Daily happiness and stock returns: The case of Chinese company listed in the United States

Existing literature exclusively focuses on the association between local investor sentiment and local stock market performance. In this paper, we investigate the contemporaneous and the lead-lag relationship between local daily happiness sentiment extracted from Twitter and stock returns of cross-listed companies, i.e., the Chinese companies listed in the United States. The empirical results show that: 1) by respectively controlling for the firm capitalization, liquidity and volatility, there exists the largest skewness on the Most-happiness subgroup. (2) There exist bi-directional relationships between daily happiness sentiment and market variables, i.e., the stock return, range-based volatility and excess trading volume. (3) There are significantly positive stock returns, higher excess trading volume and higher range-based volatility around the daily happiness sentiment spike days. These findings not only suggest that there exists significant interdependence between online activities and stock market dynamics, but also provide evidence for the existence of “home bias”.     

Spillovers of volatility index: evidence from U.S., European,and Asian stock markets

We investigated the cross-market relations of volatility indexes with U.S. and non-U.S. stock market returns. We found that the pervasive VIX influence at both U.S. and non-U.S. stock markets. The VSTOXX and VKOSPI capture the major shocks to the global economy and show movements similar to the VIX. The empirical findings indicate that volatility index changes are important in explaining stock returns. We also examined spillover effects across volatility indexes. The VIX is a main transmitter, and the VKOSPI the main receiver, of these spillovers. The results point to a leading role for the VIX in the international market.     

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.     

中国封闭式基金价格报酬过度波动的经验分析

本文研究了中国封闭式基金价格报酬与净资产报酬的数据特征及其影响关系 ,主要的结果是 :( 1 )中国封闭式基金的价格报酬相对于基金的净资产报酬一方面存在过度波动 ,另一方面又存在反映不足 ;( 2 )通过检验表明 ,投资者情绪风险对价格报酬过度波动具有显著的影响 ,而Fama的三因素风险因子对价格报酬的过度波动几乎没有解释力 ;( 3 )封闭基金价格报酬的过度波动表明 :由于投资者行为使基金股票价格相对于基金净值存在额外的系统风险 ,封闭式基金折价正是对这种系统风险的一种补偿。     

An information theoretic analysis of stock returns,volatility and trading volumes

Information theory is used to examine the dynamic relationships between stock returns, volatility and trading volumes for S&P500 stocks. This provides an alternative approach to traditional Granger causality tests when dealing with nonlinear relationships. The article highlights the dominant role played by trading volumes in all of these relationships – even in the return–volatility relation – and finds evidence of a market level feedback effect from index returns to the return–volatility relation at the stock level. The article also produces a number of stylized facts from an information theoretic perspective.     

股市收益、收益波动与中国城镇居民消费行为

本文通过构造边际消费倾向理论模型,发现股市收益波动是影响居民边际消费倾向的重要因子,而股市收益对居民边际消费倾向的影响带有不确定性;股市正财富效应的发挥与否的主要因素之一是经济风险大小;并依据模型分析了股市财富效应的非对称性特征。实证研究证实了模型的结论,且发现股市收益产生的影响随着时滞的增长将变得更加不确定。     

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.     

R&D, patents and stock return volatility

Recent finance literature highlights the role of technological change in increasing firm specific (idiosyncratic) and aggregate stock return volatility, yet innovation data is not used in these analyses, leaving the direct relationship between innovation and stock return volatility untested. The paper investigates the relationship between volatility and innovation using firm level patent data. The analysis builds on the empirical work by Mazzucato (Rev Econ Dyn 5:318–345, 2002; J Evol Econ 13(5):491–512, 2003) where it is found that stock return volatility is highest during periods in the industry life-cycle when innovation is the most ‘radical’. In this paper we ask whether firms which invest more in innovation (more R&D and more patents) and/or which have more important innovations (patents with more citations) experience more volatility in their returns. Given that returns should in theory be higher, on average, for higher risk stocks, we also look at the effect of innovation on the level of returns. To take into account the competition between firms within industries, firm returns and volatility are measured relative to the industry average. We focus the analysis on firms in the pharmaceutical industry between 1974 and 1999. Results suggest that there is a positive and significant relationship between volatility, R&D intensity and the various patent related measures—especially when the innovation measures are filtered to distinguish the very innovative firms from the less innovate ones.     

Asymmetric Linkages between BRICS Stock Returns and Country Risk Ratings: Evidence from Dynamic Panel Threshold Models

This study investigates the asymmetric linkages between the five BRICS (Brazil, Russia, India, China and South Africa) countries’ stock markets and three country risk ratings (financial, economic and political risk) in the presence of major global economic and financial factors. Using the dynamic panel threshold models, we find evidence of asymmetry in most cases. However, the significance and the signs of the effects of these risk ratings on the BRICS market returns differ across the lower and upper regimes. Furthermore, improvements in the global stock, West Texas Intermediate (WTI) and gold markets enhance the BRICS stock market performance. Increases in implied volatility indices lead to drops in the BRICS markets.     

Exchange Rate Exposure of Sectoral Returns and Volatilities: Further Evidence From Japanese Industrial Sectors

In this paper we argue that the commonly employed exposure coefficient/beta is inadequate for capturing the entire impact of exchange rate changes on firms' future operating cash flows. Instead, we employ the bivariate Glosten–Jagannathan–Runkle generalized autoregressive conditional heteroskedasticity mean model to investigate four aspects of exchange rate exposure, including sensitivity of stock returns to exchange rate changes, sensitivity of stock returns to the volatility of exchange rate changes, sensitivity of conditional variance of returns to exchange rate volatility, and the dynamic conditional correlation between returns and exchange rate changes, respectively, using data from 10 industrial sectors in Japan. We find significant evidence of such exchange rate exposure which is not captured by the conventional measure. The diagnostic statistics confirm the adequacy of our model, and, hence, the robustness of the results.     

Politics and the stock market: Evidence from Germany

We analyze the interaction of stock market movements and politics in Germany. Evidence from popularity functions and VAR-based evidence suggests that stock market returns have affected the popularity of German governments. We only find weak evidence that the political process has had an impact on the stock market. In contrast to empirical evidence for the U.S., we do not find that German stock market returns tend to be higher during left-wing than during right-wing governments. Also in contrast to results for the U.S., we find no evidence for an election cycle in German stock market returns.     

The role of the political cycle in the relationship between economic policy uncertainty and the long-run volatility of industry-level stock returns in the United States

In this study, we investigate how US economic policy uncertainty (EPU) drives the long-run components of volatilities in industry-level stock markets. We use a modified specification of GARCH-MIDAS and find that EPU increases the long-run volatility of the industrials and materials industries and decreases it in 4 of the 10 industries considered here: consumer staples, healthcare, information technology and materials. In addition, we add a dummy variable for the political cycle (PLC) to study whether the relationship between EPU and the volatility of industry returns is significantly different under different political regimes. The results imply that a Republican presidency dampens the effects of EPU on the long-run volatility of the consumer staples, healthcare and information technology industries. We also decompose the aggregated EPU into 11 category-specific EPUs to explore the detailed relationship between category-specific EPU and long-run volatility driven by aggregate EPU. The results for the category-specific EPU are consistent with the findings for the aggregate EPU. In particular, the weakened effect of PLC on the relationship between EPU and the long-run volatility of industry-level returns is also confirmed by MIDAS regression with beta weight scheme.     

An analysis of commercial bank common stock returns: 1802–97

This study creates analyses for the first time a continous index of returns on commercial bank common stocks listed in a specific market. The index is constructed from a unique set of historical data and is calculated on both a weighted and unweighted basis, first including and then excluding dividends. A measure of volatility is calculated annually.

The results indicate that the dividend component of holding period returns is very important. Including dividends, average returns were 6.0% for the century; excluding dividends, average returns were 0.1%. Excess returns were calculated using two different measures of a riskless rate of return. Cumulative excess returns for the first half of the nineteenth century were negative. Real returns were calculated, and found to be generally positive over the century. The volatility of returns was quite high during certain periods.

Examining the effects of significant economic and political events on bank common stock returns, we find that the War of 1812, the Civil War, and the National Banking System had a significant impact on bank stock returns. Several economic panics, several depressions, the First and Second Banks of the United States, the Embargo of 1807, and the Suffolk Bank had no measureable impact.     

THE DYNAMIC RELATION BETWEEN RETURNS,TRADING VOLUME,AND VOLATILITY: LESSONS FROM SPILLOVERS BETWEEN ASIA AND THE UNITED STATES

This paper investigates the dynamic relationship between index returns, return volatility, and trading volume for eight Asian markets and the US. We find cross‐border spillovers in returns to be non‐existent, spillovers in absolute returns between Asia and the US to be strong in both directions, and spillovers in volatility to run from Asia to the US. Trading volume, especially on the Asian markets, depends on shocks in domestic and foreign returns as well as on volatility, especially those shocks originating in the US. However, only weak evidence is found for trading volume influencing other variables. In the light of the theoretical models, these results suggest sequential information arrivals, with investors being overconfident and applying positive feedback strategy. Furthermore, new information causes price volatility to rise due to differences in its interpretation among traders, but the subsequent market reaction takes the form of adjustment in price level, not volatility. Lastly, the intensity of cross‐border spillovers seems to have increased following the 1997 crisis, which we interpret as evidence of increased noisiness in prices and diversity in opinions about news originating abroad. Our findings might also help to understand the nature of financial crises, to predict their further developments and consequences.     

The effect of political volatility on capital markets in EU accession and neighborhood countries

Political instability has the potential to disrupt financial markets. But how do political institutions affect financial movements in an environment where all institutions are in flux? This paper looks at the effects of formal and informal political volatility in the new EU countries of central and eastern Europe, in the Eastern Neighborhood, and farther afield in Central Asia to answer this question. Using asymmetric GARCH modeling on monthly data, I find that informal political volatility has a significant negative effect on stock returns, while formal political institutions generate much higher financial volatility than changes in monetary policy.     

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.     

Has the Asian crisis changed the role of foreign investors in emerging equity markets: Taiwan's experience

This paper examines whether the 1997 Asian crisis changed the trading behaviors of foreign investors and of local institutional investors in Taiwan's stock market. There is little evidence that the Asian crisis changed the relationship between equity flows and market returns in Taiwan's stock market but there is evidence that volatility effects and volatility spillover were strengthened after the crisis. The general findings are (i) feedback trading arguments are much stronger than information arguments; (ii) relationships between returns and sale changes are the weakest but volatility effects using sale measures are the strongest; (iii) strong volatility effects and volatility spillover are found after the crisis; and (iv) the results for domestic institutional investors are slightly stronger than those for foreign investors.     

A prospect-theoretical interpretation of momentum returns

The puzzling evidence of seemingly high momentum returns is related to an understanding of risk as a simple covariance. However, by applying a prospect-theoretical assessment of US stock momentum returns we provide a possible direction for explaining the puzzle.     

PREDICTING STOCK RETURNS AND VOLATILITY WITH INVESTOR SENTIMENT INDICES: A RECONSIDERATION USING A NONPARAMETRIC CAUSALITY‐IN‐QUANTILES TEST

Evidence of monthly stock returns predictability based on popular investor sentiment indices, namely S^BW and S^PLS as introduced by Baker and Wurgler (2006, 2007) and Huang et al. (2015) respectively are mixed. While, linear predictive models show that only S^PLS can predict excess stock returns, nonparametric models (which accounts for misspecification of the linear frameworks due to nonlinearity and regime changes) finds no evidence of predictability based on either of these two indices for not only stock returns, but also its volatility. However, in this paper, we show that when we use a more general nonparametric causality‐in‐quantiles model of Balcilar et al., (forthcoming), in fact, both S^BW and S^PLS can predict stock returns and its volatility, with S^PLS being a relatively stronger predictor of excess returns during bear and bull regimes, and S^BW being a relatively powerful predictor of volatility of excess stock returns, barring the median of the conditional distribution.     

On the robustness of alternative rankings methodologies: Australian and New Zealand economics departments, 1988 to 2002

Theoretical considerations appear to support the conjecture that stock returns are positively related to growth in the long run. However, the empirical literature does not give unanimous support to the theory. Based on a stochastic general equilibrium model it is argued that the long-run relationship between stock returns and per capita income growth is ambiguous and depends on output volatility. Using a century of data for 20 Organization for Economic Co-operation and Development (OECD) countries it is shown that the relationship between stock returns and growth is positive over the period 1916–1951, in which output volatility was persistent. Outside this period no relationship between stock returns and growth is found. These findings are consistent with the predictions of the theoretical model.