A note on the Robust Trend and ARARMA methodologies used in the M3 Competition

This brief note describes two of the forecasting methods used in the M3 Competition, Robust Trend and ARARMA. The origins of these methods are very different. Robust Trend was introduced to model the special features of some telecommunications time series. It was subsequently found to be competitive with Holt’s linear model for the more varied set of time series used in the M1 Competition. The ARARMA methodology was proposed by Parzen as a general time series modelling procedure, and can be thought of as an alternative to the ARIMA methodology of Box and Jenkins. This method was used in the M1 Competition and achieved the lowest mean absolute percentage error for longer forecasting horizons. These methods will be described in more detail and some comments on their use in the M3 Competition conclude this note.     

Mean squared error of the empirical best linear unbiased predictor in an orthogonal finite discrete spectrum linear regression model

The mean squared error (MSE) of the empirical best linear unbiased predictor in an orthogonal finite discrete spectrum linear regression model is derived and a comparison with the MSE of the best linear unbiased predictor in this model is made. It is shown that under weak conditions these two mean square errors are asymptotically the same.     

The asymmetry of judgemental confidence intervals in time series forecasting

In forecasting a time series, one may be asked to communicate the likely distribution of the future actual value, often expressed as a confidence interval. Whilst the accuracy (calibration) of these intervals has dominated most studies to date, this paper is concerned with other possible characteristics of the intervals. It reports a study in which the prevalence and determinants of the symmetry of judgemental confidence intervals in time series forecasting was examined. Most prior work has assumed that this interval is symmetrically placed around the forecast. However, this study shows that people generally estimate asymmetric confidence intervals where the forecast is not the midpoint of the estimated interval. Many of these intervals are grossly asymmetric. Results indicate that the placement of the forecast in relation to the last actual value of a time series is a major determinant of the direction and size of the asymmetry.     

Distance in time between transition economies and the European Union

The time distance methodology used offers a new perspective to the problem, an additional statistical measure, and a presentation tool for policy analysis and debate readily understood by policy makers, media and general public. Disparity between the analysed transition economies and EU countries is considerably smaller for other indicators than for GDP per capita. Compared with Ireland, Portugal and Greece Slovenia was in 1995 in 13 cases behind (but time lag of Slovenia never exceeded 10 years) and in 13 cases ahead of them. Sicherl (1997a) discusses application of S-distance to time series regressions, models, forecasting and monitoring. First version received: October 1995/final version received: April 1998     

评审专家抽取中的时间距离约束分析

针对现有评审专家抽取中距离约束存在的不足,本文提出了一种新的时间距离约束。本文介绍了时间距离的含义及其提出的必要性,并给出了基于GIS技术的时间距离计算方法,具体包括相关假设、计算步骤、解决方案以及实现过程。时间距离约束的提出不仅可以保证所有被选专家都可按时到达评审地点,而且还能打破行政区域的限制,合理调配专家资源,具有重要的现实意义。     

一种利用短时DFT分析实现全数字2DPSK接收机解调的新算法

本文提出了一种简单而实用的利用短时DFT（ST-DFT）分析实现全数字2DPSK接收机的解调算法。该算法对由多谱勒效应引起的时变频率漂移具有鲁棒性。由于该算法是通过检测在载频处的瞬时能量谱的跳变来实现2DPSK信号的解调，所以该算法不需要进行专门的载波相位恢复、符号定时，且具有较好的抗噪性能，实现起来简单。     

未确认融资费用的实际利率摊销法研究——资金时间价值轴上的全新思路

本文从财务管理时间价值角度阐述未确认融资费用如何合理分摊的问题,提出了与一般会计实务教材标准解法完全相反的思路,得到了相同的效果,并对两种解题思路作了详细的比较分析,并在此基础上提出有关会计计量的若干假说。     

Comparing the accuracy of several network-based COVID-19 prediction algorithms

Researchers from various scientific disciplines have attempted to forecast the spread of coronavirus disease 2019 (COVID-19). The proposed epidemic prediction methods range from basic curve fitting methods and traffic interaction models to machine-learning approaches. If we combine all these approaches, we obtain the Network Inference-based Prediction Algorithm (NIPA). In this paper, we analyse a diverse set of COVID-19 forecast algorithms, including several modifications of NIPA. Among the algorithms that we evaluated, the original NIPA performed best at forecasting the spread of COVID-19 in Hubei, China and in the Netherlands. In particular, we show that network-based forecasting is superior to any other forecasting algorithm.     

2008: Golden Time in Gold Market

Pushed by increased demand from both jewelers and investors, China has become the drivin, g force behind the world's gold market in 2007. Chinas gold market this year has maintained its growing momentum with booming demand, not only in the domestic market but also in the international market.     

The Persistence of Profits in the Long Run: A New Approach

We present a trend‐based alternative to the standard first‐order autoregression model in persistence of profits studies. This is motivated by reservations over the interpretation of the standard model, and rests on a different concept of dynamic competition. A nine‐category taxonomy of long‐run persistence stereotypes is developed. Structural time series estimates are presented for a sample of UK companies. We find the null of long run competitive equilibrium not rejected in nearly a third of cases, but non‐eroding persistence to be present in around 60%.