34 resultados para stochastic stability


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The purpose of this paper is to examine the stability and predictive abilities of the beta coefficients of individual equities in the Finnish stock market. As beta is widely used in several areas of finance, including risk management, asset pricing and performance evaluation among others, it is important to understand its characteristics and find out whether its estimates can be trusted and utilized.

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THE WAY TO ORGANIZATIONAL LONGEVITY – Balancing stability and change in Shinise firms The overall purpose of this dissertation is to investigate the secret of longevity in Shinise firms. On the basic assumption that organizational longevity is about balancing stability and change, the theoretical perspectives incorporate routine practice, organizational culture, and organizational identity. These theories explain stability and change in an organization separately and in combination. Qualitative inductive theory building was used in the study. Overall, the empirical data comprised 75 in-depth and semi-structured interviews, 137 archival materials, and observations made over 17 weeks. According to the empirical findings, longevity in Shinise firms is attributable to the internal mechanisms (Shinise tenacity, stability in motion, and emergent change) to secure a balance between stability and change, the continuing stability of the socio-cultural environment in the local community, and active interaction between organizational and local cultures. The contribution of the study to the literature on organizational longevity and the alternative theoretical approaches is first, in theorizing the mechanisms of Shinise tenacity and cross-level cultural dynamism, and second, in pointing out the critical role of: the way firms set their ultimate goal, the dynamism in culture, and the effect of history of the firm to the current business in securing longevity. KEY WORDS Change; Culture; Organizational identity; Organizational longevity; Routines; Shinise firms; Stability; Qualitative research

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Since its discovery, chaos has been a very interesting and challenging topic of research. Many great minds spent their entire lives trying to give some rules to it. Nowadays, thanks to the research of last century and the advent of computers, it is possible to predict chaotic phenomena of nature for a certain limited amount of time. The aim of this study is to present a recently discovered method for the parameter estimation of the chaotic dynamical system models via the correlation integral likelihood, and give some hints for a more optimized use of it, together with a possible application to the industry. The main part of our study concerned two chaotic attractors whose general behaviour is diff erent, in order to capture eventual di fferences in the results. In the various simulations that we performed, the initial conditions have been changed in a quite exhaustive way. The results obtained show that, under certain conditions, this method works very well in all the case. In particular, it came out that the most important aspect is to be very careful while creating the training set and the empirical likelihood, since a lack of information in this part of the procedure leads to low quality results.

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The aim of this study is to propose a stochastic model for commodity markets linked with the Burgers equation from fluid dynamics. We construct a stochastic particles method for commodity markets, in which particles represent market participants. A discontinuity in the model is included through an interacting kernel equal to the Heaviside function and its link with the Burgers equation is given. The Burgers equation and the connection of this model with stochastic differential equations are also studied. Further, based on the law of large numbers, we prove the convergence, for large N, of a system of stochastic differential equations describing the evolution of the prices of N traders to a deterministic partial differential equation of Burgers type. Numerical experiments highlight the success of the new proposal in modeling some commodity markets, and this is confirmed by the ability of the model to reproduce price spikes when their effects occur in a sufficiently long period of time.