消费者信心指数与股票市场收益的实证研究

基于行为金融学的视角，研究消费者信心和股票市场收益的互动关系，结果发现消费者信心指数与殷市收益具有较强的相关性。利用脉）辛响应和方差分解分析消费者信心与股市收益之间的互动关系，结果表明，消费者信心指数能预测一部分收益，股市收益与消费者信心指数间的冲击具有不对称性。     

Does investor sentiment dynamically impact stock returns from different investor horizons? Evidence from the US stock market using a multi-scale method

This article uses the investor sentiment index to investigate the Granger causality between investor sentiment and stock returns for the US economy using a multi-scale method. To focus on the local analysis of different investor horizons, bivariate empirical mode decomposition is used to decompose time series of investor sentiment and stock returns at different timescales. We employ the linear and nonlinear integrated Granger causality method to examine the causal relationship of decomposed series on similar timescales. The results indicate both strong bilateral linear and nonlinear causality between longer-term investor sentiment and stock returns. However, there is no strong evidence for correlation of stock returns and investor sentiment on shorter timescales.     

Consumer confidence and consumption expenditure in Indonesia

We estimate several competing regressions and find that confidence predicts consumption expenditure in Indonesia. Our estimations employ data on two measures of confidence, namely consumer and business confidence indexes, consumption and three standard predictors of consumption, namely labour income, stock price, and interest rate. We show that there are economic and statistical gains from consumption growth frameworks that account for consumer and business sentiments. Specifically, we show that policymakers can improve their forecast accuracy by between 4% and 13% by incorporating consumer and business sentiments into their forecasting frameworks.     

The Behaviour of Banking Stocks During the Financial Crisis and Recessions. Evidence from Changes‐in‐Changes Panel Data Estimations

This paper examines the impact of the financial crisis and economic recessions on bank shares compared to the overall stock market index for 18 OECD countries from 1993 to 2015. The empirical methodology utilizes the changes‐in‐changes approach. We compare and contrast the returns of the banking stock price index (treatment group) in each country with their general stock price index (control group), which experiences smaller changes. Our results suggest that bank returns on average perform significantly worse than that of the general stock price index during recessions. In addition, we also find significantly greater volatility in bank share returns.     

An analysis of the spillover effects of exchange-traded funds

This article used the Generalized Autoregressive Conditional Heteroscedasticity-Autoregressive Moving Average (GARCH-ARMA) and the exponentially Generalized Autoregressive Conditional Heteroscedasticity-Autoregressive Moving Average (EGARCH-ARMA) models to study the impact of the spillover and the leverage effects on returns and volatilities of stock index and Exchange Trade Fund (ETF) for developed and emerging markets. Previous unexpected returns for developed and emerging markets which have an opposite influence pattern on ETFs’ returns were identified. The spillover effects from returns are excellent for Hong Kong, followed by Singapore. Meanwhile, Taiwan's stock index return was recorded to have a strong negative impact on ETF return. Notably, this article shows that the spillover effects on stock index and ETF volatilities existed with bilateral influences. Despite a strong positive asymmetric volatility effect in Korea's ETF market, the leverage effect appears to play important roles in the explanation of both stock index and ETF returns.     

中国股票市场和债券市场收益率动态相关性分析

基于A股综合市场收益率和中信全债指数收益率数据来研究中国股票市场和债券市场收益率的动态相关性,并分析时变的股债相关性影响因素,以及在横截面上对股票收益率的定价影响进行考察后得知:股债相关性是时变的,股票市场的不确定性和预期通货膨胀率是影响股债相关性的主要因素;通过虚拟变量回归发现,股债相关性在横截面上对股票收益率的影响很小。这些结论对于投资者来说具有直接的现实意义。     

A nonlinear Granger causality test between stock returns and investor sentiment for Chinese stock market: a wavelet-based approach

In this article, we re-examine the causality between the stock returns and investor sentiment in China. The number of net added accounts is used as a proxy for investor sentiment. To mimic the different investment horizons of market participants, we use the wavelet method to decompose stock returns and investor sentiment into time series with different frequencies. Additionally, we test for nonlinear causal relationships based on Taylor series approximation. Our results indicate that there is a one-directional linear causality from stock returns to investor sentiment on the original series, while there is a strong bi-directional nonlinear causality between stock returns and investor sentiment at different timescales.     

A Study of Social Network Effects on the Stock Market

Consumer confidence is an economic indicator that measures the degree of optimism that consumers feel about the overall state of the economy as well as their personal financial situation. The authors measure consumer sentiment via analysis of social networks and show that such sentiment affects stock prices; specifically, the S&P 500 and the Dow Jones Industrial Average. Shiller, Fischer and Freidman [1984], Fisher and Statman [2003], and Bremmer [2008] also examine the influence of consumer sentiment, measured from Conference Board data, on the stock market. The authors add to this literature by creating a measure of consumer confidence by utilizing Twitter data and by examining the relationship between our measure of consumer sentiment and the S&P 500 and the Dow. They implemented lexicographic analysis of Twitter data over a three-month period and found that talk intensity of economic issues not only causes shifts in the daily stock market prices, but also has a significant negative effect.     

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.     

New Evidence on Psychology and Stock Returns

This article provides econometric evidence on the importance of psychological considerations for aggregate stock price fluctuations. To this end, a novel measure of stock market sentiment, dubbed the Net Psychology Index (NPI), based on information contained in Bloomberg News's end-of-the-day stock market reports, is confronted with a battery of multivariate empirical analyses. Results suggest that NPI is statistically different from popular sentiment proxies within the literature. NPI exhibits predictive power, increasing stock returns in the short run with this impact dissipating in the medium term. NPI does not exhibit asymmetric effects on returns for size- and momentum-related portfolios. A trading strategy based on NPI generates a statistically significant positive monthly return. Recursive out-of-sample fit analyses report a lower standard deviation of forecasting errors for NPI-based returns models versus competing accounts.     

我国期货价格风险管理研究——基于VaR方法与GARCH-t模型的视角

本文利用我国商品期货及金融期货2010年9月份合约数据采用VaR方法对其收益率序列的波动性进行了检验。研究结果发现:首先,应用GARCH-t模型的方法对期货商品的价格风险进行管理具有显著的有效性和适用性,特别是在95%的置信水平下对收益率波动性的拟合效果最佳,同时该方法对期货商品正收益率的拟合效果比负收益率更好。其次,我国股指期货正式推出后,收益率波动性较模拟交易时期显著变小,表明改进后的交易制度及政府监管等措施可能限制了市场上的过度投机行为。最后,农副产品期货的风险暴露程度比股指、金属和能源化工等期货品种要小。     

Changes in Investors' Market Attention and Near-Term Stock Market Returns

We use Google Search volume to track changes investors' positive and negative market attention. Our results support the hypothesis that this information reflects investors' optimistic and pessimistic anticipation and can be used to predict near-term future returns. We find that changes in negative search term volume of “market crash” and “bear market” and changes in positive search term volume “market rally” explain near-term stock returns. Changes in investors' attention are partly related to past stock market returns, implying that investors are prone to pay attention to possible price reversals. These measures of market attention are potential gauges of investor sentiment.     

How are gold returns related to stock or bond returns in the U.S. market? Evidence from the past 10-year gold market

Although the gold market over the past decade has been soaring relative to its prior history, there have been few studies on the relationship between the gold market and other major financial markets based on the past decade of data. To re-investigate how the gold market interacts with the stock market and the bond market, we re-visit economic and financial characteristics of gold using the past 10-year data in terms of co-integration, causality, predictive power, and extreme returns. We find that while gold returns are not co-integrated with stock returns and bond returns, gold returns have a unidirectional causality with both of them. Also, we discover that gold returns have some predictive power on subsequent short-term stock returns. Under extreme market scenarios, it turns out that gold returns tend to deteriorate more simultaneously with bond returns than stock returns. This means that gold can better serve as a safe haven for stock in a relative sense during temporary market downturns.     

Politics, stock markets, and model uncertainty

The available evidence on the effects of political variables on both returns and volatility of aggregate stock indices is scant and mixed. Applying Bayesian Model Averaging to a panel dataset of 17 parliamentary democracies spanning the post-war period until 1995, we test the robustness of political variables in explaining stock returns and stock return volatility. While we find that the influence of political variables on excess returns is weak, there is evidence of some political variables explaining return volatility.     

Time-varying relationship of news sentiment,implied volatility and stock returns

I examine the relationship between aggregate news sentiment, S&P 500 index (SPX) returns, and changes in the implied volatility index (VIX). I find a significant negative contemporaneous relationship between changes in VIX and both news sentiment and stock returns. This relationship is asymmetric whereby changes in VIX are larger following negative news and/or stock market declines. Vector autoregression (VAR) analysis of the dynamics and cross-dependencies between variables reveals a strong positive relationship between previous and current period changes in implied volatility and stock returns, while current period and lagged news sentiment has a significant positive (negative) relationship with stock returns (changes in VIX). I develop a simple trading strategy whereby high (low) levels of implied volatility signal attractive opportunities to take short (long) positions in the underlying index, while extremely negative (positive) news sentiment signals opportunities to enter short (long) index positions. The investor fear gauge (VIX) appears to perform better than news sentiment measures in forecasting future returns.     

From Returns to Tweets and Back: An Investigation of the Stocks in the Dow Jones Industrial Average

A sizeable percentage of investors are using social media to obtain information about companies (Cogent Research [2008]). As a consequence, social media content about firms may have an impact on stock prices (Hachman [2011]). Various studies utilize social media content to forecast stock market-related factors such as returns, volatility, or trading volume. The objective of this article is to investigate whether a bidirectional intraday relationship between stock returns and volatility and tweets exists. The study analyzed 150,180 minute-by-minute stock price and tweet data for the 30 stocks in the Dow Jones Industrial Average over a random 13-day interval from June 2 to June 18, 2014 using a BEKK-MVGARCH methodology. Findings indicate that 87% of stock returns are influenced by lagged innovations of the tweets data, but there is little evidence to support that the direction is reciprocal, with only 7% of tweets being influenced by lagged innovations of the stock returns. Results further show that the lagged innovations from 40 percent of stock returns affect the current conditional volatility of the tweets, while 73 percent of tweets affect the current conditional volatility of stock returns. Moreover, there is strong evidence to suggest that the volatility originating from the returns to the tweets persists for 33 percent of stocks; the volatility originating from the tweets to the returns persists for 73 percent of stocks. Last, 53 percent of stocks exhibit both immediate and persistent impacts from returns to tweets, while 90 percent of stocks exhibit both immediate and persistent impacts from tweets to returns. These results may help traders achieve superior returns by buying and selling individual stocks or options. Also, asset and mutual fund managers may benefit by developing a social media strategy.     

Industry-level determinants of the linkage between credit and stock markets

This paper examines the relationship between US credit default swaps (CDS) and stock returns on an industry-wide basis across a number of investment horizons, with particular focus on the major determinants of such a relationship. Wavelet analysis is first applied to extract the CDS–stock wavelet correlation for each US industry. Then, Bayesian Model Averaging is employed to identify the key driving factors of the industry CDS–stock wavelet correlations at short- and long-term horizons. The empirical results indicate that the wavelet correlations between the industry CDS and stock returns are primarily negative over time and across time scales. Moreover, the CDS–stock correlation at longer horizons exhibits a much more stable pattern than its counterpart at shorter time frames. The results also demonstrate that the volatility of US Treasury and stock markets, as measured by the MOVE and VIX indices, respectively, the volatility of volatility, as captured by the VVIX index, and US economic policy uncertainty, as measured by the EPU index, are the most robust determinants of the correlation between CDS and stock returns at shorter and longer horizons for most US industries. In contrast, the Fama–French systematic equity factors exhibit a practically negligible explanatory power on the CDS–stock link.     

Monopsony and discriminating monopsony in the nursing market

Theory suggests that equities are a good hedge against inflation. However, most of the empirical evidence for industrialized economies suggests that the relationship between stock returns and inflation is negative. One explanation is the negative correlation between inflation and real output growth. This paper examines the relationship between inflation and stock returns for ten important Emerging Stock Market (ESM) markets, namely, Chile, Mexico, Brazil, Argentina, Thailand, S. Korea, Malaysia, Hong Kong, Philippines and Turkey, during the 1990s. To anticipate the results, the relationship between stock returns and inflation, for the whole sample period, is positive and statistically significant for three of the sample ESMs, while it is positive (but statistically insignificant) for a further three. Only for one ESM is the relationship negative and statistically significant. This result may be due to the role of money and the positive relationship between consumer prices and output.     

非同步交易下股指期货与股票市场开收盘收益率间引导关系的实证研究

运用Granger因果检验、脉冲响应函数分析和方差分解,基于819组5分钟高频数据,对沪深300股指期货及其股票指数的开盘价格、收盘价格之间的引导关系进行检验。结果表明:期货市场与股票市场的开盘收益率相互引导;期货市场收盘收益率引导现货市场的收盘收益率和第二天开盘收益率;期货市场受自身和现货市场新息的冲击;现货市场受自身新息的冲击较大;期货市场对现货市场新息的变动更敏感;期货与现货的开盘收益率变化的总方差主要来自于现货市场,期货与现货的收盘收益率变化的总方差主要来自于期货市场。     

基于吉布斯抽样的我国股票市场周期性研究

本文使用一个两区制马尔可夫均值转换模型和贝叶斯吉布斯抽样非参数估计方法对深证成份指数月度收益率进行了实证分析。研究表明,我国股票市场收益率可以划分成两状态：“高收益状态”和“低收益状态”;市场的“高收益状态”总是发生在股票市场上涨阶段。