Objetivo: Evaluar la asociación entre la exposición a pantallas de dispositivos electrónicos y el síntomas del síndrome visual informático en estudiantes de pregrado del área de la salud de la Universidad Peruana de Ciencias Aplicadas en el año 2021. Metodología: Estudio transversal analítico. Población compuesta por 1554 estudiantes del área de salud con código universitario 2010 a 2020 de una universidad privada en Lima, Perú, matriculados en el ciclo académico 2021-01. Se utilizará el instrumento CVS-q (Computer Vision Syndrome Questionnaire) validado en Perú para medir SVI y sus síntomas.

Este trabalho tem por objetivo verificar a eficácia do modelo parametrizado SVI (Stochastic Volatility Inspired), apresentando-o como um método alternativo à construção da volatilidade implícita para opções de ações e de índice no mercado brasileiro. Primeiramente, o conceito financeiro de opção e sua teoria de precificação são apresentados, incluindo os modelos de Black-Scholes e Heston, a importância da volatilidade implícita e seu comportamento estocástico e detalhando o funcionamento de cada parâmetro do modelo SVI (Stochastic Volatility Inspired). Um algoritmo é desenvolvido em cima da base teórica, assim como sua implementação computacional. Além disso, são feitos experimentos com dados de mercado reais e seus resultados analisados e comparados com os de publicações anteriores. / This work aims to verify the efficiency of parameterized SVI (Stochastic Volatility Inspired) model, presenting it as an alternative method to construct the implied volatility for stock and index options in Brazilian market. First, the financial option concept and its pricing theory are presented, including Black-Scholes and Heston models, the importance of implied volatility and its stochastic behavior and detailing the operation of each parameter of the SVI (Stochastic Volatility Inspired) model. An algorithm is developed on top of the theoretical basis, as well as its computational implementation. In addition, experiments are performed with real market data and their results are analyzed and compared with those of previous publications.

Este trabalho tem por objetivo verificar a eficácia do modelo parametrizado SVI (Stochastic Volatility Inspired), apresentando-o como um método alternativo à construção da volatilidade implícita para opções de ações e de índice no mercado brasileiro. Primeiramente, o conceito financeiro de opção e sua teoria de precificação são apresentados, incluindo os modelos de Black-Scholes e Heston, a importância da volatilidade implícita e seu comportamento estocástico e detalhando o funcionamento de cada parâmetro do modelo SVI (Stochastic Volatility Inspired). Um algoritmo é desenvolvido em cima da base teórica, assim como sua implementação computacional. Além disso, são feitos experimentos com dados de mercado reais e seus resultados analisados e comparados com os de publicações anteriores. / This work aims to verify the efficiency of parameterized SVI (Stochastic Volatility Inspired) model, presenting it as an alternative method to construct the implied volatility for stock and index options in Brazilian market. First, the financial option concept and its pricing theory are presented, including Black-Scholes and Heston models, the importance of implied volatility and its stochastic behavior and detailing the operation of each parameter of the SVI (Stochastic Volatility Inspired) model. An algorithm is developed on top of the theoretical basis, as well as its computational implementation. In addition, experiments are performed with real market data and their results are analyzed and compared with those of previous publications.

With the help of investor search behavior on Google, we study the possibilities of predicting the closing price of an initial public offering after its first day on the market. During the sample period of 2017 to 2020 we find a significant positive correlation between companies whose name has an increased google-search-value during its initial offering period, and a higher return after the first day on the market. / Denna uppsats undersöker möjligheterna att använda sig av företagsspecifika Googlesökningar för att predicera en akties slutkurs första handelsdag efter en börsintroduktion. Under observationsperioden 2017 till 2020 finner vi ett signifikant positivt samband mellan de företag vars namn ökar i antal sökningar på Google under teckningsperioden, och en högre avkastning under första handelsdag.

Coronapandemin har varit en faktor som påverkat i princip alla delar av samhället under senaste året med utspridda sociala och ekonomiska konsekvenser. Men är effekterna på aktiemarknaden verkligen drivna av rationella värdeförändringar i bolagen? Tidigare studier har, genom att mäta sökintensitet på internet och kurser på världsindex, dragit slutsatsen att det under 2020 funnits en stark koppling mellan rädsla för coronaviruset och utvecklingen på världens börser. Syftet med denna studie är att följa tidigare forskning men att specifikt analysera en bransch som enligt tidigare studier varit relativt motståndskraftig mot effekterna av coronaviruset. Denna studie undersöker kopplingen mellan rädsla för coronaviruset på börsen och aktiekurser inom läkemedelsbolag som handlas på Stockholmsbörsen. Studien utförs genom att titta på korrelationen mellan Google Search Volume Index (SVI) och aktiekurser på 28 läkemedelsbolag som handlas på Stockholmsbörsen. Utgångshypotesen är att det finns en koppling mellan rädsla för coronaviruset mätt genom SVI och aktiekurser inom läkemedelsbranschen. För att bedöma hypotesen görs en rad regressioner med aktiepriser inom läkemedelsbranschen som beroende variabel och SVI samt OMXS30 som oberoende variabler. Resultaten visar att det inte finns en stark koppling mellan SVI och aktiepriser i läkemedelsbranschen vilket leder till att huvudhypotesen förkastas. Slutligen diskuteras hur resultaten tyder på att en semistark form av den effektiva marknadshypotesen lyder på läkemedelsmarknaden men att flera inslag av beteendeekonomi påverkar prissättningen.

To understand and model the dynamics of the implied volatility smile is essential for trading, pricing and risk management portfolio. We suggest a  linear Kalman filter for updating of the Stochastic Volatility Inspired (SVI) model of the volatility. From a risk management perspective we generate the 1-day ahead forecast of profit and loss (P\&L) of option portfolios. We compare the estimation of the implied volatility using the SVI model with the cubic polynomial model. We find that the SVI Kalman filter has outperformed the  others.

Settling properties of activated sludge or mixed liquor suspended solids (MLSS) have been studied for more than 75 years at wastewater treatment plants. Temperature, together with MLSS concentration, has been acknowledged as important contributors to MLSS settling variations. Batch MLSS settling tests are performed on a regular basis at most of the plants. The majority of these MLSS settling test reports reflect the complete absence of any form of temperature compensation or even MLSS sample temperature (Ts) recordings. The objective of this study is to evaluate the effects of short-term temperature variations on MLSS settling parameters. This is done by means of simplified theoretical calculations, followed by operational reactor temperature (Tr) observations, and batch MLSS settling tests. The experimental work concludes with the implementation of an on-line MLSS settling test procedure at a full-scale plant reactor to develop settling models based on diurnal Tr fluctuations. These settling models illustrate that parameter correlations improve when Tr is included in on-line MLSS concentration-based settling models. The unhindered settling velocity of a single solid biofloc in water is considered in a simplified calculation to estimate the effect of temperature variations on MLSS settling. Over a Ts increase of 20°C, water density and viscosity reductions result in a calculated biofloc settling velocity increase of less than 0.5 m/hr. Similarly, biofloc density, shape, and size changes result in calculated biofloc settling velocity increases of about 11, 10, and 2 m/hr respectively over the 20°C Ts range. Plant temperature recordings show significant short- to long-term variations. Ambient temperature (Ta) and Tr fluctuate about 20°C and 1.8°C respectively per day, and Tr changes by about 4°C within a week, as measured on-line at local plants during the test period in winter. The aeration method can have a significant impact on Tr. Differences in Tr in adjacent surface and bubble aeration reactors in the same plant were about 5°C. Large enough Tr and Ta variations exist at these local plants to affect MLSS settling test results. The MLSS settling test cylinder environment and meteorological conditions have a direct influence on Ts during batch settling tests. Direct solar radiation increases the average Ts by 4.3°C, or by 0.15°C per minute, during a 30-minute MLSS settling test duration. This Ts change leads to a sludge volume index (SVI) change of 63 mℓ/g, at an average SVI decrease of 14.8 mℓ/g per 1°C Ts increase. Changes to other parameters include an initial settling velocity (ISV) increase of about 0.12 m/hr for every 1°C Ts increase, together with a clarified supernatant turbidity increase of about 1.4 formazine nephelometric unit (FNU) for every 1°C Ts increase. Ts adjusts towards Ta before and during a batch MLSS settling test, thereby influencing MLSS settling results. Compensation for Ts variations during routine MLSS settling tests is nevertheless not reported as a common practice. To some extent, this is due to a lack of temperature-controlled MLSS settling test equipment. An automated MLSS settling meter demonstrates a semi-continuous on-line method to determine settling parameters in situ at the operational Tr of a full-scale plant. A basic polynomial fits 11 MLSS settling parameters that indicate in most instances improved MLSS settling at increased Tr. The average SVI decreases by 14.8 mℓ/g for every 1°C Tr increase. Similarly, for every 1°C Tr increase, the maximum settling velocity (u_max) increase is 0.1 m/hr, and the time to reach maximum settling velocity (t_umax) decreases by 2.4 minutes. The incremental 5-minute duration average settling velocities increase over the first 15 minutes of a MLSS settling test, as the MLSS concentration decreases and the Tr increases. This direct incremental settling velocity trend with Tr is reversed between 15 and 30 minutes, as the average 5-minute MLSS settling velocity increases at a reduced Tr. The inclusion of Tr in MLSS concentration-based settling best-fit correlations with SVI, u_max, and t_umax improves the coefficient of multiple determinations (R2) by an average of 0.32. Best-fit SVI models with u_max and t_umax have R2-values of 0.90 and 0.95 respectively. The developed models are only valid for the individual reactor MLSS conditions within the experimental parameter ranges. The main contribution of this study is to present temperature-based MLSS settling models. These models illustrate that an automated on-line MLSS settling meter is suitable to identify and model temperature related MLSS settling data with minimal experimental effort. A suitable approach is provided to improve the reliability of MLSS settling data, as effects of short-term temperature variations can be practically eliminated from settling test. / Thesis (PhD)--University of Pretoria, 2008. / Chemical Engineering / unrestricted

In this thesis will the question of how to construct implied volatility surfaces in a robust and arbitrage free way be investigated. To be able to know if the solutions are arbitrage free was an initial investigation about arbitrage in volatility surfaces made. From this investigation where two comprehensive theorems found. These theorems came from Roper in \cite{Roper2010}. Based on these where then two applicable arbitrage tests created. These tests came to be very important tools in the remaining thesis.The most reasonable classes of models for modeling the implied volatility surface where then investigated. It was concluded that the classes that seemed to have the best potential where the stochastic volatility models and the parametric representation models. The choice between these two classes where concluded to be based on a trade-off between simplicity and quality of the result. If it where possible to make the parametric representation models improve its result the best applicable choice would be that class. For the remaining thesis was it therefore decided to investigate this class. The parametric representation model that was chosen to be investigated where the SVI parametrization family since it seemed to have the most potential outside of its already strong foundation.The SVI parametrization family is diveded into 3 parametrizations, the raw SVI parametrization, the SSVI parametrization and the eSSVI parametrization. It was concluded that the raw SVI parametrization even though it gives very good market fits, was not robust enough to be chosen. This ment that the raw SVI parametrization would in most cases generate arbitrage in its surfaces. The SSVI model was concluded to be a very strong model compared to the raw SVI, since it was able to generate completely arbitrage free solutions with good enough results. The eSSVI is an extended parametrization of the SSVI with purpose to improve its short maturity results. It was concluded to give small improvements but with the trade of making the optimization procedure harder. It was therefore concluded that the SSVI parametrization might be the better application.To try to improve the results of the SSVI parametrization was a complementary procedure developed which got named the calibrated SSVI method. This method compared to the eSSVI parametrization would not change the parametrization but instead focusing on calibrating the initial fit that the SSVI generated. This method would heavily improve the initial fit of the SSVI surface but was less robust since it generated harder cases for the interpolation and extrapolation. / I det här examensarbetet undersöks frågan om hur man bör modellera implied volatilitetsytor på ett robust och arbitragefritt sätt. För att kunna veta om lösningarna är arbigtragefria börjades arbetet med en undersökning inom arbitrageområdet. De mest heltäckande resultatet som hittades var två theorem av Roper i \cite{Roper2010}. Baserat på dessa theorem kunde två applicerbara arbitragetester skapas som sedan kom att bli en av hörnstenarna i detta arbete. Genom att undersöka de modellklasser som verkade vara de bästa inom området valdes den parametriseringsbeskrivande modellklassen.  I denna klass valdes sedan SVI parametriseringsfamiljen för vidare undersökning eftersom det verkade vara den familj av modeller som hade störst potential att uppnå jämnvikt mellan enkel applikation samt bra resultat.  För den klassiska SVI modellen i SVI familjen drogs slutsatsen att modellen inte var tillräcklig för att kunna rekommenderas. Detta berodde på att SVI modellen i princip alltid genererade lösningar med arbitrage i. SVI modellen genererar dock väldigt bra lösningar mot marknadsdatan enskilt och kan därför vara ett bra alternativ om man bara ska modellera ett implied volatilitetssmil. SSVI modellen ansågs däremot vara ett väldigt bra alternativ. SSVI modellen genererar komplett aribragefria lösningar men har samtidigt rimligt bra marknadspassning.  För att försöka förbättra resultaten från SSVI modellen, var en kompleterande metod kallad den kalibrerade SSVI metoden skapad. Denna metod kom att förbättra marknadspassningen som SSVI modellen genererade men som resultat kom robustheten att sjunka, då interpoleringen och extrapoleringen blev svårare att genomföra arbitragefritt.

Introducción: El Síndrome Visual Informático (SVI) es un conjunto de problemas oculares y visuales relacionados con actividades, que estresan la visión de cerca, y que se experimentan debido al frecuente uso de computadora y otros dispositivos. Esto ha despertado la preocupación del personal de salud y autoridades; aún más, a raíz del aumento masivo de la digitalización durante la pandemia, que ha predispuesto a millones de personas en el mundo a un mayor riesgo de padecerla, resultando ser necesario ver los patrones asociados a este síndrome. Objetivo: Determinar los factores asociados al SVI en estudiantes de pregrado de la Facultad de Medicina de una universidad privada de Lambayeque-Perú, durante el semestre 2021-II. Materiales y métodos: Estudio observacional analítico de corte trasversal. Se incluyó a estudiantes de la facultad de medicina (incluye Medicina Humana, Odontología, Psicología y Enfermería) de la Universidad Católica Santo Toribio de Mogrovejo que reciben clases virtuales durante Octubre-Diciembre del 2021. El desenlace fue el SVI evaluado mediante el instrumento Computer Vision Syndrome Questionnaire. Los factores asociados al desenlace fueron evaluados mediante la regresión de Poisson, con ajuste de varianzas robustas, obteniéndose razones de prevalencia (RP). Resultados: Se evaluó a 372 estudiantes (30,9% de medicina humana, 25,8% de enfermería, 22,0% de psicología, y 21,2% de odontología), de los cuales el 90,8% presentó SVI. Se encontró que el realizar descansos adecuados durante el uso de dispositivos (adecuados según el tiempo del descanso) incrementó la prevalencia del SVI (RP 1,08; IC95% 1,01 – 1,16). Conclusión: Identificamos de aproximadamente 9 de cada 10 estudiantes presentaron SVI, por lo que es imperativo el abordaje de prevención y manejo de este síndrome en los estudiantes durante esta época de educación virtual. Paradójicamente, el realizar descansos adecuados durante el uso de dispositivos conllevó a una mayor prevalencia de SVI. Futuros estudios deben explorar dicho resultado, considerando que podría ser producto a la forma de medición de la variable.