lenders with information about borrowers and their loan purpose. They also assign a grade to each loan. The empirical study is based on loans'' data collected from Lending Club (N = 24, 449) from 2008 to 2014 that are first analyzed by using univariate means tests and survival analysis. Factors explaining default are loan purpose, annual income, current housing situation, credit history and indebtedness. Secondly, a logistic regression model is developed to predict defaults. The grade assigned by the P2P lending site is the most predictive factor of default, but the accuracy of the model is improved by adding other information, especially the borrower''s debt level.

Ethical banking, microfinance institutions or certain credit cooperatives, among others, grant socially responsible loans. This paper presents a credit score system for them. The model evaluates social and financial aspects of the borrower. The financial aspects are evaluated under the conventional banking framework, by analysing accounting statements and financial projections. The social aspects try to quantify the loan impact on the achievement of Millennium Development Goals such as employment, education, environment, health or community impact. The social credit score model should incorporate the lender’s know-how and should also be coherent with its mission. This is done using Multi-Criteria Decision Making (MCDM). The paper illustrates a real case: a loan application by a social entrepreneur presented to a socially responsible lender. The decision support system not only produces a score, but also reveals strengths and weaknesses of the application.

This paper proposes a comprehensive explanatory model to explain both causes and consequences of over-indebtedness. It presents as causes some borrower aspects, such as propensity to indebtedness and low financial literacy. Other causes are borrower circumstances: adverse external shocks, borrower internal problems and financial institutions' pressure. The model incorporates consequences on the borrower, the lender and the society. The model has been tested with a survey filled in by experts and over-indebted individuals. Results have been analysed using multivariate techniques, including canonical correlations. There are differences in the opinions of experts and individuals: the latter blame external shocks or financial institutions' pressure, while the former find relevant factors the financial illiteracy or the tendency to imitate others. Experts and individuals agree on the consequences: poverty growth in the society and declining borrower's welfare. The paper concludes with the need to improve financial literacy, especially in the risks involved in over-indebtedness.

This study examines the performance of managers over time, as well as its persistence, taking into account both manager characteristics and market conditions. Applying parametric and non-parametric methodologies, we examine a sample of UK equity pension fund managers. Our results help to understand the importance of manager assignments in the industry and reveal the importance and benefits of management specialization. We find certain manager performance persistence, revealing that some managers are better than others and possess superior investment skills. Additionally, we find that managers achieve better results when they run a single fund or one investment-objective funds, which allows managers to focus on specific tasks. Nonetheless, manager performance varies with market conditions and highlights managers’ different skills. Specialist managers perform better in bullish markets, and generalists perform better in bearish periods.

Method: The article is based on survey data (N = 2,304) collected in Spain, which are analyzed using multiple regression, principal component analysis, and cluster analysis.
Results: Two dimensions are identified: the first is the comprehensive use of Internet and the second is the nature of this use, differentiating between a professional use and a recreational and social use of Internet. The article verifies that factors explaining the digital divide are age, education level, and income.
Conclusions: The article identifies digitally excluded segments, and the efforts and actions for digital training to eradicate the digital divide should be directed at these groups. The most serious problem is encountered in homeworkers who are mainly woman. NEETs (not in education, employment, or training) are frequent users of Internet, but they only use it for entertainment and to certain extent they are digitally excluded.

We propose a novel performance attribution model for equity fund portfolios. The model analyses investment decisions based on portfolio holdings and measures the value added from different sources of performance such as past return strategies, security selection, market timing and passive timing. The model was tested for a sample of mutual funds. Empirical results show that security selection is the main contributor to fund performance regardless of the sample period considered or the asset pricing model used. The evidence of timing ability is mixed with low significance. Nevertheless there are noticeable differences between the timing ability of the best and worst performing funds, especially in crisis periods. Analysing the relationship between mutual fund performance (and its different components) and fund characteristics, we find that top funds are significantly smaller and more concentrated than other funds. Finally, we also examine the persistence in the performance and in its components finding evidence of positive persistence in past return strategies and picking skills although this persistence is not shown in the overall performance.

This paper develops an innovative slacks-based manager efficiency index (SMEI) to evaluate the efficiency of mutual fund managers. First, the SMEI contributes to decisions by evaluating the efficiency of the manager as a whole instead of focusing on individual mutual funds. Second, the SMEI includes socio-demographic variables to extend the mere consideration of financial variables in the model. Third, the SMEI identifies locally efficient but globally inefficient managers. This local SMEI evaluates managers in reference to the ‘best practice’ competitors with similar management characteristics. Finally, this paper includes a real application of the SMEI in a sample of individual managers in the Spanish mutual fund industry. This empirical illustration further examines the persistence of the efficiency scores and the influence of the SMEI variables on the efficiency of individual managers.

Numerous articles demonstrate the usefulness of financial ratios in predicting the bankruptcy of companies, but in the case of new companies their usefulness is questionable. Many of the firms that are successful today made few profits when they were first created. On the other hand, structural inertia from the theory of organizational ecology and the “survival of the fitter” principle advocate that companies that are healthy in their early years will go ahead in greater proportion than those that start with many difficulties. Our empirical study used financial data from a sample of 6, 167 newborn Spanish startup companies, analyzing their evolution up to eight years later. We found healthier financial indicators in the first years of startup companies that survived eight years than in those that failed, supporting the organizational ecology theory. We found statistically significant differences in profitability, productivity, liquidity, leverage, and size. The models developed showed predictive capacity, but they did not reach that of the bankruptcy models made with mature companies. The analyzed period corresponded to a period of economic crisis. The study was repeated with data from another noncrisis period to enhance the validity of the results, and obtained similar results.

This study examines the influence of founding conditions and decisions on new companies' performance, analysing how both environmental context and organisational dynamics interact to determine their success. It distinguishes between two different success indicators: survival and profitable growth. An empirical study conducted using a sample of 3,722 new agri-food companies in two different periods, one of economic stability and the other of recession, showed that founding conditions had long-lasting effects on post-entry performance. The economic context acted as a moderator of the relationship between individual factors and success. Adverse environmental conditions were also a determinant of success, making surviving firms more competitive and resilient. The results reflect the survival of the fitter principle by showing that early profitability reduced the risk of failure and made firms more likely to become profitable in the medium term. Internationalisation strategies developed organisational capabilities that created an imprint for adaptability and growth.

Our findings indicate that herding behavior is affected not only by the cultural variables already discussed in the literature but also by other variables associated with organizational and environmental issues such as governance, technology, education and training, business style and conditions, and the development of equity and non-equity markets. Some of these act as catalysts, for example governance and technology. Others may have a corrective effect, such as the development of financial markets, business style, and education and training. If corrective factors are sufficiently developed, intentional herding practices could be reduced in the future.

Our findings indicate that herding behavior is affected not only by the cultural variables already discussed in the literature but also by other variables associated with organizational and environmental issues such as governance, technology, education and training, business style and conditions, and the development of equity and non-equity markets. Some of these act as catalysts, for example governance and technology. Others may have a corrective effect, such as the development of financial markets, business style, and education and training. If corrective factors are sufficiently developed, intentional herding practices could be reduced in the future., This paper has received financial support from the Spanish Ministry of Economy and Competitiveness (ECO2016-77631-R and ECO2013-45568-R), and the Government of Aragón/European Social Fund (S14/2).

The relation between informed trading and volatility is analyzed using the change in the proportion of informed transactions calculated through the probability of informed trading variable. The analysis relates to the Spanish market during 1997–2010, given that the Spanish market covers a very diverse range of listed companies. Some companies are comparable to companies listed on U.S. markets while others are smaller in size and have a lower trading volume and inferior quality of information. The methodology is based on a modification of the model proposed by Avramov, Chordia, and Goyal [2006]. The authors’ proposal incorporates the change in the proportion of informed transactions, calculated with intraday data, into the volatility model. The results are also presented using a conditional volatility model in which the change in the proportion of informed transactions is incorporated. These results attest to the influence of informed trading as a price-stabilizing factor in heavily traded and highly capitalized stocks (familiar stocks). Informed trading leads to a marked decrease in volatility for these particular stocks both in periods of calm and crisis., This article has received financial support from the Spanish Ministry of Economy and Competitiveness (ECO2012-35946-C02-01, ECO2016-77631-R AEI/FEDER, UE, and ECO2013-45568-R), and from the Government of Aragón/European Social Fund (S14/2).

Herding among analysts emerges when analysts give priority to their peers’ opinions instead of their own beliefs or information. Some circumstances may enhance or restrain this type of behaviour. We postulate that market sentiment is one of them. This article analyses the effect that investor sentiment may have on analysts’ herding behaviour in the U.K. Our results suggest that ‘easy situations’ such as analysing easy-to-value securities and releasing optimistic information at times of high market sentiment clearly reduce herding practices, whereas herding clearly increases in difficult situations when analysts have to release negative information at moments of high investor sentiment., This article has received financial support from the Spanish Ministry of Economy and Competitiveness (ECO2016-77631-R (AEI/FEDER, UE) and ECO2013-45568-R), and the Government of Aragón/European Social Fund (S14/2).