Departamento de Estadística
http://hdl.handle.net/10016/12
Fri, 24 Nov 2017 00:10:41 GMT2017-11-24T00:10:41ZOptimal portfolio with insider information on the stochastic interest rate
http://hdl.handle.net/10016/25819
Optimal portfolio with insider information on the stochastic interest rate
D'Auria, Bernardo; García Martí, Dolores; Salmeron Garrido, Jose Antonio
Universidad Carlos III de Madrid. Departamento de Estadística
We consider the optimal portfolio problem where the interest rate is stochastic and the agent has insider information on its value at a finite terminal time. The agent's objective is to optimize the terminal value of herportfolio under a logarithmic utility function. Using techniques of initial enlargement of filtration, we identify the optimal strategy and compute the value of the information. The interest rate is first assumed to be an affine diffusion, then more explicit formulas are computed for the Vasicek interest rate model where the interest rate moves according to an Ornstein-Uhlenbeck process. We show that when the interest rate process is correlated with the price process of the risky asset, the value of the information is infinite, as is usually the case for initial-enlargement-type problems. However, since the agent does not know exactly the correlation factor, this may induce an infinite loss instead of an infinite gain. Finally weakening the information own by the agent, and assuming that she only knows a lower-bound for the terminal value of the interest rate process, we show that the value of the information is finite.
Wed, 01 Nov 2017 00:00:00 GMThttp://hdl.handle.net/10016/258192017-11-01T00:00:00ZDiscovering pervasive and non-pervasive common cycles
http://hdl.handle.net/10016/25392
Discovering pervasive and non-pervasive common cycles
Carlomagno Real, Guillermo; Espasa Terrades, Antoni
Universidad Carlos III de Madrid. Departamento de Estadística
The objective of this paper is to propose a strategy to exploit short-run commonalities in the sectoral components of macroeconomic variables to obtain better models and more accurate forecasts of the aggregate and of the components. Our main contribution concerns cases in which the number of components is large, so that traditional multivariate approaches are not feasible. We show analytically and by Monte Carlo methods that subsets of components in which all the elements share a single common cycle can be discovered by pairwise methods. As the procedure does not rely on any kind of cross-sectional averaging strategy: it does not need to assume pervasiveness, it can deal with highly correlated idiosyncratic components and it does not need to assume that the size of the subsets goes to infinity. Nonetheless, the procedure works both with fixed N and T going to infinity, and with T and N both going to infinity.
Fri, 01 Sep 2017 00:00:00 GMThttp://hdl.handle.net/10016/253922017-09-01T00:00:00ZVine copula models for predicting water flow discharge at King George Island, Antarctica
http://hdl.handle.net/10016/23812
Vine copula models for predicting water flow discharge at King George Island, Antarctica
Gómez Díaz, Mario; Ausín Olivera, María Concepción; Domínguez, M. Carmen
Universidad Carlos III de Madrid. Departamento de Estadística
In order to understand the future behavior of the glaciers, their mass balance should
be
studied. The loss of water produced by melting, known as glacier discharge, is one
of the components of this mass balance. In this paper, a vine copula structure is
proposed to model the multivariate and nonlinear dependence among the glacier
discharge and other related meteorological variables such as temperature, humidity,
solar radiation and precipitation. The multivariate distribution of these variables is
divided in four cases according to the presence or not of positive discharge and/or
positive precipitation. Then, each different case is modelled with a vine copula. The
conditional probability of zero discharge for given meteorological conditions is
obtained from the proposed joint distribution. Moreover, the structure of the vine
copula allows us to derive the conditional distribution for the glacier discharge for the
given meteorological conditions. Three different prediction methods for the future
values of the discharge are used and compared.
The proposed methodology is applied to a large database collected since 2002 by the
GLACKMA association from a measurement station located in the King George Island in
the Antarctica. Seasonal effects are included by using different parameters for each
season.
We have found that the proposed vine copula model outperforms a previous work
where we only used the temperature to predict the glacier discharge using a time-
varying bivariate copula.
Sat, 01 Oct 2016 00:00:00 GMThttp://hdl.handle.net/10016/238122016-10-01T00:00:00Z22 Years of inflation assessment and forecasting experience at the bulletin of EU & US inflation and macroeconomic analysis
http://hdl.handle.net/10016/24678
22 Years of inflation assessment and forecasting experience at the bulletin of EU & US inflation and macroeconomic analysis
Espasa Terrades, Antoni; Senra, Eva
Universidad Carlos III de Madrid. Departamento de Estadística
The Bulletin of EU & US Inflation and Macroeconomic Analysis (BIAM) is a monthly publication that has been reporting real time analysis and forecasts for inflation and other macroeconomic aggregates for the Euro Area, the US and Spain since 1994. The BIAM inflation forecasting methodology stands on working with useful disaggregation schemes, using leading indicators when possible and applying outliers' correction. The paper relates this methodology to corresponding topics in the literature and discusses the design of disaggregation schemes. It concludes that those schemes would be useful if they were formulated according to economic, institutional and statistical criteria aiming to end up with a set of components with very different statistical properties for which valid single-equation models could be built. The BIAM assessment, which derives from a new observation, is based on (a) an evaluation of the forecasting errors (innovations) at the components' level. It provides information on which sectors they come from and allows, when required, for the appropriate correction in the specific models. (b) In updating the path forecast with its corresponding fan chart. Finally, we show that BIAM real time Euro Area inflation forecasts compare successfully with the consensus from the ECB Survey of Professional Forecasters, one and two years ahead.
Thu, 01 Jun 2017 00:00:00 GMThttp://hdl.handle.net/10016/246782017-06-01T00:00:00Z