Sentiment-scaled CAPM and market mispricing

This study explores the conditional version of the capital asset pricing model on sentiment to provide a behavioural intuition behind the value premium and market mispricing. We find betas (β) and the market risk premium to vary over time across different sentiment indices and portfolios. More importantly, the state β derived from this sentiment-scaled model provides a behavioural explanation of the value premium and a set of anomalies driven by mispricing. Different from the static β–return relation that gives a flat security market line, we document upward security market lines when plotting portfolio returns against their state βs and portfolios with higher state βs earn higher returns.     

航班计划优化研究概述

从航班计划优化的不同时间阶段分析,可以将航班计划优化分为航班计划静态编排优化、基于航班延误预测的航班计划动态反馈优化和基于机场协同决策(A-CDM)的航班计划动态调整角度三类;进而从航班时刻、机型指派、航班频率等编制环节分析了航班计划静态编排优化;随后利用延误波及预测与数据挖掘预测的优化方法分析了基于航班延误预测的航班计划动态反馈优化的相关研究。最后,根据航班计划优化复杂性分析,给出了航班计划优化的发展趋势和未来研究方向。     

乘积型指数滤波器及其在多目标时延估计中的应用

指数滤波器是一类新构造出来的输出信噪比和目标时延分辨力随指数变化的滤波器，该滤波器在损失一定输出信噪比的前提下可以有效提高目标时延分辨力，从而提高目标时延估计精度,但仅采用单个指数滤波器仍存在输出信噪比和目标时延分辨力均达不到实际需求的情况。在乘积型高阶模糊函数乘积运算的启发下，在指数滤波器的基础上提出了一种新的乘积型指数滤波器，并分析了该乘积型指数滤波器的输出信噪比及目标时延分辨力等性能。仿真实验表明，所提的乘积型指数滤波器在低信噪比情况下可以更有效提高多目标时延估计精度，且算法简单易于实现，适用于背景复杂的多目标参数估计任务。     

职业延迟满足对员工过劳的影响研究——职业成长机会的调节作用

目前，员工过劳问题在我国企业发展中日益凸显，需要予以重视和解决。基于个体与组织互动角度，通过对338名企业员工的问卷调查分析职业延迟满足和职业成长机会对员工过劳的影响，并检验职业成长机会对职业延迟满足影响员工过劳的调节作用，结果表明：职业延迟满足的两个维度（工作延迟满足和职业生涯延迟满足）均对员工过劳有显著正向影响，而职业成长机会对员工过劳有显著负向影响；职业成长机会对职业延迟满足影响员工过劳具有负向调节作用，即职业成长机会越大，职业延迟满足与员工过劳的正向关系越弱。因此，企业管理者应合理引导和帮助员工做好职业生涯规划，为员工提供合适的多元化发展通道，以有效预防和缓解员工过劳。     

Collaborative delay management towards demand-capacity balancing within User Driven Prioritisation Process

The concept of User Driven Prioritisation Process (UDPP) was introduced to give Airspace Users (AUs) more flexibility under demand-capacity imbalance. This paper presents two UDPP-DCB models, built on the UDPP principle, using the Selective Flight Protection (SFP) approach to minimize the total delay cost. AUs are enabled to adapt their operations in a more cost-efficient way in the presence of capacity constraints in airspace, optimizing their flights to keep the priorities track. Then, ATFM integrates the AUs’ decision to reassign the time slots and the preferred rerouting trajectories. Results suggest that the delay cost for AUs can be largely reduced through applying the UDPP-DCB models proposed in this paper, while allowing rerouting proves effective in reducing the system delay cost.     

Is there a role for uncertainty in forecasting output growth in OECD countries? Evidence from a time-varying parameter-panel vector autoregressive model

This paper uses a time-varying parameter-panel vector autoregressive (TVP-PVAR) model to analyze the role played by domestic and US news-based measures of uncertainty in forecasting the growth of industrial production of 12 Organisation for Economic Co-operation and Development (OECD) countries. Based on a monthly out-of-sample period of 2009:06 to 2017:05, given an in-sample of 2003:03 to 2009:05, there are only 46% of cases where domestic uncertainty can improve the forecast of output growth relative to a baseline monetary TVP-PVAR model, which includes inflation, interest rate and nominal exchange rate growth, besides output growth. Moreover, including US uncertainty does not necessarily improve the forecasting performance of output growth from the TVP-PVAR model which includes only the domestic uncertainty along with the baseline variables. So, in general, while uncertainty is important in predicting the future path of output growth in the 12 advanced economies considered, a forecaster can do better in majority of the instances by just considering the information from standard macroeconomic variables.     

Services inflation dynamics and persistence puzzle in Brazil: a time-varying parameter approach

This article analyses services inflation dynamics in Brazil, focusing on the Services Inflation Persistence Puzzle, for monthly data from January 2004 to February 2016. We apply a time-varying parameter (TVP) approach, via a Kalman filter, to estimate hybrid Phillips curves and compare inflation inertia for tradable goods and services inflation. Aggregate Brazilian Extended Consumer Price Index inflation serves as a benchmark. To justify the TVP analysis, parameter instability and structural change tests are implemented, based on OLS and Generalized Method of Moments (GMM) frameworks. The main results are as follows: (i) the TVP approach is relevant due to observed instability in some parameters estimated; (ii) inflation expectation coefficients are higher than lagged inflation in all calculations, but inflation inertia is not negligible at all; (iii) services inflation persistence ranges from 27 to 36%, whereas tradable goods inflation persistence ranges from 36 to 47%, providing evidence of the Services Inflation Persistence Puzzle in Brazil; (iv) from 2009 onwards an increase in one percentage point in real wages raises monthly services inflation rate by 0.02 to 0.03 percentage point; (v) there is evidence that cost-push pressures, due to wage increases in the service sector, are more important to explain services inflation than demand pressures from early 2009 to mid-2014.     

单光子卫星量子通信噪声和干扰分析

卫星量子通信是建立全球量子通信网络的最佳选择之一。针对采用偏振编码的卫星量子通信中的偏振保持问题,研究了大气散射和卫星与地面站间相对运动等因素对量子偏振态相位和对准的影响以及相位延迟和对准误差对系统量子误码率的影响,分析了背景噪声和系统硬件噪声对通信产生的影响以及单光子通信过程中可能受到的光子分离攻击干扰,为量子信号认知设计提供借鉴意义。     

Bayesian forecasting and portfolio decisions using dynamic dependent sparse factor models

We extend the recently introduced latent threshold dynamic models to include dependencies among the dynamic latent factors which underlie multivariate volatility. With an ability to induce time-varying sparsity in factor loadings, these models now also allow time-varying correlations among factors, which may be exploited in order to improve volatility forecasts. We couple multi-period, out-of-sample forecasting with portfolio analysis using standard and novel benchmark neutral portfolios. Detailed studies of stock index and FX time series include: multi-period, out-of-sample forecasting, statistical model comparisons, and portfolio performance testing using raw returns, risk-adjusted returns and portfolio volatility. We find uniform improvements on all measures relative to standard dynamic factor models. This is due to the parsimony of latent threshold models and their ability to exploit between-factor correlations so as to improve the characterization and prediction of volatility. These advances will be of interest to financial analysts, investors and practitioners, as well as to modeling researchers.     

Interrelationship between crude oil and the stock markets of major demanders and suppliers in emerging and developed markets

This paper investigates the time-varying relationship between the stock markets of advanced and emerging oil-exporting and oil-importing countries and the international crude oil price indices. The results reveal that the time-varying among the oil-exporting and oil-importing countries responds similarly to aggregate supply- and demand-side effects. Oil-exporting countries have a slightly higher integration with the oil markets, while oil supply shocks have a slightly higher impact on emerging oil-exporting countries. The oil markets exhibit a lower time-varying relationship with the Asia-Pacific oil-importing markets, which indicates those markets may be attractive to investors during periods of turbulence in the oil market.