Factors affecting the stock price performance of share issued privatizations

Shareholders in many share issued privatizations (SIPs) have enjoyed substantial increases in the value of their investments. This study examines the factors that influence the long-run stock price performance of an international sample of SIPs, focusing on three-year buy and hold returns. After controlling for market-wide changes in stock prices, one finds that the relative size of the company has a negative effect on stock price performance, retained government ownership has a positive effect, the presence of a golden share has a negative effect, initial underpricing has a positive effect, and the timing of the privatization has no effect. Performance also depends on the industry and home country.     

What are the effects of fiscal policy on asset markets?

We investigate the link between fiscal policy shocks and asset markets. Our results show that spending shocks have: a positive and persistent effect on GDP in the U.S. and in the U.K., while for Germany and Italy, such impact is temporary; a positive and persistent effect on housing prices; a negative effect on stock prices; and mixed effects on the price level. A VAR counter-factual exercise suggests that fiscal shocks play a minor role in the asset markets of the U.S. and Germany, and substantially increase the variability of housing and stock prices in the U.K., while government revenue shocks have increased volatility in Italy.     

Market News in Commodity Price Theory: Application to the Ethiopian Grain Market

This paper examines the effect of "news" or advance information about future production on competitive storage behaviour and prices using a structural model of commodity markets. In particular, it generalizes the neoclassical storage model to incorporate information on future harvests, while allowing for seasonal production, two features important to African and other developing country grain markets. The model is first developed to suit the case of the Ethiopian grain markets, and a general model is then stated. The effects on welfare and price variability of the addition of news are discussed, as well as changes in key demand and uncertainty parameters. The model is shown to replicate some features of the data better than the model without news, particularly the high autocorrelation in price, and performs better in formal estimation. However, it appears that the incorporation of news still fails to explain the extreme seasonal price movements observed.     

THE MEASUREMENT OF POVERTY WITH GEOGRAPHICAL AND INTERTEMPORAL PRICE DISPERSION: EVIDENCE FROM RWANDA

It is not known to what extent welfare measures result from seasonal and geographical price differences rather than from differences in living standards across households. Using data from Rwanda in 1983, we show that the change in mean living standard indicators caused by local and seasonal price deflation is moderately significant at every quarter. By contrast, the differences in poverty measures caused by this deflation can be considerable, for chronic as well as transient or seasonal poverty indicators. Thus, poverty monitoring and anti-poverty targeting can be badly affected by inaccurate deflation of living standard data. Moreover, when measuring seasonal poverty, the deflation based on regional prices instead of local prices only partially corrects for spatial price dispersion. Using annual local prices instead of quarterly local prices only yields a partial deflation, which distorts the measure of poverty fluctuations across seasons and biases estimates of annual and chronic poverty.     

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.     

Using time-varying transition probabilities in Markov switching processes to adjust US fiscal policy for asset prices

This paper tests for nonlinear effects of asset prices on the US fiscal policy. By modeling government spending and taxes as time-varying transition probability Markovian processes (TVPMS), we find that taxes significantly adjust in a nonlinear fashion to asset prices. In particular, taxes respond to housing and (to a smaller extent) to stock price changes during normal times. However, at periods characterized by high financial volatility, government taxation only counteracts stock market developments (and not the dynamics of the housing sector). As for government spending, it is neutral vis-a-vis the asset market cycles. We conclude that, correcting the fiscal balance and, notably, the revenue side for time-varying effects of asset prices provides a more accurate assessment of the fiscal stance and its sustainability.     

OIL PRICE SHOCKS AND STOCK MARKET BOOMS IN AN OIL EXPORTING COUNTRY

This paper analyses the effects of oil price shocks on stock returns in Norway, an oil-exporting country, highlighting the transmission channels of oil prices for macroeconomic behaviour. To capture the interaction between the different variables, stock returns are incorporated into a structural VAR model. I find that following a 10% increase in oil prices, stock returns increase by 2.5%, after which the effect gradually dies out. The results are robust to different (linear and non-linear) transformations of oil prices. The effects on the other variables are more modest. However, all variables indicate that the Norwegian economy responds to higher oil prices by increasing aggregate wealth and demand. The results also emphasize the role of other shocks; monetary policy shocks in particular, as important driving forces behind stock price variability in the short term.     

Taxation, collateral use of land, and Japanese asset prices

Japan experienced a significant increase in land and stock prices in the late 1980s and a subsequent reversal in these asset prices in the 1990s. I use a neoclassical growth model to determine how much of these asset price movements can be accounted for by the observed changes in output growth and land-related taxation. In the model, corporations issue land-collateralized debt to reduce their tax liabilities, and the government follows a land-taxation policy that is countercyclical to land prices. Without these features, the model cannot generate any significant change in land values, even with a permanent increase in the growth rate of the economy, because a permanent increase in the growth rate results in a comparable increase at the rate at which agents discount future returns. The collateral use of land and countercyclical land-tax policy introduce a substantial magnification mechanism for asset prices by reducing the required return on land. I calibrate the model to Japanese data, and conduct steady-state experiments and deterministic simulations. I show that if the observed increase in the growth rate of productivity and the decline in land taxes were expected to be permanent by market participants, then the model can by and large account for the movements in land and stock prices, but has counterfactual predictions regarding the behavior of capital. If agents expect the observed changes in the fundamentals to be temporary, then the model cannot generate a significant increase in these asset prices.     

Institutional development and stock price synchronicity: Evidence from China

Better developed legal and political institutions result in greater availability of reliable firm-specific information. When stock prices reflect more firm-specific information there will be less stock price synchronicity. This paper traces the experience of China, an economy undergoing dramatic institutional change in the last 20 years with rich variation in experiences across provinces. We show that stock price synchronicity is lower when there is institutional development in terms of property rights protection and rule of law. Furthermore, we investigate the influence of political pluralism on synchronicity. A more pluralistic regime reduces uncertainty and opaqueness regarding government interventions and therefore increases the value of firm-specific information that reduces synchronicity.     

Oil price risk in the Spanish stock market: An industry perspective

This study examines the sensitivity of the Spanish stock market at the industry level to movements in oil prices over the period 1993–2010, paying special attention to the presence of endogenously determined structural changes in the relationship between oil price changes and industry equity returns. The empirical results show that the degree of oil price exposure of Spanish industries is rather limited, although significant differences are found across industries. The oil price sensitivity is very weak in the 1990s, a period of fairly stable and low oil prices. Instead, the link between crude oil and stock prices seems to have increased during the 2000s, becoming primarily positive. This evidence highlights the key role played by aggregate demand-side oil price shocks associated with the global real economic activity in the link between oil price fluctuations and the Spanish stock market.     

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.     

Market Underreaction and Overreaction of Technology Stocks

Several studies have assessed stock market under- or overreaction of stocks and there is some agreement among them. However, there is much disagreement about what constitutes market underreaction or overreaction, and the conditions that cause it. The substantial variation in results among studies may be partially attributed to the types of firms that are contained in any sample. We investigate this premise by focusing on a sample of technology stocks that experienced an extreme change in stock price, along with a corresponding control sample of non-technology stocks that experienced a similar extreme change in stock price on the same day.

Based on the subsequent stock price behavior of each sample, we find a greater degree of overreaction within extreme positive changes in technology stock prices (winners) than in non-technology stock prices. In addition, we find a greater degree of underreaction within extreme negative changes in technology stock prices (losers) than in non-technology stock prices. When considering winners and losers collectively for technology and non-technology firms, it appears the market is overoptimistic when it initially revalues technology stock prices relative to non-technology stock prices.

The degree of under- or overreaction of technology stocks varies within the sample of technology stocks, and is conditioned on firm-specific characteristics. Overall, our results suggest that technology stocks exhibit unique stock price behavior subsequent to an extreme change in price, and that this unique behavior can even vary among technology firms according to firm-specific characteristics.     

Exploring the influence of industries and randomness in stock prices

This study explores the behavior of time series of historical prices and makes two additional contributions to the literature. In summarized form, we present an overview of each of the financial theories that discuss the movements of stock prices and their connection with industry trends. Within this theoretical framework, we first propose that prices be distinguished by following stock prices and a random-walk approach, and second, that the analysis of historical prices be broken down by industries. Similarities among price series are extracted through a clustering methodology based on an approach to non-computable Kolmogorov complexity. We model price series by following geometric Brownian motion and compare them to historical series of stock prices. Our first contribution confirms the existence of hidden common patterns in time series of historical prices that are clearly distinguishable from simulated series. The second contribution claims strong connections among firms carrying out similar industrial activities. The results confirm that stock prices belonging to the same industry behave similarly, whereas they behave differently from those of firms in other industries. Our research sheds new light on the stylized feature of the non-randomness of stock prices by pointing at fundamental aspects related to the industry as partial explanatory factors behind price movements.     

Fiscal policy and asset price volatility

This paper investigates the relationship between volatility of different asset prices and the volatility of various indicators of fiscal policy (primary balance, spending and revenue). We find evidence that asset price volatility affects the volatility of fiscal policy stance in a positive and significant way. The effect comes primarily through residential property and equity price volatility on government revenue and spending. Increased volatility in commercial property prices is associated with increased variability of government revenue. Output growth volatility is the dominant determinant of revenue and primary balance variability, whereas bad budgetary conditions and the size of the public sector are the most significant determinants of spending variability. Trade openness leads to greater variability of government spending, revenue and primary balance to GDP ratios.     

消费传导视角下资产 价格对物价水平的影响

本文在生命周期-持久收入（LC PIH）模型基础上分析了资产价格波动对居民消费及物价水平的影响，发现资产价格波动可以通过预算约束效应、实际收入效应、预期收入效应与替代效应四个渠道影响资产持有者的消费行为，进而影响物价水平。在此基础上，本文运用ARDL UECM模型实证分析了资产价格对物价水平的影响，实证结果发现股票、房地产价格在长期内与物价存在相关关系，房地产价格是影响物价水平的重要因素，但股票价格对物价的影响不显著且不稳定。     

Can oil prices help predict US stock market returns? Evidence using a dynamic model averaging (DMA) approach

Crude oil price behaviour has fluctuated wildly since 1973 which has a major impact on key macroeconomic variables. Although the relationship between stock market returns and oil price changes has been scrutinized excessively in the literature, the possibility of predicting future stock market returns using oil prices has attracted less attention. This paper investigates the ability of oil prices to predict S&P 500 price index returns with the use of other macroeconomic and financial variables. Including all the potential variables in a forecasting model may result in an over-fitted model. So instead, dynamic model averaging (DMA) and dynamic model selection (DMS) are applied to utilize their ability of allowing the best forecasting model to change over time while parameters are also allowed to change. The empirical evidence shows that applying the DMA/DMS approach leads to significant improvements in forecasting performance in comparison to other forecasting methodologies and the performance of these models are better when oil prices are included within predictors.     

股票价格波动与宏观经济关系的理论和实证探讨

受各种因素的综合影响,证券价格经常发生大幅波动.国外学者对证券价格波动的研究已开展了多年,并伴随着西方证券市场的发展而日益成熟.相对而言,我国的证券市场起步较晚,市场成熟度不高,价格波动频繁剧烈,这对我国经济发展产生了一定的影响.本文就利率、货币供应量、汇率等因素对股市发展的影响进行了分析,发现宏观经济变量与股市之间存在着相互影响的关系.宏观经济变量除了可以单独影响股市外,还可以通过相互作用来共同影响股市.工业增加值增长率、商品价格、人民币汇率与上证指数同向变动,货币供应量与上证指数反向变动.     

Cointegration relationships and hedonic pricing of differentiated commodities: an application to price dynamics in the US dairy sector

This study investigates the implications of hedonic pricing for price dynamics of differentiated commodities. A conceptual model of hedonic pricing is developed under a Leontief technology, showing how commodity prices reflect the underlying value of their components. Implications for the existence of cointegration relationships among commodity prices are derived. An application to the pricing and dynamics of selected US dairy commodities is presented. It provides evidence on the role of component valuation in the dynamics of dairy commodity prices in the short run as well as in the long run. Distinguishing between market regime and government regime (when the government price support is active), the analysis finds significant differences in dairy price dynamics between the two regimes.     

How does the diversity of investors’ beliefs affect stock price informativeness?

A growing number of studies have investigated the role of stock prices in aggregating private information and guiding resource reallocation. However, this article may be the first attempt to study how the diversity of beliefs affects stock price informativeness. The framework of the noisy rational expectations model shows that stock informativeness is determined by both the precision and use of private information in trading. If private beliefs about the value are highly diverse, the aggregate average opinion revealed in a stock’s price will be more accurate and, thus, more informative. As the price becomes more informative, however, individual investors will rely less on their private information. When this occurs, less private information will be absorbed in price, which, in turn, reduces price informativeness. Our model shows that the relationship between belief diversity and price informativeness is U-shaped in equilibrium.     

Explaining House Prices in Australia: 1970–2003*

This paper aims to explain changes in real house prices in Australia from 1970 to 2003. We develop and estimate a long-run equilibrium model that shows the real long-run economic determinants of house prices and a short-run asymmetric error correction model to represent house price changes in the short run. We find that, in the long run, real house prices are determined significantly and positively by real disposable income and the consumer price index. They are also determined significantly and negatively by the unemployment rate, real mortgage rates, equity prices and the housing stock. Employing our short-run asymmetric error correction model, we find that there are significant lags in adjustment to equilibrium. When real house prices are rising at more than 2 per cent per annum, the housing market adjusts to equilibrium in approximately four quarters. When real house prices are static or falling, the adjustment process takes six quarters.