Seasoned Equity Issues in a Closely Held Market: Evidence from France

This paper examines seasoned equity offerings in France.Even though a rights offering is the primary flotation method, French companies are increasingly usingthe relatively expensive public offering method. We show that the market reaction to the announcementof seasoned equity issues is significantly negative for rights issues and insignificantly negative forpublic offerings. Our results suggest that the adverse selection effect is greater for rights issues thanfor public offerings, due to stronger underwriter certification for the public offerings. We find that theshare price effect is positively related to blockholders take-up renouncements for firms with priorconcentrated ownership. For these firms, the favourable ownership dispersion effect offsets the adverse selection effect.     

基于模糊控制的三相异步电动机的软起动系统

本系统主要通过对模糊控制器的设计 ,将异步电动机的起动电流既限制在了一定的范围内 ,又可得到较大的起动力矩。由于又采用了参数自调整作为辅助控制 ,不但改善了起动时的动态性能 ,而且改善了稳定运行时的静态性能     

信息技术对竞争景框的影响--对波特观点的完善与修正

在分析信息技术对企业的影响时，波特教授对竞争景框变化的论述并不全面和完全正确。不全面在于，他只述及信息技术对地理景框和产业景框的影响，没有提到另两个方面——细分景框和纵向景框的变化。不正确在于，他笼统地提竞争景框的扩大或缩小，而竞争景框四方面在外力作用下变化并不总是一致的。本文认为，在信息技术影响下，竞争景框发生了四个方面不同的变化：细分景框、产业景框和纵向景框三个方面是缩小的，地理景框是扩大的。     

基于MATLAB提高Pt100测温系统响应速度的研究

通过对外加保护铜套的Pt100测温系统的实验研究,利用MATLAB建立了该系统对温度输入响应的数学模型,并通过合理增设串联相位超前校正网络提高了Pt100测温系统的响应速度。对于不同组成的Pt100测温系统,可选择不同的串联相位超前校正装置参数实现响应速度的提高。     

A Semiparametric Method for Valuing Residential Locations: Application to Automated Valuation

This paper is motivated by automated valuation systems, which would benefit from an ability to estimate spatial variation in location value. It develops theory for the local regression model (LRM), a semiparametric approach to estimating a location value surface. There are two parts to the LRM: (1) an ordinary least square (OLS) model to hold constant for interior square footage, land area, bathrooms, and other structural characteristics; and (2) a non-parametric smoother (local polynomial regression, LPR) which calculates location value as a function of latitude and longitude. Several methods are used to consistently estimate both parts of the model. The LRM was fit to geocoded hedonic sales data for six towns in the suburbs of Boston, MA. The estimates yield substantial, significant and plausible spatial patterns in location values. Using the LRM as an exploratory tool, local peaks and valleys in location value identified by the model are close to points identified by the tax assessor, and they are shown to add to the explanatory power of an OLS model. Out-of-sample MSE shows that the LRM with a first-degree polynomial (local linear smoothing) is somewhat better than polynomials of degree zero or degree two. Future applications might use degree zero (the well-known NW estimator) because this is available in popular commercial software. The optimized LRM reduces MSE from the OLS model by between 5 percent and 11 percent while adding information on statistically significant variations in location value.     

Real estate return correlations: Real-world limitations on relationships inferred from NCREIF data

Correlation estimates for returns between individual properties are subject to large inherent uncertainties due to limits on the amount of data that is likely to be available for the foreseeable future. After allowance for correlation sampling error, it is impossible to distinguish on an ex ante basis between the risk-reduction capabilities of mean-variance portfolio selection models and naive diversification without regard to property type or geographical location. The naive portfolio diversification strategies of typical institutional real estate portfolio managers are rational responses to limitations on the informational content of statistical analyses of historical real estate data.     

An integrated multi-model credit rating system for private firms

This paper presents a integrated credit risk modelling approach for private firms which fulfil 2001 Basel Accord requirements in the case of the adoption of the foundation approach. Our model comprises: (a) a bottom-up technique to initially assess the through-the-cycle one-year Probability of Default (PD) and (b) a top-down approach to refine and calibrate this historical PD in a forward-looking credit risk assessment based on next year’s economic outlook. We present findings from applying this model to a large sample of client firms of the Bank of Rome.     

Inference with Dependent Data in Accounting and Finance Applications

We review developments in conducting inference for model parameters in the presence of intertemporal and cross‐sectional dependence with an emphasis on panel data applications. We review the use of heteroskedasticity and autocorrelation consistent (HAC) standard error estimators, which include the standard clustered and multiway clustered estimators, and discuss alternative sample‐splitting inference procedures, such as the Fama–Macbeth procedure, within this context. We outline pros and cons of the different procedures. We then illustrate the properties of the discussed procedures within a simulation experiment designed to mimic the type of firm‐level panel data that might be encountered in accounting and finance applications. Our conclusion, based on theoretical properties and simulation performance, is that sample‐splitting procedures with suitably chosen splits are the most likely to deliver robust inferential statements with approximately correct coverage properties in the types of large, heterogeneous panels many researchers are likely to face.     

Industry Costs of Equity: Incorporating Prior Information

I examine whether incorporating economically motivated prior information yields more accurate forecasts of industry costs of equity. I find that incorporating the long‐run mean of the Capital Asset Pricing Model (CAPM) parameters and the industry characteristics in the cross section produces more accurate parameter estimates, which subsequently translate into more accurate out‐of‐sample forecasts of industry costs of equity. The outperformance of this method over rolling‐window estimates becomes larger as the forecast horizon extends into the future. These findings provide evidence that the CAPM parameters have a long‐run mean‐reversion property and correlate with the industry characteristics in a systematic way.     

ETF Premiums and Liquidity Segmentation

Exchange traded funds (ETFs) provide a means for investors to access assets indirectly that may be accessible at a high cost otherwise. I show that liquidity segmentation can explain the tendency for ETFs to trade at a premium to net asset value (NAV) as well as the life‐cycle pattern in premiums. ETFs with larger NAV tracking error standard deviations (TESDs) tend to trade at higher premiums and the liquidity benefits offered by foreign ETFs and fixed income ETFs are revealed to be the most valuable to investors. Further tests validate that TESD has the desirable properties of a liquidity segmentation measure.