Short-term Price Behavior and the Effect of Foreign Investors in Finnish Equity Markets (summary section only)

As globalization and capital free movement has increased, so has interest in the effects of that global money flow, especially during financial crises. The concern has been that large global money flows will affect the pricing of small local markets by causing, in particular, overreaction. The purpose of this thesis is to contribute to the body of work concerning short-term under- and overreaction and the short-term effects of foreign investment flow in the small Finnish equity markets. This thesis also compares foreign execution return to domestic execution return. This study’s results indicate that short-term under- and overreaction occurs in domestic-buy portfolios (domestic net buying) rather than in foreign-buy portfolios. This under- and overreaction, however, is not economically meaningful after controlling for the bid-ask bounce effect. Based on this finding, one can conclude that foreign investors do not have a destabilizing effect in the short-term in the Finnish markets. Foreign activity affects short-term returns. When foreign investors are net buyers (sellers) there are positive (negative) market adjusted returns. Literature related to nationality and institutional effect leads us to expect these kind of results. These foreign flows are persistent at a 5 % to 21 % level and the persistence of foreign buy flow is higher than the foreign sell flow. Foreign daily trading execution is worse than domestic execution. Literature which quantifies foreign investors as liquidity demanders and literature related to front-running leads us to expect poorer foreign execution than domestic execution.

The Homeless Etiquette : Social Interaction and Behavior Among the Homeless in Taito Ward, Tokyo

The thesis focuses on the social interaction and behavior of the homeless living in Tokyo's Taito Ward. The study is based on the author's own ethnographic field research carried out in the autumn 2003. The chosen methodologies were based on the methodology called "participant observation", and they were used depending on the context. The ethnographic field research was carried out from the mid-August to the beginning of the October in 2003. The most important targets of the research were three separate loosely knit groups placed in certain parts of Taito Ward. One of these groups was based in proximity to the Ueno train station, one group gathered every morning around a homeless support organization called San'yûkai, and one was based in Tamahime Park located in the old San'ya area of Tokyo. The analysis is based on the aspects of Takie Sugiyama Lebra's theory of "social relativism". Lebra's theory consists of the following, arguably universal aspects: belongingness, empathy, dependence, place in the society, and reciprocity. In addition, all the interaction and behavior is tied to the context and the situation. According to Lebra, ritual and intimate situations produce similar action, which is socially relative. Of these, the norms of the ritual behavior are more regulated, while the intimate bahavior is less spontaneous. On the contrary, an anomic situation produces anomic behavior, which is not socially relative. Lebra's theory is critically reviewed by the author of the thesis, and the author has attempted to modify the theory to make it more adaptable to the present-day society and to the analysis. Erving Goffman's views of the social interaction and Anthony Giddens' theories about the social structures have been used as complementary thoretical basis. The aim of the thesis is to clarify, how and why the interaction and the behavior of some homeless individuals in some situations follow the aspects of Lebra's "social relativism", and on the other hand, why in some situations they do not. In the latter cases the answers can be sought from regional and individual differences, or from the inaptness of the theory to analyze the presented situation. Here, a significant factor is the major finding of the field study: the so called "homeless etiquette", which is an abstract set of norms and values that influences the social interaction and behavior of the homeless, and with which many homeless individuals presented in the study complied. The fundamental goal of the thesis is to reach profound understanding about the daily life of the homeless, whose lives were studied. The author argues that this kind of profound understanding is necessary in looking for sustainable solutions in the areas of social and housing policy to improve the position of the homeless and the qualitative functioning of the society.

Fuel conditions and fire behavior characteristics of managed Picea abies and Pinus sylvestris forests in Finland

The objectives of this study were to analyze the impact of structural stand characteristics on ignition potential, surface fuel moisture, and fire behavior in Pinus sylvestris L. and Picea abies (L.) Karst stands in Finland and to explain stand-specific fire danger using the Canadian Fire Weather Index System and the Finnish Fire Risk Index. Additionally, the study analyzes the relationship between observed fire activity and fire weather indices at different stages of growing season. Field experiments were carried out in Pinus sylvestris or Picea abies dominated stands during fire seasons 2001 and 2002. Observations on ignition potential, fuel moisture, and fire behavior were analyzed in relation to stand structure and the outputs of the Finnish and Canadian fire weather indices. Seasonal patterns of fire activity were examined based on national fire statistics 1996 2003, effective temperature sum, and the fire weather indices. Point fire ignition potential was highest in Pinus clear-cuts and lowest in closed Picea stands. Moss-dominated surface fuels were driest in clear-cut and sapling stage stands and presented the highest moisture content under closed Picea canopy. Pinus sylvestris stands carried fire under a wide range of fire weather conditions under which Picea abies stands failed to sustain fire. In the national fire records, the daily number of reported ignitions presented its highest value during late fire season whereas the daily area burned peaked most substantially during early season. The fire weather indices correlated significantly with ignition potential and fuel moisture but were unable to explain fire behavior in the experimental fires. During the initial and final stages of the growing season, fire activity was disconnected from weather-based fire danger ratings. Information on stand structure and season stage would benefit the assessment of fire danger in Finnish forest landscape for fire suppression and controlled burning purposes.

Mathematical Aspects of Financial Markets with Frictions

Frictions are factors that hinder trading of securities in financial markets. Typical frictions include limited market depth, transaction costs, lack of infinite divisibility of securities, and taxes. Conventional models used in mathematical finance often gloss over these issues, which affect almost all financial markets, by arguing that the impact of frictions is negligible and, consequently, the frictionless models are valid approximations. This dissertation consists of three research papers, which are related to the study of the validity of such approximations in two distinct modeling problems. Models of price dynamics that are based on diffusion processes, i.e., continuous strong Markov processes, are widely used in the frictionless scenario. The first paper establishes that diffusion models can indeed be understood as approximations of price dynamics in markets with frictions. This is achieved by introducing an agent-based model of a financial market where finitely many agents trade a financial security, the price of which evolves according to price impacts generated by trades. It is shown that, if the number of agents is large, then under certain assumptions the price process of security, which is a pure-jump process, can be approximated by a one-dimensional diffusion process. In a slightly extended model, in which agents may exhibit herd behavior, the approximating diffusion model turns out to be a stochastic volatility model. Finally, it is shown that when agents' tendency to herd is strong, logarithmic returns in the approximating stochastic volatility model are heavy-tailed. The remaining papers are related to no-arbitrage criteria and superhedging in continuous-time option pricing models under small-transaction-cost asymptotics. Guasoni, Rásonyi, and Schachermayer have recently shown that, in such a setting, any financial security admits no arbitrage opportunities and there exist no feasible superhedging strategies for European call and put options written on it, as long as its price process is continuous and has the so-called conditional full support (CFS) property. Motivated by this result, CFS is established for certain stochastic integrals and a subclass of Brownian semistationary processes in the two papers. As a consequence, a wide range of possibly non-Markovian local and stochastic volatility models have the CFS property.

Elements of Volatility at High Frequency

Volatility is central in options pricing and risk management. It reflects the uncertainty of investors and the inherent instability of the economy. Time series methods are among the most widely applied scientific methods to analyze and predict volatility. Very frequently sampled data contain much valuable information about the different elements of volatility and may ultimately reveal the reasons for time varying volatility. The use of such ultra-high-frequency data is common to all three essays of the dissertation. The dissertation belongs to the field of financial econometrics. The first essay uses wavelet methods to study the time-varying behavior of scaling laws and long-memory in the five-minute volatility series of Nokia on the Helsinki Stock Exchange around the burst of the IT-bubble. The essay is motivated by earlier findings which suggest that different scaling laws may apply to intraday time-scales and to larger time-scales, implying that the so-called annualized volatility depends on the data sampling frequency. The empirical results confirm the appearance of time varying long-memory and different scaling laws that, for a significant part, can be attributed to investor irrationality and to an intraday volatility periodicity called the New York effect. The findings have potentially important consequences for options pricing and risk management that commonly assume constant memory and scaling. The second essay investigates modelling the duration between trades in stock markets. Durations convoy information about investor intentions and provide an alternative view at volatility. Generalizations of standard autoregressive conditional duration (ACD) models are developed to meet needs observed in previous applications of the standard models. According to the empirical results based on data of actively traded stocks on the New York Stock Exchange and the Helsinki Stock Exchange the proposed generalization clearly outperforms the standard models and also performs well in comparison to another recently proposed alternative to the standard models. The distribution used to derive the generalization may also prove valuable in other areas of risk management. The third essay studies empirically the effect of decimalization on volatility and market microstructure noise. Decimalization refers to the change from fractional pricing to decimal pricing and it was carried out on the New York Stock Exchange in January, 2001. The methods used here are more accurate than in the earlier studies and put more weight on market microstructure. The main result is that decimalization decreased observed volatility by reducing noise variance especially for the highly active stocks. The results help risk management and market mechanism designing.

Glutamatergic Modulation of Cue-Induced Drug-Seeking Behavior in the Rat

The characteristics of drug addiction include compulsive drug use despite negative consequences and re-occurring relapses, returns to drug use after a period of abstinence. Therefore, relapse prevention is one of the major challenges for the treatment of drug addiction. There are three main factors capable of inducing craving for drugs and triggering relapse long after cessation of drug use and dissipation of physical withdrawal signs: stress, re-exposure to the drug, and environmental stimuli (cues) that have been previously associated with drug use. The neurotransmitters dopamine and glutamate have been implicated in the modulation of drug-seeking behavior. The aim of this project was to examine the role of glutamatergic neurotransmission in relapse triggered by conditioned drug-associated stimuli. The focus was on clarifying whether relapse to drug seeking can be attenuated by blockade of glutamate receptors. In addition, as the nucleus accumbens has been proposed to participate in the modulation of drug-seeking behavior, the effects of glutamate receptor blockade in this brain structure on cue-induced relapse were investigated. The studies employed animals models in which rats were trained to press a lever in a test cage to obtain alcohol or intravenous cocaine. Drug availability was paired with distinct olfactory, auditory, or visual stimuli. This phase was followed by extinction training, during which lever presses did not result in the presentation of the drug or the drug-associated stimuli. Extinction training led to a gradual decrease in the number of lever presses during test sessions. Relapse was triggered by presenting the rats with the drug-associated stimuli in the absence of alcohol or cocaine. The drug-associated stimuli were alone capable of inducing resumption of lever pressing and maintaining this behavior during repeated testing. The number of lever presses during a session represented the intensity of drug-seeking and relapse behavior. The results suggest that glutamatergic neurotransmission is involved in the modulation of drug-seeking behavior. Both alcohol and cocaine relapse were attenuated by systemic pretreatment with glutamate receptor antagonists. However, differences were found in the ability of ionotropic AMPA/kainate and NMDA receptor antagonists to regulate drug-seeking behavior. The AMPA/kainate antagonists CNQX and NBQX, and L-701,324, an antagonist with affinity for the glycine site of the NMDA receptor, attenuated cue-induced drug seeking, whereas the competitive NMDA antagonist CGP39551 and the NMDA channel blocker MK-801 were without effect. MPEP, an antagonist at metabotropic mGlu5 glutamate receptors, also decreased drug seeking, but its administration was found to lead to conditioned suppression of behavior during subsequent treatment sessions, suggesting that MPEP may have undesirable side effects. The mGluR2/3 agonist LY379268 and the mGluR8 agonist (S)-3,4-DCPG decreased both cue-induced relapse to alcohol drinking and alcohol consumption. Control experiments showed however that administration of the agonists was accompanied by motor suppression limiting their usefulness. Administration of the AMPA/kainate antagonist CNQX, the NMDA antagonist D-AP5, and the mGluR5 antagonist MPEP into the nucleus accumbens resulted also in a decrease in drug-seeking behavior, suggesting that the nucleus accumbens is at least one of the anatomical sites regulating drug seeking and mediating the effects of glutamate receptor antagonists on this behavior.

On the mechanical behavior of compacted pack ice : A theoretical and numerical investigation

Pack ice is an aggregate of ice floes drifting on the sea surface. The forces controlling the motion and deformation of pack ice are air and water drag forces, sea surface tilt, Coriolis force and the internal force due to the interaction between ice floes. In this thesis, the mechanical behavior of compacted pack ice is investigated using theoretical and numerical methods, focusing on the three basic material properties: compressive strength, yield curve and flow rule. A high-resolution three-category sea ice model is applied to investigate the sea ice dynamics in two small basins, the whole Gulf Riga and the inside Pärnu Bay, focusing on the calibration of the compressive strength for thin ice. These two basins are on the scales of 100 km and 20 km, respectively, with typical ice thickness of 10-30 cm. The model is found capable of capturing the main characteristics of the ice dynamics. The compressive strength is calibrated to be about 30 kPa, consistent with the values from most large-scale sea ice dynamic studies. In addition, the numerical study in Pärnu Bay suggests that the shear strength drops significantly when the ice-floe size markedly decreases. A characteristic inversion method is developed to probe the yield curve of compacted pack ice. The basis of this method is the relationship between the intersection angle of linear kinematic features (LKFs) in sea ice and the slope of the yield curve. A summary of the observed LKFs shows that they can be basically divided into three groups: intersecting leads, uniaxial opening leads and uniaxial pressure ridges. Based on the available observed angles, the yield curve is determined to be a curved diamond. Comparisons of this yield curve with those from other methods show that it possesses almost all the advantages identified by the other methods. A new constitutive law is proposed, where the yield curve is a diamond and the flow rule is a combination of the normal and co-axial flow rule. The non-normal co-axial flow rule is necessary for the Coulombic yield constraint. This constitutive law not only captures the main features of forming LKFs but also takes the advantage of avoiding overestimating divergence during shear deformation. Moreover, this study provides a method for observing the flow rule for pack ice during deformation.

Studies on Binary Time Series Models with Applications to Empirical Macroeconomics and Finance

This thesis studies binary time series models and their applications in empirical macroeconomics and finance. In addition to previously suggested models, new dynamic extensions are proposed to the static probit model commonly used in the previous literature. In particular, we are interested in probit models with an autoregressive model structure. In Chapter 2, the main objective is to compare the predictive performance of the static and dynamic probit models in forecasting the U.S. and German business cycle recession periods. Financial variables, such as interest rates and stock market returns, are used as predictive variables. The empirical results suggest that the recession periods are predictable and dynamic probit models, especially models with the autoregressive structure, outperform the static model. Chapter 3 proposes a Lagrange Multiplier (LM) test for the usefulness of the autoregressive structure of the probit model. The finite sample properties of the LM test are considered with simulation experiments. Results indicate that the two alternative LM test statistics have reasonable size and power in large samples. In small samples, a parametric bootstrap method is suggested to obtain approximately correct size. In Chapter 4, the predictive power of dynamic probit models in predicting the direction of stock market returns are examined. The novel idea is to use recession forecast (see Chapter 2) as a predictor of the stock return sign. The evidence suggests that the signs of the U.S. excess stock returns over the risk-free return are predictable both in and out of sample. The new "error correction" probit model yields the best forecasts and it also outperforms other predictive models, such as ARMAX models, in terms of statistical and economic goodness-of-fit measures. Chapter 5 generalizes the analysis of univariate models considered in Chapters 2 4 to the case of a bivariate model. A new bivariate autoregressive probit model is applied to predict the current state of the U.S. business cycle and growth rate cycle periods. Evidence of predictability of both cycle indicators is obtained and the bivariate model is found to outperform the univariate models in terms of predictive power.