The asymmetric effects of investor sentiment and monetary policy on stock prices

We examine the impact of investor sentiment and monetary policy on the stock prices under different market states based on the Markov-switching vector autoregression (MS-VAR) model. The results show that the sentiment shocks, more than monetary policy shocks, lead to not only much larger fluctuations of stock prices but also much longer duration in the stock market downturn than in the stock market expansion, which shows obvious asymmetric effect. Moreover, the responses of stock prices to the sentiment shocks present an immediate effect, while the responses of stock prices to the monetary policy shocks show one-period lag effect.     

Daily market news sentiment and stock prices

In recent years there has been a tremendous growth in readily available news related to traded assets in international financial markets. This financial news is now available through real-time online sources such as Internet news and social media sources. The increase in the availability of financial news and investor’s ease of access to it has a potentially significant impact on market stock price movement as these news items are swiftly transformed into investors sentiment which in turn drives prices. In this study, we use the Thomson Reuters News Analytics (TRNA) data set to construct a series of daily sentiment scores for Dow Jones Industrial Average (DJIA) stock index constituents. We use these daily DJIA market sentiment scores to study the influence of financial news sentiment scores on the stock returns of these constituents using a multi-factor model. We augment the Fama–French three-factor model with the day’s sentiment score along with lagged scores to evaluate the additional effects of financial news sentiment on stock prices in the context of this model using Ordinary Least Square (OLS) and Quantile Regression (QR) to analyse the effect around the tail of the return distribution. We also conduct the analysis using the seven-day simple moving average (SMA) of the scores to account for news released on non-trading days. Our results suggest that even when market factors are taken into account, sentiment scores have a significant effect on Dow Jones constituent returns and that lagged daily sentiment scores are often significant, suggesting that information compounded in these scores is not immediately reflected in security prices and related return series. The results also indicate that the SMA measure does not have a significant effect on the returns. The analysis using Quantile Regression provides evidence that the news has more impact on left tail compared to the right tail of the returns.     

Does mixed-frequency investor sentiment impact stock returns? Based on the empirical study of MIDAS regression model

We examine whether mixed-frequency investor sentiment affects stock returns. In line with recent evidence from China, we find that the aggregate effect and the individual effect of mixed-frequency investor sentiment are statistically significant, and mixed-frequency investor sentiment is more important than the low-frequency one. Moreover, mixed-frequency investor sentiment, which is mixed by high-frequency data, can be more important than the market premium.     

Investor sentiment,trading behavior and stock returns

This article examines how investor sentiment and trading behaviour affect asset returns. By analysing the unique stock trading dataset of the Korean market, we find that high investor sentiment induces higher stock market returns. We also find that institutional (individual) trades are positively (negatively) associated with stock returns, suggesting the information superiority (inferiority) of institutional (individual) investors. Investor sentiment generally plays a more important role in explaining stock market returns than investor trading behaviour.     

Investor sentiment,variance risk premium and delta-hedged gains

Delta-hedged gains are supposed to be negative and represent a volatility risk premium. Using a sample of Standard & Poor 500 index options from 2006 to 2009, this study documents two anomalies that cannot be explained by the volatility risk premium. First, delta-hedged gains are more negative for out-of-money options than for at-the-money options. Second, delta-hedged gains are significantly positive during financial crisis period. We propose a behavioural explanation in which both option prices and stock prices are affected by investor’s sentiment, but pessimistic sentiment has a greater impact on stock market than option market. This asymmetric response to pessimistic mood in turn affects the relative expensiveness of option prices.     

Understanding the recent performance of China's stock market

Employing time-series extrapolation and an out-of-sample forecast based on a bivariate VAR (vector auto-regression), we argue that the current boom of China's stock market represents a recovery that corrects the previous divergence of the stock market from the aggregate economic performance. Nevertheless, we caution that the speed of the recent rise in stock prices is alarming. If the current speed continues, then the stock market will soon become overheated in the sense that the level of stock prices will exceed the level justified by economic fundamentals.     

货币政策对资产价格冲击效果透视

文章在VECM模型的基础上,运用脉冲响应方法分析了股票市场在低迷时期和膨胀时期对不同货币政策冲击响应的效果。结果表明:货币政策可以有效地调节资产价格,在资产价格低迷阶段,用利率调节具有相对持久和明显的作用,金融机构贷款也在推动股票价格上涨中起到了一定的作用;在资产价格膨胀阶段,利率可在一定时期内起到微调作用,控制货币供应量可对价格泡沫的控制起到即时效果。     

The importance of fear: investor sentiment and stock market returns

The presence of investor sentiment pushes asset prices away from the equilibrium level justified by underlying fundamentals. While sentiment is not directly observable, identifying appropriate proxies and, quantifying the impact of sentiment on asset prices is an important topic. Asset prices that do not appropriately reflect fundamental values may result in inefficient allocation of capital – impacting portfolio allocation decisions and the cost of capital. Utilizing a number of sentiment proxies, over the period 1990–2015, we demonstrate a strong relationship between investor sentiment and stock returns that is consistent with theoretical explanations of sentiment. We determine that implied volatility index (VIX) is the preferred measure of sentiment in terms of improving model fit and adding explanatory power. Causality tests suggest that investor fear (VIX) drives returns across firm-size and value, and also across industry. We also illustrate that firms that are more subjective to value, or face limits to arbitrage, such as small-cap stocks, or those in the business equipment (technology) or telecoms industry, are most responsive to changes investor sentiment. Finally, we demonstrate that sentiment has a greater influence on market returns during recession, when sentiment is at its lowest ebb, and this is particularly true for those stocks most susceptible to speculative demand.     

Stock return autocorrelations and predictability in the Chinese stock market—Evidence from threshold quantile autoregressive models

This paper applies the threshold quantile autoregressive model to study stock return autocorrelations and predictability in the Chinese stock market from 2005 to 2014. The results show that the Shanghai A-share stock index has significant negative autocorrelations in the lower regime and has significant positive autocorrelations in the higher regime. It attributes that Chinese investors overreact and underreact in two different states. These results are similar when we employ individual stocks. Besides, we investigate stock return autocorrelations by different stock characteristics, including liquidity, volatility, market to book ratio and investor sentiment. The results show autocorrelations are significantly large in the middle and higher regimes of market to book ratio and volatility. Psychological biases can result into return autocorrelations by using investor sentiment proxy since autocorrelations are significantly larger in the middle and higher regime of investor sentiment. The empirical results show that predictability exists in the Chinese stock market.     

Threshold effect in the relationship between investor sentiment and stock market returns: a PSTR specification

This article verifies whether the hypothesis of heterogeneous agent modelling and the behavioural heterogeneity framework can reproduce recent stylized facts regarding stock markets (e.g. the 1987 crash, internet bubble, and subprime crisis). To this end, we investigate the relationship between investor sentiment and stock market returns for the G7 countries from June 1987 to February 2014. We propose an empirical non-linear panel data specification based on the panel switching transition model to capture the investor sentiment-stock return relationship, while enabling investor sentiment to act asymmetrically, non-linearly, and time varyingly according to the market state and investor attitude towards risk. Our findings are twofold. First, we show that the hypotheses of efficiency, rationality, and representative agent do not hold in reproducing stock market dynamics. Second, investor sentiment affects stock returns significantly and non-linearly, but its effects vary with the market conditions. Indeed, the market appears predominated by fundamental investors in the first regime. In the second regime, investor sentiment effect is positively activated, increasing stock returns; however, when their overconfidence sentiment exceeds some threshold, this effect becomes inverse in the third regime for a high threshold level of market confidence and investor over-optimism.     

Housing prices,stock prices and the US economy

This paper studies the relationship between housing prices, stock prices, interest rates and aggregate output in the US using monthly data from 1993 to 2014. Evidence from causality tests and a variance decomposition procedure suggest that stock prices have a much larger effect on aggregate output in the US economy than do either housing prices or interest rates. Instead, the wealth effect created by changes in stock prices has a relatively large impact on US aggregate output. Separate estimations and variance decompositions for the sample periods 1993–2001, 2002–2008 and 2009–2014 show that the impact of housing prices relative to stock prices has been waning over time.     

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.     

投资者情绪对资本市场稳定性的实证研究——来自截面效应的分析

文章借鉴心理学家在赛马赌博中发现的规律,对股票市场的截面效应进行了理论推测。同时,通过构建一个新的投资者情绪指标,采用非参数统计和回归模型实证检验了情绪指标的变动对特征组合收益率的影响并给出解释,并通过考虑系统风险的情绪变化与其他情绪代理变量验证了实证结果的稳健性。     

Published stock recommendations as investor sentiment in the near-term stock market

This paper investigates the role of published stock recommendations in print and online media as investor sentiment in the near-term German stock market. In line with extant literature on other sentiment measures, vector autoregressions reveal that past stock returns drive today’s sentiment, but not the other way around, and that sentiment is a powerful predictor of itself. In particular, sentiment based on printed analyst recommendations follows reversals, that is, when analysts face a stock market downturn, they see a buying opportunity and become optimistic.     

市场情绪如何影响城市房价

基于行为金融学理论建立了房地产情绪指数影响房价的模型，借鉴Baker and Wurgler（2006）提出的构建资本市场投资者情绪指数的方法，从供需两方选取合适的情绪指标；同时，运用大数据方法，选取百度指数作为情绪指标，运用主成分分析法构建了我国35个大中城市房地产市场的情绪指数，实证研究了市场情绪对房地产价格的影响。另外，还测度不同区域房地产市场情绪指数，通过实证分析横向对比东部和中西部城市市场情绪对房价的影响程度。实证结果表明，市场情绪对房地产价格有着显著的正向影响；市场情绪对房地产价格的正向影响呈现区域异质性，东部地区市场情绪对房地产价格的正向影响强于中西部地区。     

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.     

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.     

小议我国股市“财富效应”及其传导机制

本文阐明了财富效应对经济增长的作用机制，并针对财富效应传导机制，从股市规模、投资者结构及收益分配结构、股市持续变动趋势、“挤出效应”等方面分析我国股市财富效应尚很微弱的原因，由此对我国股市的健康发展给出了政策建议。     

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.     

Co-movements of Shanghai and New York stock prices by time-varying regressions

We use time-varying regression to model the relationship between returns in the Shanghai and New York stock markets, with possible inclusion of lagged returns. The parameters of the regressions reveal that the effect of current stock return of New York on Shanghai steadily increases after the 1997 Asian financial crisis and turns significantly and persistently positive after 2002 when China entered WTO. The effect of current return of Shanghai on New York also becomes significantly positive and increasing after 2002. The upward trend has been interrupted during the recent global financial crisis, but reaches the level of about 0.4–0.5 in 2010 for both markets. Our results show that China’s stock market has become more and more integrated to the world market in the past twenty years with interruptions occurring during the recent global economic downturn.