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.

Substance misuse problems during pregnancy with special emphasis on buprenorphine

Maternal drug abuse during pregnancy endangers the future health and wellbeing of the infant and growing child. On the other hand, via maternal abstinence, these problems would never occur; so the problems would be totally preventable. Buprenorphine is widely used in opioid maintenance treatment as a substitute medication. In Finland, during 2000 s buprenorphine misuse has steadily increased. In 2009 almost one third of clientele of substance treatment units were in treatment because of buprenorphine dependence. At Helsinki Women s Clinic the first child with prenatal buprenorphine exposure was born in 2001. During 1992-2001 in the three capital area maternity hospitals (Women s clinic, Maternity hospital, Jorvi hospital) 524 women were followed at special antenatal clinics due to substance abuse problems. Three control women were drawn from birth register to each case woman and matched for parity and same place and date of the index birth. According to register data mortality rate was 38-fold higher among cases than controls within 6-15 years after index birth. Especially, the risk for violent or accidental death was increased. The women with substance misuse problems had also elevated risk for viral hepatitis and psychiatric morbidity. They were more often reimbursed for psychopharmaceuticals. Disability pensions and rehabilitation allowances were more often granted to cases than controls. In total 626 children were born from these pregnancies. According to register data 38% of these children were placed in out-of-home care as part of child protection services by the age of two years, and half of them by the age of 12 years, the median follow-up time was 5.8 years. The risk for out-of-home care was associated with factors identifiable during the pre- and perinatal period. In 2002-2005 67 pregnant women with buprenorphine dependence were followed up at the Helsinki University Hospital, Department of Obstetrics and Gynecology. Their pregnancies were uneventful. The prematurity rate was similar and there were no more major anomalies compared to the national statistics. The neonates were lighter compared to the national statistics. They were also born in good condition, with no perinatal hypoxia as defined by standard clinical parameters or certain biochemical markers in the cord blood: erythropoietin, S100 and cardiac troponin-t. Almost 80% of newborns developed neonatal abstinence syndrome (NAS) and two third of them needed morphine medication for it. Maternal smoking over ten cigarettes per day aggravated and benzodiazepine use attenuated NAS. An infant s highest urinary norbuprenorphine concentration during their first 3 days of life correlated with the duration of morphine treatment. The average length of infant s hospital stay was 25 days.

Quantification problems in the design of forest policy programs.

XVIII IUFRO World Congress, Ljubljana 1986.

Private and municipal forests and the forestry planning system in Japan - trends and problems after World War II.

XVIII IUFRO World Congress, Ljubljana 1986.

Optimisation problems in wireless sensor networks

This thesis studies optimisation problems related to modern large-scale distributed systems, such as wireless sensor networks and wireless ad-hoc networks. The concrete tasks that we use as motivating examples are the following: (i) maximising the lifetime of a battery-powered wireless sensor network, (ii) maximising the capacity of a wireless communication network, and (iii) minimising the number of sensors in a surveillance application. A sensor node consumes energy both when it is transmitting or forwarding data, and when it is performing measurements. Hence task (i), lifetime maximisation, can be approached from two different perspectives. First, we can seek for optimal data flows that make the most out of the energy resources available in the network; such optimisation problems are examples of so-called max-min linear programs. Second, we can conserve energy by putting redundant sensors into sleep mode; we arrive at the sleep scheduling problem, in which the objective is to find an optimal schedule that determines when each sensor node is asleep and when it is awake. In a wireless network simultaneous radio transmissions may interfere with each other. Task (ii), capacity maximisation, therefore gives rise to another scheduling problem, the activity scheduling problem, in which the objective is to find a minimum-length conflict-free schedule that satisfies the data transmission requirements of all wireless communication links. Task (iii), minimising the number of sensors, is related to the classical graph problem of finding a minimum dominating set. However, if we are not only interested in detecting an intruder but also locating the intruder, it is not sufficient to solve the dominating set problem; formulations such as minimum-size identifying codes and locating–dominating codes are more appropriate. This thesis presents approximation algorithms for each of these optimisation problems, i.e., for max-min linear programs, sleep scheduling, activity scheduling, identifying codes, and locating–dominating codes. Two complementary approaches are taken. The main focus is on local algorithms, which are constant-time distributed algorithms. The contributions include local approximation algorithms for max-min linear programs, sleep scheduling, and activity scheduling. In the case of max-min linear programs, tight upper and lower bounds are proved for the best possible approximation ratio that can be achieved by any local algorithm. The second approach is the study of centralised polynomial-time algorithms in local graphs – these are geometric graphs whose structure exhibits spatial locality. Among other contributions, it is shown that while identifying codes and locating–dominating codes are hard to approximate in general graphs, they admit a polynomial-time approximation scheme in local graphs.