Stock Price and Volume Effects Associated with Compositional Changes in European Stock Indices

This paper provides further evidence of price and volume effects associated with index compositional changes by analysing the inclusions (exclusions) from the French CAC40 and SBF120 indices, as well as the FTSE100. I find evidence supporting the price pressure hypothesis associated with index fund rebalancing, but weak or no evidence for the imperfect substitution, liquidity and information hypotheses. The results improve on recent evidence from the S&P500 index. The evidence for the FTSE100 additions shows, in particular, that markets learn about an imminent inclusion and incorporate this information into prices, even before the announcement date.     

中国A股量价之间动态关系的实证研究

本文采用了VAR模型以及Granger因果检验的方法来考察量价之间的动态相关关系。我们选定1996年12月16日至2008年12月31日作为样本研究区间,实证发现滞后期的交易量和收益对当前期交易量与收益的解释力度存在下降趋势;同时,交易量同收益之间由收益对交易量的单向引导发展为双方互为Granger原因。本文得到的交易模式的动态演变轨迹反映了我国投资者式逐步趋于理性成熟。     

Nonparametric Estimation of a Multifactor Heath-Jarrow-Morton Model: An Integrated Approach

We propose a new nonparametric estimator for the volatilitystructure of the zero-coupon yield curve inside the Heath-Jarrow-Mortonframework. The estimator incorporates cross-sectional restrictionsalong the maturity dimension, and also allows for measurementerrors, which can arise from estimation of the yield curve fromnoisy data. The estimates are implemented with daily CRSP bonddata.     

中国A股量价之间动态关系的实证研究

本文采用了VAR模型以及Granger因果检验的方法来考察量价之间的动态相关关系.我们选定1996年12月16日至2008年12月31日作为样本研究区间,实证发现滞后期的交易量和收益对当前期交易量与收益的解释力度存在下降趋势;同时,交易量同收益之间由收益对交易量的单向引导发展为双方互为Granger原因.本文得到的交易模式的动态演变轨迹反映了我国投资者式逐步趋于理性成熟.     

股票价格"虚拟"问题的研究

从现代市场经济的视角看,股票作为一种能够为投资者带来一定收入的资本所有权证书,是最典型的虚拟资本形式。作为虚拟资本的股票价格不外乎是一种与利息率相关的股息收入的资本化。由于利息率是股票价格一个决定性因素,致使股票价格与利息率相关性极强,而与其净资产的高低相关性较弱。因此,在证券市场上,股票价格往往高于其真实价格(每股净资产价值),从而具有了“虚拟”成分。这样,股票价格虚拟运动便成为一种独特的经济范畴。为此,只有注重对股票价格虚拟的合理范围的判断,确定出股票价格可投资的界限,才能以价值投资的理念,引导市场的投资行为,促进中国股市健康发展。     

The Impact of Information Release on Stock Price Volatility and Trading Volume: The Rights Offering Case

This paper examines whether information released via rights offering announcements induces changes in price volatility and trading volume of underlying stock. The results of this paper provide support for the release of new information via offering announcements and evidence of its effects on price volatility and volume of underlying stock. Specifically, utilization of the announced information by investors is evidenced by greater trading volume following the announcement date than during the pre-announcement period. We interpret this result to mean that informedness dominates consensus. However, stock price volatility decreased from the pre-announcement period to the post-expiration period of rights offerings.     

Nonparametric Estimation of State-Price Densities Implicit in Financial Asset Prices

Implicit in the prices of traded financial assets are Arrow–Debreu prices or, with continuous states, the state-price density (SPD). We construct a nonparametric estimator for the SPD implicit in option prices and we derive its asymptotic sampling theory. This estimator provides an arbitrage-free method of pricing new, complex, or illiquid securities while capturing those features of the data that are most relevant from an asset-pricing perspective, for example, negative skewness and excess kurtosis for asset returns, and volatility "smiles" for option prices. We perform Monte Carlo experiments and extract the SPD from actual S&P 500 option prices.     

Clustering in US Stock Prices after Decimalisation

Early in 2001, US equity markets transitioned from trading in discrete price fractions to a smoother decimal format with a tick size of one penny. Theory suggests in an unconstrained world, stock prices should be distributed uniformly, particularly if the cost of defeating time priority is low. This regime change provides a natural experiment to test whether investors prefer to trade at particular price points even when their choices are essentially unconstrained by regulation. Instead of uniformity, we find widespread evidence of price clustering at increments of five and ten cents (nickels and dimes); the overall magnitude of clustering is double in scale of what is otherwise expected. Previous studies which documented clustering around even‐eighths argued that these patterns were a rational market response to trading impediments. We report consistent findings, but also find that the overall level of post‐decimalisation clustering is far more extensive than is reasonably explained by prior hypotheses. The evidence instead suggests a more fundamental human bias for prominent numbers as discussed in the psychology literature. Contrary to previous studies, we find no difference in price clustering, ceteris paribus, between the Nasdaq and NYSE after decimalisation. Should regulators choose to revisit the notion of tick size, our evidence suggests that for many stocks there would be only minor impact between the transaction prices that prevail now and those that would occur if the tick size were increased to five cents.     

Drift Estimation of Generalized Security Price Processes from High Frequency Derivative Prices

This paper presents a framework for using high frequency derivative prices to estimate the drift of generalized security price processes. This work may be seen more generally as a quasi-likelihood approach to estimating continuous-time parameters of derivative pricing models using discrete option data. We develop a generalized derivative-based estimator for the drift where the underlying security price process follows any arbitrary state-time separable diffusion process (including arithmetic and geometric Brownian motion as special cases). The framework provides a method to measure premia in derivative prices, test for risk-neutral pricing and leads to a new empirical approach to pricing derivative contingent claims. A sufficient condition for the asymptotic consistency of the generalized estimator is also obtained. A study based on generating the S&P500 index and calls shows that the estimator can correctly estimate the drift parameter. This revised version was published online in November 2006 with corrections to the Cover Date.     

A Primer on Piecewise Parabolic Multiple Regression Analysis via Estimations of Chicago CBD Land Prices

This article proposes a non-parametric method for estimating spatial price functions. Space is divided into squares. The independent variables are barycentric coordinates that uniquely describe the location of observations in space. The regression coefficients are estimates of the height of the function directly over the vertices of the square spatial units. Within each square the function has hyperbolic iso-price curves and parabolic sections. The price function is continuous, but not differentiable, at the boundaries between contiguous squares. This method is applied to the problem of describing the price per front foot of land in the Chicago CBD. A rather complex price surface is revealed that would be difficult to estimate using other methodologies but was easily estimated by this simple method.     

投资者异质后验信念对股票价格影响的实证研究

过度自信程度不同的投资者因消息确认精度差异引起意见分歧,产生异质后验信念,导致投资者对股价高估或者低估。在此基础上,以盈余公告信息作为利好或利空消息,研究不同环境下异质后验信念对我国股票价格的影响。实证结果表明:不管在牛市还是在熊市环境下,异质后验信念均会对股价产生影响,当盈余公告为利好消息时,异质后验信念程度越高,当期股价被高估的程度越显著;当盈余公告为利空消息时,异质后验信念程度越高,当期股价被低估的程度越显著。此外,在盈余公告前投资者就对盈余消息作出了反映,但对好消息与坏消息的反映程度不同。     

Aggregation of Nonparametric Estimators for Volatility Matrix

An aggregated method of nonparametric estimators based on time-domainand state-domain estimators is proposed and studied. To attenuatethe curse of dimensionality, we propose a factor modeling strategy.We first investigate the asymptotic behavior of nonparametricestimators of the volatility matrix in the time domain and inthe state domain. Asymptotic normality is separately establishedfor nonparametric estimators in the time domain and state domain.These two estimators are asymptotically independent. Hence,they can be combined, through a dynamic weighting scheme, toimprove the efficiency of volatility matrix estimation. Theoptimal dynamic weights are derived, and it is shown that theaggregated estimator uniformly dominates volatility matrix estimatorsusing time-domain or state-domain smoothing alone. A simulationstudy, based on an essentially affine model for the term structure,is conducted, and it demonstrates convincingly that the newlyproposed procedure outperforms both time- and state-domain estimators.Empirical studies further endorse the advantages of our aggregatedmethod.     

IFRS Adoption and Stock Prices of Japanese Firms in Governance System Transition

This study examines firms' decision to voluntarily adopt IFRS in a setting where there are changes to the governance system in a traditionally code law country, as well as how the market responds to such decisions. We find the probability of voluntary IFRS adoption to be higher among firms that have a high proportion of foreign shareholders, undertake quality audits, have low levels of leverage, feature a nominating committee, and are included in the new market index. In addition, the stock prices of IFRS adopters tend to increase around the announcement date of IFRS adoption, compared to those of non-adopters. Finally, market reactions are smaller for firms that feature a nominating committee, and are included in the new market index—perhaps because IFRS adoption by these firms is less surprising to market participants, and because IFRS adoption is not expected to add large incremental value to these firms.     

Option Volume and Stock Prices: Evidence on Where Informed Traders Trade

This paper investigates the informational role of transactions volume in options markets. We develop an asymmetric information model in which informed traders may trade in option or equity markets. We show conditions under which informed traders trade options, and we investigate the implications of this for the linkage between markets. Our model predicts an important informational role for the volume of particular types of option trades. We empirically test our model's hypotheses with intraday option data. Our main empirical result is that negative and positive option volumes contain information about future stock prices.     

利率与股价之间的价格溢出效应与波动溢出效应

基于具有外生变量的二元VAR-MGARCH模型对中国货币市场利率和股价之间的关联进行了理论分析和实证研究。结果表明,利率和股价之间基本不存在价格溢出效应;货币市场利率和股价序列均表现出时变方差的特征和波动的持久性特征,货币市场和股市之间存在双向波动溢出效应;货币供给的正向冲击对利率的影响是正向的。     

The Effect of Tick Size on Price Clustering and Trading Volume

Proposals have been made for some stock exchanges to reduce the size of their trading tick in order to lower transactions costs and, as a result, attract more trading volume and firm listings. We investigate the impact of tick size on price clustering and trading volume when the minimum price change varies with price level. Controlling the firm specific variables, we find that a smaller trading tick tends to exacerbate price clustering. Furthermore, a reduction in tick size is more likely to increase trading volume if the shares are heavily traded. These results suggest that previous studies on other stock markets may have overstated the benefits of a smaller trading tick to traders.     

Fundamental Real Estate Prices: An Empirical Estimation with International Data

We propose two alternative models to estimate fundamental prices on real estate markets. The first model is based on a no-arbitrage condition between renting and buying. The second model interprets the period costs as the result of market equilibrium between housing demand and supply. We estimate both models for the USA, the UK, Japan, Switzerland, and the Netherlands. We find that observed prices deviate substantially and for long periods from their estimated fundamental values. However, we find some evidence that, in the long-run, actual prices tend to return to their fundamental values progressively. This result is due to both impulse–response functions and forecast analyses. In particular, we find that using the fundamental price significantly increases the accuracy of out-of-sample long-term forecasts of the price.

投资者分歧、异常交易量和股票横截面收益率预测——基于中国股票市场的经验证据

本文定义月度异常交易量为本月与上个月交易金额的比值,发现中国市场月度收益率与滞后一个月的异常交易量显著负相关。在控制了公司规模、账面市值比、流动性以及动量效应等指标后仍然具有显著的解释作用。进一步研究表明,在出现高异常交易量后的12个月内,换手率和特质性波动率都有大幅上升。本文认为,交易量上升代表着市场分歧程度和受关注程度的增加,在卖空约束下会使得股票价值高估,从而造成未来收益率下降。     

Testing the bivariate mixture hypothesis using German Stock market data

According to the bivariate mixture hypothesis (BMH) as proposed by Tauchen and Pitts (1983) and Harris (1986, 1987) the daily price changes and the corresponding trading volume on speculative markets follow a joint mixture of distributions with the unobservable number of daily information events serving as the mixing variable. Using German stock market data of 15 major companies the distributional properties of the BMH is tested employing maximum-likelihood as well as generalised method of moments estimation techniques. In addition to providing a new approach for the pointwise estimation of the latent information arrival rate based on the maximum-likelihood method, we investigate the time-series properties of the BMH. the major results can be summarised as follows: (i) the distributional characteristics of the data (especially leptokurtosis and skewness in the distribution of price changes and volume respectively) cannot be explained satisfactorily by the BMH; univariate mixture models for price changes and trading volume separately reveal a possible specification error in the model; (ii) a univariate normal mixture model can account for the observed distributional characteristics of price changes; (iii) the estimated process of the latent information rate cannot fully explain the time-series characteristics of the data (especially the volatility clustering or ARCH-effects).