Att spara pengar i aktier blir allt vanligare. Det kan leda till en hög avkastning, men det kan också medfölja en stor risk. Det kräver en viss kunskap och förståelse för vad risk är och kan leda till. Nyckeltal kan hjälpa investerare då de berättar hur företag mår och hur deras framtid ser ut. De teoretiska perspektiv som låg till grund för studien var den effektiva marknadsteorin, beteendeekonomi, Prospect Theory, teorier om riskbenägenhet, portföljteori och teorier om nyckeltal. Syftet med studien var att undersöka hur respondenterna uttrycker sina attityder gentemot risk och vikten av nyckeltal vid köp av aktier. Samt att analysera hur respondenternas uttryckta personliga egenskaper kön, ålder, erfarenhet, utbildningsnivå och självförtroende speglar deras riskbenägenhet och vikten av nyckeltal. Studien är en kvantitativ metod med tvärsnittsdesign. Forskningsansatsen är deduktiv. En enkätundersökning genomfördes och besvarades av 352 respondenter som uttryckt att de sparar i aktier. Data analyserades med en multipel regressionsanalys för att hitta samband mellan variabler. Resultatet visar att över sextio procent av respondenterna väljer det säkrare alternativet före det riskfyllda. Respondenterna är riskaverta. De personliga egenskaperna som har det starkaste sambandet med riskbenägenhet är ett högt självförtroende (R = 0,2111) och kön (R = 0,1970). Resultatet visar även att nyckeltalen är viktigt för över sextio procent av respondenterna. Nyckeltalen som var mest populära är P/E-talet (60 %), direktavkastning (45 %) och EPS (37 %). De personliga egenskaperna som hade det starkaste sambandet med vikten av nyckeltal var ett högt självförtroende (R = 0,2785) och utbildningsnivå (R = 0,2079). / To save money in shares are becoming more and more popular. It can lead to a high revenue, but it also comes with a risk. It takes knowledge and an understanding for what risk is and what it can lead to. Financial ratios can help by telling investors how a firm feels financially and what their future looks like. The theoretical perspectives on which this study was based on were the efficient market theory, behavioral finance, Prospect Theory, theories about risk, portfolio selection and theories about financial ratios. The purpose of this study is to explore how the respondents express their attitudes towards risk and the importance of financial ratios when buying shares. And also to analyze how the respondents expressed personal qualities gender, age, experience, level of education and self- confidence reflects their risk level and the importance of financial ratios. The method in this study is a quantitative method with cross-sectional design. This study takes a deductive approach. The data collection is from a survey that got 352 responses. The data has been analyzed by multiple regression to find relationships between variables. The result shows that over sixty percent of the respondents chose the risk-free alternative over the riskier one. The respondents are risk averse. The personal qualities that have the strongest connection with risk are high self-confidence (R = 0,2111) and gender (R = 0,1970). The results also show that the financial ratios are important for over sixty percent of the respondents. The financial ratio that were most popular were P/E (60 %), yield (45 %) and EPS (37 %). The personal qualities that had the strongest connection with the importance of financial ratios are a high self-confidence (R = 0,2785) and level of education (R = 0,2079).

Yes / This paper examines whether and how bidders' conservative tone in 10-K filings influences the subsequent mergers and acquisitions (M&A) investment decisions of these US firms from 1996 to 2013. Based on 39,260 firm-year observations, we find, consistent with behavioural consistency theory, that conservative bidders are less likely to engage in M&A deals. Further, those that decide to engage in M&As are likely to acquire public targets and within-industry firms. These bidders are inclined to employ more stock acquisitions than cash acquisitions. Our results also indicate that conservative bidders experience abnormally poor stock returns around the announcements of M&A investments. This provides new insights on the mechanism through which bidders' sentiments influence shareholders' wealth. Overall, these findings highlight the implications of the textual sentiment of corporate disclosure for the forecasting of corporate investment and financing decisions. Our results have practical implications, since they shed light on the value relevance of the information content of major Securities Exchange Commission (SEC)-mandated 10-K filings.

We consider a class of periodic preventive maintenance (PM) optimization problems, for a single piece of equipment that deteriorates with time or use, and can be repaired upon failure, through corrective maintenance (CM). We develop analytical and simulation-based optimization models that seek an optimal periodic PM policy, which minimizes the sum of the expected total cost of PMs and the risk-averse cost of CMs, over a finite planning horizon. In the simulation-based models, we assume that both types of maintenance actions are imperfect, whereas our analytical models consider imperfect PMs with minimal CMs. The effectiveness of maintenance actions is modeled using age reduction factors. For a repairable unit of equipment, its virtual age, and not its calendar age, determines the associated failure rate. Therefore, two sets of parameters, one describing the effectiveness of maintenance actions, and the other that defines the underlying failure rate of a piece of equipment, are critical to our models. Under a given maintenance policy, the two sets of parameters and a virtual-age-based age-reduction model, completely define the failure process of a piece of equipment. In practice, the true failure rate, and exact quality of the maintenance actions, cannot be determined, and are often estimated from the equipment failure history. We use a Bayesian approach to parameter estimation, under which a random-walk-based Gibbs sampler provides posterior estimates for the parameters of interest. Our posterior estimates for a few datasets from the literature, are consistent with published results. Furthermore, our computational results successfully demonstrate that our Gibbs sampler is arguably the obvious choice over a general rejection sampling-based parameter estimation method, for this class of problems. We present a general simulation-based periodic PM optimization model, which uses the posterior estimates to simulate the number of operational equipment failures, under a given periodic PM policy. Optimal periodic PM policies, under the classical maximum likelihood (ML) and Bayesian estimates are obtained for a few datasets. Limitations of the ML approach are revealed for a dataset from the literature, in which the use of ML estimates of the parameters, in the maintenance optimization model, fails to capture a trivial optimal PM policy. Finally, we introduce a single-stage and a two-stage formulation of the risk-averse periodic PM optimization model, with imperfect PMs and minimal CMs. Such models apply to a class of complex equipment with many parts, operational failures of which are addressed by replacing or repairing a few parts, thereby not affecting the failure rate of the equipment under consideration. For general values of PM age reduction factors, we provide sufficient conditions to establish the convexity of the first and second moments of the number of failures, and the risk-averse expected total maintenance cost, over a finite planning horizon. For increasing Weibull rates and a general class of increasing and convex failure rates, we show that these convexity results are independent of the PM age reduction factors. In general, the optimal periodic PM policy under the single-stage model is no better than the optimal two-stage policy. But if PMs are assumed perfect, then we establish that the single-stage and the two-stage optimization models are equivalent. / text

Orientador: Michel Daoud Yacoub / Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Eletrica e de Computação / Made available in DSpace on 2018-08-10T01:21:53Z (GMT). No. of bitstreams: 1 CaceresZuniga_YusefRafael_D.pdf: 1196886 bytes, checksum: b589961266e398a3fd22bfd7b30719e4 (MD5) Previous issue date: 2007 / Resumo: Nesta tese, estuda-se o problema da alocação de potência através de duas abordagens: estocástica e robusta, sendo os ganhos do canal, que descrevem o estado do sistema de comunicações sem fio, parcialmente observados pelo decisor. Na abordagem estocástica, considera-se que os ganhos do canal são variáveis aleatórias, que representam a variação rápida do sinal de rádio. Nesse contexto, reformula-se o índice de desempenho do sistema através do CVaR (Conditional. Value-at-Risk). Na abordagem robusta, considera-se que os ganhos do canal e o ruído pertencem a um determinado conjunto convexo. Em ambas as abordagens, a solução ótima é obtida em termos de um problema de otimização convexa. Adicionalmente, na abordagem estocástica, apresenta-se um algoritmo recursivo e distribuído, que converge para uma solução subótima, quando o ruído é nulo e a potência transmitida é limitada tanto superior como inferiormente. Também mostra-se que, em um sistema onde os ganhos do canal coincidem com o seu valor esperado, esse algoritmo converge para a soluçãã ótima quando a qualidade do enlace é muito maior que a mínima requerida / Abstract: This thesis deals with the power allocation problem under the stochastic and robust approaches, where the channel gains describe the wireless communication system state and are partially known by the controller. The stochastic approach considers the channel gains as random variables which represent the fast fading of the radio signal. Under these settings, the system performance index is reformulated using CVaR (Conditional Value-at-Risk). The robust approach considers that the channels gains and noise belong to a determined convex set. ln both approaches, the optimal solution is determined in terms of a convex optimization problem. Additionally, under the stochastic approach, a recursive and distributed algorithm is presented which converges to its suboptimal solution when noise is null and the transmitted power is upper and lower bounded. It is also show that this algorithm converges to its optimal solution when the link quality is much greater than the minimum required quality in a system where the channels gains match its expected value / Doutorado / Telecomunicações e Telemática / Doutor em Engenharia Elétrica