Income ineqaulity from 1960-2012: a brief time-series history of capital and labour

This commentary examines two principal forms of inequality and their evolution since the 1960s: the division of national income between capital and labour, and the share of total income held by the top 1 per cent of earners. Trends are linked to current discussions of inequality drivers such as financialisation, and a brief time-series analysis of the effects of trade and financial sector growth on top incomes is presented.

Bandwidth selection by cross-validation for forecasting long memory financial time series

The paper addresses the issue of choice of bandwidth in the application of semiparametric estimation of the long memory parameter in a univariate time series process. The focus is on the properties of forecasts from the long memory model. A variety of cross-validation methods based on out of sample forecasting properties are proposed. These procedures are used for the choice of bandwidth and subsequent model selection. Simulation evidence is presented that demonstrates the advantage of the proposed new methodology.

Optimal Time Series Momentum

We develop a continuous-time asset price model to capture the timeseries momentum documented recently. The underlying stochastic delay differentialsystem facilitates the analysis of effects of different time horizons used bymomentum trading. By studying an optimal asset allocation problem, we find thatthe performance of time series momentum strategy can be significantly improvedby combining with market fundamentals and timing opportunity with respect tomarket trend and volatility. Furthermore, the results also hold for different timehorizons, the out-of-sample tests and with short-sale constraints. The outperformanceof the optimal strategy is immune to market states, investor sentiment andmarket volatility.

Learning from time series:Supervised Aggregative Feature Extraction

Many modeling problems require to estimate a scalar output from one or more time series. Such problems are usually tackled by extracting a fixed number of features from the time series (like their statistical moments), with a consequent loss in information that leads to suboptimal predictive models. Moreover, feature extraction techniques usually make assumptions that are not met by real world settings (e.g. uniformly sampled time series of constant length), and fail to deliver a thorough methodology to deal with noisy data. In this paper a methodology based on functional learning is proposed to overcome the aforementioned problems; the proposed Supervised Aggregative Feature Extraction (SAFE) approach allows to derive continuous, smooth estimates of time series data (yielding aggregate local information), while simultaneously estimating a continuous shape function yielding optimal predictions. The SAFE paradigm enjoys several properties like closed form solution, incorporation of first and second order derivative information into the regressor matrix, interpretability of the generated functional predictor and the possibility to exploit Reproducing Kernel Hilbert Spaces setting to yield nonlinear predictive models. Simulation studies are provided to highlight the strengths of the new methodology w.r.t. standard unsupervised feature selection approaches. © 2012 IEEE.

Ferroelectricity in epitaxial pulsed laser deposited bismuth-layered perovskite thin films of different crystallographic orientations

Epitaxial thin films Of various bismuth-layered perovskites SrBi(2)Ta(2)O(9), Bi(4)Ti(3)O(12), BaBi(4)Ti(4)O(15), and Ba(2)Bi(4)Ti(5)O(18) were deposited by pulsed laser deposition onto epitaxial conducting LaNiO(3) or SrRuO(3) electrodes on single crystalline SrTiO(3) substrates with different crystallographic orientations or on top of epitaxial buffer layers on (100) silicon. The conductive perovskite electrodes and the epitaxial ferroelectric films are strongly influenced by the nature of the substrate, and bismuth-layered perovskite ferroelectric films with mixed (100), (110)- and (001)-orientations as well as with uniform (001)-, (116)- and (103)- orientations have been obtained. Structure and morphology investigations performed by X-ray diffraction analysis, scanning probe microscopy, and transmission electron microscopy reveal the different epitaxial relationships between films and substrates. A clear correlation of the crystallographic orientation of the epitaxial films with their ferroelectric properties is illustrated by macroscopic and microscopic measurements of epitaxial bismuth-layered perovskite thin films of different crystallographic orientations.

Validation of non‑stationary precipitation series for site‑specific impact assessment: comparison of two statistical downscaling techniques

Statistical downscaling (SD) methods have become a popular, low-cost and accessible means of bridging the gap between the coarse spatial resolution at which climate models output climate scenarios and the finer spatial scale at which impact modellers require these scenarios, with various different SD techniques used for a wide range of applications across the world. This paper compares the Generator for Point Climate Change (GPCC) model and the Statistical DownScaling Model (SDSM)—two contrasting SD methods—in terms of their ability to generate precipitation series under non-stationary conditions across ten contrasting global climates. The mean, maximum and a selection of distribution statistics as well as the cumulative frequencies of dry and wet spells for four different temporal resolutions were compared between the models and the observed series for a validation period. Results indicate that both methods can generate daily precipitation series that generally closely mirror observed series for a wide range of non-stationary climates. However, GPCC tends to overestimate higher precipitation amounts, whilst SDSM tends to underestimate these. This infers that GPCC is more likely to overestimate the effects of precipitation on a given impact sector, whilst SDSM is likely to underestimate the effects. GPCC performs better than SDSM in reproducing wet and dry day frequency, which is a key advantage for many impact sectors. Overall, the mixed performance of the two methods illustrates the importance of users performing a thorough validation in order to determine the influence of simulated precipitation on their chosen impact sector.

An ultra-short-term wind power prediction method using “offline classification and optimization, online model matching” based on time series features

The applicability of ultra-short-term wind power prediction (USTWPP) models is reviewed. The USTWPP method proposed extracts featrues from historical data of wind power time series (WPTS), and classifies every short WPTS into one of several different subsets well defined by stationary patterns. All the WPTS that cannot match any one of the stationary patterns are sorted into the subset of nonstationary pattern. Every above WPTS subset needs a USTWPP model specially optimized for it offline. For on-line application, the pattern of the last short WPTS is recognized, then the corresponding prediction model is called for USTWPP. The validity of the proposed method is verified by simulations.

Synthesis, thermal characterization and rheological properties of a homologous series of polymethacrylate-based side-chain liquid crystal polymers

A new homologous series of side-chain liquid crystal polymers, the poly[omega-(4-cyanoazobenzene-4'-oxy)alkyl methacrylate]s, have been prepared in which the length of the flexible alkyl spacer is varied from 3 to 12 methylene units. All the polymers exhibit liquid crystalline behaviour; specifically, crystal E, smectic A and nematic phases are observed. The glass transition temperatures decrease on increasing spacer length before reaching a limiting value at ca. 30 degrees C. The clearing temperatures exhibit an odd-even effect on varying the length and parity of the spacer. This is attributed to the change in the average shape of the side chain as the parity of the spacer is varied. This rationalization also accounts for the observed alternation in the entropy change associated with the clearing transition. A weak relaxation is observed theologically for several members of this polymer series at temperatures above their respective glass transition temperatures. This is attributed either to specific motions of the smectic layers or to 180 degrees reorientational jumps of the long axis of the mesogenic unit about the polymer backbone. (C) 1997 Elsevier Science Ltd. All rights reserved.