融资融券对我国股市波动性的影响

本文采集股价指数月收益率和融资融券交易额每月日平均变化率的数据,针对融资融券对我国股市波动性的影响,进行实证检验,并对结果做进一步的解释。     

Stock Market Volatility and Learning

We show that consumption‐based asset pricing models with time‐separable preferences generate realistic amounts of stock price volatility if one allows for small deviations from rational expectations. Rational investors with subjective beliefs about price behavior optimally learn from past price observations. This imparts momentum and mean reversion into stock prices. The model quantitatively accounts for the volatility of returns, the volatility and persistence of the price‐dividend ratio, and the predictability of long‐horizon returns. It passes a formal statistical test for the overall fit of a set of moments provided one excludes the equity premium.     

Imperfect Information and Stock Market Volatility

The purpose of this paper is to (1) develop a model to show how imperfect information can create excess volatility in asset returns and (2) provide empirical evidence consistent with the model. In this framework, variations in information quality cause the market prices to fluctuate more than the corresponding economic fundamentals. Using high‐frequency data from 1988 to 2002, the empirical evidence supports the predictions of the model by showing that economic volatility, defined as squared deviations of the quarterly gross domestic product (GDP) growth rate from its long‐run trend, can explain about half of the variation in S&P 500‐stock index quarterly volatility.     

Stock Market Volatility and Economic Factors

This paper examines the ability of rational economic factors to explain stock market volatility. A simple model of the economy under uncertainty identifies four determinants of stock market volatility: uncertainty about the price level, the riskless rate of interest, the risk premium on equity and the ratio of expected profits to expected revenues. In initial tests these variables have significant explanatory power and account for over 50 per cent of the variation in market volatility from 1929 to 1989. When the regression coefficients are allowed to vary over time using cluster regression, the four factors explain over 90 per cent of the variation in market volatility. The results are useful in explaining the past behavior of stock market volatility and in forecasting future volatility.     

The Asymmetric Relation Between Initial Margin Requirements and Stock Market Volatility Across Bull and Bear Markets

Higher initial margin requirements are associated with lowersubsequent stock market volatility during normal and bull periods,but show no relationship during bear periods. Higher marginsare also negatively related to the conditional mean of stockreturns, apparently because they reduce systemic risk. We concludethat a prudential rule for setting margins (or other regulatoryrestrictions) is to lower them in sharply declining marketsin order to enhance liquidity and avoid a depyramiding effectin stock prices, but subsequently raise them and keep them atthe higher level in order to prevent a future pyramiding effect.     

Animal Spirits,Margin Requirements,and Stock Price Volatility

A simple overlapping generations model is used to characterize the effects of initial margin requirements on the volatility of risky asset prices. Investors are assumed to exhibit heterogeneous preferences for risk-bearing, the distribution of which evolves stochastically across generations. This framework is used to show that imposing a binding initial margin requirement may either increase or decrease stock price volatility, depending upon the microeconomic structure behind fluctuations in economy-wide average risk-bearing propensity. The ambiguous effect on volatility similarly arises when the source of heterogeneity is noise trader beliefs.     

An Unbiased Reexamination of Stock Market Volatility

Recent work demonstrates serious statistical problems with standard volatility tests. This paper proposes new tests that are unbiased in small samples and that do not require assumptions of stationarity. The new tests continue to find evidence against the model positing rational expectations and a constant required rate of return on equity.     

Expectations,Behavior, and Stock Market Volatility

Stock market volatility is caused by investors’ expectations and behavior. To study the implication relationship, on the one hand, we present an investor’s expectation-forming and decision-making model to summarize the key features of individual behavior. We think the individual expectation is determined mainly by the number of differences between positive signals and negative signals in the information flow. The behavior is determined by both the expectations of investors around him (her) and the expected returns from a potential action. On the other hand, we simulate an investor community to verify if the model is able to replicate the related stylized facts. Mainly, three conclusions are drawn from the simulation: (1) A relationship of asymmetrical conditional dependence exists between expectation consistency and behavior consistency. (2) Market volatility is caused mainly by the difference between expectation consistency and behavior consistency. As the density of connections in the investor community network increases, the difference between them grows. (3) Influential investors have profound impacts on the formation of normal investors’ expectations and behavior. Thus influential investors play an important role in determining the degree of market volatility.     

Price Limits and Stock Market Volatility in the Athens Stock Exchange

In this paper, we have examined the effects of price limits on the stock volatility in the Athens Stock Exchange. We put forward two hypotheses, the information hypothesis, which implies that price limits only slow down the process of adjustment and have no effect on stock volatility; and the over-reaction hypothesis, which assumes that investors tend to overreact to new information, so that price limits give them time to reassess the information and reduce stock volatility. Our results show strong support for the information hypothesis. This evidence is obtained by performing the tests on ten stocks, which include heavily traded stocks as well as less active stocks, and covering a variety of industries, and on a market wide price index. The results are also robust to the frequency of the measurement of the returns, and to the tightness of the limits.     

Macroeconomic Determinants of European Stock Market Volatility

In this paper we investigate whether macroeconomic variability can explain time variation in European stock market volatility. We find that unlike the documented case of the USA, in many cases, the time variation in stock market volatility is found to be significantly affected by the past variability of either monetary or real macroeconomic factors. Our findings have important implications for capital and portfolio allocations.     

央行汇率沟通与股票市场波动

本文基于2005年7月至2017年2月的日度数据,检验中国央行汇率沟通对于股票市场波动率的影响,研究结果发现:(1)央行汇率沟通会对本国股票市场产生明显的溢出效应,并显著增加股票市场的波动率,B股市场波动率反应程度显著强于A股市场。(2)书面沟通的效果强于口头沟通,口头沟通中行长沟通效果强于非行长沟通;汇率贬值的沟通效果显著强于汇率升值沟通。(3)汇率沟通对于股票市场波动率的影响存在着明显的非线性。     

股指期货的引入对现货市场波动的影响分析

本文研究沪深300股指期货引入后,对现货市场的影响以及股指期货是否有助于现货市场在信息传递速度与效率方面的提升.实证分析发现:在期指上市前,波动性干扰反应在时间上的持续性效果较持久;在期指推出后,可以观察到波动性干扰因素的影响会更快速地反应到现货市场股价指数中,此时的波动过程更趋稳定.由此推论出期货交易加速了现货市场信息传递的效率.     

货币政策、流动性溢价与股票市场波动

国内外大量研究表明货币政策与股票市场的波动有着千丝万缕的联系。本文基于固浮利差对货币政策进行了分解,采用事件研究法,分析了货币政策对股票市场波动的影响,并探索了货币政策对股票市场波动影响的传导途径。实证结果表明:第一,货币政策对股票市场波动率有负向的影响;第二,未预期的货币政策对股票市场收益率的变化有显著的负向影响;第三,未预期的货币政策对流动性资产的流动性溢价有显著正向影响;第四,准备金和政府债券的流动性溢价在未预期的货币政策对股票市场收益率的影响关系中具有中介效应。     

中国股市融资融券标的股票“异质性波动率之谜”研究

本文研究了中国A股市场融资融券标的股票的"异质性波动率之谜",分别在我国融资融券制度推行初期和后期,构建了两阶段的双重差分回归模型,比较融资融券制度的政策效果。实证结果表明,在融资融券制度推行初期,两融标的股票"异质性波动率之谜"现象未能得到有效抑制。融资融券制度推行后期,A股市场融券交易总量快速增长,融资融券标的股票的"异质性波动率之谜"现象相对非融资融券股票得到明显抑制,这一抑制效应对于融券交易活跃的股票更为显著,说明融券交易的活跃程度对于抑制融资融券标的股票"异质性波动率之谜"现象起主要作用。     

融资融券交易对市场和标的个股波动影响的研究

作为证券市场的重要制度之一,融资融券交易理论上应具有价格发现,价格稳定,提高流动性等基本功能。本文从融资、融券交易对市场和个股两个层面系统而全面的分析融资交易和融券交易的价格稳定作用。对市场波动性的影响的研究上主要借助GARCH族模型,VAR模型,脉冲响应和方差分解等计量分析方法;在对个股的影响上主要是借助面板数据分对个股的总体效应和个体效应展开分析。研究发现：融资交易对指数波动没有显著影响,融券交易对指数波动有一定平抑作用;融资融券交易对标的个股有价格稳定作用,除极个别个股的融资作用表现不确定。     

Stock Market Volatility in an Emerging Market: Further Evidence from the Athens Stock Exchange

We investigate the time series properties of the daily and weekly returns from the Athens Stock Exchange (ASE) index for the years 1987 to 1997. We investigate whether important time-series characteristics have changed significantly over time. The Greek market has recently undergone major changes including complete capital flow liberalization, the implementation of computerized trading, as well as significant increases in market volume and capitalization; we thus contrast the 1987–90 and 1991–97 periods. Our findings suggest the dynamics of the ASE composite index returns have changed as the market has developed.     

限制股指期货对股市波动性影响的实证研究

本文利用2013—2016年沪深300指数收盘价的日收益率数据,首先采用GARCH(1,1)模型,分析了在剔除融资融券变量之后,限制股指期货的政策对股市的波动影响,然后使用EGARCH(1,1)模型分析股指期货限制对股市非对称效应的影响,最后通过中证500、上证50股指期货收盘价数据和调整数据周期进行了稳健性检验。研究结果表明:限制股指期货的政策降低了股市的波动性,但加剧了股市的非对称效应。     

Market Structure and Return Volatility: Evidence from the Hong Kong Stock Market

There is no consensus about the cause for higher volatility at the market open than at the market close in the U.S. market. As an order–driven, nonspecialist market, the Hong Kong stock market provides a useful setting for an examination. If halt of trade were the major cause of higher open–to–open volatility, the open–to–open volatility in the Hong Kong market would be higher. However, this is not observed. The autocorrelation of the open–to–open return series also indicates that the temporary price deviation at the market opening is not significant. We view these findings as consistent with the specialist argument.     

The Differential Impact of Federal Reserve Margin Requirements on Stock Return Volatility

This study examines the effect of changes in margin requirements on stock price volatility. We examine the possibility that the impact of margin requirements varies with a stock's degree of speculative interest. Using four alternative measures of speculative interest, we divide our sample into ten portfolios. We find no consistent evidence of a relationship between margin requirements and changes in volatility for any portfolio. The inconsistent and often contradictory results produced by these changes question its usefulness by Federal Reserve decision makers.