A comparative study of alternative approaches for common factors identification

Preliminary versionFor multivariate non-stationary time series modeling is essential to know the number of common factors that define the behavior of the series. The traditional way to approach this problem is to study the cointegration relations among data through tests of the trace or maximum eigenvalue, obtaining the number of stationary long-run relations. Alternatively this problem can be analyzed using dynamic factor models as in Peña and Poncela (2006), estimating in this case the number of all independent common factors, stationary or not, that describe the behavior of data. In this context, we analyze empirically the power of such alternative approaches by applying them to series simulated using known factorial models. The results show that when there are stationary common factors, when the number of observations is reduced and/or when the series have involved more than one cointegration relation, the common factor test is more powerful than the usual cointegration tests. These results together with the greater flexibility of dynamic factor models for identify the load matrix of the DGP make them more suitable for use in multivariate analysis

The US actuarial balance model for the pay-as-you-go system and its application to Spain

The aim of this paper is to formulate an approximation of the US actuarial balance model and apply it to the Spanish public retirement pension system under various scenarios in order to determine a consistent indicator of the system's financial state comparable to those used by the most advanced social security systems. This will enable us to answer the question as to whether there is any justification for reforming the pension system in Spain. This type of actuarial balance uses projections to show future challenges to the financial side of the pension system deriving basically from ageing, the projected increase in longevity and fluctuations in economic activity. If one is compiled periodically it can provide various indicators to help depoliticize the management of the pay-as-you-go system by bringing the planning horizons of politicians and the system itself closer together

Genetic algorithm estimation of interest rate term

The term structure of interest rates is an instrument that gives us the necessary information for valuing deterministic financial cash flows, measuring the economic market expectations and testing the effectiveness of monetary policy decisions. However, it is not directly observable and needs to be measured by smoothing data obtained from asset prices through statistical techniques. Adjusting parsimonious functional forms - as proposed by Nelson and Siegel (1987) and Svensson (1994) - is the most popular technique. This method is based on bond yields to maturity and the high degree of non linearity of the functions to be optimised make it very sensitive to the initial values employed. In this context, this paper proposes the use of genetic algorithms to find these values and reduce the risk of false convergence, showing that stable time series parameters are obtained without the need to impose any kind of restriction

Genetic algorithm estimation of interest rate term structure

The term structure of interest rates is an instrument that gives us the necessary information for valuing deterministic financial cash flows, measuring the economic market expectations and testing the effectiveness of monetary policy decisions. However, it is not directly observable and needs to be measured by smoothing data obtained from asset prices through statistical techniques. Adjusting parsimonious functional forms ¿ as proposed by Nelson and Siegel (1987) and Svensson (1994) ¿ is the most popular technique. This method is based on bond yields to maturity and the high degree of non-linearity of the functions to be optimised make it very sensitive to the initial values employed. In this context, this paper proposes the use of genetic algorithms to find these values and reduce the risk of false convergence, showing that stable time series parameters are obtained without the need to impose any kind of restrictions

La hipótesis de las expectativas en el largo plazo: evidencia en el mercado español de deuda pública

En el presente trabajo se contrasta la Hipótesis de las Expectativas en los plazos más largos de la estructura temporal de tipos de interés. Para ello se aplica la metodología propuesta en Campbell y Shiller (1987, 1991), basada en la obtención de predicciones de los futuros cambios en los tipos de interés mediante un vector autorregresivo, a estimaciones no paramétricas de la curva de tipos cupón-cero. Los resultados muestran evidencia a favor de la Hipótesis de las Expectativas y que el diferencial de tipos es un buen estimador de los cambios futuros de los tipos de interés también en el largo plazo. (Copyright: Fundación SEPI)Estructura temporal de tipos de interés, teoría de las expectativas, mercado español de Deuda Pública, modelos VAR.

Modelización de la volatilidad del tipo de interés a corto plazo

Este trabajo se centra en la modelización de la volatilidad de los cambios del tipo de interés a corto plazo. Para ello se estiman y comparan distintos modelos de heteroscedasticidad condicional agrupados en tres bloques: (1) los modelos Nivel; (2) los modelos GARCH; y (3) los modelos Mixtos que combinan los efectos recogidos por los anteriores. El análisis realizado revela la superioridad de los modelos Mixtos, confirmando las conclusiones de Brenner et al. (1996). Asimismo, se detecta cierta asimetría en la respuesta de la volatilidad condicional del tipo de interés a corto plazo frente a sus innovaciones