489 research outputs found

    A stochastic variance factor model for large datasets and an application to S&P data

    Get PDF
    The aim of this paper is to consider multivariate stochastic volatility models for large dimensional datasets. For this purpose we use a common factor approach along the lines of Harvey, Ruiz, and Shephard (1994). More recently, Bayesian estimation methods, relying on Markov Chain Monte Carlo, have been put forward by Chib, Nardari, and Shephard (2006) to estimate relatively large multivariate stochastic volatility models. However, computational constraints can be binding when dealing with very large datasets such as, e.g., S&P 500 constituents. For instance, the Bayesian modelling approach put forward by Chib, Nardari, and Shephard (2006) is illustrated by modelling a dataset of only 20 series of stock returns. Recently, Stock and Watson (2002) have shown that principal component estimates of the common factor underlying large datasets can be used successfully in forecasting conditional means. We propose the use of principal component estimation for the volatility processes of large datasets. A Monte Carlo study and an application to the modelling of the volatilities of the S&P constituents illustrate the usefulness of our approach

    Forecasting financial crises and contagion in Asia using dynamic factor analysis

    Get PDF
    In this paper we use principal components analysis to obtain vulnerability indicators able to predict financial turmoil. Probit modelling through principal components and also stochastic simulation of a Dynamic Factor model are used to produce the corresponding probability forecasts regarding the currency crisis events affecting a number of East Asian countries during the 1997-1998 period. The principal components model improves upon a number of competing models, in terms of out-of-sample forecasting performanc

    Dynamic factor analysis of industry sector default rates and implication for portfolio credit risk modelling

    Get PDF
    In this paper we use a reduced form model for the analysis of Portfolio Credit Risk. For this purpose, we fit a Dynamic Factor model, DF, to a large dataset of default rates proxies and macrovariables for Italy. Multi step ahead density and probability forecasts are obtained by employing both the direct and indirect method of prediction together with stochastic simulation of the DF model. We, first, find that the direct method is the best performer regarding the out of sample projection of financial distressful events. In a second stage of the analysis, we find that reduced form Portfolio Credit Risk measures obtained through DF are lower than the one corresponding to the Internal Ratings Based analytic formula suggested by Basel 2. Moreover, the direct method of forecasting gives the smallest Portfolio Credit Risk measures. Finally, when using the indirect method of forecasting, the simulation results suggest that an increase in the number of dynamic factors (for a given number of principal components) increases Portfolio Credit Risk

    Modeling Envisat RA-2 waveforms in the coastal zone: case-study of calm water contamination

    Get PDF
    Radar altimeters have so far had limited use in the coastal zone, the area with most societal impact. This is due to both lack of, or insufficient accuracy in the necessary corrections, and more complicated altimeter signals. This paper examines waveform data from the Envisat RA-2 as it passes regularly over Pianosa (a 10 km2 island in the NW Mediterranean). Forty-six repeat passes were analysed, with most showing a reduction in signal upon passing over the island, with weak early returns corresponding to the reflections from land. Intriguingly one third of cases showed an anomalously bright hyperbolic feature. This feature may be due to extremely calm waters in the Golfo della Botte (northern side of the island), but the cause of its intermittency is not clear. The modelling of waveforms in such a complex land/sea environment demonstrates the potential for sea surface height retrievals much closer to the coast than is achieved by routine processing. The long-term development of altimetric records in the coastal zone will not only improve the calibration of altimetric data with coastal tide gauges, but also greatly enhance the study of storm surges and other coastal phenomena

    Modeling Envisat RA-2 waveforms in the coastal zone: Case study of calm water contamination

    Full text link
    This letter examines waveform data from the Envisat RA-2 as it passes regularly over Pianosa (a 10-km 2 island in the northwestern Mediterranean). Forty-six repeat passes were analyzed, with most showing a reduction in signal upon passing over the island, with weak early returns corresponding to the reflections from land. Intriguingly, one third of cases showed an anomalously bright hyperbolic feature. This feature may be due to extremely calm waters in the Golfo della Botte (northern side of the island), but the cause of its intermittency is not clear. The modeling of waveforms in such a complex land/sea environment demonstrates the potential for sea surface height retrievals much closer to the coast than is achieved by routine processing. The long-term development of altimetric records in the coastal zone will not only improve the calibration of altimetric data with coastal tide gauges but also greatly enhance the study of storm surges and other coastal phenomena

    Whole mitochondrial DNA sequencing in Alpine populations and the genetic history of the Neolithic Tyrolean Iceman

    Get PDF
    The Tyrolean Iceman is an extraordinarily well-preserved natural mummy that lived south of the Alpine ridge ~5,200 years before present (ybp), during the Copper Age. Despite studies that have investigated his genetic profile, the relation of the Iceman´s maternal lineage with present-day mitochondrial variation remains elusive. Studies of the Iceman have shown that his mitochondrial DNA (mtDNA) belongs to a novel lineage of haplogroup K1 (K1f) not found in extant populations. We analyzed the complete mtDNA sequences of 42 haplogroup K bearing individuals from populations of the Eastern Italian Alps – putatively in genetic continuity with the Tyrolean Iceman—and compared his mitogenome with a large dataset of worldwide K1 sequences. Our results allow a re-definition of the K1 phylogeny and indicate that the K1f haplogroup is absent or rare in present-day populations. We suggest that mtDNA Iceman´s lineage could have disappeared during demographic events starting in Europe from ~5,000 ybp. Based on the comparison of our results with published data, we propose a scenario that could explain the apparent contrast between the phylogeographic features of maternal and paternal lineages of the Tyrolean Iceman within the context of the demographic dynamics happening in Europe from 8,000 ybp.This study was financed by the Provincia Autonoma di Bolzano – Alto Adige, Ripartizione Diritto allo studio, università e ricerca scientifica, funds to VCS
    corecore