Combining information for prediction in linear regression

This article deals with the prediction problem in linear regression where the measurements are obtained using k different devices or collected from k different independent sources. For the case of k=2, a Graybill-Deal type combined estimtor for the regression parameters is shown to dominate the individual least squares estimators under the covariance criterion. Two predictors ŷ _c and ŷ _p are proposed. ŷ _c is based on a combined estimator of the regression coefficient vector, and ŷ _p is obtained by combining the individual predictors from different models. Prediction mean square errors of both predictors are derived. It is shown that the predictor ŷ _p is better than the individual predictors for k≥2 and the predictor ŷ _c is better than the individual predictors for k=2. Numerical comparison between ŷ _c and ŷ _p shows that the former is superior to the latter for the case k=2.     

现代企业委托代理问题的“中庸之道”

孔子提出的“中庸之道”从根本上说是一种管理思想和方法,它要求人们作任何事情都要遵循适度原则,这对现代企业中的委托代理问题同样具有重要意义。在这一思想方法的指导下,本文论证了解决委托代理问题的最优激励机制设计,寻找激励与监督的均衡点。     

外生冲击与房地产真实价格波动--对1998～2003年中国31省(市、区)的实证研究

文章首先根据经济学模型界定了两个重要指标:自相关系数与收敛系数.认为不同的外生冲击对这两个系数有不同的影响,而它们决定了房地产真实价格波动形态的差异.在此基础上,文章利用1998～2003年中国31个省(市、区)的面板数据对中国房地产市场进行了实证研究,其结论是,在真实人均可支配收入和真实建筑成本较高、真实税后住宅抵押贷款利率较低的地区有较大的自相关系数和较小的收敛系数,从而房地产真实价格具有更大的波动性.为使房地产真实价格在均衡价格附近平稳运行,降低开发成本和提高消费者购买成本能收到较好的效果.     

MSE-improvement of the least squares estimator by dropping variables

It is well known that dropping variables in regression analysis decreases the variance of the least squares (LS) estimator of the remaining parameters. However, after elimination estimates of these parameters are biased, if the full model is correct. In his recent paper, Boscher (1991) showed that the LS-estimator in the special case of a mean shift model (cf. Cook and Weisberg, 1982) which assumes no “outliers” can be considered in the framework of a linear regression model where some variables are deleted. He derived conditions under which this estimator outperforms the LS-estimator of the full model in terms of the mean squared error (MSE)-matrix criterion. We demonstrate that this approach can be extended to the general set-up of dropping variables. Necessary and sufficient conditions for the MSE-matrix superiority of the LS-estimator in the reduced model over that in the full model are derived. We also provide a uniformly most powerful F-statistic for testing the MSE-improvement.     

Diversification Benefits of Japanese Real Estate Over the Last Four Decades

This paper studies the benefits of diversifying into real estate and other assets that typify the wealth held by Japanese investors. We examine movements in mean variance frontiers by employing spanning tests to assess the statistical significance of frontier shifts. We also investigate the impact of shifts in mean variance frontiers before and after the precipitous decline in Japanese real estate and stock market values that began in 1990. Spanning tests show that real estate, short and long-term bonds, and Japanese equity provide significant diversification benefits. We find that mean variance frontiers shift after 1990. Statistically significant shifts are also economically important as measured by Sharpe ratio changes. Although significant, the portfolio weights on Japanese real estate are relatively small compared to their composition found in surveys of Japanese household wealth.     

基于UG的螺旋桨逆向建模

文章对螺旋桨的一般设计过程和基于UG的建模功能,以及对已有的螺旋桨进行逆向建模的整个过程进行了系统介绍。     

Measuring financial risk and portfolio reversion with time changed tempered stable Lévy processes

Given that underlying assets in financial markets exhibit stylized facts such as leptokurtosis, asymmetry, clustering properties and heteroskedasticity effect, this paper applies the stochastic volatility models driven by tempered stable Lévy processes to construct time changed tempered stable Lévy processes (TSSV) for financial risk measurement and portfolio reversion. The TSSV model framework permits infinite activity jump behaviors of returns dynamics and time varying volatility consistently observed in financial markets by introducing time changing volatility into tempered stable processes which specially refer to normal tempered stable (NTS) distribution as well as classical tempered stable (CTS) distribution, capturing leptokurtosis, fat tailedness and asymmetry features of returns in addition to volatility clustering effect in stochastic volatility. Through employing the analytical characteristic function and fast Fourier transform (FFT) technique, the closed form formulas for probability density function (PDF) of returns, value at risk (VaR) and conditional value at risk (CVaR) can be derived. Finally, in order to forecast extreme events and volatile market, we perform empirical researches on Hangseng index to measure risks and construct portfolio based on risk adjusted reward risk stock selection criteria employing TSSV models, with the stochastic volatility normal tempered stable (NTSSV) model producing superior performances relative to others.     

Growth and value hybrid valuation model based on mean reversion

This article proposes a novel valuation model, growth and value hybrid model, to estimate the stock price. This proposed model combines the essence of the asset-based approach, the income-based approach, and the principle of mean reversion to develop the theoretical closed-form formula consisting of three coefficients: value coefficient, value support coefficient and growth coefficient. Regression analysis is employed to fit market data to determine these coefficients. Moreover, this study proposes the double sorting method to build the quantile regression models of the formula to estimate the stock price at a specific quantile. The results show that the predictive capability of the hybrid valuation model is superior to the model without using value support coefficient, which supports the assumption that the PBR is not associated with the ROE when the ROE is less than a threshold. In different time periods of the stock market, no significant difference exists on the value support coefficient. However, the variations of the value coefficient and the growth coefficient are significant.     

Mean reversion in annual earnings and its implications for security valuation

This article documents the long-horizon mean reverting character of annual earnings and tests the implications of such mean reversion for security valuation. First, both theory-based and nonparametric measures of earnings persistence decrease as the estimation order increases, revealing 40 percent less long-horizon persistence than expected under the commonly used random walk model. Second, the return responses to the earnings shocks are more closely related across firms to the higher-order measures of persistence that reflect significant long-horizon mean reversion. Third, the persistence measure derived from classical valuation theory outperforms the generic measure in explaining the return responses. Taken as a whole, these results provide evidence for significant mean reversion in the higher-order properties of earnings and for the stock market incorporating these properties in a manner consistent with classical valuation theory.     

S&P 500 implied volatility and monetary policy announcements

While many studies have investigated the link between macroeconomic events and equity market volatility, few have considered the impact on option implied volatilities. Given the recent focus on trading in implied volatility, in the context of the S&P 500 VIX index, this paper examines how the VIX index behaves around US monetary policy announcements. It is revealed that the VIX index falls significantly on the day of Federal Open Market Committee meetings.