市场择时理论的中国适用性--基于1998～2003年上市公司的实证分析

自2002年Baker和Murgler明确提出市场择时理论以来,传统资本结构理论的解释力度受到一定程度的质疑,国外学者围绕这一新兴的资本结构理论展开激烈的争论.文章运用1998年1月1日～2003年12月31日间中国沪深两市IPO公司财务数据试图第一次较为全面地检验市场择时理论在中国的适用性.实证结果表明在样本期内中国上市公司确实存在着股票融资和债务融资的市场择时行为;债务融资的市场择时行为并不显著影响中国上市公司的资本结构,而股票融资的市场择时行为短期内显著影响公司的资本结构;股票融资的市场择时行为不具有持久影响资本结构的效应,总的说来,市场择时理论并不适用于中国的上市公司.     

自由现金流量、并购溢价与我国上市公司并购绩效的实证研究

国内外的研究结果表明高自由现金流量低成长性公司在并购后绩效会出现明显的下滑,并把绩效下滑归因于代理成本。文章力图在自由现金流量与并购绩效之间搭建一座桥梁,深入分析导致并购绩效下滑的直接客观原因。通过利用我国上市公司2001-2003年436次并购事件进行实证分析的结果表明,支付过高的并购溢价是导致高自由现金流量低成长性上市公司并购绩效低下的直接客观原因。     

Effects of cohort size on college premium: Evidence from China's higher education expansion

In this paper, we document the lesser-known heterogeneous trends of college/non-college earnings premium across age groups from 1995 to 2013 in China. Specifically, the college premium in 2013 for the younger group (age 25–34) was about 30 percentage points, similar to the level in 1995, while the college premium in 2013 for the older group (age 45–54) increased to 50 percentage points, nearly double that of 1995. To attribute these divergent trends of the college premium to the changes in the relative size of college workers, we use the model by Card and Lemieux (2001), which incorporates imperfect substitution between similarly educated workers in different age cohorts. Due to the distinctions of these trends in China, our identification is free of the overestimation issue that the existing studies suffer. Our results are similar to those in the U.S., U.K., Canada, and Japan. Holding the age cohort and survey year constant, a one unit increase in log relative size of college workers is associated with about 10 percentage points decrease in college/non-college premium and about 18 percentage points decrease in college/high school premium. We further find that the negative effect is much more substantial among the new entrants (age 25–29) than experienced workers (age 30–54). By this pattern, we demonstrate that the new labor market entrants are more sensitive to their own cohort size and argue that the confounding ability composition effect should not be a serious issue.     

Sentiment-scaled CAPM and market mispricing

This study explores the conditional version of the capital asset pricing model on sentiment to provide a behavioural intuition behind the value premium and market mispricing. We find betas (β) and the market risk premium to vary over time across different sentiment indices and portfolios. More importantly, the state β derived from this sentiment-scaled model provides a behavioural explanation of the value premium and a set of anomalies driven by mispricing. Different from the static β–return relation that gives a flat security market line, we document upward security market lines when plotting portfolio returns against their state βs and portfolios with higher state βs earn higher returns.     

Which institutional investor types are the most informed?

We examine the informativeness of quarterly disclosed portfolio holdings across four institutional investor types: hedge funds, mutual funds, pension funds and private banking firms. Overweight positions outperform underweight positions only for hedge funds. By decomposing holdings and stock returns, we find that hedge funds are superior to other institutional investors both at picking industries and stocks and that they are better at forecasting long‐term as well as short‐term returns. Furthermore, our results show that hedge funds, mutual funds and pension funds are able to successfully time the market. The outperformance of hedge funds is not explained by a liquidity premium.     

Effect of Participation of Foreign Migrant Workers in Labour Market on Native Workers: Evidence Based on Change Noticed in College Premium in Taiwan ROC

Using Manpower Utilization Survey data for 14 years from 1999 to 2012, we applied the DDDD (Differences–in–differences–in–differences–in–differences) estimation method to check if rising presence of foreign migrant workers in Taiwan’s domestic labour market had any impact on employment opportunities and wages earned by native Taiwanese workers over time. We used the data capturing the effect of college premium (viz., the additional cost to be borne for getting admission into college) paid by the natives on domestic wage rate during this period. College premium is an indicator of demand and supply for educated labour and we intend to see if the premium has grown with time when influx of foreign migrant workers has grown too. From the results, two interesting phenomena caught our attention. First, labour policy adopted by the Government in Taiwan has played an important role in increasing the influx of foreign workers into domestic labour market, which resulted in significant change in college premium paid by the natives. And, this effect lasted even when instances of strikes and reported cases of labour disputes were relatively higher. Second, the effect of the policy has been varying across genders as our data shows that policy on employment of foreign workers has affected job opportunities of native men workers more than it affected job opportunities of their female counterpart.     

An application of two-stage quantile regression to insurance ratemaking

Two-part models based on generalized linear models are widely used in insurance rate-making for predicting the expected loss. This paper explores an alternative method based on quantile regression which provides more information about the loss distribution and can be also used for insurance underwriting. Quantile regression allows estimating the aggregate claim cost quantiles of a policy given a number of covariates. To do so, a first stage is required, which involves fitting a logistic regression to estimate, for every policy, the probability of submitting at least one claim. The proposed methodology is illustrated using a portfolio of car insurance policies. This application shows that the results of the quantile regression are highly dependent on the claim probability estimates. The paper also examines an application of quantile regression to premium safety loading calculation, the so-called Quantile Premium Principle (QPP). We propose a premium calculation based on quantile regression which inherits the good properties of the quantiles. Using the same insurance portfolio data-set, we find that the QPP captures the riskiness of the policies better than the expected value premium principle.     

Equity premium prediction and optimal portfolio decision with Bagging

We propose using the statistical method of Bagging to forecast the equity premium out-of-sample for multivariate regression models. Bagging allows for the flexible and efficient extraction of valuable informational content from a large set of predictors, leading to statistically and economically significant gains relative to not only the historical mean, but also other soft-threshold methods such as forecast combinations and shrinkage estimators in our empirical results. Furthermore, we find that the source of economic gains for Bagging primarily comes from the fact that it encourages the investor to actively manage portfolio by flexibly utilizing short selling or leveraging to better time the market following correctly prognosticated trends. However, other strategies such as forecast combinations keep the equity shares nearly fixed regardless of the predicted market prospect.