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.

Finnish Short-Term Stock Returns

Functioning capital markets are a crucial part of a competitive economy since they provide the mechanisms to allocate resources. In order to be well functioning a capital market has to be efficient. Market efficiency is defined as a market where prices at any time fully reflect all available information. Basically, this means that abnormal returns cannot be predicted since they are dependent on future, presently unknown, information. The debate of market efficiency has been going on for several decades. Most academics today would probably agree that financial markets are reasonably efficient since virtually nobody has been able to achieve continuous abnormal positive returns. However, it is clear that a set of return anomalies exists, although they are apparently to small to enable substantial economic profit. Moreover, these anomalies can often be attributed to market design. The motivation for this work is to expand the knowledge of short-term trading patterns and to offer some explanations for these patterns. In the first essay the return pattern during the day is examined. On average stock prices move during two time periods of the day, namely, immediately after the opening and around the formal close of the market. Since stock prices, on average, move upwards these abnormal returns are generally positive and cause the distinct U-shape of intraday returns. In the second essay the results in the first essay are examined further. The return pattern around the former close is shown to partly be the result of manipulative action by market participants. In the third essay the focus is shifted towards trading patterns of the underlying stocks on days when index options and index futures on the stocks expire. Generally no expiration day effect was found. However, some indication of an expiration day effect was found when a large amount of open in- or at-the-money contracts existed. Also, the effects were likelier to be found for shares with high index-weight but fairly low trading volume. Last, in the forth essay the attention is turned to the behaviour of different tax clienteles around the dividend ex-day. Two groups of investors showed abnormal trading behaviour. Domestic non-financial investors, especially domestic companies, showed a dividend capturing behaviour, i.e. buying cum-dividend and selling ex-dividend shares. The opposite behaviour was found for foreign investors and domestic financial institutions. The effect was more notable for high yield, high volume stocks.

Modelling and Forecasting Property Rents and Returns (summary section only)

Recently, focus of real estate investment has expanded from the building-specific level to the aggregate portfolio level. The portfolio perspective requires investment analysis for real estate which is comparable with that of other asset classes, such as stocks and bonds. Thus, despite its distinctive features, such as heterogeneity, high unit value, illiquidity and the use of valuations to measure performance, real estate should not be considered in isolation. This means that techniques which are widely used for other assets classes can also be applied to real estate. An important part of investment strategies which support decisions on multi-asset portfolios is identifying the fundamentals of movements in property rents and returns, and predicting them on the basis of these fundamentals. The main objective of this thesis is to find the key drivers and the best methods for modelling and forecasting property rents and returns in markets which have experienced structural changes. The Finnish property market, which is a small European market with structural changes and limited property data, is used as a case study. The findings in the thesis show that is it possible to use modern econometric tools for modelling and forecasting property markets. The thesis consists of an introduction part and four essays. Essays 1 and 3 model Helsinki office rents and returns, and assess the suitability of alternative techniques for forecasting these series. Simple time series techniques are able to account for structural changes in the way markets operate, and thus provide the best forecasting tool. Theory-based econometric models, in particular error correction models, which are constrained by long-run information, are better for explaining past movements in rents and returns than for predicting their future movements. Essay 2 proceeds by examining the key drivers of rent movements for several property types in a number of Finnish property markets. The essay shows that commercial rents in local markets can be modelled using national macroeconomic variables and a panel approach. Finally, Essay 4 investigates whether forecasting models can be improved by accounting for asymmetric responses of office returns to the business cycle. The essay finds that the forecast performance of time series models can be improved by introducing asymmetries, and the improvement is sufficient to justify the extra computational time and effort associated with the application of these techniques.

Three Essays on the Volatility of Finnish Stock Returns (summary section only)

First, in Essay 1, we test whether it is possible to forecast Finnish Options Index return volatility by examining the out-of-sample predictive ability of several common volatility models with alternative well-known methods; and find additional evidence for the predictability of volatility and for the superiority of the more complicated models over the simpler ones. Secondly, in Essay 2, the aggregated volatility of stocks listed on the Helsinki Stock Exchange is decomposed into a market, industry-and firm-level component, and it is found that firm-level (i.e., idiosyncratic) volatility has increased in time, is more substantial than the two former, predicts GDP growth, moves countercyclically and as well as the other components is persistent. Thirdly, in Essay 3, we are among the first in the literature to seek for firm-specific determinants of idiosyncratic volatility in a multivariate setting, and find for the cross-section of stocks listed on the Helsinki Stock Exchange that industrial focus, trading volume, and block ownership, are positively associated with idiosyncratic volatility estimates––obtained from both the CAPM and the Fama and French three-factor model with local and international benchmark portfolios––whereas a negative relation holds between firm age as well as size and idiosyncratic volatility.

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.

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.

Anthraquinones from the Fungus Dermocybe sanguinea as Textile Dyes

This study is based on the multidiciplinary approach of using natural colorants as textile dyes. The author was interested in both the historical and traditional aspects of natural dyeing as well as the modern industrial applications of the pure natural compounds. In the study, the anthraquinone compounds were isolated as aglycones from the ectomycorrhizal fungus Dermocybe sanguinea. The endogenous beta-glucosidase of the fungus was used to catalyse the hydrolysis of the O-glycosyl linkage in emodin- and dermocybin-1-beta-D-glucopyranosides. The method, in which 10.45 kg of fresh fungi was starting material, yielded two fractions: 56.0 g of Fraction 1 (94% of the total amount of pigment,) consisting almost exclusively of the main pigments emodin and dermocybin, and 3.3 g of Fraction 2 (6%) consisting mainly of the anthraquinone carboxylic acids. The anthraquinone compounds in Fractions 1 and 2 were separated by one- and two-dimensional thin-layer-chromatography (TLC) using silica plates. 1D TLC showed that neither an acidic nor a basic solvent system alone separated completely all the anthraquinones isolated from D. sanguinea, in spite of the variation of the rations of the solvent components in the systems. Thus, a new 2D TLC technique was developed, applying n-pentanol-pyridine-methanol (6:4:3, v/v/v) and toluene-ethyl acetate-ethanol-formic acid (10:8:1:2, v/v/v/v) as eluents. Fifteen different anthraquinone derivatives were completely separated from one another. Emodin, physcion, endocrocin, dermolutein, dermorubin, 5-chlorodermorubin, emodin-1-beta-D-glucopyranoside, dermocybin-1-beta-D-glucopyranoside and dermocybin, and five new compounds, not earlier identified in D. sanguinea, 7-chloroemodin, 5,7-dichloroemodin, 5,7-dichloroendocrocin, 4-hydroxyaustrocorticone and austrocorticone, were separated and identified on the basis of their Rf-values, UV/Vis spectra and mass spectra. One substance remained unidentified, because of its very low concentration. The anthraquinones in Fractions 1 and 2 were preparatively separeted by liquid-liquid partition, with isopropylmethyl ketone and aqueous phosphate buffer as the solvent system. Advantage was taken of the principle of stepwise pH-gradient elution. The multiple liquid-liquid partition (MLLP) offered an excellent method for the preparative separation of compounds, which contain acidic groups such as the phenolic OH and COOH groups. Due to their strong aggregation properties, these compounds are, without derivatization, very difficult to separate on a preparative scale by chromatographic methods. By the MLLP method remarkable separations were achieved for the components in each mixture. Emodin and dermocybin were both obtained from Fraction 1 in a purity of at least 99%. Pure emodin and dermocybin were applied as mordant dyes to wool and polyamide and as disperse dyes to polyester and polyamide, using the high temperature (HT) technique. A mixture of dermorubin and 5-chlorodermorubin was applied as an acid dye to wool. In these experiments, synthetic dyes were used as references. Experiments were also performed using water extract of the air-dried fungi as dye liquor for wool and silk. The main colouring compounds in the crude water extract were emodin and dermocybin, which indicated that the O-glycosyl linkages in emodin- and dermocybin-1-beta-D-glucopyranosides were broken by the beta-glucosidase enzyme. Apparently, the hydrolysis occurred during the drying of the fungi and during the soaking of the dried fruit bodies overnight when preparing the dyebath. The colour of each dyed material was investigated in terms of the CIELAB L*, a* and b* values, and the colour fastness to light, washing and rubbing was tested according to the ISO standards. In the mordant dyeing experiments, emodin dyed wool and polyamide yellow and red, depending on the pH of the dyebath. Dermocybin gave purple and violet colours. The colour fastness of the mordant-dyed fabrics varied from good to moderate. The fastness properties of the natural anthraquinone carboxylic acids on wool were good, indicating the strength of the ionic bonds between the COO- groups of the dyes and the NH3+ groups of the fibres. In the disperse dyeing experiments, emodin dyed polyester bright yellow and dermocybin bright reddish-orange, and the fabrics showed excellent colour fastness. In contrast, emodin and dermocybin successfully dyed polyamide brownish-orange and wine-red, respectively, but with only moderate fastness. In industrial dyeing processes, natural anthraquinone aglycone mixtures dyed wool and silk well even at low concentrations of mordants, i.e. with 10% of the weight of the fibre (owf) of KAl(SO4)2 and 1 or 0.5% owf of other mordants. This study showed that purified natural anthraquinone compounds can produce bright hues with good colour-fastness properties in different textile materials. Natural anthraquinones have a significant potential for new dyeing techniques and will provide useful alternatives to synthetic dyes.