Forecasting recovery rates on non-performing loans with machine learning

We compare the performance of a wide set of regression techniques and machine-learning algorithms for predicting recovery rates on non-performing loans, using a private database from a European debt collection agency. We find that rule-based algorithms such as Cubist, boosted trees, and random forests perform significantly better than other approaches. In addition to loan contract specificities, predictors that refer to the bank recovery process — prior to the portfolio’s sale to a debt collector — are also shown to enhance forecasting performance. These variables, derived from the time series of contacts to defaulted clients and client reimbursements to the bank, help all algorithms better identify debtors with different repayment ability and/or commitment, and in general those with different recovery potential.     

Are stock markets really so inefficient? The case of the “Halloween Indicator”

The old and simple investment strategy “Sell in May and Go Away” (also referred to as the “Halloween effect”) enjoys an unbroken popularity. Recent studies suggest that the Halloween effect even strengthened rather than weakened since its first publication by Bouman and Jacobsen (2002). We implement regression models as well as Hansen’s (2005) “Superior Predictive Ability” test to analyze whether stock markets are really so inefficient. In line with the predictions of market efficiency, our results reject the hypothesis that a trading strategy based on the Halloween effect significantly outperforms.     

New cross-proposal entrepreneurship and innovation in educational programs in third level (tertiary) education

Capitalism has promoted and requires the growing knowledge of entrepreneurs, creative people who have the ability to solve problems in the form of innovation. The types of enterprises they create can be social, public and private. By creating an enterprising company new products and new production methods can be introduced, new markets are open, new sources of raw materials and inputs are developed and new market structures in an industry are created. Entrepreneurship can be taught, the question is how to do it. Teaching entrepreneurship should go beyond the business plan. It proposes a form that overcomes the mistakes found by the author in two research studies in 2008 and 2014 in the programs of management in Bogotá.     

Service quality dimensions and superior customer perceived value in retail banks: An empirical study on Mexican consumers

This study concerns the service quality topic in the retail bank sector. A sample of 209 retail bank clients was taken, measuring the performance of service quality attributes of their principle retail bank. Behavioral performance variables such as satisfaction, loyalty and customer perceived value were also measured. In a factor analyses the attributes were separated into three factors. These three independent factors explain a considerable amount of variability of a satisfaction–loyalty factor. On the other hand, they could not explain the superior perceived value; and no differences between the service quality performances of the bank brands were found. In conclusion, regardless of the degree of satisfaction and loyalty, the customer is not willing to pay more for banking services at his regular bank than he would at other brands. This implies that superior perceived value is not being achieved via service quality, which suggests a lack of differentiation between brands in this sector.     

Forecasting volatility: A reality check based on option pricing, utility function, value-at-risk, and predictive likelihood

We analyze the predictive performance of various volatility models for stock returns. To compare their performance, we choose loss functions for which volatility estimation is of paramount importance. We deal with two economic loss functions (an option pricing function and an utility function) and two statistical loss functions (a goodness-of-fit measure for a value-at-risk (VaR) calculation and a predictive likelihood function). We implement the tests for superior predictive ability of White [Econometrica 68 (5) (2000) 1097] and Hansen [Hansen, P. R. (2001). An unbiased and powerful test for superior predictive ability. Brown University]. We find that, for option pricing, simple models like the Riskmetrics exponentially weighted moving average (EWMA) or a simple moving average, which do not require estimation, perform as well as other more sophisticated specifications. For a utility-based loss function, an asymmetric quadratic GARCH seems to dominate, and this result is robust to different degrees of risk aversion. For a VaR-based loss function, a stochastic volatility model is preferred. Interestingly, the Riskmetrics EWMA model, proposed to calculate VaR, seems to be the worst performer. For the predictive likelihood-based loss function, modeling the conditional standard deviation instead of the variance seems to be a dominant modeling strategy.     

Dispersion of influence between Marketing and Sales: Its effects on superior customer value and market performance

In this study the authors investigate how dispersion of influence between Marketing and Sales (DIMS) affects the creation of superior customer value and the firm's market performance. Hypotheses are tested on a sample of 326 strategic business units using structural equation modelling analysis. Three main results emerge which contribute to the understanding of the consequences of DIMS within companies. First, DIMS increases interaction and collaboration between Marketing and Sales, without blurring their respective goals, roles and responsibilities. Second, DIMS contributes to the diffusion of a customer oriented-culture across the organization. Third, the findings of this study clarify how and why DIMS affects organizational performance by showing simultaneously that superior customer value mediates the effects of DIMS on market performance, and that Marketing–Sales interface and customer-oriented culture mediate the effects of DIMS on superior customer value. The authors discuss the study's theoretical contributions and offer directions for future research. Overall, this study provides a new and broader perspective to managers responsible for the allocation of decision making influence between Marketing and Sales over a range of market-related issues.     

Los efectos de largo plazo de la asimetría y persistencia en la predicción de la volatilidad: evidencia para mercados accionarios de América Latina

This article proposes an extension to the CGARCH model in order to capture the characteristics of short-run and long-run asymmetry and persistence, and examine their effects in modeling and forecasting the conditional volatility of the stock markets from the region of Latin America during the period from 2 January 1992 to 31 December 2014. In the sample analysis, the estimation results of the CGARCH-class model family reveal the presence of short-run and long-run significant asymmetric effects and long-run persistency in the structure of stock price return volatility. The empirical results also show that the use of symmetric and asymmetric loss functions and the statistical test of Hansen (2005) are sound alternatives for evaluating the predictive ability of the asymmetric CGARCH models. In addition, the inclusion of long-run asymmetry and long-run persistency in the variance equation improves significantly the out of sample volatility forecasts for emerging stock markets of Argentina and Mexico.     

Long-term effects of the asymmetry and persistence of the prediction of volatility: Evidence for the equity markets of Latin America

This article proposes an extension to the CGARCH model in order to capture the characteristics of short-run and long-run asymmetry and persistence, and examine their effects in modeling and forecasting the conditional volatility of the stock markets from the region of Latin America during the period from 2 January 1992 to 31 December 2014. In the sample analysis, the estimation results of the CGARCH-class model family reveal the presence of short-run and long-run significant asymmetric effects and long-run persistency in the structure of stock price return volatility. The empirical results also show that the use of symmetric and asymmetric loss functions and the statistical test of Hansen (2005) are sound alternatives for evaluating the predictive ability of the asymmetric CGARCH models. In addition, the inclusion of long-run asymmetry and long-run persistency in the variance equation improves significantly the out of sample volatility forecasts for emerging stock markets of Argentina and Mexico.     

Economic indicators and stock market volatility in an emerging economy

By analyzing the daily realized volatility series calculated from intraday stock price observations, this study examines the direct causality between one-day-ahead aggregate stock market volatility and several economic and financial indicators in the Korean market, a leading emerging market. Using the predictive regression and superior predictive ability tests, we find that the model-free implied volatility index (VKOSPI) and stock market indicators both lead the daily market volatility. However, daily economic indicators provide no predictive information beyond that contained in historical volatility. Though in-sample causality does not guarantee a better out-of-sample forecasting performance, the VKOSPI and combinations of predictors exhibit significant predictive ability regardless of the time period. Our study verifies the information role of the VKOSPI as an indicator of daily market risk.     

开发图书馆人力资源搞好图书馆管理

图书馆要充分开发利用人力资源,就必须创造条件促进馆员的学习和提高,根据需要合理设置图书馆的工作岗位,在图书馆分配制度上实现效率与公平的统一。