The Negative News Threshold - an Explanation for Negative Skewness in Stock Returns

A vast literature documents negative skewness and excess kurtosis in stock return distributions on several markets. We approach the issue of negative skewness from a different angle than in previous studies by suggesting a model, which we denote the “negative news threshold” hypothesis, that builds on asymmetrically distributed information and symmetric market responses. Our empirical tests reveal that returns for days when non-scheduled news are disclosed are the source of negative skewness in stock returns. This finding lends solid support to our model and suggests that negative skewness in stock returns is induced by asymmetries in the news disclosure policies of firm management.

Essays on Stock Market Reactions to New Information

A functioning stock market is an essential component of a competitive economy, since it provides a mechanism for allocating the economy’s capital stock. In an ideal situation, the stock market will steer capital in a manner that maximizes the total utility of the economy. As prices of traded stocks depend on and vary with information available to investors, it is apparent that information plays a crucial role in a functioning stock market. However, even though information indisputably matters, several issues regarding how stock markets process and react to new information still remain unanswered. The purpose of this thesis is to explore the link between new information and stock market reactions. The first essay utilizes new methodological tools in order to investigate the average reaction of investors to new financial statement information. The second essay explores the behavior of different types of investors when new financial statement information is disclosed to the market. The third essay looks into the interrelation between investor size, behavior and overconfidence. The fourth essay approaches the puzzle of negative skewness in stock returns from an altogether different angle than previous studies. The first essay presents evidence of the second derivatives of some financial statement signals containing more information than the first derivatives. Further, empirical evidence also indicates that some of the investigated signals proxy risk while others contain information priced with a delay. The second essay documents different categories of investors demonstrating systematical differences in their behavior when new financial statement information arrives to the market. In addition, a theoretical model building on differences in investor overconfidence is put forward in order to explain the observed behavior. The third essay shows that investor size describes investor behavior very well. This finding is predicted by the model proposed in the second essay, and hence strengthens the model. The behavioral differences between investors of different size furthermore have significant economic implications. Finally, the fourth essay finds strong evidence of management news disclosure practices causing negative skewness in stock returns.

Essays on the Modeling and Prediction of Volatility and Higher Moments of Stock Returns (summary section only)

One of the most fundamental and widely accepted ideas in finance is that investors are compensated through higher returns for taking on non-diversifiable risk. Hence the quantification, modeling and prediction of risk have been, and still are one of the most prolific research areas in financial economics. It was recognized early on that there are predictable patterns in the variance of speculative prices. Later research has shown that there may also be systematic variation in the skewness and kurtosis of financial returns. Lacking in the literature so far, is an out-of-sample forecast evaluation of the potential benefits of these new more complicated models with time-varying higher moments. Such an evaluation is the topic of this dissertation. Essay 1 investigates the forecast performance of the GARCH (1,1) model when estimated with 9 different error distributions on Standard and Poor’s 500 Index Future returns. By utilizing the theory of realized variance to construct an appropriate ex post measure of variance from intra-day data it is shown that allowing for a leptokurtic error distribution leads to significant improvements in variance forecasts compared to using the normal distribution. This result holds for daily, weekly as well as monthly forecast horizons. It is also found that allowing for skewness and time variation in the higher moments of the distribution does not further improve forecasts. In Essay 2, by using 20 years of daily Standard and Poor 500 index returns, it is found that density forecasts are much improved by allowing for constant excess kurtosis but not improved by allowing for skewness. By allowing the kurtosis and skewness to be time varying the density forecasts are not further improved but on the contrary made slightly worse. In Essay 3 a new model incorporating conditional variance, skewness and kurtosis based on the Normal Inverse Gaussian (NIG) distribution is proposed. The new model and two previously used NIG models are evaluated by their Value at Risk (VaR) forecasts on a long series of daily Standard and Poor’s 500 returns. The results show that only the new model produces satisfactory VaR forecasts for both 1% and 5% VaR Taken together the results of the thesis show that kurtosis appears not to exhibit predictable time variation, whereas there is found some predictability in the skewness. However, the dynamic properties of the skewness are not completely captured by any of the models.

Essays on Stock Options, Incentives, and Managerial Action

Executive compensation and managerial behavior have received an increasing amount of attention in the financial economics literature since the mid 1970s. The purpose of this thesis is to extend our understanding of managerial compensation, especially how stock option compensation is linked to the actions undertaken by the management. Furthermore, managerial compensation is continuously and heatedly debated in the media and an emerging consensus from this discussion seems to be that there still exists gaps in our knowledge of optimal contracting. In Finland, the first executive stock options were introduced in the 1980s and throughout the last 15 years it has become increasingly popular for Finnish listed firms to use this type of managerial compensation. The empirical work in the thesis is conducted using data from Finland, in contrast to most previous studies that predominantly use U.S. data. Using Finnish data provides insight of how market conditions affect compensation and managerial action and provides an opportunity to explore what parts of the U.S. evidence can be generalized to other markets. The thesis consists of four essays. The first essay investigates the exercise policy of the executive stock option holders in Finland. In summary, Essay 1 contributes to our understanding of the exercise policies by examining both the determinants of the exercise decision and the markets reaction to the actual exercises. The second essay analyzes the factors driving stock option grants using data for Finnish publicly listed firms. Several agency theory based variables are found to have have explanatory power on the likelihood of a stock option grant. Essay 2 also contributes to our understanding of behavioral factors, such as prior stock return, as determinants of stock option compensation. The third essay investigates the tax and stock option motives for share repurchases and dividend distributions. We document strong support for the tax motive for share repurchases. Furthermore, we also analyze the dividend distribution decision in companies with stock options and find a significant difference between companies with and without dividend protected options. We thus document that the cutting of dividends found in previous U.S. studies can be avoided by dividend protection. In the fourth essay we approach the puzzle of negative skewness in stock returns from an altogether different angle than in previous studies. We suggest that negative skewness in stock returns is generated by management disclosure practices and find proof for this. More specifically, we find that negative skewness in daily returns is induced by returns for days when non-scheduled firm specific news is disclosed.

Conditional Moments in Asset Pricing

A better understanding of stock price changes is important in guiding many economic activities. Since prices often do not change without good reasons, searching for related explanatory variables has involved many enthusiasts. This book seeks answers from prices per se by relating price changes to their conditional moments. This is based on the belief that prices are the products of a complex psychological and economic process and their conditional moments derive ultimately from these psychological and economic shocks. Utilizing information about conditional moments hence makes it an attractive alternative to using other selective financial variables in explaining price changes. The first paper examines the relation between the conditional mean and the conditional variance using information about moments in three types of conditional distributions; it finds that the significance of the estimated mean and variance ratio can be affected by the assumed distributions and the time variations in skewness. The second paper decomposes the conditional industry volatility into a concurrent market component and an industry specific component; it finds that market volatility is on average responsible for a rather small share of total industry volatility — 6 to 9 percent in UK and 2 to 3 percent in Germany. The third paper looks at the heteroskedasticity in stock returns through an ARCH process supplemented with a set of conditioning information variables; it finds that the heteroskedasticity in stock returns allows for several forms of heteroskedasticity that include deterministic changes in variances due to seasonal factors, random adjustments in variances due to market and macro factors, and ARCH processes with past information. The fourth paper examines the role of higher moments — especially skewness and kurtosis — in determining the expected returns; it finds that total skewness and total kurtosis are more relevant non-beta risk measures and that they are costly to be diversified due either to the possible eliminations of their desirable parts or to the unsustainability of diversification strategies based on them.

Modeling Nonlinearities and Asymmetries in Asset Pricing

Financial time series tend to behave in a manner that is not directly drawn from a normal distribution. Asymmetries and nonlinearities are usually seen and these characteristics need to be taken into account. To make forecasts and predictions of future return and risk is rather complicated. The existing models for predicting risk are of help to a certain degree, but the complexity in financial time series data makes it difficult. The introduction of nonlinearities and asymmetries for the purpose of better models and forecasts regarding both mean and variance is supported by the essays in this dissertation. Linear and nonlinear models are consequently introduced in this dissertation. The advantages of nonlinear models are that they can take into account asymmetries. Asymmetric patterns usually mean that large negative returns appear more often than positive returns of the same magnitude. This goes hand in hand with the fact that negative returns are associated with higher risk than in the case where positive returns of the same magnitude are observed. The reason why these models are of high importance lies in the ability to make the best possible estimations and predictions of future returns and for predicting risk.

An Empirical Comparison of Linear and Nonlinear Volatility Models for Nordic Stock Returns

This paper examines how volatility in financial markets can preferable be modeled. The examination investigates how good the models for the volatility, both linear and nonlinear, are in absorbing skewness and kurtosis. The examination is done on the Nordic stock markets, including Finland, Sweden, Norway and Denmark. Different linear and nonlinear models are applied, and the results indicates that a linear model can almost always be used for modeling the series under investigation, even though nonlinear models performs slightly better in some cases. These results indicate that the markets under study are exposed to asymmetric patterns only to a certain degree. Negative shocks generally have a more prominent effect on the markets, but these effects are not really strong. However, in terms of absorbing skewness and kurtosis, nonlinear models outperform linear ones.

Technology-related peso problems in stock returns

Although empirical evidence suggests the contrary, many asset pricing models assume stock returns to be symmetrically distributed. In this paper it is argued that the occurrence of negative jumps in a firm's future earnings and, consequently, in its stock price, is positively related to the level of network externalities in the firm's product market. If the ex post frequency of these negative jumps in a sample does not equal the ex ante assessed probability of occurrence, the sample is subject to a peso problem. The hypothesis is tested for by regressing the skewness coefficient of a firm’s realised stock return distribution on the firm’s R&D intensity, i.e. the ratio of the firm’s research and development expenditure to its net sales. The empirical results support the technology-related peso problem hypothesis. In samples subject to such a peso problem, the returns are biased up and the variance is biased down.

Evaluating the Predictability of the Volatility Smile Using Return Distributions

In this paper, we examine the predictability of observed volatility smiles in three major European index options markets, utilising the historical return distributions of the respective underlying assets. The analysis involves an application of the Black (1976) pricing model adjusted in accordance with the Jarrow-Rudd methodology as proposed in 1982. Thereby we adjust the expected future returns for the third and fourth central moments as these represent deviations from normality in the distributions of observed returns. Thus, they are considered one possible explanation to the existence of the smile. The obtained results indicate that the inclusion of the higher moments in the pricing model to some extent reduces the volatility smile, compared with the unadjusted Black-76 model. However, as the smile is partly a function of supply, demand, and liquidity, and as such intricate to model, this modification does not appear sufficient to fully capture the characteristics of the smile.

An Empirical Investigation of Value-at-Risk in Long and Short Trading Positions

This paper uses the Value-at-Risk approach to define the risk in both long and short trading positions. The investigation is done on some major market indices(Japanese, UK, German and US). The performance of models that takes into account skewness and fat-tails are compared to symmetric models in relation to both the specific model for estimating the variance, and the distribution of the variance estimate used as input in the VaR estimation. The results indicate that more flexible models not necessarily perform better in predicting the VaR forecast; the reason for this is most probably the complexity of these models. A general result is that different methods for estimating the variance are needed for different confidence levels of the VaR, and for the different indices. Also, different models are to be used for the left respectively the right tail of the distribution.