Rain or Shine: Where is the Weather Effect?

There is considerable empirical evidence that emotion influences decision‐making. In this paper, we use a database of individual investor accounts to examine the weather effects on traders. Our analysis of the trading activity in five major US cities over a six‐year period finds virtually no difference in individuals’ propensity to buy or sell equities on cloudy days as opposed to sunny days. If the association between cloud cover and stock returns documented for New York and other world cities is indeed caused by investor mood swings, our findings suggest that researchers should focus on the attitudes of market‐makers, news providers or other agents physically located in the city hosting the exchange. NYSE spreads widen on cloudy days. When we control for this, the weather effect becomes smaller and insignificant. We interpret this as evidence that the behaviour of market‐makers, rather than individual investors, may be responsible for the relation between returns and weather.     

中国房地产市场与股票市场相关性的实证研究——基于预期效应、财富效应与替代效应的传递机制

本文利用1998年第一季度到2011年第三季度的季度数据,基于预期效应、财富效应与替代效应的传递机制来研究中国房地产市场与股票市场之间的相关性。研究结果表明,在长期内,预期效应与替代效应的传递作用微弱以及关系复杂导致房地产市场与股票市场长期不存在稳定关系;在短期内,房地产市场对股票市场的替代效应引起的负效应起主导作用且较显著,股票市场对房地产市场的财富效应引起的正效应起主导作用但较微弱,两者存在相互的Granger因果关系。     

Does the weather affect stock market volatility?

This paper investigates the empirical association between stock market volatility and investor mood-proxies related to the weather (cloudiness, temperature and precipitation) and the environment (nighttime length). Overall, our results suggest that cloudiness and length of nighttime are inversely related to historical, implied and realized measures of volatility. The strength of association seems to vary with the location of an exchange on Earth with respect to the equator. Weather deviations from seasonal norms and dummies representing extreme weather conditions do not offer additional explanatory power in our datasets.     

我国股票市场的财富效应分析

股市可以形成一定的虚拟财富效应,对刺激有效需求能产生正效应。而股市的实际财富效应取决于股市行情上涨对企业投资的传导,这一点又受制于股票市场规模、股市上涨持续的时间以及市场的有效性。     

On the Existence of Visual Technical Patterns in the UK Stock Market

The aim in this paper is to replicate and extend the analysis of visual technical patterns by Lo et al. (2000) using data on the UK market. A non‐parametric smoother is used to model a nonlinear trend in stock price series. Technical patterns, such as the 'head‐and‐shoulders' pattern, that are characterised by a sequence of turning points are identified in the smoothed data. Statistical tests are used to determine whether returns conditioned on the technical patterns are different from random returns and, in an extension to the analysis of Lo et al. (2000), whether they can outperform a market benchmark return. For the stocks in the FTSE 100 and FTSE 250 indices over the period 1986 to 2001, we find that technical patterns occur with different frequencies to each other and in different relativities to the frequencies found in the US market. Our extended statistical testing indicates that UK stock returns are less influenced by technical patterns than was the case for US stock returns.     

中国股市规模效应和账面市值比效应的实证分析

本文以2002—2010年中国A股股票作为研究对象,对中国股市的规模效应和账面市值比效应进行了实证分析。结果表明,在样本期间内中国股市存在规模效应和账面市值比效应,而且规模效应不具有显著性、账面市值比效应具有显著性。本文认为风险溢价和投资者非理性行为的综合作用是规模效应和账面市值比效应产生的主要原因。     

International Stock Market Efficiency and Integration: A Study of Eighteen Nations

This study examines the relationships among stock prices in eighteen national stock markets by using unit root and cointegration tests for the period 1961--92. All the markets were analyzed individually and collectively in regions to test for market efficiency. The results from unit root tests suggest that the world equity markets are weak-form efficient. The cointegration test results show that there are only a small number of significant cointegrating vectors over the last three decades. However, the number of significant cointegrating vectors increases after the October 1987 stock market crash, a result that is consistent with the contagion effect.     

Herding and market volatility

In this paper, we explore the impact of investor herding behavior on stock market volatility. We adopt a direct herding measure based on the variation of cross-sectional stock betas. The measure can be readily separated into positive and adverse components, whereby investors herd towards and away from the market portfolio, respectively. Using A-shares listed in the Chinese equity market from August 2005 to March 2021, we show that the market volatility is Granger caused by the measure, and that there exists an asymmetric effect between positive and adverse herding on volatility. Furthermore, we provide robust evidence that the information contained in the herding measure helps generate significantly improved volatility forecasts and add economic value to investors. Our paper not only contributes to the volatility forecasting literature but also advances our understanding of herding in the equity market.     

Can (unusual) weather conditions in New York predict South African stock returns?

This paper investigates the explanatory power of certain weather variables, measured as deviations from their monthly averages, in a leading international financial trading centre, i.e., New York, for South African stock returns, over the daily period January 2nd, 1973 to December, 31, 2015. The empirical results highlight that these unusual deviations of weather variables have a statistically significant negative effect on the stock returns in South Africa, indicating that unusual weather conditions in New York can be used to predict South African stock returns, which otherwise seems to be highly unpredictable. In fact, a forecasting exercise recommends that a trading rule that considers those weather variables through a GARCH modelling approach seems to outperform the random walk model and thus beat the market.     

COVID-19 Sentiment and the Chinese Stock Market: Evidence from the Official News Media and Sina Weibo

This study quantitatively measures the Chinese stock market’s reaction to sentiments regarding the Novel Coronavirus 2019 (COVID-19). Using 6.3 million items of textual data extracted from the official news media and Sina Weibo blogsite, we develop two COVID-19 sentiment indices that capture the moods related to COVID-19. Our sentiment indices are real-time and forward-looking indices in the stock market. We discover that stock returns and turnover rates were positively predicted by the COVID-19 sentiments during the period from December 17, 2019 to March 13, 2020. Consistent with this prediction, margin trading and short selling activities intensified proactively with growth sentiment. Overall, these results illustrate how the effects of the pandemic crisis were amplified by the sentiments.     

我国股票市场财富效应的实证研究——基于中国牛市期省际面板数据的经验分析

本文基于2005年1月至2007年12月的月度数据,利用面板数据模型对我国股票市场的财富效应进行了实证分析,结果发现我国股票市场对居民总体消费量存在着财富效应,但这种影响却是极其微弱的;同时股票市场对我国东部、中部与西部的影响也是不同的,仅有东部地区存在着股票市场的财富效应,中部与西部均不存在这种效应,最后本文对其作出了一定的解释并根据我国的现状提出了相应的政策建议。     

Market development and market efficiency: evidence based on nonlinear panel unit root tests

This study tests the weak form market efficiency of 32 European stock markets. Utilizing monthly data from June 2006 to June 2017, six different, newly developed nonlinear panel root tests were applied in three different groups of European markets: Frontier, Emerging and Developed. The results show that there is a meaningful relationship between different levels of economic development and the weak form market efficiency. Considering the nonlinear structure of the stock market indices, use of linear models might lead to wrong conclusions regarding market efficiency. Using several nonlinear panel root tests, the results of this study shed more light on the true data generating process of the stock market indices and more appropriately model market efficiency.     

Tehran stock exchange prediction using sentiment analysis of online textual opinions

We investigate the impact of social media data in predicting the Tehran Stock Exchange variables for the first time. We consider the closing price and daily return of three different stocks for this investigation. We collected our social media data from Sahamyab.com/stocktwits for about 3 months. To extract information from online comments, we propose a hybrid sentiment analysis approach that combines lexicon‐based and learning‐based methods. Since lexicons that are available for the Persian language are not practical for sentiment analysis in the stock market domain, we built a particular sentiment lexicon for this domain. After designing and calculating daily sentiment indices using the sentiment of the comments, we examine their impact on the baseline models that only use historical market data and propose new predictor models using multi‐regression analysis. In addition to the sentiments, we also examine the comments volume and the users' reliabilities. We conclude that the predictability of various stocks in the Tehran Stock Exchange is different depending on their attributes. Moreover, we indicate that only comments volume could be useful for predicting the closing price, and both the volume and the sentiment of the comments could be useful for predicting the daily return. We demonstrate that users' trust coefficients have different behaviours toward the three stocks.     

Intraday Empirical Analysis and Modeling of Diversified World Stock Indices

This paper proposes an approach to the intraday analysis of diversified world stock accumulation indices. The growth optimal portfolio (GOP) is used as reference unit or benchmark in a continuous financial market model. Diversified portfolios, covering the world stock market, are constructed and shown to approximate the GOP, providing the basis for a range of financial applications. The normalized GOP is modeled as a time transformed square root process of dimension four. Its dynamics are empirically verified for several world stock indices. Furthermore, the evolution of the transformed time is modeled as the integral over a rapidly evolving mean-reverting market activity process with deterministic volatility. The empirical findings suggest a rather simple and robust model for a world stock index that reflects the historical evolution, by using only a few readily observable parameters. Mathematics Subject Classification: (1991) primary 90A12, secondary 60G30,62P20 JEL Classification: G10, G13     

中国股票市场效率的实证检验

了解股票市场是否有效对于监管者和投资者具有重要意义。近年来,大多数实证分析结果倾向于中国证券市场尚未达到半强式有效的结论,但对于是否达到弱式有效,则存在较大分歧。自回归检验结果表明,目前我国沪、深股市已达到弱式有效。这一结论对于进一步制定我国股票市场的发展对策具有重要的指导意义。     

The investigation of the dynamic linkages between real estate market and stock market in Greece

ABSTRACT

We use quarterly data from Greece over the period 1997:1–2015:2 and investigate the dynamic linkages between the price of the real estate market and the price of the stock market focusing on two transmission mechanisms, namely the wealth and credit-price effects. The empirical analysis employs advanced methodological techniques and presents evidence supporting the existence of both the wealth effect and the credit effect in the long-run while in the short-run there is a one-way causal effect running from stock market towards house market. Results reveal asymmetric adjustment to equilibrium process and considerably stronger for positive deviations from the equilibrium.     

The Asymmetry and Volatility of the Chinese Stock Market Caused by the “New National Ten”

ABSTRACT

To curb the excessively rapid rise in housing prices in China, the State Council of China promulgated the New National Ten, which restrains speculative investment behavior and has a linkage effect on the stock market. In this study, we use a series of GARCH models to analyze the effect of the New National Ten on the volatility and asymmetry of the Shanghai Composite Index. Specifically, we investigate how changes in investors’ expectations due to regulations affect the stock market. The result clearly illustrates that this policy is effective in stabilizing the stock market. Investors expect a bullish future stock market and only care about the continuing execution of the policy. Finally, policy implications of our findings are discussed.     

The linkage between the US and Korean stock markets: the case of NASDAQ, KOSDAQ, and the semiconductor stocks

This paper examines the interrelationship between stock prices in the US and Korea by applying the vector autoregression (VAR) model to the daily stock prices at three different level of aggregation – the national aggregate index level, the high-tech industry level and the semiconductor firm level – for the period of July 1996 through February 2001. The major findings of this study are as follows. First, the US stock market plays a leading role over the Korean market at every level of aggregation. The reverse direction of influence, from Korea to the US, was found to be minimal. Second, the evidence also suggests that the speed of transmission of innovation from the US to Korea is swift and finished for the most part within a 24-h period, although it takes three or four days to complete the whole process. Third, the influence of the US stock prices on Korean stock prices, which is measured by the innovation transmission using the impulse–response function (IRF) analysis, seems to be somewhat stronger in the composite national stock price indices and the tech-laden indices than high-tech firms. Fourth, at the firm level, the influence of Micron Technology on the leading semiconductor manufacturers in Korea is shown to be strong and persistent by passing about 34 percent of its innovations to the Korean firms within the three-day period. The impact of IBM and Intel on the Korean chip makers seems to be relatively smaller. Finally, stock prices in Korea, national stock price indices and individual high-tech stocks alike, have become much more responsive to innovations in the US stock prices after the 1997 financial crisis. The implications of the main findings in this paper are also discussed.     

Primacy in stock market participation: the effect of initial returns on market re-entry decisions

We examine whether initial returns influence investors’ decisions to return to the stock market following withdrawal. Using a survival analysis technique to estimate Finnish retail investors’ likelihood of stock market re-entry reveals that investors who experience lower initial returns are less likely to return, even after controlling for returns in the last month and average monthly returns for the duration of investing. This primacy effect is robust to accounting for endogeneity in investors’ exit decisions, and other behavioural biases such as recency and saliency of investment experience. Individual investors appear to be subject to primacy bias and tend to put a significant weight on initial experiences in re-entry decisions.     

Stock Market Reaction to Monetary Policy: An Event Study Analysis of the Brazilian Case

This article examines the relationship between the monetary policy implemented by the Central Bank of Brazil and the stock market. We implement event study analysis and analyze the effect of the anticipated and unanticipated components of monetary policy decisions on the returns of the IBOVESPA index and 53 stocks. We find that monetary policy has a significant effect on the stock market, but is only responsible for a small proportion of market variation. The analysis at the sector level with expected returns identifies that the financial sector is the most affected by this policy, whereas with excess returns only industrial goods are significantly affected. Moreover, individual assets respond in a rather heterogeneous fashion to monetary policy; however, when we look at excess returns, we identify a reduction in the intensity and in the number of companies impacted by monetary policy. Finally, the monetary shock is explained by unanticipated variations in the unemployment rate, in the Industrial Production Index, in the General Market Price Index, and in the Broad Consumer Price Index.