Cox-Ingersoll-Ross模型的统计推断

该文在离散样本观察下,研究了Cox-Ingersoll-Ross模型的统计推问题,给出了CIR过程的平稳均值m与平稳方差ν的矩估计,并用-m和-ν给出了CIR过程中尺度参数α与β波动率之间的关系,基于CIR过程的平方变差,得到参数β的平方变差估计和参数α的估计.通过数值模拟的方法对平方变差估计与条件矩估计([9])方法作了比较,并选择1997-2006年的R007数据对这两种方法进行了实证分析.     

Heteroskedasticity-consistent covariance matrix estimators for spatial autoregressive models

In the presence of heteroskedasticity, conventional test statistics based on the ordinary least squares (OLS) estimator lead to incorrect inference results for the linear regression model. Given that heteroskedasticity is common in cross-sectional data, the test statistics based on various forms of heteroskedasticity-consistent covariance matrices (HCCMs) have been developed in the literature. In contrast to the standard linear regression model, heteroskedasticity is a more serious problem for spatial econometric models, generally causing inconsistent extremum estimators of model coefficients. This paper investigates the finite sample properties of the heteroskedasticity-robust generalized method of moments estimator (RGMME) for a spatial econometric model with an unknown form of heteroskedasticity. In particular, it develops various HCCM-type corrections to improve the finite sample properties of the RGMME and the conventional Wald test. The Monte Carlo results indicate that the HCCM-type corrections can produce more accurate results for inference on model parameters and the impact effects estimates in small samples.     

中国国债发行规模影响因素的实证研究

基于VAR模型,并运用协整检验、方差分解、向量自回归误差修正模型的计量经济分析方法,对我国国债规模的影响因素进行实证分析.实证结果显示,我国国债发行规模与国内生产总值、财政赤字、国债还本付息额、居民储蓄之间存在着长期稳定的均衡关系,影响国债规模的主要因素是国内生产总值、居民储蓄、国债发行规模本身、财政赤字.     

股票价格稳定性的非参数平滑估计

股票的优质性主要由股票价格的稳定性来决定。通过建立条件风险函数非参数平滑估计的估计方法,证明条件风险函数平滑后的非参数估计值具有一致性和渐进正态性,并将此方法扩展到了截尾数据中。通过蒙特卡罗模拟表明条件风险函数平滑后的非参数估计值在非截尾数据以及截尾数据中的有限样本行为都要优于非平滑的估计值。实证分析中用截尾数据条件风险函数非参数平滑估计方法非参数估计中国14大行业股票价格的稳定性,发现房地产行业的股票价格最不稳定,建筑材料行业的股票价格表现最稳定     

我国地区经济增长收敛的动态变化:1978—2017年

改革开放40年来，我国地区经济增长收敛现象较为明显。地区人均GDP增长不仅持续上升，而且水平差距也在不断缩小，存在条件收敛现象，并且东部和沿海地区经济增长的"俱乐部收敛"现象显著。进入20世纪90年代后，增长收敛趋势愈发突出，2008年国际金融危机也未影响增长收敛的发展态势。未来要继续坚持改革开放，补上各地制度和要素的短板，积极培育和发展有利于地区人均GDP增长收敛现象产生的一系列基础性因素，以实现区域更加协调发展。     

Estimation of Asymmetric Stochastic Volatility Models: Application to Daily Average Prices of Energy Products

Energy supply and demand, and as a consequence energy prices, are likely to represent one of the biggest challenges of the 21st century. Commodity markets exhibit increased volatility when there is little or no underutilized supply capability to meet natural fluctuations in demand. In the case of energy markets, the large capital requirements and significant lead times associated with energy production and delivery make them more susceptible to the imbalances in supply capability and demand. Energy price volatility has destructive impact on market agents, and this impact is intensified when the prices exhibit asymmetric volatility. This article pursues two aspects of the issue. First we consider general aspects, especially the asymmetric pattern of volatility of daily returns of different types of energy products. Then, we analyze the behaviour of daily returns by using traditional models of volatility that include AGARCH, TGARCH, EGARCH, and ARSV strategies, as well as a threshold asymmetric autoregressive stochastic volatility (TA-ARSV) model that we propose. The energy products considered in this analysis are probably the most relevant energy products for the economic activity of the nations and the economic relations between countries: Crude Oil (OPEC reference basket and London Brent index), Gasoline, Natural Gas, Butane, and Propane. We use spot prices and the time reference ranges from 1986–1993 to 2009 depending on the product.     

A novel cluster HAR-type model for forecasting realized volatility

This paper proposes a cluster HAR-type model that adopts the hierarchical clustering technique to form the cascade of heterogeneous volatility components. In contrast to the conventional HAR-type models, the proposed cluster models are based on the relevant lagged volatilities selected by the cluster group Lasso. Our simulation evidence suggests that the cluster group Lasso dominates other alternatives in terms of variable screening and that the cluster HAR serves as the top performer in forecasting the future realized volatility. The forecasting superiority of the cluster models are also demonstrated in an empirical application where the highest forecasting accuracy tends to be achieved by separating the jumps from the continuous sample path volatility process.     

用几何画板软件探讨二元函数的条件极值问题

利用几何画板软件先绘制出约束条件的图象,再把图象上的动点代入二元函数,观测函数性态,寻求极值。     

二阶自回归效应有限时间最优相对保费稳健性

在汽车保险奖惩系统相对保费研究中,需要考虑随机效应的动态异质性。在假设随机效应是一个二阶自回归随机序列的条件下,李俊海、赵振英、常沙沙(2011)给出了有限时间下最优相对保费计算公式,但是没有研究该公式的稳健性。在相同条件下,可以证明该文保费公式的稳健性。     

Karl Pearson and the Origin of Kurtosis

Although the kurtosis index proposed by Karl Pearson in 1905 is introduced in statistical textbooks at all levels, the measure is not easily interpreted and has been a subject of considerable debate. In this study, the theoretical development of kurtosis is surveyed from a historical perspective of Pearson's work on evolution. It surprisingly emerges that there was no emphasis in Pearson's papers on kurtosis as measuring (in part) tail heaviness. However, it is found that Pearson used to frequently adjust the formalisation of kurtosis depending on his changing needs. This complex development partly explains the confusion that would surround kurtosis in subsequent literature. Our conclusion is that most misunderstandings arise from improper use of the kurtosis coefficient outside the Pearson system of frequency curves.