上市公司、资本虹吸与房价的地区差异

鉴于上市公司与房价地区差异的研究鲜见,文章首次从地区层面寻找上市公司影响房价的微观传导路径.研究发现,上市公司从一级市场上融资、内部人在二级市场上减持均会"虹吸"全国资金,增加当地货币资本,进而正向影响房价,即高融资或高减持地区成为"虹吸方";融资虹吸与减持虹吸对房价的影响存在差异,减持虹吸引起财富集聚,对房价的影响更多地由富裕阶层的购房需求所推动,而融资虹吸带来的财富影响比较分散.地区股票市值与房价呈现螺旋增长关系,在股市上涨期间替代效应占主导地位,两者的增长率负相关;而在下跌期间财富效应占主导地位,两者的增长率正相关.文章从企业层面阐释了房价地区差异的金融成因及路径,并试图厘清股票市场与房价的增长结构,为地区经济的协调发展提供了参考.     

Capital flows to an emerging financial market in Turkey

Increased globalization in financial markets implies that the percentage of all shares under foreign ownership in domestic stock markets has been rising. Speculative attacks on the foreign exchange market in February 2001 led to deep economic crisis in Turkey. This article will explore various indicators of the financial crisis in Turkey based on a macro-model. The foreign share of the domestic economy is a key variable to establish the degree of vulnerability during a financial crisis. An empirical investigation shows that the percentage of shares owned by foreigners on the Istanbul Stock Exchange (ISE) has been increasing since 1995 and is currently about 50 percent of the total. Furthermore, the general index of stock market prices in 1999 was at its highest level since 1995. This would imply that the general price index of the stock market is another strong indicator of an impending financial crisis. An empirical investigation of Turkish data based on a theoretical model is presented in this paper. An unexpected capital outflow would certainly cause exchange rate fluctuations, balance of payments problems, and international debt crisis. Hot money inflows boost share prices and keep the real exchange rate high. However, short-term stay of capital implies a sudden capital outflow that creates financial crisis, which results in international debt crisis. This in turn leads to a further increase in loans from the International Monetary Fund (IMF). Relatively high stock market prices may suggest an impending financial crisis. Using Turkish stock market price data, an impending financial crisis can be statistically predicted.     

我国资产价格波动与货币政策关系研究

随着金融自由化的逐步推进,资本市场存量日益增大.这既体现了金融深化程度的提高,又意味着货币供应与国民经济主要指标之间稳定性的弱化.资产价格对货币政策的制订和执行会产生深刻的影响.其中股价、房价等资产价格在货币政策传导机制中扮演的角色越来越重要.本文从实证角度出发,通过构建VAR模型检验我国资产价格对货币政策的反应以及资产价格对货币政策目标的影响,发现资产价格、货币政策及货币政策目标间存在长期协整关系,资产价格对产出有正向冲击作用,股市显著影响通货膨胀,但房地产市场对通货膨胀推动作用不明显,资产价格受货币政策的冲击影响显著,其中股市对货币政策冲击的反应明显大于房地产市场.     

Informed trade,uninformed trade and stock price delay

The probability of informed trading (PIN), a measure of information-based trading risk, has been broadly applied to empirical studies on asset pricing. However, it is still controversial whether PIN measures exclusively the risk of firm-specific private information or it also captures the private interpretation of market wide public information. This article examines the relevance of PIN to the delayed response of stock prices to market-wide information. We find that PIN significantly explains individual stock price delay even controlling for size, liquidity and risk, and low-PIN stock prices adjust to market information more rapidly not only because of a notably high level of informed trading but also an even much higher level of uninformed trading. Our findings support the notion that PIN also captures the private skilled interpretation of public common factor information by sophisticated investors, and provide new empirical evidence on how information-based trading affects the speed at which stock prices adjust to information.     

Finance–Growth Nexus and the P‐bias: Evidence from OECD Countries

Recent studies provide new empirical evidence confirming that financial development is linked to economic growth in OECD countries. Using new dynamic panel regression techniques, these appraisals indicate that within the group of high‐income countries stock market size as a measure of financial advancement contributes significantly to overall economic activity. Applying the same advanced techniques, this paper questions this conclusion by showing that the findings of these studies seem to be not only not robust with respect to adding new observations but also likely to be plagued by a severe price bias which belittles the information content of the used financial indicator (stock market capitalization). We provide evidence that anticipative price effects (i.e. expectations of future growth, reflected in current stock prices) may be driving the statistical relationship between stock market activities and economic growth in high‐income countries to a much larger extent than recent analyses of the finance– growth link in OECD countries suggest .     

Oil price risk in the Spanish stock market: An industry perspective

This study examines the sensitivity of the Spanish stock market at the industry level to movements in oil prices over the period 1993–2010, paying special attention to the presence of endogenously determined structural changes in the relationship between oil price changes and industry equity returns. The empirical results show that the degree of oil price exposure of Spanish industries is rather limited, although significant differences are found across industries. The oil price sensitivity is very weak in the 1990s, a period of fairly stable and low oil prices. Instead, the link between crude oil and stock prices seems to have increased during the 2000s, becoming primarily positive. This evidence highlights the key role played by aggregate demand-side oil price shocks associated with the global real economic activity in the link between oil price fluctuations and the Spanish stock market.     

The effect of oil prices on stock prices: fresh evidence from asymmetric causality tests

This article investigates the causal impact of oil prices on stock prices in each G7 market as well as in the world market. An asymmetric causality test developed by Hatemi-J is used for this purpose. Since the underlying data appears to be non-normal with time-varying volatility, we use bootstrap simulations with leverage adjustments in order to produce more reliable critical values than the asymptotic ones. Based on symmetric causality tests, we find no causal effect of oil prices on the stock prices of the world market or any of the G7 countries. However, when we apply an asymmetric causality test, we find that increasing oil prices cause stock prices to rise in the world, the U.S. and Japan while decreasing oil prices cause stock prices to fall in Germany. This may imply that the world, the U.S. and Japanese stock markets consider increases in oil prices as an indicator of good news as this may mean that there is an increase in oil demand due to an expected growth in the economy while the German stock market treats decreasing oil prices as a signal of an expected contraction in the economy.     

The Relationship Between Economic Factors and Equity Markets in Central Europe

This paper investigates the possibility that newly-emerging equity markets in Central Europe exhibit semi-strong form efficiency such that no relationship exists between lagged values of changes in economic variables and changes in equity prices. We find that while there are connections between the real economy and equity market returns in Poland and Hungary, these links occur with lags, suggesting the possibility of profitable trading strategies based on public information and rejecting semi-strong efficiency. For the Czech Republic the situation is more complex. In recent periods, little connection exists between lagged economic variables and equity market returns. Although this finding might be viewed as consistent with semi-strong efficiency, in fact there is also little connection between current economic values and stock prices in the Czech Republic. Thus, instead of processing information efficiently, the Czech market appears to be entirely divorced from the real world. It is suggested that the difference in the current status of these markets may be due to the different methods by which they were created.     

Asset prices and economic fluctuations: The implications of stochastic volatility

This paper investigates whether the multi-factor stochastic volatility of stock returns is related to economic fluctuations and affects asset prices. We address these issues in a dynamic Fama-French three-factor volatility model framework. Consistent with the ICAPM with stochastic volatility (Campbell et al., 2017), we find that the conditional volatility of the size and value factors is significantly related to economic uncertainty. These volatilities are also significant pricing factors. The out-of-sample forecasting analysis further reveals that the conditional volatility can predict stock returns and deliver economic gain in asset allocation. Our analysis sharpens the understanding on the link between the stock market and economic fundamentals.     

The cross-section and time-series effects of individual stock sentiment on stock prices

In this article, we construct an individual stock sentiment index by using the principal component analysis method. We empirically study the cross-section and time-series effects of investor sentiment on the stock prices based on the panel data model with dummy variable. The results indicate that individual stock sentiment has greater impact on small-firm stock prices than big-firm stock prices, which presents obvious cross-section effect. Moreover, individual stock sentiment leads to much sharper ?uctuations of stock prices in the stock market downturn than in the stock market expansion, which shows obvious time-series effect. Specifically, the individual stock sentiment has the greatest impact on small-firm stock prices under the stock market downturn, exerting significant dual asymmetric effect. Our results are helpful to understanding the micro-mechanism of sentiment effect.     

Information and adjustment in a local housing market

Existing studies on bubbles have been mainly concerned with investigating the stationarity properties of stock prices and market fundamentals. We develop a new method of testing for bubbles that relates the bubble component of stock prices to the probability of bursting in the context of the Weibull distribution. There were several eruptions and subsequent collapses of seeming bubbles over the past three decades: 1987 (Black Monday), 2000 (information technology (IT) boom) and 2007 (housing market boom). Using US monthly data for the S&P 500 and NASDAQ series, we have found that the S&P 500 series contained an explosive bubble only during the boom of the housing market that occurred before the 2007 global economic crisis, and the NASDAQ market contained an explosive bubble during the surge of stock prices peaking in 1987 and 2007, although our stationarity tests fail to detect the bubbles. No bubble was found in both the S&P and NASDAQ series during the 2000 IT boom. Our evidence corroborates the criticism that the traditional unit root and cointegration tests may not be able to detect some important class of bubbles.     

中国股票价格与房地产价格关联性研究

国际经验表明,房地产价格和股票价格的剧烈震荡之间存在紧密联系,一旦价格泡沫破灭,将给整体经济造成严重后果甚至导致经济衰退.近年来,我国房价虚高,股价大起大落,给经济发展带来了一系列不利影响.在这种背景下,揭示两者之间的内在联系对于抑制资产价格泡沫,促进股票市场和房地产市场健康发展非常必要.本文运用时间序列相关方法对我国股票市场与房地产市场的关系进行了实证研究,结果表明:房地产价格上涨对股票价格上升有显著影响,而股票价格上涨对房地产价格上升的影响较为微弱;房地产价格的上升与股票价格的上升存在两季左右的间隔,且两者呈现出螺旋式变化的趋势.对此,本文分析了产生这种现象的原因并提出了一些政策建议.     

Market Underreaction and Overreaction of Technology Stocks

Several studies have assessed stock market under- or overreaction of stocks and there is some agreement among them. However, there is much disagreement about what constitutes market underreaction or overreaction, and the conditions that cause it. The substantial variation in results among studies may be partially attributed to the types of firms that are contained in any sample. We investigate this premise by focusing on a sample of technology stocks that experienced an extreme change in stock price, along with a corresponding control sample of non-technology stocks that experienced a similar extreme change in stock price on the same day.

Based on the subsequent stock price behavior of each sample, we find a greater degree of overreaction within extreme positive changes in technology stock prices (winners) than in non-technology stock prices. In addition, we find a greater degree of underreaction within extreme negative changes in technology stock prices (losers) than in non-technology stock prices. When considering winners and losers collectively for technology and non-technology firms, it appears the market is overoptimistic when it initially revalues technology stock prices relative to non-technology stock prices.

The degree of under- or overreaction of technology stocks varies within the sample of technology stocks, and is conditioned on firm-specific characteristics. Overall, our results suggest that technology stocks exhibit unique stock price behavior subsequent to an extreme change in price, and that this unique behavior can even vary among technology firms according to firm-specific characteristics.     

Oil shocks,policy uncertainty and stock returns in China

This paper examines the interdependence of China's policy uncertainty, the global oil market and stock market returns in China. A structural VAR model is estimated that shows that a positive shock to economic policy uncertainty in China has a delayed negative effect on global oil production, real oil prices and real stock market returns. Shocks to oil market‐specific demand significantly raise China's economic policy uncertainty and reduce the real stock market returns. As measured by a spillover index, the interdependence between these variables has been rising since 2003 as China's influence in the oil market has increased. An equivalent spillover index calculated for the US is smaller and has been largely flat over time.     

Does the stock market affect investment by Chinese firms? Some new evidence

During the 1990s, the Chinese government increasingly relied on the stock market as the major tool for state‐owned enterprise (SOE) reform and for the allocation of investment resources. This paper investigates the impact of stock market development in China on firm‐level capital investment by using a panel data set constructed by the author of all Chinese listed firms for the period 1992 to 1999. The results show that stock market valuation, as measured by Tobin’s q, has a highly independent, significant and positive influence on listed firms’ investment decisions, particularly during the stock market boom from 1996 to 1999. Given the sizable real effects of the stock market, deviations of stock prices from fundamentals can have substantially negative consequences. As a result, this study suggests that sensible regulation of the Chinese stock market is needed in order to enhance the efficiency of stock prices and facilitate an effective channeling of investment funds.     

The dark side of the black gold shock onto Europe: One stock's joy is another stock's sorrow

This paper examines the impact of the current oil prices fall on Europe. We estimate a Bayesian shrinkage VAR model and analyse the impulse response functions to investigate the reaction of European stock markets to the current oil prices collapse. Using data covering the March 2002 to May 2014 period, our main result is that European stock markets are negatively and significantly affected by the crude oil shock. We prove that this result is robust to reasonable changes in the Bayesian shrinkage VAR model of the variables order and inclusion of additional variables. The findings shed light that common features exist among the European stock markets. Furthermore, the results highlight that the most exposed stock market is the French one, and that the least affected market is the Austrian one.     

送转与定向增发：基于市值管理的视角

送转和定向增发是 A 股市场上常见的两种公司行为。文章旨在从市值管理的视角，揭示上市企业送转与定向增发的内在关联及其经济逻辑。研究发现：(1)定向增发企业送转的比例与规模显著高于配对的未增发企业，而且两者的差异在增发后显著大于增发前；(2)在有外部机构投资者参与的定向增发中，企业送转的比例与规模显著高于其他类型的定向增发；(3)企业送转行为会显著影响增发折价，增发后送转企业的增发折价显著低于增发前送转(从未送转)的企业。文章研究表明，送转是 A 股市场上定向增发企业广为使用的一种市值管理手段，送转的规模与时机是企业与外部投资者理性博弈的结果。文章的研究不仅从市值管理角度为我国资本市场上频频出现的上市公司高送转行为提供了经验证据，而且对于监管层制定与送转和定向增发相关的政策具有重要的参考价值。     

Do market prices aggregate information about macroeconomic uncertainty (or risk)?

This article examines several economic variables that represent either confidence in future economic conditions or the degree of risk/uncertainty about future conditions in order to determine which contain more information about future employment and output. Some of these variables are prices, while others are from surveys. Causality tests, historical decompositions within a VAR and out-of-sample forecasts are among the tools used. This article concludes that monthly stock returns contain much more information about future economic conditions than the other variables. The spread between Moody’s BAA and AAA bonds, the spread between the constant maturity 10-year government bond and the federal funds rate, as well as uncertainty in future economic conditions as measured by the Federal Reserve Bank of Philadelphia’s Business Outlook Survey also provide information about future economic conditions. Notably, this article finds that monthly stock returns contain more information about future economic conditions than does the vix and that variables based on market prices provide more information than survey data. This result provides some support for the notion that market prices aggregate information.     

A time series analysis of causality between aggregate merger and stock prices: the case of Canada

It is widely agreed that a positive relationship exists between measures of aggregate merger activity and measures of stock market performance, at least for the USA. Evidence from other countries is relatively sparse. in this paper we pursue the causality question using Canadian data. Most of the previous studies used only a bivariate system (merger and stock prices). We have extended the analysis to trivariate system (merger, stock prices and interest rate) to better reflect the capital market conditions argument for changes in merger activity. The results suggest a bidirectional causality between mergers and stock prices.     

Does measurement error matter in volatility forecasting? Empirical evidence from the Chinese stock market

Based on methods developed by Bollerslev et al. (2016), we explicitly accounted for the heteroskedasticity in the measurement errors and for the high volatility of Chinese stock prices; we proposed a new model, the LogHARQ model, as a way to appropriately forecast the realized volatility of the Chinese stock market. Out-of-sample findings suggest that the LogHARQ model performs better than existing logarithmic and linear forecast models, particularly when the realized quarticity is large. The better performance is also confirmed by the utility based economic value test through volatility timing.