The ability of some neural nets to predict the direction of the Mexican economy —represented by its LEI— when taking as inputs the simultaneous versions (smooth- ing and predictive) of a Gaussian Process fed with a Stock Index and a Bonds Index representing the Mexican market, is favorably...

The nonlinear modelization has experimented a great resurgence of the hand of Chaos Theory, which shown the possibility of obtaining complex behaviors produced endogenously by the dynamics of the model, without the necessity to include exogenous random shocks. On the other hand, the importance...

This paper compares two different strategies for managing interest rate exposure. One involves maintaining a borrowing portfolio using short and long term debt lines in order to maintain an average borrowing cost. The second involves using interest rate caps to manage exposure to interest rate...

The concept of the gamma of a financed return as the highest level of stress that a return distribution can withstand is introduced. Stress is measured by positive expectation under a concave distortion of the return distribution accessed. Four distortions introduced in Cherny and Madan (2008)...

Diversifying into commodity futures indices to improve risk-return trade-offs had seemed an inviting prospect a couple of decades ago, due to the increasing correlations between equities themselves and the stable low or negative correlations they exhibited with commodities. But there is a view...

Contrary to the classic framework of passive strategies, if investors exploit return predictability through active strategies then there is a tension between the mean-variance frontiers that drive empirical work and the mean-variance preferences that are used in finance theory. We show that...

We compare the Sharpe ratios of investment funds which combine one riskless and one risky asset following: i) timing strategies which forecast excess returns using simple regressions; ii) a strategy which uses multiple regression instead; and iii) a passive allocation which combines the funds in i)...

El Aprendizaje Automático es una rama de la Inteligencia Artificial que tiene por objetivo desarrollar técnicas mediante las cuales las computadoras puedan aprender y ayudar al hombre en la solución de problemas complejos. Los algoritmos de aprendizaje pueden clasificarse de acuerdo a la...

En el trabajo, se propone el uso de las redes neuronales artificiales para el pronóstico de consumo de energía eléctrica. Se estudiaron los principales factores influyentes en el consumo de energía eléctrica en el sector público del país. Se determinan las principales variables...

In a remarkably short time, economic globalisation has changed the world’s economic order, bringing new challenges and opportunities to SMEs. These processes pushed the need to measure innovation capability, which has become a crucial issue for today’s economic and political decision makers....