Online learning of time-varying stochastic factor structure by variational sequential Bayesian factor analysis

Investment tasks include forecasting volatilities and correlations of assets and portfolios. One of the tools widely utilized is stochastic factor analysis on a set of correlated time-series (e.g. asset returns). Published time-series factor models require either sufficiently wide time windows of observed data or numeric solutions by simulations. We developed a ‘variational sequential Bayesian factor analysis’ (VSBFA) algorithm to make online learning of time-varying stochastic factor structure. The VSBFA is an analytic filter to estimate unknown factor scores, factor loadings and residual variances. The covariance matrix of the time-series predicted by the VSBFA can be decomposed into loadings-based covariance and specific variances, and the former can be expressed by ‘explanatory factors’ such as systematic components of various financial market indices. We compared the VSBFA with the most practiced factor model relying on wide data windows, the rolling PCA (principal components analysis), by applying them to 9-year daily returns of 200 simulated stocks with the ‘true’ daily data-generating model completely known, and by using them to forecast volatilities of long-only and long/short global stock portfolios with 25-year monthly returns of more than 800 stocks worldwide. Accuracy of the forecast covariance matrices is measured by a (symmetrized) Kullback–Leibler distance, and accuracy of the forecast portfolio volatilities is measured by bias statistic, log-likelihood, Q-statistic, and portfolio volatility minimization. The factor-based covariance and specific variances predicted by the best VSBFA are significantly more accurate than those by the best rolling PCA.     

Arrendamiento o compra de inmovilizado utilizando el endeudamiento

This work introduces the VNA (Clear Advantage of the Lease) criterion with the goal of letting any company that wants to incorporate fixed assets into his productive process, know whether it is better to realize it by means of a lease or through a debt-financed purchase. After analyzing the main lease types, the VNA criterion is applied to two different assumptions which also include an approximation to the legal Spanish regulation. Anyway, given its flexibility, the above mentioned criterion can be adapted to different cases and regulations. All kinds of results are obtained in this work, depending on the assumption adopted and on the variability granted to the different parameters used. In this respect, far from making hasty a priori affirmations on the convenience of leasing or buying fixed assets by means of debt, we recommend an ad hoc analysis in every case.     

A systemic approach to modelling and estimating demand for money(ies)

This article uses a consumer theory-based systemic approach to model the demand for monetary liquid asset holdings in Chile. We implement the suggestions and caveats of aggregation theory for the estimation of a demand system for liquid assets (monies) in static, dynamic and time-varying parameters setups. Our results are robust and theoretically consistent with consumer theory restrictions, as a system derived from a utility maximizing framework and a quasi concave utility function. In our estimations, we find stability of interest rate elasticities, in contrast to previous related literature. We also document evidence that long (short) maturity rates are associated to less (more) liquid assets.     

大位移井水力参数软件编制研究

传统的水力参数设计理论,一般不考虑岩屑运移的影响,这在直井、井深不大的定向井和水平井应用时不会产生较大误差,但在应用于大位移井时,由于斜井段和水平段很长,如果不考虑岩屑运移(岩屑床)的影响,将会产生较大误差,同时过高的岩屑床也会带来许多安全问题。必须结合大位移井特点,建立适合于大位移井的水力参数计算和设计体系。因此在理论研究的基础上,本文利用VB6.0程序编制了此套大位移井岩屑床及最小排量水力参数设计软件,经过现场证明,此套软件对现场的钻井施工具有很好的指导作用。     

路基压实度检测技术初探

路基压实度是路基路面施工质量检测的关键指标之一,路基压实度的高低直接制约着路基路面施工质量的好坏和今后的使用效果。本文在分析路基最大干密度和最佳含水量的基础上,对目前路基压实度常用检测方法进行了探讨。     

Estimating time-varying parameters in brand choice models: A semiparametric approach

Nowadays, brand choice models are standard tools in quantitative marketing. In most applications, parameters representing brand intercepts and covariate effects are assumed to be constant over time. However, marketing theories, as well as the experience of marketing practitioners, suggest the existence of trends or short-term variations in particular parameters. Hence, having constant parameters over time is a highly restrictive assumption, which is not necessarily justified in a marketing context and may lead to biased inferences and misleading managerial insights.In this paper, we develop flexible, heterogeneous multinomial logit models based on penalized splines to estimate time-varying parameters. The estimation procedure is fully data-driven, determining the flexible function estimates and the corresponding degree of smoothness in a unified approach. The model flexibly accounts for parameter dynamics without any prior knowledge needed by the analyst or decision maker. Thus, we position our approach as an exploratory tool that can uncover interesting and managerially relevant parameter paths from the data without imposing assumptions on their shape and smoothness.Our approach further allows for heterogeneity in all parameters by additively decomposing parameter variation into time variation (at the population level) and cross-sectional heterogeneity (at the individual household level). It comprises models without time-varying parameters or heterogeneity, as well as random walk parameter evolutions used in recent state space models, as special cases. The results of our extensive model comparison suggest that models considering parameter dynamics and household heterogeneity outperform less complex models regarding fit and predictive validity. Although models with random walk dynamics for brand intercepts and covariate effects perform well, the proposed semiparametric approach still provides a higher predictive validity for two of the three data sets analyzed.For joint estimation of all regression coefficients and hyperparameters, we employ the publicly available software BayesX, making the proposed approach directly applicable.     

关于金刚石环形带锯条在硅晶圆棒切割中的技术要求及应用问题的探讨

随着太阳能光伏行业的迅速发展,硅太阳能电池已经得到大规模应用,并在工业生产中占据主导地位,从而金刚石环形带锯条也广泛应用在硅材料的加工中。文章对金刚石环形带锯条在硅晶圆棒切割应用中的技术要求及使用中常出现的一些问题进行了分析和探讨。     

大型矿井动力操控员工安全心理参数探究

随着矿产资源不断向地层深部开采，矿井亦不断延伸，尤其是千米深井日渐增多，矿井动力提升速度和提升功能不断加快、增强，矿井数字化水平提高，对矿井动力操控员工的心理反应能力、注意能力、时空判断能力等一系列心理素质水平的要求不断增强。员工的反应准确性、注意集中和分配能力及情绪稳定性和人格状况是构成影响员工操控行为安全稳定的核心心理品质。探究矿井动力提升系统操控员工的各项安全心理阈限值及其安全心理参数标准，建立员工安全心理选拔准入制，是保障矿井人一机和谐安全运行的重要措施。     

Price transmission across the U.S. food distribution system

Price transmission models are estimated using recursive methods across 100 food commodities. From the individual commodities, short- and long-run price transmission coefficients are estimated for rising and falling prices. These coefficients are classified into five commodity categories and expressed as one vector while coding for causality, market levels, rising/falling prices, short and long run, and time period. Then the impact of each variable is estimated and inferences are drawn about the degree of price transmission. Results show that price linkages are strong but slightly declining over time, with some evidence of asymmetric behavior. Long-run rising prices are passed through more than long-run falling prices, except for fruits and vegetables.     

The Euro and inflation uncertainty in the European Monetary Union

This paper adopts a time-varying GARCH framework to estimate short-run and steady-state inflation uncertainty in 12 EMU countries, and then investigates their relationship with inflation. The effects of the Euro introduction in 1999 are examined by utilising a dummy variable. Tests for endogenously determined breaks are also employed. We find a considerable degree of heterogeneity across EMU countries in terms of average inflation, its degree of persistence, and both types of uncertainty, whilst the trend component of inflation is generally decreasing. Various breaks in the relationship between inflation and inflation uncertainty are found, frequently well before the Euro introduction.