每日结算价确定方法与股指期货价格发现效率的关系——以HSI指数期货为例

价格发现效率作为价格发现的一项基础研究一直备受理论重视。以价格发现速度作为价格发现效率的代理变量,在总结现有价格发现速度研究的基础上,提出了一般价格发现模型(GPDM)。通过GPDM,以HSI指数期货为例,从结算价确定方法对价格发现速度影响的角度,比较了α-温塞平均数法、不完全平均数法、成交量加权平均数法和指数平滑法确定的结算价以及现行结算价的价格发现效率。结果发现,α-温塞平均数法确定的结算价最具价格发现效率,而现行结算价最不具价格发现效率。     

灰色预测模型拓广方法研究

利用函数 a- x (a 1 )对灰色预测模型的原始离散数据列 {x( 0 ) (k) }进行变换 ,提高了离散数据列的光滑度 ,拓宽了灰色预测模型的应用范围 ,并从理论上证明了该方法比“对数函数”法及“幂函数”法更有效.     

一种时用水量的联合预测方法

提出了时用水量的季节指数、趋势移动及自适应过滤联合预测方法，该法可满足供水系统优化调度的需要。     

Forecasting European GNP data through common factor models and other procedures

In this paper we present an extensive study of annual GNP data for five European countries. We look for intercountry dependence and analyse how the different economies interact, using several univariate ARIMA and unobserved components models and a multivariate model for the GNP incorporating all the common information among the variables. We use a dynamic factor model to take account of the common dynamic structure of the variables. This common dynamic structure can be non‐stationary (i.e. common trends) or stationary (i.e. common cycles). Comparisons of the models are made in terms of the root mean square error (RMSE) for one‐step‐ahead forecasts. For this particular group of European countries, the factor model outperforms the remaining ones. Copyright © 2002 John Wiley & Sons, Ltd.     

引入时变递增因子的加权等维新息模型及预测

从灰色系统理论入手 ,针对已发生的时间序列的一组变形观测数据 ,按其可靠性随时间成正比例变化的特性 ,引入时变递增因子来定权 ,并及时更新数据 ,用最新的数据替换老的数据 ,建立等维新息模型 ,以保证原始数据对模型的作用 ,使模型更能反映实际 .实例计算分析表明 :该模型样本需求量小 ,计算简单 ,能动态地反映出系统的时变特性 ,并使预测精度得到有效的提高     

交易者异质性条件下系统风险冲击与企业创新能力对股票价格波动性的影响机理:理论模型与仿真分析

基于信息交易者和非信息交易者行为特征，建立数学模型从理论上研究交易者异质性条件下系统风险冲击与企业创新能力对股票价格波动性的影响机理，并利用MATLAB编程对理论模型结果进行仿真分析.研究结果表明：企业创新能力在任何系统风险冲击和交易者结构下都将发挥股票价格稳定器作用；在企业创新能力较高时，股票价格波动性与信息交易者持股比例负相关，与系统风险冲击之间的相关性因交易者结构不同而呈现出不同特征；在企业创新能力较低时，股票价格波动性与系统风险冲击正相关，与信息交易者持股比例之间呈U型关系；信息交易者持股比例较高的股票市场更具优胜劣汰选择机制.提升企业创新能力、提高信息交易者持股比例、完善信息披露制度是抵御系统风险冲击、保障股票市场稳定可持续发展的重要途径.     

员工股权激励能够降低股价崩盘风险吗?

股权激励是上市公司重要的治理机制，高管和员工构成股权激励的两大激励对象.然而，现有研究多关注高管股权激励的治理作用，却普遍忽略了非高管层员工.利用2007-2017年的A股上市公司数据，从股价崩盘风险的视角，考察了员工股权激励的治理作用.研究发现，员工股权激励能够显著降低股价崩盘风险.作用机制分析表明，员工股权激励可通过改善公司信息环境、降低公司经营风险两种途径降低股价崩盘风险.进一步分析还发现，产权性质并不影响员工股权激励对股价崩盘风险的降低作用.文章发现的员工股权激励对股价崩盘风险的治理作用，能够为规范上市公司信息披露、维护股票市场稳定等相关政策的完善提供参考.     

From the editors

Political forecasting provides the contextuality needed for decision-making and for forecasting ‘non-political’ trends. To gear political forecasting to these needs, rather than mimicking approaches in other areas, requires recognition of the distinctive nature of political trends, and realism regarding forecast uses, which generally do not benefit from ‘precise’ probabilities, predictions of only major events, or ‘sophisticated’ methodology that sacrifices comprehensiveness for explicitness. Approaches borrowed from other forecasting disciplines have been counterproductive, although contextual approaches, including cross-impact analyses and developmental constructs that integrate political and non-political trends, are promising. Explorations of the consistency of scenario dynamics, taking into account policy responses and non-formalizable complexity, are also useful. Thus the separation of political forecasting from political analysis should be minimized, calling for a redirection of effort away from developing methodology uniquely geared to forecasting, and towards organizing more comprehensive and systematic analytical efforts.     

减小指数投资组合跟踪误差的研究

在有效股票市场中，投资者一般按照股票指数来构造投资组合，目的是为了获得与股票相同的业绩。但是，由于按照股票指数复制投资组合时存在佣金，市场冲击成本及持有股票保管费等成本，复制性投资组合的业绩一般要比股票指数业绩差。本文就此问题，采用三种方法，来减少投资组合跟踪误差。     

Volatility forecasting for risk management

Recent research has suggested that forecast evaluation on the basis of standard statistical loss functions could prefer models which are sub‐optimal when used in a practical setting. This paper explores a number of statistical models for predicting the daily volatility of several key UK financial time series. The out‐of‐sample forecasting performance of various linear and GARCH‐type models of volatility are compared with forecasts derived from a multivariate approach. The forecasts are evaluated using traditional metrics, such as mean squared error, and also by how adequately they perform in a modern risk management setting. We find that the relative accuracies of the various methods are highly sensitive to the measure used to evaluate them. Such results have implications for any econometric time series forecasts which are subsequently employed in financial decision making. Copyright © 2002 John Wiley & Sons, Ltd.