A management orientated approach to combination forecasting of tourism demand

Volatility, exponential smoothing, regression and Naïve 2 models are considered singly and in combination in terms of forecasting demand for international tourism. These models generate accurate predictions of tourism flows, but their prime utility is when combined with other models. Usually, models are combined by means of purely statistical criteria. We show that goal programming (GP) offers an alternative, flexible approach to model combination. GP offers planners a practical solution to tourism forecasting problems, since the method is more adaptable than conventional minimisation of prediction error, by permitting practitioners to prioritise a series of management related goals. Forecasters can focus on longer- and short-term goals, minimising forecast under- and over-estimation and/or concentrate on prediction errors in tourism flows at various times of the year.     

浅析高校内证卡使用问题及其解决措施

证卡和票据曾经是高校内身份识别和消费的主要方式,现介绍高校内现有证卡和票据使用现状及存在的问题,分析其原因,提出基于校园一卡通系统的解决方案,总结了使用效果,并对下一步工作进行了展望。     

Evaluating portfolio Value-at-Risk using semi-parametric GARCH models

In this paper we examine the usefulness of multivariate semi-parametric GARCH models for evaluating the Value-at-Risk (VaR) of a portfolio with arbitrary weights. We specify and estimate several alternative multivariate GARCH models for daily returns on the S&P 500 and Nasdaq indexes. Examining the within-sample VaRs of a set of given portfolios shows that the semi-parametric model performs uniformly well, while parametric models in several cases have unacceptable failure rates. Interestingly, distributional assumptions appear to have a much larger impact on the performance of the VaR estimates than the particular parametric specification chosen for the GARCH equations.     

Time varying country risk: an assessment of alternative modelling techniques

Three different techniques for the estimation of a time-varying beta are investigated: a bivariate GARCH model, the Schwert and Seguin approach, and the Kalman filter method. These approaches are applied to a set of monthly Morgan Stanley country index data over the period 1970 to 1995 and their relative performances compared. In-sample forecast tests of the performance of each of these methods for generating conditional beta suggest that the GARCH-based estimates of risk generate the lowest forecast error although these are not necessarily significantly less than those generated by the other techniques considered.     

Volatility forecasts and at-the-money implied volatility: a multi-component ARCH approach and its relation to market models

This article explores the relationships between several forecasts for the volatility built from multi-scale linear ARCH processes, and linear market models for the forward variance. This shows that the structures of the forecast equations are identical, but with different dependencies on the forecast horizon. The process equations for the forward variance are induced by the process equations for an ARCH model, but postulated in a market model. In the ARCH case, they are different from the usual diffusive type. The conceptual differences between both approaches and their implication for volatility forecasts are analysed. The volatility forecast is compared with the realized volatility (the volatility that will occur between date t and t + ΔT), and the implied volatility (corresponding to an at-the-money option with expiry at t + ΔT). For the ARCH forecasts, the parameters are set a priori. An empirical analysis across multiple time horizons ΔT shows that a forecast provided by an I-GARCH(1) process (one time scale) does not capture correctly the dynamics of the realized volatility. An I-GARCH(2) process (two time scales, similar to GARCH(1,1)) is better, while a long-memory LM-ARCH process (multiple time scales) replicates correctly the dynamics of the implied and realized volatilities and delivers consistently good forecasts for the realized volatility.     

论税收的时效性

时效性是税收强制性在时间上的体现，是税法赋予的一种规定性，是国家财政收支及时稳定的重要保证，是依法治税的必然要求，是衡量税务机关征管水平的基本依据。不论是税收法治的严肃性，还是国家各项事业急需财政资金的现实，都迫切需求提高税收的时效性。及时有效地组织好财政收入。     

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     

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。     

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%.