Options are an important part in today's financial market. It's therefore of high importance to be able to understand when options are overvalued and undervalued to get a lead on the market. To determine this, the relation between the volatility of the underlying asset, called realized volatility, and the market's expected volatility, called implied volatility, can be analyzed. In this thesis five models were investigated for modeling the relation between implied and realized volatility. The five models consisted of one Ornstein–Uhlenbeck model, two autoregressive models and two artificial neural networks. To analyze the performance of the models, different accuracy measures were calculated for out-of-sample forecasts. Signals from the models were also calculated and used in a simulated options trading environment to get a better understanding of how well they perform in trading applications. The results suggest that artificial neural networks are able to model the relation more accurately compared to more traditional time series models. It was also shown that a trading strategy based on forecasting the relation was able to generate significant profits. Furthermore, it was shown that profits could be increased by combining a forecasting model with a signal classification model. / Optioner är en viktig del i dagens finansiella marknad. Det är därför viktigt att kunna förstå när optioner är över- och undervärderade för att vara i framkant av marknaden. För att bestämma detta kan relationen mellan den underliggande tillgångens volatilitet, kallad realiserad volatilitet, och marknadens förväntade volatilitet, kallad implicit volatilitet, analyseras. I den här avhandlingen undersöktes fem modeller för att modellera relationen mellan implicit och realiserad volatilitet. De fem modellerna var en Ornstein–Uhlenbeck modell, två autoregressiva modeller samt två artificiella neurala nätverk. För att analysera modellernas prestanda undersöktes olika nogrannhetsmått för prognoser från modellerna. Signaler från modellerna beräknades även och användes i en simulerad optionshandelsmiljö för att få en bättre förståelse för hur väl de presterar i en handelstillämpning. Resultaten tyder på att artificiella neurala nätverk kan modellera relationen bättre än mer traditionella tidsseriemodellerna. Det visades även att en handelsstrategi baserad på prognoser av relationen kunde generera en signifikant vinst. Det visades dessutom att vinster kunde ökas genom att kombinera en prognosmodell med en modell som klassificerar signaler.

Two mm-wave frequency modulated continuous wave (FMCW) radars were combined with a recurrent neural network (RNN) to perform fall detection. The purpose was to find methods to implement a multi-radar setup for healthcare monitoring and to study the resulting models’ resilience to interference and other obstacles, such as re-arranging the radars in the room. Single-board computers (SBCs) controlled the radars to record and transfer data over Ethernet to a PC. The Ethernet connection also allowed synchronization with the network time protocol (NTP), which was necessary to put the data from the two sensors in correspondence. The proposed RNN used two bidirectional long-short term memory (Bi-LSTM) layers with L2-regularization and dropout layers. It had an overall accuracy of 95.15% and 98.11% recall with a test set. Performance in live testing varied with different arrangements, with an accuracy of 98% with the radars along the same wall, 94% with the radars diagonally, and 90% with an alternative arrangement that the RNN model had not seen during training. However, the latter arrangement resulted in a recall of 95.7%, with false alarms reducing the overall performance. In conclusion, the model performed adequately for fall detection, even with different radar arrangements but could still be sensitive to interference. / Två millimetervågs-radarsystem av typen frequency modulated continuous wave (FMCW) kombinerades för att med hjälp av ett recurrent neural network (RNN) utföra falldetektering. Syftet var att finna metoder för att implementera en multiradarplatform för hälsoövervakning samt att studera de resulterande modellernas tolerans mot interferens och andra hinder så som att radarsystemen placeras på olika sätt i rummet. Enkortsdatorer kontrollerade radarsystemen för att kunna spela in och överföra data över Ethernet till en PC. Ethernetanslutningen möjliggjorde även synkronisering över network time protocol (NTP), vilket var nödvändigt för att sammanlänka datan från de båda sensorerna. Det föreslagna RNN:et använde två dubbelriktade (bidirectional) long-short term memory (Bi-LSTM) lager med L2-regularisering och dropout-lager. Det hade en total noggrannhet på 95.15% och 98.11% recall med ett test-set. Prestandan vid testning i drift varierade beroende på olika uppställningar av radarmodulerna, med en noggrannhet på 98% då de placerades längs samma vägg, 94% då de placerades diagonalt och 90% vid en alternativ uppställning som RNN-modellen inte hade sett när den tränades. Det senare resulterade dock i 95.7% recall, där falsklarm var den främsta felkällan. Sammanfattningsvis presterade modellen bra för falldetektering, även med olika uppställningar, men den verkar fortfarande vara känslig för interferens.

The present thesis focuses on exploration of the applicability of realized measures in volatility modeling and forecasting. We provide a first comprehensive study of jump variation impact on future volatility of Central and Eastern European stock markets. As a main workhorse, the recently proposed Realized Jump GARCH model, which enables a study of the impact of jump variation on future volatility forecasts, is used. In addition, we estimate Realized GARCH and heterogeneous autoregressive (HAR) models using one-minute and five-minute high frequency data. We find that jumps are important for future volatility, but only to a limited extent due to the high level of information aggregation within the stock market index. Moreover, Realized (Jump) GARCH models outperform the standard GARCH model in terms of data fit and forecasting performance. Comparison of forecasts with HAR models reveals that Realized (Jump) GARCH models capture higher portion of volatility variation. Eventually, Realized Jump GARCH compared to other Realized GARCH models provides comparable or even better forecasting performance.

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Submitted by Cristiane Shirayama (cristiane.shirayama@fgv.br) on 2011-05-30T17:33:11Z No. of bitstreams: 1 63090100002.pdf: 637269 bytes, checksum: 70c3797dc3ee51a70250b12457f359c0 (MD5) / Approved for entry into archive by Cristiane Shirayama(cristiane.shirayama@fgv.br) on 2011-05-30T17:34:40Z (GMT) No. of bitstreams: 1 63090100002.pdf: 637269 bytes, checksum: 70c3797dc3ee51a70250b12457f359c0 (MD5) / Approved for entry into archive by Cristiane Shirayama(cristiane.shirayama@fgv.br) on 2011-05-30T17:35:51Z (GMT) No. of bitstreams: 1 63090100002.pdf: 637269 bytes, checksum: 70c3797dc3ee51a70250b12457f359c0 (MD5) / Made available in DSpace on 2011-05-30T17:36:31Z (GMT). No. of bitstreams: 1 63090100002.pdf: 637269 bytes, checksum: 70c3797dc3ee51a70250b12457f359c0 (MD5) Previous issue date: 2011-04-08 / Usando dados intradiários dos ativos mais negociados do Bovespa, este trabalho considerou dois modelos recentemente desenvolvidos na literatura de estimação e previsão de volatilidade realizada. São eles; Heterogeneous Autorregresive Model of Realized Volatility (HAR-RV), desenvolvido por Corsi (2009)e o Mixed Data Sampling (MIDAS-RV) desenvolvido por Ghysels et. al (2004). Através de medidas de comparação de previsão dentro e fora da amostra, constatou-se resultados superiores do modelo MIDAS-RV apenas para previsões dentro da amostra. Para previsões fora da amostra, no entanto, não houve diferença estatisticamente significativa entre os modelos. Também encontram-se evidências que a utilização da volatilidade realizada induz distribuições dos retornos padronizados mais próximas da normal.

The main objective of this thesis is to investigate whether multivariate models using Highfrequency data provide significantly more accurate forecasts of Value at Risk and Expected Shortfall than multivariate models using only daily data. Our objective is very topical since the Basel Committee announced in 2013 that is going to change the risk measure used for calculation of capital requirement from Value at Risk to Expected Shortfall. The further improvement of accuracy of both risk measures can be also achieved by incorporation of high-frequency data that are rapidly more available due to significant technological progress. Therefore, we employed parsimonious Heterogeneous Autoregression and its asymmetric version that uses high-frequency data for the modeling of realized covariance matrix. The benchmark models are chosen well established DCC-GARCH and EWMA. The computation of Value at Risk (VaR) and Expected Shortfall (ES) is done through parametric, semi-parametric and Monte Carlo simulations. The loss distributions are represented by multivariate Gaussian, Student t, multivariate distributions simulated by Copula functions and multivariate filtered historical simulations. There are used univariate loss distributions: Generalized Pareto Distribution from EVT, empirical and standard parametric distributions. The main finding is that Heterogeneous Autoregression model using high-frequency data delivered superior or at least the same accuracy of forecasts of VaR to benchmark models based on daily data. Finally, the backtesting of ES remains still very challenging and applied Test I. and II. did not provide credible validation of the forecasts.

Being a social worker in a child and family-oriented unit means that through their position within an organization, a certain scope of action has been allocated. The scope of action creates a choice, but also entails a requirement to take responsibility and to take a stand. The purpose of the study is to investigate how social workers discuss their room for action in assessments regarding interaction between placed children and their guardians where the child is subjected to domestic violence, based on prevailing laws, guidelines, professional knowledge, client needs and research. We hope to achieve a in-depth understanding how these factors affect the scope for action of social workers in these cases. Through interviews with social workers working within the child and family unit as well as family home care, we intended to gain insight into their experiences and reasoning about the scope for action and how this is impacting on their assessments and decisions.The results of our study shows that the social workers do have a considerable scope of action in these kinds of cases, although some individuals choose to look at it as something more static, while others see it as something more dynamic. It appears that the general reunification principle (word for word translation) is very dominant in the daily life of social workers and affects their decisions. This despite the fact that the group we were investigating are divergent compared to the general group of placed children, which therefore should be exempt in certain cases, given the research that is available. Despite the complexity of the cases, there are no direct tendencies among social workers to fall into excessive bureaucracy in their behavior to manage their professional role. Based on the interviewer'sexperiences and reasoning, the best interest of the child, entails extremely complex assessments. From the reasonings of the interviewees’ we can see a clear parental perspective, that can partly depend on all the perspectives that a social worker has to take in consideration in their decisions, and partly on the strong parental right that is taught in Sweden. The result also shows that it is difficult for research to assimilate the assessments, which mainly depends on organizational reasons.

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Ett antal förskollärare har intervjuats om sin syn på barn som har svårt att leka med andra barn. Pedagogerna har en samstämmig bild av att dessa barn oftast reagerar med att antingen dra sig tillbaka eller med att bli utagerande vid kamratkontakt. För att stötta dessa barn är det vanligaste arbetssättet för pedagogerna att gå in i leken. De intervjuade uttrycker speciellt oro för att de inåtvända barnen blir bortglömda samt att de utagerande barnen skall få stämpeln "de som alltid förstör". / A number of preschool teachers have been interviewed about their view on children, who find it difficult to play with other children. The teachers have an unanimous view on how such children react: either by retiring from the playing or by spoiling the other childrens play. The interviewed teachers are especially concerned that these children will be neglected or constantly seen as a nuisance.