Subordinated Market Index Models: A Comparison

The paper compares various processes subordinated to the Wiener process tomodel the leptokurtic characteristics of index returns. Empirical analysisis performed on the Dow Jones and Nikkei 225 indexes. A good model to capturethe typical tail behaviour of these indexes turns out to be a long Studentt distributed one.     

Stock Return Predictability and Asset Pricing Models

This article develops an asset allocation framework that incorporatesprior beliefs about the extent of stock return predictabilityexplained by asset pricing models. We find that when prior beliefsallow even minor deviations from pricing model implications,the resulting asset allocations depart considerably from andsubstantially outperform allocations dictated by either theunderlying models or the sample evidence on return predictability.Under a wide range of beliefs about model pricing abilities,asset allocations based on conditional models outperform theirunconditional counterparts that exclude return predictability.     

A Market Efficiency Comparison of Islamic and Non-Islamic Stock Indices

This article examines the martingale difference hypothesis (MDH) and the random walk hypothesis (RWH) for nine conventional and nine Islamic stock indices: Asia-Pacific, Canadian, Developed Country, Emerging, European, Global, Japanese, UK, and United States. It investigates whether Islamic stock indices are more, less, or as efficient as their conventional counterparts. We test four sub-periods of bullish and bearish stock markets, together with the financial meltdown and its recovery, over the period 1997–2012. We use the Escanciano and Lobato’s (2009) automatic portmanteau test (AQ) and Deo’s (2000) test for the MDH. We also apply the automatic variance ratio test (AVR) developed by Choi (1999) and Kim (2009) for the RWH. Over the period from 1997 to 2012, we find that three conventional indices (Europe, Japan, and UK) are efficient, but that none of the Islamic indices are efficient in these markets. During the recent financial crisis, our results indicate slightly more efficiency for the Islamic indices than their conventional counterparts. Our study finds that overall the conventional indices are more efficient than their Islamic counterparts. Nevertheless, during periods of general downturns the Islamic indices have shown the same level of efficiency as their counterparts. Furthermore, it appears that during the last two sub-periods under study, the Islamic indices have moved toward efficiency, displaying the same level of efficiency as their counterparts.     

CAPM, Higher Co‐moment and Factor Models of UK Stock Returns

In this paper we examine the variables that explain the cross‐section of UK stock returns. Previous studies have found that the CAPM beta has moderate or even insignificant explanatory power once the Fama French factors are included. However, we control for different realised risk premia in up and down markets by using the same methodology as Pettengill, Sundaram and Mathur (1995). Unlike previous work, we find that beta is highly significant in explaining the cross‐section of UK stock returns and more importantly remains significant even when the Fama French factors are included in the cross‐sectional regressions. We also investigate whether higher co‐moments (co‐skewness and co‐kurtosis) have any explanatory power but find that empirical support is weaker.     

A Comparison of Alternative Forecast Models of REIT Volatility

This study compares the relative performance of several well-known models in the forecasting of REIT volatility. Overall our results suggest that long-memory models (ARFIMA & FIGARCH) provide the best forecasts. Using either a large sample or some statistically justified small subsamples, we find that long memory models consistently outperform their short-memory counterparts (GARCH & Stochastic Volatility models) over a variety of forecast horizons. We also find that asymmetric models (EGARCH & FIEGARCH) are the worst performers among all models. Our study complements and extends a recent study of Cotter and Stevenson (2008) which demonstrates the usefulness of long-memory models in modeling REIT volatility. We conclude that in addition to modeling REIT volatility, long-memory models should also be adopted to forecast REIT volatility.     

Common Stock Returns and Rating Changes: A Methodological Comparison

This paper examines the adjustments in a firm's common stock price during the eleven months before and during the month of announcement of a bond rating change. Based on several different measures of abnormal security return, the findings are consistent with the proposition that bond downgradings convey information to common stockholders. For bond upgradings, the price adjustments were statistically insignificant in the month of announcement, although in the eleven preceding months, upgraded firms exhibited positive abnormal returns. While the results do not fully support earlier research, we stress that the main contribution of this article lies in the scrutiny it gives to issues of methodology in assessing the possible price effects of bond reclassifications.     

三种合伙企业课税模式比较

三种合伙企业模式基于不同的理论认识，通过不同的处理机制与方法，反映出其差异。在一个具体国家在选择适用评税模式时，要充分考虑其特点，我国属实体课税模式，处于起步阶段，涉及的制度线条较粗，应作充实。     

理论比率模型与股票价值评估

本文以回收期模型为基础,探讨相对价值评估三大比率的理论模型,即理论市盈率、理论市净率和理论市销率模型。至今为止三大比率主要应用于相对价值评估,理论比率模型的建立连通了相对价值评估与绝对价值评估,有利于克服相对价值评估的主观随意问题,也有利于解决合理比率的标准确定和股市泡沫判断问题。     

Convertible Preferred Stock Valuation: Tests of Alternative Models

We undertake a comprehensive test of several contingent claim valuation models adapted to callable, convertible preferred stocks employing a sample of 24 issues and over 27,000 daily price observations. To our knowledge, no large-scale tests of these models have been published. The most complete model tested is an extension of the 1970s developments of Ingersoll and of Brennan and Schwartz, allowing for realistic contract features including delayed callability and nonconstant call prices. The mean and the mean absolute pricing errors are approximately –0.18 percent and 5.4 percent, respectively, and this model fits the data substantially better than the simpler alternatives that ignore such features. Thus, the added computational complexity required for the most complete model examined is evidently merited. Moreover, to the extent that the most complete model accurately mirrors reality, the evidence suggests that investors rationally account for many of the complex features imbedded in typical contracts.     

Accuracy of Premium Calculation Models for CAT Bonds—An Empirical Analysis

CAT bonds are of significant importance in the field of alternative risk transfer. Because the market of CAT bonds is not complete, the application of an appropriate pricing model is of high relevance. We apply different premium calculation models to compare them with regard to their predictive power. Without taking the financial crisis into account, a version of the Wang transformation model and the linear model are the most accurate ones. In contrast, under consideration of the financial crisis, all analyzed models are approximately equivalent. Furthermore, we find that CAT bond specific information does not improve out‐of‐sample results.     

Empirical Evaluation of Asset–Pricing Models: A Comparison of the SDF and Beta Methods

The stochastic discount factor (SDF) method provides a unified general framework for econometric analysis of asset–pricing models. There have been concerns that, compared to the classical beta method, the generality of the SDF method comes at the cost of efficiency in parameter estimation and power in specification tests. We establish the correct framework for comparing the two methods and show that the SDF method is as efficient as the beta method for estimating risk premiums. Also, the specification test based on the SDF method is as powerful as the one based on the beta method.     

Forecasting the Correlation Structure of German Stock Returns: A Test of Firm-Specific Factor Models

This paper evaluates the performance of various factor models with firm-specific variables in forecasting correlation matrices at the German stock market. We investigate forecasts of correlations for a comprehensive sample and a sample of blue chips and analyse the impact of stock market crashes on the forecasting accuracy. Our empirical results show that the multi-factor models do not generally produce better forecasts than 'naive' models. Specifically, the traditional industry mean model significantly outperforms all other techniques in most of the time periods.     

期权激励与企业并购行为

本文以2006年至2015年我国上市公司为研究对象,考察了期权激励对企业并购行为的影响。研究发现:授予高管的期权激励显著提升了企业发起并购的可能性和并购规模。缓解代理问题和提升风险承担是潜在的作用渠道。进一步研究表明,激励对象异质性会影响期权激励的效果,期权激励对企业并购倾向和并购规模的提升作用在管理者年龄较高、管理者任期较长以及管理者相对薪酬水平较低的企业中更加明显。此外,期权激励对企业并购行为的影响在非国有企业中更加突出。最后,本文还发现期权激励提升了企业并购的财务业绩。本文的研究不仅丰富了有关期权激励效果方面的文献,而且对于理解企业并购行为具有一定的参考意义。     

An Examination of Alternative Factor Models in UK Stock Returns

This paper examines the mean-variance efficiency of a number offactor models in UK stock returns. The paper also explores, using theapproach of MacKinlay (1995), whether missing risk factors ornonrisk-based explanations best explain the pricing errors of thedifferent factor models. The evidence in the paper suggests that themean-variance efficiency of each factor model is rejected and missing riskfactors are unable to explain the pricing errors of any of the models.Some nonrisk-based explanations, which posit a wide spread in abnormalreturns, may be a more plausible source of explaining the pricing errorsof the factor models.