The New York Times and Wall Street Journal: Does Their Coverage of Earnings Announcements Cause “Stale” News to Become “New” News?

Recent research suggests that the stock market reacts to stale information if it is reported in the media because it is gives the impression of being “new” news. The objective of this study is to provide a unique test of this hypothesis using the time-series properties of quarterly earnings. It is well documented that seasonally differenced quarterly earnings for adjacent quarters are positively correlated. Therefore a component of current quarter earnings when reported is news that was known or predictable at the end of the prior quarter and thus is old news. We find for those firms that receive media coverage in the Wall Street Journal and The New York Times that the price reaction at the time of the announcement of current earnings to past quarter's seasonally differenced quarterly earnings is greater than those firms that do not receive media coverage. The result is consistent with stale earnings information being given the appearance of new information resulting in a further price reaction. This suggests that the stale information hypothesis and media coverage could be a partial explanation for post-earnings announcement drift.     

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.     

Oil price uncertainty and the business cycle: Accounting for the influences of global supply and demand within a VAR GARCH-in-mean framework

ABSTRACT

This article reinvestigates the influence of oil price uncertainty on real economic activity in the United States using a four-variable VAR GARCH-in-mean asymmetric BEKK model. In contrast to previous studies in this area, the analysis focuses on business cycle fluctuations and we control for global supply and demand factors that might affect the real price of oil, its volatility as well as the US economy. We find that – even after accounting for these factors – oil price uncertainty still has a highly significant negative influence on the US business cycle. Our computations show that the effect is economically important during several periods, mostly after a significant variance shift in the mid-1980s. We simultaneously estimate the effect on the global business cycle but find that it is comparatively weak. Finally, significant spillover effects in the GARCH model suggest that oil price volatility is a gauge and channel of transmission of more general macroeconomic shocks and uncertainty. These linkages are particularly strong in case of unexpected bad news.     

Market clearing, utility functions, and securities prices

Summary. We prove the existence of equilibrium in a continuous-time finance model; our results include the case of dynamically incomplete markets as well as dynamically complete markets. In addition, we derive explicitly the stochastic process describing securities prices. The price process depends on the risk-aversion characteristics of the utility function, as well as on the presence of additional sources of wealth (including endowments and other securities). With a single stock, zero endowment in the terminal period, and Constant Relative Risk Aversion (CRRA) utility, the price process is geometric Brownian motion; in essentially any other situation, the price process is not a geometric Brownian motion.JEL Classification Numbers: D52.This paper is part of my Dissertation (UC Berkeley). I am very grateful to my advisor Professor Robert M. Anderson. I also would like to thank Steve Evans, Roger Purves, Jacob Sagi, Chris Shannon and the participants of the 2002 NBER General Equilibrium Conference at the University of Minnesota (Minneapolis) for very helpful discussions and comments. This work was supported by Grant SES-9710424 from the National Science Foundation.     

The NIRCU and the Phillips curve: an approach based on micro data

Abstract In this paper we propose a straightforward method to derive a non‐inflationary rate of capacity utilization (NIRCU) based on micro data. We condition the current capacity utilization of firms on their current and planned price adjustments. The non‐inflationary capacity utilization rate is then defined as the rate where a firm feels no price adjustment pressure. One of the main advantages is that this methodology uses structural aspects and does not make it necessary to operate with – often rather arbitrary – statistical filters. We show that our aggregate NIRCU performs remarkably well as an indicator of inflationary pressure in a Phillips curve estimation.     

Border tax adjustments and tariff‐tax reforms with consumption pollution

We develop a model of a small open economy, where pollution per unit of consumption between domestically produced and imported quantities of the same good differs. We show that the first‐best policy combination calls for consumption taxes on all polluting goods, and border tax adjustment (BTA) measures, that is, tariffs or import subsidies. We identify conditions under which well‐known tariff‐tax reform policies for developing economies, such as a consumer‐price‐neutral piecemeal reform of trade and a consumption tax, and a consumer‐price‐neutral reform of all trade and consumption taxes improve welfare. We also evaluate whether reforms of trade taxes alone are superior to consumer‐price‐neutral reforms of trade and consumption taxes.     

Nominal rigidities and retail price dispersion in Canada over the twentieth century

Abstract We introduce a new data set on over 230,000 monthly prices for 10 goods in 50 Canadian cities over the 40‐year period from 1910 to 1950. This information, coupled with previously published price information from the late twentieth century, allows us to present one of the first comprehensive views of nominal rigidities and retail price dispersion over the past 100 years. We find that nominal rigidities have been conditioned upon prevailing rates of inflation with a greater frequency of price changes occurring in the 1920s and the 1970s. Additionally, the process of retail market integration has followed a U‐shaped trajectory with many domestic markets being better integrated – as measured by the average dispersion of retail prices – at mid‐century than in the 1990s. We also consider the linkages between nominal rigidities and price dispersion, finding results consistent with present‐day data.     

Foreign News and Spillovers in Emerging European Stock Markets

We analyze foreign news and spillovers in the emerging EU stock markets (the Czech Republic, Hungary, and Poland). We employ high‐frequency five‐minute intraday data on stock market index returns and four classes of EU and US macroeconomic announcements during 2004–07. We account for the difference of each announcement from its market expectation and we jointly model the volatility of the returns accounting for intraday movements and day‐of‐the‐week effects. Our findings show that intraday interactions on the new EU markets are strongly determined by mature stock markets as well as the macroeconomic news originating thereby. We show that strong contemporaneous links across markets are present even after controlling for macroeconomic announcements. Finally, in terms of specific announcements, we are able to show the exact sources of macro news spillovers from the developed foreign markets to the three new EU markets under research.     

Mass media effects on trading activities: television broadcasting evidence from Japan

This study examines how information broadcasting through television (TV) media influences stock market activities. Consistent with the effect of TV information to attract investor attention, we find that increased information flow through TV is significantly associated with greater trading volume and larger price change. For information type, hard news from business-oriented programmes and earnings-related news strongly contributes to the attention effect, while the effect of soft news is weaker. Bid–ask spread widens for more TV information flows, suggesting that new information arrival in the market expands information asymmetry. Finally, the impact of TV is more influential for stocks with more individual shareholders than those with institutional shareholders.     

Loss aversion and market crashes

This study proposes a rational expectation equilibrium model of stock market crashes with information asymmetry and loss averse speculators. We obtain a state-dependent linear optimal trading strategy, which makes the equilibrium price tractable. The model predicts nonlinear market depth and the result that small shocks to fundamentals (e.g., supply or informational shocks) can cause abrupt price movements. We demonstrate that short-sale constraints intensify asset price collapses relative to upward movements. The model also generates contagion between uncorrelated assets. These results are consistent with the main puzzling features observed during market crashes, namely abrupt and asymmetric price movements that are not driven by major news events but coupled with a spillover effect between unrelated markets.     

Cheating in markets: A laboratory experiment

We develop a two-market model under three conditions: autarky, frictionless free trade, and free trade with cheating. With cheating, buyers can underpay by π% in cross-market trades and sellers can deliver π% of full value. We solve for competitive equilibrium with cheating and obtain novel testable predictions on price, volume and surplus. We test these in a laboratory experiment using parameters intended to challenge the theory. The results are generally consistent with competitive equilibrium. We find evidence of price unification, market segmentation, a cross-market volume of trade lower under cheating than in frictionless free trade, but a higher overall volume.     

A FURTHER EXAMINATION OF THE PRICE AND VOLATILITY IMPACT OF STOCK DIVIDENDS AT EX‐DATES*

We examine the price and volatility reaction around stock dividend ex‐dates for an Australian sample, over the period January 1992 to December 2000. We find that price reaction around stock dividend ex‐dates provides positive abnormal returns both prior, and subsequent, to the abolishment of par value of shares in July 1998. When we partitioned the sample into financial, industrial non‐financial and mining firms, the price reaction is found to be positive and significant only for industrial non‐financial companies. Volatility of daily returns for periods subsequent to ex‐dates is significantly greater than corresponding periods prior to announcement dates, while cumulative raw returns subsequent to ex‐dates are significantly lower than periods prior to announcement dates for industrial non‐financial companies. The magnitude of the price reaction is statistically significantly related to an increase in the volatility of daily returns and to a reduction in cumulative raw returns subsequent to the ex‐dates, for industrial non‐financial companies. These findings support buying pressure hypothesis suggested by Dhatt et al. (1994, 1996 ).     

Modelling the dynamics of Bitcoin and Litecoin: GARCH versus stochastic volatility models

We examine and compare a large number of generalized autoregressive conditional heteroskedastic (GARCH) and stochastic volatility (SV) models using series of Bitcoin and Litecoin price returns to assess the model fit for dynamics of these cryptocurrency price returns series. The various models examined include the standard GARCH(1,1) and SV with an AR(1) log-volatility process, as well as more flexible models with jumps, volatility in mean, leverage effects, t-distributed and moving average innovations. We report that the best model for Bitcoin is SV-t while it is GARCH-t for Litecoin. Overall, the t-class of models performs better than other classes for both cryptocurrencies. For Bitcoin, the SV models consistently outperform the GARCH models and the same holds true for Litecoin in most cases. Finally, the comparison of GARCH models with GARCH-GJR models reveals that the leverage effect is not significant for cryptocurrencies, suggesting that these do not behave like stock prices.     

THE EFFECTS OF THE 1996 U.S.‐CANADA SOFTWOOD LUMBER AGREEMENT ON THE INDUSTRIAL USERS OF LUMBER: AN EVENT STUDY

In this article, we analyze whether the Softwood Lumber Agreement between the United States and Canada imposed significant economic costs on industries that use softwood lumber in the United States. To ascertain this impact, we use an event study. Our event study analyzes variations in the stock prices of lumber‐using firms listed at the major stock markets in the United States. We find that the news of events leading to the Softwood Lumber Agreement had significant negative impacts on the stock prices of industries using softwood lumber. The average reduction of stock prices for our sample of firms was approximately 5.42% over all the events considered. (JEL F13, F23)     

On the Effects of Asset Purchase Programs on Emerging Stock Markets

ABSTRACT

It is well documented that there has been a relationship between stock markets and unconventional monetary policies. However, most research concentrates on developed economies and analyzes the effects of shocks from such polices on stock prices. This paper is different from this research in that we investigate the impact of surprises from the Fed’s and the ECB’s announcements on the stock returns and volatility in Gulf Cooperation Council (GCC) countries using GARCH models. We find that a positive surprise associated with a fall in the U.S. Treasury yield causes an increase in ADX returns. We show significant effects of the ECB’s shocks on price returns. In particular, announcement that induces a decline in yield spreads in Italian sovereign bonds leads to higher stock prices. We also document a significant impact of surprises both by the Fed and ECB on volatility. However, the estimates are mixed. We note that volatility went down in response to the ECB’s policies, while they increased after the Fed’s asset purchases. Finally, when we distinguish surprises by their sign, the GJR-GARCH model estimates indicate that the effect on the volatility which is, perhaps surprisingly, symmetric for both types of news.     

Exogeneity of Money and its Policy Implications for Price Control: Evidence from South Asia

Abstract. We investigate the policy role that could be assigned to money stock in controlling the price level in four South Asian countries, namely, India, Nepal, Pakistan and Sri Lanka. The problem of policy assignment associated with the Granger non‐causality tests is pointed out. Various forms of exogeneity are tested. Money stocks (M₁ and M₂), consumer price index (CPI) and real GDP are cointegrated and causally related but we find overwhelming evidence of endogeneity of money. The endogeneity of money does not support the authorities’ policy stance of controlling price level through the control of money stock.     

“牛市”和“熊市”对信息的不平衡性反应研究

“利好”和“利空”信息对股票市场具有不平衡性的影响 ,研究这一现象对资产定价、投资组合构造及风险头寸确定都有重要作用。而新信息的出现对股票市场的影响应该区分股市所处的位置 ,这一点正是已有的波动性研究所忽视的。中国股票市场总体上不平衡性信息表现与国外不同 ,本文将股票市场波动划分为“牛市”和“熊市”两个阶段 ,采用EGARCH模型实证研究我国股票市场在牛市和熊市阶段对“利好”与“利空”的不平衡性反应特征。然后从投资者预期、结构、心理和交易机制等方面解释产生“强市恒强、弱市恒弱”现象的原因 ,指出进一步研究的方向 ,以期为投资者选择投资策略和政府制订政策提供参考     

Stock market crash of 2008: an empirical study of the deviation of share prices from company fundamentals

The aim of this study is to investigate quantitatively whether share prices deviated from company fundamentals in the stock market crash of 2008. For this purpose, we use a large database containing the balance sheets and share prices of 7796 worldwide companies for the period 2004–2013. We develop a panel regression model using three financial indicators – dividends per share, cash flow per share and book value per share – as explanatory variables for share price. We then estimate individual company fundamentals for each year by removing the time fixed effects from the two-way fixed effects model, which we identified as the best of the panel regression models.

Based on these results, we analyse the market anomaly quantitatively using the divergence rate – the rate of the deviation of share price from a company’s fundamentals. We find that share prices on average were overvalued in the period from 2005 to 2007 and were undervalued significantly in 2008, when the global financial crisis occurred. Share prices were equivalent to the fundamentals on average in the subsequent period. Our empirical results clearly demonstrate that the worldwide stock market fluctuated excessively in the time period before and just after the global financial crisis of 2008.     

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.     

What does tax aggressiveness signal? Evidence from stock price reactions to news about tax shelter involvement

We study the stock price reaction to news about corporate tax aggressiveness. We find that, on average, a company's stock price declines when there is news about its involvement in tax shelters. We find some limited evidence for cross-sectional variation in the reaction. For example, the reaction is more negative for firms in the retail sector, suggesting that part of the reaction may be a consumer/taxpayer backlash. In addition, the reaction is less negative for firms that are viewed to be generally less tax aggressive, as proxied by the firm's cash effective tax rate. We interpret this as being consistent with the market reacting positively to evidence that a firm is trying to reduce taxes when their financial reports would lead one to believe the firm is not tax aggressive.