CAPM模型在上海股票市场的有效性检验

根据资本资产定价模型(CAPM),从上海A股市场随机抽取100支股票,计算它们的收益率,选择上证综合指数为市场组合的市场指数,并利用双层回归分析方法对2007年1月1日至2011年12月31日这段时间的100支股票进行实证检验。虽然很多国外研究表明,CAPM模型在一定程度上能够解释市场收益,并在资产估价、资本预算、投资风险分析方面已经得到了广泛应用,同时也有利于投资者构建最优的证券投资组合,但本文实证研究结果发现,CAPM模型并不适合中国的股票市场,股票预期收益率和系统风险之间不仅不存在正相关的关系,而且也不存在线性关系,除了系统风险外,非系统风险在解释股票收益上也具有一定的作用。     

Forecasting multivariate realized stock market volatility

We present a new matrix-logarithm model of the realized covariance matrix of stock returns. The model uses latent factors which are functions of lagged volatility, lagged returns and other forecasting variables. The model has several advantages: it is parsimonious; it does not require imposing parameter restrictions; and, it results in a positive-definite estimated covariance matrix. We apply the model to the covariance matrix of size-sorted stock returns and find that two factors are sufficient to capture most of the dynamics.     

Stock returns and economic activity in mature and emerging markets

This paper empirically investigates the dynamic interdependencies between stock returns and economic activity in mature and emerging markets. The existence, kind and strength of potential uni-directional and/or bi-directional relations are examined, running from stock returns to future economic activity and/or from economic activity to future stock returns. A bivariate VAR(12) model is applied and Granger causality tests are performed. Monthly data covering the January 1991–December 2006 period are used. The existence of an empirical relationship, with forecasting ability, between stock returns and future economic activity is confirmed. The results are strongly differentiated between mature and emerging markets.     

Risk and return in the Tehran stock exchange

This paper analyzes market index returns in the Tehran stock exchange (TSE) within the context of three variants of the Capital Asset Pricing Model: the static international; the constant-parameter intertemporal; and a Markov-switching intertemporal CAPM, which allows for time-varying degree of integration with regional and international equity markets. We find that TSE returns are CAPM-efficient at monthly frequency with respect to several international market indices. Moreover, we find evidence in support of international integration of the TSE with respect to international markets. In addition, we conduct an extensive investigation for the direction of causality between TSE returns, international market index returns, and those in neighboring countries.     

行为资产定价模型的适用性研究

作为行为金融学主干的行为资产定价理论近些年来发展迅速。行为资产定价模型能否指导现实中的投资行为,取决于对行为资产定价模型的实证检验结果。本文利用我国证券市场数据对行为资产定价模型的适用性进行了检验,发现行为资产定价模型适用于股价上涨时期,而非股价下跌时期。     

Risk and return: CAPM and CCAPM

Can consumption growth risk (or consumption beta) serve a better measure of risk than market beta? This paper answers this question by testing and comparing the performance of the traditional Capital Asset Pricing Model (CAPM) and consumption-based CAPM (CCAPM) across seven financial market sub-sectors in the emerging Taiwan stock market. The empirical performance of the CAPM is encouraging. The relationship between stock returns and beta is statistically significant and the coefficient of determination of the regression is high across all of seven industry sub-sectors. In comparison, the CCAPM fails to explain the Taiwan stock market although the consumption beta should offer a better measure of systematic risk theoretically.     

Do short selling restrictions destabilize stock markets? Lessons from Taiwan

Short sellers have been routinely blamed for triggering, or exacerbating, stock market declines. The experience of Taiwan provides an interesting case study of the impact of short selling bans on stock returns volatility in a time series framework due to the length of time the short selling ban was in place there. Estimating several variants of an asymmetric GARCH model and a Markov switching GARCH model we find robust evidence that short selling restrictions raise stock returns volatility. The only qualifier is that the impact of short sale bans is a feature of the expansionary phase of business cycles. During recessions this effect dissipates.     

Non‐linear Predictability of UK Stock Market Returns*

Linear predictability of stock market returns has been widely reported. However, recently developed theoretical research has suggested that due to the interaction of noise and arbitrage traders, stock returns are inherently non‐linear, whereby market dynamics differ between small and large returns. This paper examines whether an exponential smooth transition threshold model, which is capable of capturing this non‐linear behaviour, can provide a better characterization of UK stock market returns than either a linear model or an alternate non‐linear model. The results of both in‐sample and out‐of‐sample specification tests support the exponential smooth transition threshold model and hence the belief that investor behaviour does differ between large and small returns.     

Do investments in intangible customer assets affect firm value?

This paper develops a simple model of investment by service firms in intangible customer assets, and tests whether the model identifies some critical drivers of firms’ stock returns. Similar to firms with significant research and development (R&D) expenditures, we argue that firms in fast-growing service industries with few tangible assets can increase firm value by investing in customer acquisition and service (A&S) expenditure. Using a unique hand-collected data set, we show that per-customer changes in firms’ revenues, customer acquisition costs, and customer service costs help to explain their abnormal stock returns.     

Cointegration tests of present value models with a time-varying discount factor

The paper analyses the impact of persistence and volatility in the discount rate in present-value models on cointegration tests in levels and in logarithms. In simulations we find that the probability of not rejecting the null of no cointegration depends on the persistence of the discount rate process and can be very high when the expected returns process is highly persistent. In contrast, the cointegration tests are very robust with respect to the level of volatility in the discount rate. We discuss the relevance of our findings for the US stock market where standard ADF tests do not reject the null of no cointegration between stock prices and dividends. Based on estimates of persistence in four asset pricing models, we find that a model which links expected returns to the dividend yield is sufficiently persistent to explain the failure of rejecting the null that stock prices and dividends are not cointegrated.     

The Information Content of Concurrently Announced Earnings, Cash Dividends, and Stock Dividends: An Investigation of the Chinese Stock Market

The firms listed on China's stock market are less than ten years old and to date there has been relatively little research on the usefulness of their accounting disclosures for investors. This study focuses on the information content of annual earnings and dividend announcements made by listed Chinese companies. Earnings, cash dividends, and stock dividends are announced concurrently in China and so this allows for tests of their information usefulness and of the interactions between the three signals. Based on a data set of up to 1,232 announcements, we find that unexpected earnings, proxied by earnings changes, are positively related to abnormal returns. Thus, earnings are used by investors in setting market prices. Stock dividends corroborate or attenuate the earnings signal. If the sign of the unexpected stock dividend (increase, decrease) is the same as the sign of the unexpected earnings, then the earnings signal is stronger. If the signs are opposite, the earnings signal is weaker. Unexpected cash dividends have little impact on the earnings signal. Stock dividends per se have a small association with stock returns. In contrast, cash dividends have no discernible association with stock returns and this is consistent with dividend irrelevance arguments. Our results are robust across a number of sensitivity tests.     

广义有效资本市场:财务理论的新视野

以深市1998-2006年的349家A股上市公司为样本,实证检验了广义有效市场假说(GEMH)的财务管理理论。广义有效市场假说用价格的分形引子来表示风险资产的收益;并把风险的定义从收益的方差或标准差复原为资本的耗散程度,从而用耗散资产定价模型(DAPM)来替代资本资产定价模型(CAPM);用双β财务政策理论来替代MM理论;而市场效率可以用给定市场的资本效率吸引子与其均衡市场的资本效率吸引子之间的比率来进行评价。     

Explanation for market response to seasoned equity offerings

In this paper, we use a multivariate framework to extend the recent univariate seasoned equity offering (SEO) research that investigated the valuation impact of inside ownership. Our multivariate findings re-enforce and add to the univariate findings as we show that the inside ownership level is a consistent factor in accounting for short-run and long-run returns around SEOs, while the decrease in inside ownership has no impact on short-run returns but influences long-run returns in a manner inconsistent with signaling theory. Compared to prior research, our regression tests do a much better job of accounting for returns associated with SEO announcements. For short-run regression tests, the four major factors associated with superior stock returns are: lower underpricing; greater profitability prior to SEO; lower inside ownership level; and, less stock price variability prior to SEO. For long-run regression tests, the four major conditions linked to superior returns are: greater profitability prior to SEO; smaller inside ownership level; relative size of the offering; and, greater decrease in inside ownership level.     

Co-determination of capital structure and stock returns—A LISREL approach: An empirical test of Taiwan stock markets

Titman and Wessels (1988) utilize a structural-equations model (LISREL) to find out the latent determinants of capital structure. Maddala and Nimalendran (1996) indicate that the problematic model specification causes the poor results in Titman and Wessels’ research. Chang, Lee, & Lee (2009) apply a Multiple Indicators and Multiple Causes (MIMIC) model to re-examine the same issue as Titman and Wessels did but found more convincing results. We extend Titman and Wessels’ research from using a single-equation approach to a multi-equations approach. In addition to the determinants of firms’ capital structure, those of stock returns are determined simultaneously. Literature indicates that a firm's capital structure may affect its stock returns (Bhandari, 1988), and the reverse is true too (Baker and Wurgler, 2002, Lucas and McDonald, 1990, Welch, 2004). Hence, a firm's determinants of its capital structure and those of its stock returns should be decided simultaneously, rather than independently. By solving the simultaneous equations, we examine the empirical relationship between the two endogenous variables: capital structure and stock returns and find out their common determinants as well. Our results show that stock returns, expected growth, uniqueness, asset structure, profitability, and industry classification are the main factors of capital structure, while the primary determinants of stock returns are leverage, expected growth, profitability, value and liquidity. The level of debt ratios and stock returns are mutually determined by the aforementioned factors and themselves.     

Cross-sectional tests of asset pricing models with full-rank mimicking portfolios

In the standard tests of asset pricing models, factor risk premia are estimated on a test asset span so that models are tested with degrees of freedom reduced by the number of factors. Risk premia of traded factors can be further restricted to be equal to their expected returns, but such restrictions cannot be imposed on models with nontraded factors, which may create a problem of testing without full restrictions or on unequal asset spans across models. We propose a full-rank mimicking portfolio approach by projecting nontraded factors onto a combined span of test assets and benchmark traded factors. Under the Hansen-Jagannathan distance framework, we demonstrate that full-rank mimicking portfolios can provide improved power and fair performance comparison against a benchmark model in both specification and model comparison tests.     

Economic policy uncertainty and stock market returns: New evidence

This paper investigates the predictive performance of the Chinese economic policy uncertainty (EPU) index constructed by Davis, Liu, and Sheng (2019) in forecasting the returns of China’s stock market. Using the univariate and bivariate predictive regression model, we confirm that the monthly EPU index can significantly and negatively impact the next month’s stock returns, and has better out-of-sample predictability than the existing EPU index and several macroeconomic variables. By comparing the forecasting effect of the EPU index before and during special events with sharply increased uncertainty, we find that the EPU’s forecasting power decline rapidly when an event of sharply increased uncertainty occurs. Finally, our conclusions are consistent through a batch of robustness tests.     

Mixed Hidden Markov Models for Longitudinal Data: An Overview

In this paper we review statistical methods which combine hidden Markov models (HMMs) and random effects models in a longitudinal setting, leading to the class of so‐called mixed HMMs. This class of models has several interesting features. It deals with the dependence of a response variable on covariates, serial dependence, and unobserved heterogeneity in an HMM framework. It exploits the properties of HMMs, such as the relatively simple dependence structure and the efficient computational procedure, and allows one to handle a variety of real‐world time‐dependent data. We give details of the Expectation‐Maximization algorithm for computing the maximum likelihood estimates of model parameters and we illustrate the method with two real applications describing the relationship between patent counts and research and development expenditures, and between stock and market returns via the Capital Asset Pricing Model.     

Nonlinear effects of monetary policy on stock returns in a smooth transition autoregressive model

This paper employs smooth transition autoregressive (STAR) models to investigate the nonlinear effect of monetary policy on stock returns. The change in the Federal funds rate is used as an endogenous measure of monetary policy, and the growth rate of industrial production is also considered in the model. Our results show that the relationship between the monetary policy and excess returns on stock prices is positive and nonlinear. A decrease in the Federal funds rate causes a larger increase in excess returns if excess stock returns are located in the extreme low excess returns regime.     

Interdependence between Eastern and Western European stock markets: Evidence from intraday data

We analyze comovements among three stock markets in Central and Eastern Europe and, in addition, interdependence which may exist between Western European (DAX, CAC, UKX) and Central and Eastern European (BUX, PX-50, WIG-20) stock markets. The novelty of our paper rests mainly on the use of 5-min tick intraday price data from mid-2003 to early 2005 for stock indices and on the wide range of econometric techniques employed. We find no robust cointegration relationship for any of the stock index pairs or for any of the extended specifications. There are signs of short-term spillover effects both in terms of stock returns and stock price volatility. Granger causality tests show the presence of bidirectional causality for returns as well as volatility series. The results based on a VAR framework indicate a more limited number of short-term relationships among the stock markets.     

Testing for linear and nonlinear granger causality in the stock price-volume relation: Korean evidence

In this paper, linear and nonlinear Granger causality tests are used to examine the dynamic relationship between daily Korean stock returns and trading volume. We find evidence of significant bidirectional linear and nonlinear causality between these two series. ARCH-ype models are used to examine whether the nonlinear causal relations can be explained by stock returns and volume serving as proxies for information flow in the stochastic process generating volume and stock returns respectively. After controlling for volatility persistent in both series and filtering for linear dependence, we find evidence of nonlinear bidirectional causality between stock returns and volume series. The finding of strong bidirectional stock price-volume causal relationships implies that knowledge of current trading volume improves the ability to forecast stock prices. This evidence is not supportive of the efficient market hypothesis. Another finding is that the nonlinear relationship is sensitive to institutional, organizational, and structural factors. The results of this study should be useful to regulators, practitioners and derivative market participants whose success precariously depends on the ability to forecast stock price movements.