基于多视角的我国东北三省工业产业结构趋同问题研究

产业结构调整是加快经济发展的核心问题,是经济高速增长的基本推动力量。因此深入研究地区产业结构趋同问题,对于地区产业结构调整以及产业结构高级化发展具有重要意义。本文利用东北三省合并后23个工业产业2001～2014年的工业总产值数据,通过产业结构相似系数、区位熵以及β趋同系数多角度分析东北三省工业产业结构趋同问题。从发展方向看,我国东北三省合并后23个工业产业相似系数最高的是辽宁和黑龙江省,最低的是吉林和黑龙江省,从专业化水平及总量和发展速度关系看,东北三省工业产业在农副食品加工业、交通运输和通用设备制造业形成了区域优势,但在低附加值、产业链低端的开采业以及劳动密集型产业上还存在不同程度趋同,并提出东北三省工业产业在转型升级中应当重点发展高加工度、高附加值等产业,避免产业间的低端雷同的政策建议。     

Assessing time-varying stock market integration in Economic and Monetary Union for normal and crisis periods

In this paper, we examine the stock market integration process amongst 17 Economic and Monetary Union (EMU) countries from January 2002 to June 2013 over a normal period as well as for the Global Financial Crisis (GFC) and Eurozone Debt Crisis (EDC) periods. We classify the economies in three groups (A, B and C) based on their GDP to examine whether the economic size influences financial integration. Seven indicators are used for the purpose, namely, beta convergence, sigma convergence, variance ratio, asymmetric DCC, dynamic cointegration, market synchronisation measure and common components approach. The results suggest that large-sized EMU economies (termed as Group A) exhibit strong stock market integration. Moderate integration is observed for middle-sized EMU economies with old membership (termed as Group B). Small-sized economies (termed as Group C) economies seemed to be least integrated within the EMU stock market system. The findings further suggest presence of contagion effects as one moves from normal to crisis periods, which are specifically stronger for more integrated economies of Group A. We recommend institutional, regulatory and other policy reforms for Group B and especially Group C to achieve higher level of integration.     

On the two-sided power distribution

This paper concerns a two-parameter two-sided power distribution introduced by van Dorp and Kotz on the interval [0,1]. We introduce a reformulated two-sided power distribution (with the same number of parameters) and provide evidence to prove that it is more flexible than the one suggested by van Dorp and Kotz. We derive various properties of the new distribution as well as provide several hitherto unknown properties of the distribution due to van Dorp and Kotz. We also discuss estimation by the method of moments and the method of maximum likelihood.Received September 2003     

Risk Interpretation of the CAPM's Beta: Evidence from a New Research Method

This study tests the validity of using the CAPM beta as a risk control in cross‐sectional accounting and finance research. We recognize that high‐risk stocks should experience either very good or very bad returns more frequently compared to low‐risk stocks, that is, high‐risk stocks should cluster in the tails of the cross‐sectional return distribution. Building on this intuition, we test the risk interpretation of the CAPM's beta by examining if high‐beta stocks are more likely than low‐beta stocks to experience either very high or very low returns. Our empirical results indicate that beta is a strong predictor of large positive and large negative returns, which confirms that beta is a valid empirical risk measure and that researchers should use beta as a risk control in empirical tests. Further, we show that because the relation between beta and returns is U‐shaped, that is, high betas predict both very high and very low returns, linear cross‐sectional regression models, for example, Fama–MacBeth regressions, will fail on average to reject the null hypothesis that beta does not capture risk. This result explains why previous studies find no significant cross‐sectional relation between beta and returns.     

Risk factors in Australian bond returns

This study examines the risk factors in Australian bond returns. The study quantifies bond liquidity and estimates a liquidity risk factor in the Australian setting. We develop a three‐factor asset pricing framework that uses term, default and liquidity risk factors to explain the variation of Australian bond returns. Our findings corroborate the US evidence on the pervasiveness of these risk factors faced by bond investors. The three‐factor model developed in this study has practical applications when calculating the cost of debt, evaluating the performance of an active bond fund manager and hedging underlying risk in a bond portfolio.     

A Tale of Two Anomalies: Higher Returns of Low‐Risk Stocks and Return Seasonality

Prior studies have shown that low beta and low volatility stocks earn higher average returns than high beta and high volatility stocks, contradicting the prediction of the capital asset pricing model and the fundamental relationship between risk and return. In this paper, we demonstrate that this phenomenon is driven by the seasonality of stock returns. We show that the risk‐return tradeoff does hold in the nonsummer months, and that switching to a portfolio of low‐risk stocks in summer outperforms—both in terms of absolute and in risk‐adjusted returns—buy and hold strategies as well as the Sell in May strategy of switching to treasury bills in summer.     

Preparing for higher inflation: Portfolio solutions using U.S. equities

Investors have always been interested in reducing inflation risk in their portfolios. However, investors face different types of inflation than those measured by the Consumer Price Index (CPI). Moreover, different asset classes can be used to hedge portfolio inflation. In this paper, we show how individual equities can be used to construct equity portfolios sensitive to customized inflation targets. We illustrate portfolios for three types of inflation: US headline CPI, Forbes Cost of Living Extremely Well Index, and the US Medical Care Price Index. We also show how alternative weighting schemes, such as minimum volatility and maximum inflation beta, can be used to construct inflation‐hedged portfolios.     

Does High Service Quality Reduce Risk or Create Idiosyncratic Returns?

This article explores the impact of service quality on idiosyncratic returns, idiosyncratic risk (nonsystematic risk), and beta (systematic risk). Service quality was derived from the airline quality rating, and three dependent variables were calculated by the Fama–French four-factor model. The data includes 1,512 monthly records from 1997 to 2006, across 21 airlines. Multiple regression and vector autoregressive models were applied to test relationships among all, low-cost, and non-low-cost airlines. The study found that service quality has a positive impact on idiosyncratic returns in non-low-cost airlines; non-low-cost airlines are less affected by changes in the external environment.     

The extent of nonstationarity of beta

This paper investigates the extent of nonstationarity of beta across the firm size and the beta magnitude by suggesting the sequential parameter stationarity model and estimating change-points of betas. The high-beta firm has shorter stationary interval, which means that its beta changes more frequently than do the low-beta firm's. The firm size, however, does not have a monotonic relation with the length of stationary interval. The small and large firms have relatively shorter stationary interval than do the mid-sized firms. The average length of stationary interval is estimated about five years (exactly 54.19 months). This fact could support the currently widely-used arbitrary 5-year assumption of beta stationarity. The fluctuation of the large firm's beta is more severe than the small firm's, and the high- and low-beta firms have the relatively greater fluctuating betas than do the mid-beta firms. The frequency of detected change-points is found to be positively related to market returns. When the market return is high, the systematic risk changes more frequently, and vice versa.     

Is Beta Dead or Alive?

The debate about whether beta is dead or alive has heated up once again. We believe the empirical work supporting either side of the argument is limited because market frictions are not adequately addressed. This study clarifies the controversy about the issue by creating a new moving-average beta and analyzing two market anomalies: the turn-of-the-year and the Monday effects. What is discovered in this research is (1) that a fundamental source of the problem underlying the two types of market anomalies is the persistence of market frictions that retard the arbitrage process; (2) that beta is seriously ill if the effects of market frictions are ignored; and (3) that beta is alive and well if the effects of market frictions are accommodated. Also, we show, by using an optimal lead/lag structure, the moving-average beta provides significantly higher explanatory power for the turn-of the-year and the Monday effects than betas created from ordinary least squares regression and Scholes-Williams and Fama-French methods because the moving-average beta accommodates the effects of market frictions into the body of beta itself. This new type of beta, a moving-average beta, is demonstrated to be robust.