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.     

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)     

Do German,Japanese, and U.S. export prices asymmetrically respond to exchange rate changes? Evidence from aggregate data

This article estimates the responses (elasticity coefficients) of the export price index to appreciation and depreciation of the nominal effective exchange rate using quarterly data (1973:1–1997:2) for Japan, Germany, and the United States. Cross-country comparisons of the elasticity magnitudes based on the statistically superior of the estimated models indicate that Japanese exporters, in the aggregate, have the highest tendency to dampen the effects of exchange rate fluctuations on the foreign currency export prices in both directions by adjusting their home currency prices. Intracountry comparisons provide some evidence of an asymmetric adjustment in export prices in the cases of Japan and Germany.     

Financial Integration and Market Efficiency: Some International Evidence from Cointegration Tests

This study investigates whether the globalization of financial markets enhances the efficiency of national stock markets. To this end, we have developed a dynamic representation of cointegration which is consistent with hypothesis that stock prices reflect the efficient discounting of new information on market fundamentals and testes for market efficiency in five industrialized markets (the United States, Canada, Japan, the United Kingdom, and Germany) over the last two decades. Our empirical analysis indicates that the U.S. and Canadian stock markets obey the long-run equilibrium path implied by our dynamic cointegration model, but the Japanese, British, and German markets do not exhibit such characteristics. Thus, it can be claimed that the stock markets of the United States and Canada are informationally efficient, whereas those of Japan, the United Kingdom, and Germany are not. [G15, G14]     

Modeling the Taiwan Stock Market and International Linkages

This paper analyzes the Taiwan stock market and examines its price and volatility linkages with those of the United States. In particular, it tests the hypothesis that the short-term volatility and price changes spill over from the developed markets, mainly the United States, to the emerging Taiwan stock market. The model and the test are built upon Engle's ARCH (autoregressive conditional heteroskedasticity) and Engle and Kroner's M-GARCH (multivariate generalized ARCH) models. The paper differs from previous studies on the Taiwan stock market in three respects. First, instead of using daily closing prices, it uses close-to-open and open-to-close returns to avoid the problem of overlapping samples. It carefully models the day-of-the-week effect in daily data to avoid misspecification of the model. Second, to circumvent the generated regressor problem arising from the two-step estimation procedure, it also employs the M-GARCH model where all parameters are estimated simultaneously. Third, the misspecification test is carried out on various kinds of asymmetric ARCH factors. A substantial volatility spillover effect is found from the US stock market to the Taiwan stock market, especially for the model using close-to-open returns. There is also evidence supporting a spillover effect in price changes. The findings can be explained by the recent gradual opening of the Taiwan stock market to foreign investors.     

Exploring the interaction between stock price index and exchange rates: an asymmetric threshold approach

This article examines the impact of stock market news on the foreign exchange markets of USA, Canada and UK, employing an innovative extension of the asymmetric threshold model of Apergis and Miller (2006). Under this framework we can disentangle the reaction of foreign exchange market to bad or good news and small or large news of stock returns. Our comprehensive daily data-set spans the period from January 1990 to June 2014. Using a cointegration and error correction model, we document the existence of a causal relationship between stock market and foreign exchange markets. Most interestingly, our results derived from the asymmetric threshold model confirm that the relationship between stock and foreign exchange markets is sensitive to short-term good or bad news and short-term small or large news. Our findings entail significant implications for policymakers, governments, risk managers and international investors.     

Return and volatility transmission between oil prices and oil-exporting and oil-importing countries

This paper provides further evidence of the comovements and dynamic volatility spillovers between stock markets and oil prices for a sample of five oil-importing countries (USA, Italy, Germany, Netherland and France) and four oil-exporting countries (United Arab Emirates, Kuwait, Saudi Arabia and Venezuela). We make use of a multivariate GJR-DCC-GARCH approach developed by Glosten et al. (1993). The results show that: i) dynamic correlations do not differ for oil-importing and oil-exporting economies; ii) cross-market comovements as measured by conditional correlation coefficients increase positively in response to significant aggregate demand (precautionary demand) and oil price shocks due to global business cycle fluctuations or world turmoil; iii) oil prices exhibit positive correlation with stock markets; and iv) oil assets are not a good ‘safe haven’ for protection against stock market losses during periods of turmoil.     

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.     

International stock return predictability: on the role of the United States in bad and good times

In this article, we document the asymmetric role that the US stock market plays in the international predictability of excess stock returns during recession and expansion periods. Most of the positive evidence accrues during the periods of recessions in the United States. During the expansions, there is only a limited evidence supporting the importance of lagged US returns in predictability of stock returns in 10 industrialized countries.     

Natural gas prices and stock prices: Evidence from EU-15 countries

This study investigates the long-run relationship between natural gas prices and stock prices by using the Johansen and Juselius cointegration test and error–correction based Granger causality models for the EU-15 countries. We employ quarterly data covering the period from 1990:1 to 2008:1. Empirical findings suggest that there is a unique long-term equilibrium relationship between natural gas prices, industrial production and stock prices in Austria, Denmark, Finland, Germany and Luxembourg. However, no relationship is found between these variables in the other ten EU-15 countries. Although we detect a significant long-run relationship between stock prices and natural gas prices, Granger causality test results imply an indirect Granger causal relationship between these two variables. In addition, we investigate the Granger causal relationship between stock returns, industrial production growth and natural gas price increase for Austria, Denmark, Finland, Germany and Luxembourg. As a result, increase in natural gas prices seem to impact industrial production growth at the first place. In turn, industrial production growth appears to affect stock returns.     

Capital Accumulation and Unemployment: A Tale of Two "Continents"

In contrast to much recent work regarding the causes of European unemployment, in this paper we emphasize the importance of capital accumulation. But unlike the few previous studies which have examined the relationship between capital accumulation and unemployment, we argue that what matters for the evolution of employment (and the unemployment rate) is not the absolute growth rate of a country's capital stock, but its evolution relative to other countries' capital stock. The empirical validity of the above statement is demonstrated for almost all OECD countries using quarterly time-series data for the period 1961–1995. More detailed evidence is also presented for Germany, Japan and the United Kingdom.     

Revisiting the oil price and stock market nexus: A nonlinear Panel ARDL approach

In this paper, we re-examine the relationship between oil price and stock prices in oil exporting and oil importing countries in the following distinct ways. First, we account for possible nonlinearities in the relationship in order to quantify the asymmetric response of stock prices of these two categories to positive and negative oil price changes. Secondly, in order to capture within group differences, we allow for heterogeneity effect in the cross-sections by formulating a nonlinear Panel ARDL model which is the panel data representation of the Shin et al. (2014) model and also analogous to the non-stationary heterogenous panel data model. Thirdly, we evaluate the relative predictability of the linear (symmetric) and nonlinear (asymmetric) Panel ARDL models using the Campbell and Thompson (2008) test. Our results depict that stock prices of both oil exporting and oil importing groups respond asymmetrically to changes in oil price although the response is stronger in the latter than the former. This finding is further corroborated by the out-of-sample forecast results suggesting that the inclusion of positive and negative oil price changes in the predictive model for stock prices will produce better forecast results only for the oil importing countries. Our results are robust to different oil price proxies, lag structure and in-sample periods. Overall, the dichotomy between oil exporting and oil importing countries has implications on oil price-stock nexus.     

Rational Expectations is not Generally Valid for Econometric Models: Evidence from Stock Market Data

In applying the rational expectations hypothesis to generate expectations in an econometric model it is assumed that (1) the model itself is capable of generating reasonable forecasts of all required expectations variables included in the model, and that (2) the economic agents whose behavior is being modeled act as if they form their psychological expectations as conditional mathematical expectations generated by the model. Both assumptions can be invalid, as demonstrated by the historical data on Hong Kong stock prices and by the successful application of the adaptive expectations hypothesis to explain panel data of prices of individual stocks and aggregate time series data on stock price indices of the United States and of Hong Kong.     

Mind the Gap! International Comparisons of Productivity in Services and Goods Production

Abstract. In this paper, we make a comparison of industry output, inputs and productivity growth and levels between seven advanced economies (Australia, Canada, France, Germany, the Netherlands, United Kingdom and United States). Our industry-level growth accounts make use of input data on labour quantity (hours) and composition (schooling levels), and distinguish between six different types of capital assets (including three information and communication technology (ICT) assets). The comparisons of levels rely on industry-specific purchasing power parities (PPPs) for output and inputs, within a consistent input–output framework for the year 1997. Our results show that differences in productivity growth and levels can be mainly traced to market services, not to goods-producing industries. Part of the strong productivity growth in market services in Anglo-Saxon countries, such as in Australia and Canada, may be related to relatively low productivity levels compared with the United States. In contrast, services productivity levels in continental European countries were on par with the United States in 1997, but growth in Europe was much weaker since then. In terms of factor input use, the United States is very different from all other countries, mostly because of the more intensive use of ICT capital in the United States.     

House Prices and Stock Prices: Different Roles in the US Monetary Transmission Mechanism*

We analyze the role of house prices and stock prices in the monetary‐policy transmission mechanism in the US, using a structural vector autoregressive model. If we allow the interest rate and asset prices to react simultaneously to news, we find different roles for house prices and stock prices in the monetary transmission mechanism. Following a contractionary monetary‐policy shock, stock prices fall immediately, while the response in house prices is more gradual. Regarding the systematic response in monetary policy, stock prices play a more important role than house prices. As a consequence, house prices contribute more than stock prices to fluctuations in gross domestic product and inflation.     

CAN HOUSEHOLDS AND WELFARE STATES MITIGATE RISING EARNINGS INSTABILITY?

We compare the evolution of earnings instability in Germany and the United Kingdom, two countries which stand for different types of welfare states. Deploying data from the German Socio‐Economic Panel (SOEP) and the British Household Panel Survey (BHPS), we estimate permanent and transitory variances of male income over the period 1984–2009 and 1991–2006, respectively. Studies in this literature generally use individual labor earnings. To uncover the role of welfare state and households in smoothening earnings shocks, we compute different income concepts ranging from gross earnings to net equivalent household income. We find evidence that the overall inequality of earnings in Germany and the United Kingdom has been rising throughout the period due to both higher permanent earnings inequality and higher earnings volatility. However, taking institutions of the welfare state and risk‐sharing households into account, we find that the volatility of net household income has remained fairly stable. Furthermore, redistribution and risk insurance provided by the welfare state is more pronounced in Germany than in the United Kingdom.     

Volatility transmission between Islamic and conventional equity markets: evidence from causality-in-variance test

This study examines whether a volatility/risk transmission exists between the Dow Jones Islamic stock and three conventional stock markets for the United States, Europe and Asia during the pre- and the in- and post-2008 crisis periods. It also explores the volatility spillover dynamics between those markets and US Monetary policy, oil prices, global financial risk and uncertainty factors. The recently developed Hafner and Herwartz (2006)’s causality-in-variance test provides evidence of risk transfers between these seemingly different equity markets, indicating a contagion between them during the full sample and the subperiods. The volatility structure of these markets is dominated by short-run volatility in the first period and by high long-run volatility in the second period. The volatility impulse response analysis indicates a similar volatility transmission pattern although it is characterized by a more volatile and short-lived structure in the second period. It also appears that the Islamic equity market responds to shocks from the risk factors and not from the oil price and the US economic policy uncertainty index during both periods.     

News and volatility of food prices

Financial markets exhibit an asymmetric news effect with unexpected low prices generating more price volatility than ‘news’ of high prices. The present study examines US food markets for such asymmetric news effects. Analysis of 25 years of monthly data for 45 retail food items shows that price news destabilizes about a third of the markets with unexpected price increases more destabilizing.     

中国股票市场对政策信息的不平衡性反应研究

本文将影响股票市场的政策信息区分为"好消息"和"坏消息"。通过 EGARCH 模型研究中国股票市场对"好消息"与"坏消息"的不平衡性反应,指出"好消息"对我国股票市场的影响大于"坏消息"的影响,这与国外股票市场的情况正好相反。根据这一结果本文创建了"信息效应曲线",具体分析我国股票市场对"好消息"与"坏消息"的不平衡性反应的特征,提出现有交易机制下的股价波动模式。     

An entropy-based analysis of the relationship between the DOW JONES Index and the TRNA Sentiment series

This article features an analysis of the relationship between the DOW JONES Industrial Average (DJIA) Index and a sentiment news series using daily data obtained from the Thomson Reuters News Analytics (TRNA) provided by SIRCA (The Securities Industry Research Centre of the Asia Pacific). The recent growth in the availability of on-line financial news sources, such as internet news and social media sources provides instantaneous access to financial news. Various commercial agencies have started developing their own filtered financial news feeds which are used by investors and traders to support their algorithmic trading strategies. TRNA is one such data set. In this study, we use the TRNA data set to construct a series of daily sentiment scores for DJIA stock index component companies. We use these daily DJIA market sentiment scores to study the relationship between financial news sentiment scores and the stock prices of these companies using entropy measures. The entropy and mutual information (MI) statistics permit an analysis of the amount of information within the sentiment series, its relationship to the DJIA and an indication of how the relationship changes over time.