Are Oil Price News Headlines Statistically and Economically Significant for Investors?

While much has been written about the effects of oil price on stock returns, surprisingly nothing is known about the effect of oil price news on stock returns. This article is a response to this research gap. For a large number of stocks on the New York Stock Exchange, the authors find that while oil price news does predict market returns it only predicts returns of some sectors and not all. They find that sorting stocks based on oil price news generates a significant return differential in the cross-section, which holds consistently across a range of models allowing for the well-known risk factors. Their findings suggest that information contained in oil price news affects stock returns.     

Return patterns of South Korean stocks following large price shocks

This study tests the market efficiency of the South Korean stock market by examining returns on stocks of the constituents of the KOSPI 50 from 2000 to 2014 following large 1-month price decreases and increases. An exponential GARCH (EGARCH) event study framework is used to analyse the stock returns. The results show that large price shocks, positive and negative, are likely to be followed by positive market returns. Moreover, the results show an increase in the beta of stocks in the years following a large price shock. The overall results therefore support the Uncertain Information Hypothesis. However, beginning in 2008, return patterns more closely reflect those hypothesised by the Efficient Market Hypothesis, possibly due to increased participation by international investors. The observed returns following large price increases and decreases can be partially explained by changes in the Korean won to US dollar exchange rate and the trading behaviour of foreign investors.     

Oil Price Shocks and Volatility in Australian Stock Returns

This paper examines the effect of oil shocks on return and volatility in the sectors of Australian stock market and finds significant effects for most sectors. For the overall market index, an increase in oil price return significantly reduces return, and an increase in oil price return volatility significantly reduces volatility. An advantage of looking at sector returns rather than a general index of stock returns is that sectors may well differ markedly in how they respond to oil price shocks. The energy and material sectors (as expected) and the financial sector (surprisingly) are out of step (in different ways) with results for the other sectors and for the overall index. A rise in oil price increases returns in the energy and material sectors and an increase in oil price return volatility increases stock return volatility in the financial sector. Explanation for the negative (positive) association between oil return (oil return volatility) and returns (volatility of returns) in the financial sector must be based on the association via lending to and/or holdings of corporate bonds issued by firms with significant exposure to oil price fluctuations and their speculative positions in oil‐related instruments.     

The Availability Heuristic and Reversals Following Large Stock Price Changes

The author explores the effect of the availability heuristic on large daily stock price changes and on subsequent stock returns. He hypothesizes that if a major positive (negative) stock price move takes place on a day when the stock market index rises (falls), then its magnitude may be amplified by the availability of positive (negative) investment outcomes. In both cases, the availability heuristic may cause price overreaction to the initial company-specific shock, resulting in subsequent price reversal. In line with the hypothesis, the author documents that both positive and negative large price moves accompanied by the same-sign contemporaneous daily market returns are followed by significant reversals on the next 2 trading days and over 5- and 20-day intervals following the event, the magnitude of the reversals increasing over longer postevent windows, while large stock price changes taking place on the days when the market index moves in the opposite direction are followed by nonsignificant price drifts. The results remain robust after accounting for additional company (size, beta, historical volatility) and event-specific (stock's return and trading volume on the event day) factors, and are stronger for small and volatile stocks.     

Impact of oil prices on firm stock return: industry-wise analysis

The study investigates the impact of oil prices on firm-level stock returns in case of Pakistan over the period 1998–2014, as this relationship is neglected by the previous literature. By using the panel data estimation, the results of full sample indicate significant positive effect of oil price changes on firm stock returns in the same period, whereas the lagged oil price changes have significant negative effect on firms’ stock return. Moreover, the industry-level analysis also confirms the similar findings; results indicate significant positive impact of oil price on firms’ stock return in full sample, textile, chemical and miscellaneous industry, while the lagged oil price changes negatively affect the stock returns of full sample and all the industries except tobacco, jute and vanaspati industries. The study confirms that rise in oil price transfers a positive signal in the stock market that boosts the firm-level stock returns in Pakistan. In contrast to the negative shocks, the stock returns are significantly affected by the positive oil price shocks.     

Market Moods and Network Dynamics of Stock Returns: The Bipolar Behavior

The authors show that a simple mood-separable preference in a network study of stock returns captures a variety of stylized facts regarding stocks’ provisional (ab)normal behavior. These behaviors are articulated in a multistate complete Euclidean network model that specifies the existence, direction, and magnitude of a self-organized dynamics for each individual stock during abnormal market moods. In the empirical setting, the authors apply suggested model along with 2 established visual approaches (multidimensional scaling and agglomerative hierarchical clustering) for benchmark purposes. Results reveal different levels of erratic return dynamics for each stock and the entire market in different abnormal market moods. The authors model and interpret these self-organized dynamics as evidence of stocks’ and market’s bipolar behavior.     

T+1 trading mechanism causes negative overnight return

The T+1 trading mechanism is unique in the Chinese stock market, thus providing a natural experimental field to study the trading mechanism and price behaviors. This paper proposes and proves that T+1 trading mechanism causes negative overnight return, the overnight return can serve as a proxy of the T+1 trading mechanism. The paper finds that the overnight return of the Chinese stock market is significantly negative, whereas those under the T+0 trading mechanism, such as China’s stock index futures, Hong Kong stocks, and major international indices, all have around 0 or positive overnight returns. T+1 trading mechanism has greater impacts on stocks with more divergent investor opinions, higher risk, more individual investor percentages, higher arbitrage restrictions, and less liquidity. The T+1 trading mechanism distorts the price generation mechanism of stocks. The paper contributes to the understanding of impact of trading mechanism on stock prices.     

Information Transmission Through Rumors in Stock Markets: A New Evidence

The authors provide new evidence of the influence of false rumors based on Taiwan's stock market. The results indicate significant patterns of abnormal returns and trading volumes surrounding the event day and that the rumors seem to be disseminated in the stock market before appearing in newspapers. The results also indicate asymmetry: Investors hearing a positive rumor about a stock may tend to buy the stock, prompting a price run-up until the rumor dies away, while negative rumors usually have greater and longer negative impacts on stock returns than positive rumors do. The presence of a daily price limit is negatively correlated to the size of abnormal returns and abnormal trading volumes on the event day, and the abnormal trading volumes are more sensitive to the price limit surrounding the event day. Finally, firm managers might receive rumor information earlier and then conduct stock trading before the rumor's announcement.     

When Do Opening Stock Returns Tend to be Higher?

Abstract

In this study, I make an effort to formulate a trading rule that would make use of some systematic interday patterns in individual stocks’ opening returns. I analyze intraday price data on all the stocks that were S&P 500 Index constituents during the period from 1993 to 2012. I document that if the general market direction of the previous day's opening session is controlled for, then a stock's opening return tends to be higher if, on the previous trading day, its opening return was relatively high (either positive, or higher than the same day's opening market return) and its open-to-close return was relatively low (either non-positive, or lower than or equal to the same day's open-to-close market return). Finally, for the sampling period, I construct two different investment portfolios involving a long position in the stocks on the days when, according to the findings, their opening returns are expected to be high and a short position in the stocks on the days when, according to the findings, their opening returns are expected to be low. Both portfolios are found to yield significantly positive returns, providing evidence for the practical applicability of the documented patterns in opening stock prices.     

Oil price and automobile stock return co-movement: A wavelet coherence analysis

This paper explores possible co-movement between oil price and automobile stock return in a joint time-frequency domain. Daily price series from August 01, 1996 to June 20, 2017 is used in this analysis. The results indicate that the co-movement between oil price and automobile stock return is strong during November, 2000–December, 2002 and March, 2006–December, 2009. The co-movement is found to be more pronounced in the long-term and stock return is sensitive to the higher oil price emanating from the demand shock. This contravenes the conventional wisdom that crude oil is always counter-cyclical to the automobile stocks. For investor, this weakens the probable gain from including oil asset in a portfolio of automobile stocks as crude oil does not offer cushion against bearish automobile stock markets during the crisis period.     

中国股市长期记忆效应的实证研究

股票市场长期记忆效应问题一直是金融经济学家们倍感兴趣的一个研究热点。本文针对中国股票市场中价格指数与个股的日收益序列 ,在已有研究文献主要采用的经典R S分析方法基础上 ,引入修正R S分析与ARFIMA模型进行了实证研究。从研究结果来看 ,2 2个样本序列并不满足传统的正态分布假设 ,序列呈现出尖峰、肥尾、右偏等有偏特征以及独特的自相关与偏自相关结构 ,这些迹象预示着非线性动态系统的存在。而进一步的研究却表明 ,中国股市中代表市场总体的股价指数不存在长期记忆效应 ,而个股收益序列的分布特征存在着较大差异 ,仅少数个股存在长期记忆行为。这一结论明显地有别于以往那些由经典R S分析所得到的研究结果。     

The Pricing of Italian Equity Returns

In this paper, we investigate the relationship between common risk factors and average returns for Italian stocks. Our research has identified the Italian stock market's economic variables by using the results from factor analyses and time series regressions. We study several multi‐factor models combining the relevant macroeconomic variables with the mimicking equity portfolios SMB (small minus big) and HML (high minus low) proposed by Fama and French (1993). The key question we want to ask ourselves, is whether the influential role of the size and book‐to‐market equity factors in explaining average stock returns can stand up well when competing with some macroeconomic factors. In other words, do stock returns carry some risk premium that is independent of either the market return or the economic forces that underlie the common variation in returns? Our empirical work estimates risk premiums using both traditional two‐pass procedures and one‐pass (full information) methodologies. We show that only the market index and variables linked to interest rate shifts are consistently priced in the Italian stock returns. The role of other factors, and in particular both the size and the price‐to book ratio, are crucially dependent on the estimation procedure. (J.E.L.: G11, G12).     

Herding on lottery-type stocks: evidence from the Chinese stock market

Previous studies have provided evidence that investors have gambling propensity in the stock market and exhibit a preference for lottery-type stocks. In this study, we use high total skewness and high maximum daily return (MAX) to measure lottery-type stocks and examine whether investors do exhibit distinct herding pattern in these stock types. Empirical results show that investors display stronger herding among lottery-type stocks, thereby indicating that such stocks induce correlated behaviour with the investors. In addition, we find that stocks with the highest skewness exhibit stronger herding under upmarkets, whereas stocks with the lowest skewness display stronger herding under downmarkets. Regarding the highest MAX portfolio, no significant herding asymmetry is seen between upmarket and downmarket. The results reported in this article demonstrate that comovement in stock returns may be partly attributed to the nonstandard preferences of investors in the stock market.     

Productivity growth and stock returns: firm- and aggregate-level analyses

A firm’s stock return is affected not only by its own productivity growth rate, but also by other firms’ productivity growth rates. We show that this spillover effect is significant and time-varying, and underlies a fallacy of composition observed in late 20th century U.S. data: stock returns and productivity growth are correlated positively in firm-level data but negatively in aggregate data. This seeming fallacy of composition reflects Schumpeterian creative destruction: a few technology winners’ stocks rise with their rising productivity while many technology losers’ stocks fall with their declining productivity. Thus, most individual firms’ stock returns correlate negatively with aggregate productivity growth. This implies that technological innovation need not be a blessing for all firms and as a result, for investors holding the market. Our findings also provide a firm-level technology innovation-based explanation of prior findings that the market return correlates negatively with aggregate earnings.     

THE IMPACT OF OIL PRICE SHOCKS ON THE U.S. STOCK MARKET*

It is shown that the reaction of U.S. real stock returns to an oil price shock differs greatly depending on whether the change in the price of oil is driven by demand or supply shocks in the oil market. The demand and supply shocks driving the global crude oil market jointly account for 22% of the long‐run variation in U.S. real stock returns. The responses of industry‐specific U.S. stock returns to demand and supply shocks in the crude oil market are consistent with accounts of the transmission of oil price shocks that emphasize the reduction in domestic final demand.     

Firm return volatility and economic gains: The role of oil prices

In this paper we investigate whether the oil price contributes to stock return volatility for 560 firms listed on the NYSE. Using daily data, we find that the oil price is a significant determinant and predictor of firm return variance. We devise trading strategies based on forecasts of firm return variance using the oil prices and historical averages. We find that investors can make substantial gains in returns by using the oil price in forecasting firm return variances.     

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.     

The impact of interest rate and exchange rate volatility on banks' stock returns and volatility: Evidence from Turkey

This paper investigates the effects of interest rate and foreign exchange rate changes on Turkish banks' stock returns using the OLS and GARCH estimation models. The results suggest that interest rate and exchange rate changes have a negative and significant impact on the conditional bank stock return. Also, bank stock return sensitivities are found to be stronger for market return than interest rates and exchange rates, implying that market return plays an important role in determining the dynamics of conditional return of bank stocks. The results further indicate that interest rate and exchange rate volatility are the major determinants of the conditional bank stock return volatility.     

Psychological Oil Price Barrier and Firm Returns

In this paper, we investigate the psychological barrier effect induced by the oil price on firm returns when the oil price reaches US$100 or more per barrel. We find evidence of the negative effect of the US$100 oil price barrier for: (a) the entire sample of 1559 firms listed on the American stock exchanges; (b) both foreign and domestic firms, with domestic firms significantly more affected; (c) the 10 different sizes of firms, with the smaller firms less affected compared to the larger firms; and (d) 17 sectors of firms, with firms in the utilities, mining, and administration sectors being the least affected.     

The effect of the liberalization of the Chinese stock market on returns

We examine the short-term effects of the liberalization of the Chinese stock market on returns. We find a positive and significant abnormal return associated with the announcement of the liberalization of the Shanghai Stock Exchange. Exploiting features of the reform, we are able to compare stocks directly and indirectly affected by the liberalization. We find that all stock prices reflect this announcement premium equally, suggesting that the premium does not reflect an increase in expected liquidity. We further find that observed liquidity, as measured by volume and price impact, did not increase following the liberalization. We conclude that the observed premium reflects a diversification benefit for Chinese investors.