基于稳态分布的资本资产定价模型上海股市实证分析

运用BS估计和OLS估计对资本资产定价模型在我国证券市场的应用进行了实证分析,分析结果显示,运用OLS方法对建立在资产收益为正态分布基础上的传统资本资产定价模型与运用BS方法对资产收益为α稳态分布的资本资产定价模型的贝塔系数估计值存在较大的差异,而BS估计方法明显比OLS估计方法更有效率。     

Multivariate Hill Estimators

We propose two classes of semi‐parametric estimators for the tail index of a regular varying elliptical random vector. The first one is based on the distance between a tail probability contour and the observations outside this contour. We denote it as the class of separating estimators. The second one is based on the norm of an arbitrary order. We denote it as the class of angular estimators. We show the asymptotic properties and the finite sample performances of both classes. We also illustrate the separating estimators with an empirical application to 21 worldwide financial market indexes.     

Leaving EMU: a real options perspective

The real option implicit in a country's decision of whether to leave an existing monetary union when there is uncertainty over the future benefits of this move is examined. The theoretical model used is calibrated for the current Euro-12 area by proxying policymakers’ inflation preferences with unemployment rates and debt-to-GDP ratios. A robust group of countries is observed that would choose to remain within EMU consisting of Belgium, Finland, Greece and Italy; France and Spain loosely also belong to this core. Only Luxembourg would robustly want to leave EMU; Ireland and The Netherlands, however, complement that core closely.     

Generalized beta distributions for describing and analysing intraday stock market data: testing the U-shape pattern

There is an impressive body of empirical evidence which indicates the existence of an intraday U-shaped curve in stock prices. In an effort to shed additional light on the U-shaped curve a new procedure for U-shape testing is introduced. From careful analysis of intraday data it is observed that minimum or maximum stock prices can occur several times during the day. Here, attention is focused on the first time during the day that the maximum or minimum stock price occurred. Because of the importance of the first time during the day that the maximum or minimum stock price occurred, an attempt is made to model these two characteristics with probability distributions. The objective of this study is to use a generalized beta distribution to examine the intradaily behaviour of stocks, using closing stock prices for each one-minute interval, using data from Athens Stock Exchange (ASE). This generalized beta distribution has not been used before to model U-shaped behaviour. The results are consistent with the intraday U-shaped curves, i.e. the time to first maximum (or minimum) stock prices follows a U-shaped pattern. In addition, some potential applications of the generalized beta distribution are discussed and exemplified by analysing the relationship between herd behaviour and U-shaped.     

The puzzle of greenhouse gas footprints of oil abundance

The present inquiry lays a groundwork for the analysis of the net greenhouse gas (GHG) footprint of oil in the oil-abundant settings. To address the research question, the study puts forward a three-sector decision model, which provides a common ground for the assessment of the interaction of the structuralist and institutional factors influencing environmental pollution in the oil-reliant economies. The study shows that fossil-fuel abundance triggers forces, which induce diametrically opposed effects concerning atmospheric pollution. These are the rising carbon-intensive oil extraction and processing and fossil-fueled power generation versus shrinkage of the carbon-intensive manufacturing and growth of the low-carbon tertiarization. The theoretical analysis enables compartmentalization of the essential factors, which determine GHG emissions in the respective countries. To assess the significance of the proposed theoretical framework, the study employs multivariate panel co-integration techniques and two-stage fixed effects estimations for a dataset of 38 oil-producing countries for the time period between 1960 and 2018. In contrast to the existing literature, this study drives apart from the black box approaches that employ just one omnibus variable, per capita income.     

Linking of sample data to small areas

We consider methods for estimating the means of survey variables in domains of a finite population, where sample sizes are too small to obtain reliable direct estimates. We construct generalized compositions from the direct and traditional design-based synthetic estimators and propose the methodology for evaluating their coefficients. This methodology measures similarities among sample elements and estimates of the domain means. We propose the compositions for two cases of auxiliary information: domain-level characteristics are available; true means of auxiliary variables are available for the estimation domains, and unit-level auxiliary vectors are known for the sample elements. In the simulation study, we show where the generalized compositions improve the traditional synthetic and composite estimators.     

Does Country Risk Promote the Informal Economy? A Cross-National Panel Data Estimation

This article investigates whether country risk plays an important role in determining the size of the informal economy. Using annualized panel data for a sample of 131 countries and regions covering 1999–2007, and controlling for a set of control variables, we find that country risk is a robust and significant determinant of the informal economy: a 1% increase in the country risk rating (decrease in the country risk) causes a 0.1% fall in the informal economy, and political risk has the largest effect, followed by economic risk. Moreover, the estimation results provide little evidence in support of an inverted-U relationship between urbanization and the share of the informal sector, which shed new light on the urbanization-the informal economy nexus.     

On the strong uniform consistency of a new kernel density estimator

Summary A new multivariate kernel probability density estimator is introduced and its strong uniform consistency is proved under certain regularity conditions. This result is then applied particularly to a kernel estimator whose mean vector and covariance matrix areμ _n andV _n, respectively, whereμ _n is an unspecified estimator of the mean vector andV _n, up to a multiplicative constant, the sample covariance matrix of the probability density to be estimated, respectively. Work supported by the Natural Sciences and Engineering Research Council of Canada and by the Fonds F.C.A.R. of the Province of Quebec.     

Is demand-pulled innovation equally important in different groups of firms?

Previous empirical literature has tested the demand-pull hypothesisand found that innovation may be driven by output. Using a balancedpanel of 216 Italian manufacturing firms (1995–2000) andchecking for the path-dependent nature of R&D we find arole of sales in inducing R&D. However, the demand-pulleffect plays a varying role for different sub-samples of firms.Exporting firms, liquidity-constrained firms, unsubsidised firmsand those not heading a group seem to be sensitive to salesin deciding R&D. These results have been obtained usinga Least Squares Dummy Variable Corrected Estimator, a recentpanel-data technique suitable for small samples.