大规模高纬度金融资产的系统风险测量——基于动态条件异方差潜在因子模型的视角

从大量的金融资产中提取出的系统风险比基于β系数的单变量方法更为有效,但资产规模的增加会导致"纬数灾难"等问题,难以获得准确估计。本文在将金融资产收益分为公共系统因素和个体特质因素基础上,提出用具有条件异方差形式的动态潜在因子模型(CHDL)估计和预测动态系统因素,用非参数核密度估计系统下跌时的边际期望损失(MES)。本文利用上海证券市场180只样本股进行实证分析,通过IC和Onat检验发现个股和各板块存在显著的系统因子;利用CHDL模型对个股和各板块的系统因子和资产未来收益进行估计和预测,在此基础上计算边际期望损失。Mincer-Zarnowitz回归最优检验法表明,CHDL模型计算的系统风险比常用的市场指数模型具有更高的准确性。     

一种新型的计量型抽样检验方法——三样本检验法

许多公司的进料检验面临检验效率低下、检验价值丧失的困境,如何提升进料检验的效率并促进进料检验发挥有价值的效用是一个现实的课题。文章针对计量型质量特性所提出的三样本检验法是一种新型的计量型抽样检验方法,希望能够为帮助企业走出进料检验的困境发挥效用。     

股市收益波动的非对称性研究

随着我国股票市场的逐步发展及证券市场监管体制的逐步完善,股票市场收益波动所呈现的非对称性效应是否会发生逆转引人关注。本文运用不同的GARCH类条件异方差模型(EGARCH、TARCH、PARCH以及非对称CARCH模型),选取1998年1月5日至2006年11月6日上证综指的日收盘价格指数数据,分析和验证了股票收益波动的非对称性效应。结果表明,上海股市股票收益波动仍然具有非对称性,即利空消息对收益波动的冲击效应大于同等程度的利好消息,从而验证了非对称效应的不可逆转性。     

不确定条件下旅游投资决策分析方法的对比与应用

已有的基于风险的LCCBA中的收益概率模型构建需要较多的案例数据积累,而目前我国旅游投资决策分析总体上处于起步阶段,缺少相应的数据积累。本文对比分析各种现有投资决策分析方法之后,得出基于Shackle模型的不确定条件下的旅游投资决策方法更适用于我国当前的旅游投资分析,并通过Monte Carlo仿真的方法分析了该方法的有效性。不同于基于风险的LCCBA,该方法不需构建完整的收益概率模型,仅需估算出收益分布范围,就可以客观地对投资项目进行经济性分析,因而更适用于我国当前情况下的旅游投资决策分析。     

交易性金融资产处置业务的会计处理问题探讨

现行交易性金融资产的会计处理包括取得、持有、处置三个主要的阶段,本文主要对处置阶段相关业务账务处理规定进行阐述,分析了通过例举实例论述了交易性金融资产处置时存在的利润虚增或虚减以及混淆了持有利得与处置收益等问题,并针对存在的问题提出了在"公允价值变动损益"账户下增设二级科目及参照"可供出售金融资产"的账务处理两种改进建议。     

行业市场

泰国香米纯度检验标准5月1日起执行《泰国茉莉香米品种鉴定及纯度检验方法》行业标准于5月1日起执行，这是目前国际上首个公开发布的泰国香米纯度检验标准，涉及泰国茉莉香米品种鉴定和纯度检测的随机扩增多态性DNA技术检测法、感官检验法、水煮检验法等3种方法，将有效规范进口香米市场。     

多种单位根检验法的比较研究

本文基于单位根检验基本原理,比较了5种单位根检验的方法,说明在小样本情况下,为提高检验功效,应针对数据生成过程的特点联合多种检验法进行检验。如果检验变量为非平稳,则需要进行进一步的结构突变检验,本文主张选用结构突变点内生的Perron检验法与外生检验法相结合来判断变量的平稳性。     

贷款利率市场化与企业金融资产投资：抑制还是促进

选取2007—2017年我国沪深上市公司的数据,实证检验了贷款利率市场化对企业金融资产投资行为的影响。研究发现,贷款利率市场化显著推动了企业金融资产投资行为,这主要是因为贷款利率市场化使企业能够获取更多的长期资金用于金融资产投资。进一步研究发现：相对于金融资产投资较多的企业,贷款利率市场化对金融资产投资行为较少的企业具有更明显的促进作用;同时,贷款利率市场化使得企业更倾向于对长期金融资产的投资;宏观经济越不景气,贷款利率市场化越能促进企业金融资产投资,而货币政策宽松程度对二者关系并不存在显著影响。研究结论能够揭示贷款利率市场化与企业金融资产投资行为的关系,为进一步考察贷款利率市场化的经济后果以及更具针对性地防控实体企业“脱实向虚”风险提供新的微观层面证据。     

产品市场竞争、竞争地位与企业金融资产配置

实体经济"脱实向虚"的微观表现就是企业金融化,而产品市场竞争程度和企业所处的竞争地位无疑是影响企业金融化的一个重要因素。本文选取2007~2018年我国A股非金融类上市公司的经验数据为样本,实证检验了产品市场竞争程度和企业竞争地位对企业金融资产配置的影响。结论表明:产品市场竞争程度和企业竞争地位与企业金融资产配置均呈正相关关系,产品市场竞争的加剧和企业竞争地位的提升都会增加企业金融资产配置规模。进一步的分析还发现:企业竞争地位在产品市场竞争程度与企业金融资产配置的关系中起到了反向的交互作用,而且竞争地位高的企业更倾向于配置金融资产,市场套利动机是企业进行金融资产配置的主要动因。因此,应降低行业进入壁垒和行业集中度,加强对企业融资后资金去向的监管,缓解企业融资难融资贵困境,提高实体经济活动的投资回报率。     

确定金融资产收益率分布形式的一种方法

准确刻画金融资产收益率的分布函数是金融市场风险测量与管理的基础。本文在对证券收益率的正态性检验基础上，提出了确定金融资产收益率分布函数的一种方法——混合辨析法，并就两种混合正态分布的情形进行了仿真计算，最后利用柯尔莫哥洛夫拟合优度法对拟合收益率的曲线进行了检验。     

An intertemporal CAPM with higher-order moments

We propose an intertemporal asset pricing model that incorporates both preference for higher-order moments and stochastic investment opportunities and encompasses a wide range of existing models. We provide supporting evidence from the U.S. stock market and find that, not only is systematic skewness negatively priced, an extra return premium is also required for accepting high systematic risk associated with a rise in risk aversion. Our findings suggest that considering both skewness preference and intertemporal hedging demands improves the estimated risk-return trade-off, and that cross-sectional anomalies such as value, momentum, and failure probability puzzles can be partially explained by our model.     

Does conditional market skewness resolve the puzzling market risk-return relationship?

In this paper, we employ instrumental variables methods that allow time-varying risk and reward-to-risk to test various conditional asset pricing models. We find a negative partial relation between the market excess return and conditional market variance. In contrast with recent findings, we show that this negative relationship is not due to the omission of the hedge term associated with the ICAPM. However, conditional market skewness seems to partly account for this negative risk-return relationship.     

Exact Skewness–Kurtosis Tests for Multivariate Normality and Goodness‐of‐Fit in Multivariate Regressions with Application to Asset Pricing Models*

We study the problem of testing the error distribution in a multivariate linear regression (MLR) model. The tests are functions of appropriately standardized multivariate least squares residuals whose distribution is invariant to the unknown cross‐equation error covariance matrix. Empirical multivariate skewness and kurtosis criteria are then compared with a simulation‐based estimate of their expected value under the hypothesized distribution. Special cases considered include testing multivariate normal and stable error distributions. In the Gaussian case, finite‐sample versions of the standard multivariate skewness and kurtosis tests are derived. To do this, we exploit simple, double and multi‐stage Monte Carlo test methods. For non‐Gaussian distribution families involving nuisance parameters, confidence sets are derived for the nuisance parameters and the error distribution. The tests are applied to an asset pricing model with observable risk‐free rates, using monthly returns on New York Stock Exchange (NYSE) portfolios over 5‐year subperiods from 1926 to 1995.     

Asymmetric positive feedback trading and stock pricing in China

Defining asymmetry of feedback trading (AFC) as the difference between buying-winners and selling-losers intensities, the paper investigates if AFC impacts stock pricing. We show that buying stocks with low AFC and selling stocks with high AFC makes significant positive returns after controlling traditional pricing factors. The return mainly comes from the long leg and cannot be simply attributed to either mispricing, liquidity, or risk premium. Further study shows that the negative impact of AFC on future stock return is reinforced with an increase in past returns, maximum daily return, relative valuation level, asset growth rate, or operating profit rate. As AFC represents retail trading intensity, the results imply that the inactiveness of retail investors may make price relative underreaction to good news and thus lead to positive expected stock return.     

Asset prices with non-permanent shocks to consumption

Most standard asset-pricing models assume that all shocks to consumption are permanent. We relax this assumption and allow also for non-permanent shocks. In our specification, the long-run mean of consumption growth is constant; consumption levels are subject to short-run deviations from their long-run trend. The implications of our model are dramatically different from those obtained in the prior literature. A canonical and parsimonious asset pricing model with CRRA preferences and non-permanent shocks can reproduce the equity premium, high return volatility and return predictability with a coefficient of relative risk aversion below ten. This finding suggests that non-permanent shocks can play an important role in explaining asset pricing puzzles.     

Shock-dependent conditional skewness in international aggregate stock markets

This article uses the S_U-normal distribution to model the dynamic behavior of skewness in ten international aggregate stock indices—five indices each from developed and emerging markets. The conditional skewness process is specified as both autoregressive and dependent on lagged return shocks. Our primary result is that a negative return shock skews the time-varying distribution to the right for mature markets but to the left for emerging markets. In addition, we find that the asymmetry in volatility is noticeably larger in developed markets than in emerging markets. Finally, including the skewness process in modeling has no effect on the asymmetry and persistence in volatility obtained. These results are different from those of previous studies, which demonstrate the existence of both effects.     

Assessing skewness in financial markets

It is a matter of common observation that investors value substantial gains but are averse to heavy losses. Obvious as it may sound, this translates into an interesting preference for right-skewed return distributions, whose right tails are heavier than their left tails. Skewness is thus not only a way to describe the shape of a distribution, but also a tool for risk measurement. We review the statistical literature on skewness and provide a comprehensive framework for its assessment. Then, we present a new measure of skewness, based on the decomposition of variance in its upward and downward components. We argue that this measure fills a gap in the literature and show in a simulation study that it strikes a good balance between robustness and sensitivity.     

On compensation for risk aversion and skewness affection in wages

This paper presents extensive empirical testing of the hypothesis that greater post-schooling earnings risk requires higher expected returns. Expanding on this notion, on the basis of utility theory, we predict that workers not only care about risk but also about the skewness in the distribution of the compensation paid: workers exhibit risk aversion and skewness affection. To test these hypotheses, this paper carefully develops various measures of risk and skewness by occupational/educational classification of the worker and finds supportive evidence: for men, wages rise with occupational earnings variance and decrease with skewness, for women only the negative effect of skewness is significant.     

Skewness preference,mean–variance and the demand for put options

This paper compares the mean–variance and the mean–variance–skewness approaches to modelling expected utility. Attention is focused on a problem encountered in risk management: determining the optimal demand for a put option hedging the return on an asset with a negatively skewed return distribution. It is demonstrated theoretically that incorporating positive skewness preference into the decision‐maker's objective function typically produces a reduction in the demand for put options when compared with the mean–variance solution. A state‐dependent example is provided to illustrate how a mean–variance–skewness objective can result in a significant reduction in the optimal amount of crop insurance demanded when compared with the mean–variance solution. Copyright © 1999 John Wiley & Sons, Ltd.     

A much robust and updated evidences of the alternative real-estate based asset pricing

To response Harvey, Liu and Zhu’s and Gospodinov, Kan and Robotti’s criticism for an empirical study, we develop an alternative real-estate based model in asset pricing for an updated robustness. We make an innovation for the perspective of practitioners: the real-estate pricing factor is an alternative excess return of real estate portfolio. The results suggest that an updated and much robust role of the real-estate based asset pricing model: for example, the t-statistic of the real-estate pricing factor is higher than 3.00, suggesting that one is not derived from a data mining strategy. Moreover, we examine the performance of our alternative real-estate based model in a series of various portfolios (sorted in some vital anomalies); eventually, the results statistically support the real-estate based model.