http://hdl.handle.net/10016/14 2013-05-24T08:15:47Z http://hdl.handle.net/10016/16996 Title: Multiperiod portfolio selection with transaction and market-impact costs Author(s): Miguel, Víctor de; Mei, Xiaoling; Nogales, Francisco J. Abstract: We carry out an analytical investigation on the optimal portfolio policy for a multiperiod mean-variance investor facing multiple risky assets. We consider the case with proportional, market impact, and quadratic transaction costs. For proportional transaction costs, we find that a buy-and-hold policy is optimal: if the starting portfolio is outside a parallelogram-shaped no-trade region, then trade to the boundary of the no-trade region at the first period, and hold this portfolio thereafter. For market impact costs, we show that the optimal portfolio policy at each period is to trade to the boundary of a state-dependent movement region. Moreover, we find that the movement region shrinks along the investment horizon, and as a result the investor trades throughout the entire investment horizon. Finally, we show numerically that the utility loss associated with ignoring transaction costs or investing myopically may be large 2013-04-30T22:00:00Z http://hdl.handle.net/10016/16969 Title: Forecasting disaggregates by sectors and regions : the case of inflation in the euro area and Spain Author(s): Pino, Gabriel; Tena, Juan de Dios; Espasa, Antoni [espasa] Abstract: We study the performance of different modelling strategies for 969 and 600 monthly price indexes disaggregated by sectors and geographical areas in Spain, regions, and in the EA12, countries, in order to obtain a detailed picture of inflation and relative sectoral prices through geographical areas for each economy, using the forecasts from those models. The study also provides a description of the spatial cointegration restrictions which could be useful for understanding price setting within an economy. We use spatial bi-dimensional vector equilibrium correction models, where the price indexes for each sector are allowed to be cointegrated with prices in neighbouring areas using different definitions of neighbourhood. We find that geographical disaggregation forecasts are very reliable on a regional level in Spain as they improve the forecasting accuracy of headline inflation relative to alternative methods. Geographical disaggregation forecasts are also reliable for the EA12 but only because derived headline inflation forecasting is not significantly worse than alternative forecasts. These results show that regional analysis within countries is appropriate in the euro area. These highly disaggregated forecasts can be used for competitive and other type of macro and regional analysis 2013-04-30T22:00:00Z http://hdl.handle.net/10016/16967 Title: A Bayesian non-parametric approach to asymmetric dynamic conditional correlation model with application to portfolio selection Author(s): Virbickaite, Audrone; Ausín, Concepción; Galeano, Pedro Abstract: We use an asymmetric dynamic conditional correlation (ADCC) GJR-GARCH model to estimate the time-varying volatilities of financial returns. The ADCC-GJR-GARCH model takes into consideration the asymmetries in individual assets volatilities, as well as in the correlations. The errors are modeled using a flexible location-scale mixture of infinite Gaussian distributions and the inference and estimation is carried out by relying on Bayesian non-parametrics. Finally, we carry out a simulation study to illustrate the flexibility of the new method and present a financial application using Apple and NASDAQ Industrial index data to solve a portfolio allocation problem 2013-04-30T22:00:00Z http://hdl.handle.net/10016/16966 Title: One for all : nesting asymmetric stochastic volatility models Author(s): Mao, Xiuping; Ruiz, Esther [ortega]; Veiga, Helena Abstract: This paper proposes a new stochastic volatility model to represent the dynamic evolution of conditionally heteroscedastic series with leverage effect. Although there are already several models proposed in the literature with the same purpose, our main justification for a further new model is that it nests some of the most popular stochastic volatility specifications usually implemented to real time series of financial returns. We derive closed-form expressions of its statistical properties and, consequently, of those of the nested specifications. Some of these properties were previously unknown in the literature although the restricted models are often fitted by empirical researchers. By comparing the properties of the restricted models, we are able to establish the advantages and limitations of each of them. Finally, we analyze the performance of a MCMC estimator of the parameters and volatilities of the new proposed model and show that it has appropriate finite sample properties. Furthermore, estimating the new model using the MCMC estimator, one can correctly identify the restricted specifications. All the results are illustrated by estimating the parameters and volatilities of simulated time series and of a series of daily S&P500 returns 2013-04-30T22:00:00Z