Spelling suggestions: "subject:"stochastic processes"" "subject:"ctochastic processes""
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A balanced view of system identificationMcGinnie, B. Paul January 1993 (has links)
No description available.
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Random polynomialsHannigan, Patrick January 1998 (has links)
No description available.
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Statistická fyzika frustrovaných evolučních her / Statistická fyzika frustrovaných evolučních herPištěk, Miroslav January 2010 (has links)
1 Title: Statistical Physics of Frustrated Evolutionary Games Author: Miroslav Pištěk Department: Institute of Theoretical Physics Supervisor: RNDr. František Slanina, CSc. Supervisor's e-mail address: slanina@fzu.cz Abstract: In last two decades, the effort devoted to interdisciplinary research of bounded sources allocation is growing, examining complex phenomena as stock markets or traffic jams. The Minority Game is a multiple-agent model of inevitable frus- tration arising in such situations. It is analytically tractable using the replica method originated in statistical physics of spin glasses. We generalised the Mi- nority Game introducing heterogenous agents. This heterogeneity causes a con- siderable decrease of an average agent's frustration. For many configurations, we achieve even a positive-sum game, which is not possible in the original game variant. This result is in accordance with real stock market data. Keywords: frustrated evolutionary games, Minority Game, Replica method
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Stochastic portfolio theory and its applications to equity managementBonney, Lisa 25 February 2014 (has links)
Stochastic portfolio theory is a novel methodology, developed by Fernholz (2002), for analysing stock and portfolio
behaviour, and equity market structure, constructing portfolios and understanding the structure of equity
markets. It thus has immediate applications to equity portfolio management and performance measurement.
This theory successfully generalises well-known models for the stock price to provide models for portfolios and
markets, leading to a better and more precise understanding of equity market structure. The aim of this
dissertation is to present an exhaustive review of stochastic portfolio theory by imitating the work done and
contributions made by Fernholz (2002) thus far. A detailed discussion of stochastic portfolio theory as well
as how the implications di er from the conclusions and results of classic portfolio theory will be provided. In
this dissertation, we will undertake a thorough investigation into stochastic portfolio theory; by focusing on
the central, innovative ideas of the excess growth rate, long-term stock market and portfolio behaviour, stock
market diversity of equity markets, portfolio generating functions, the concept of how to select stocks by their
rank and the existence of relative arbitrage opportunities within the context of stochastic portfolio theory. Thus,
we shall review the central concepts of stochastic portfolio theory, this will include a detailed explanation of
the excess growth rate, long-term behaviour of portfolios, stock market diversity, portfolio generating functions
and stocks selected by rank. We will also present examples of portfolios and markets with a wide variety of
di erent properties. We will also show how this new and fast-evolving theory can be applied, in particular, to
equity management, by considering the performance of certain functionally generated portfolios. Furthermore,
several results and implications of stochastic portfolio theory will be discussed, and in this dissertation, we shall
examine these results in far greater depth.
Keywords and Phrases: Stochastic portfolio theory, Portfolios, Stock market and portfolio behaviour, Stock
market diversity, Portfolio generating functions, Functionally generated portfolios, Rank-dependent portfolio
generating functions, Local time, Relative arbitrage opportunities, Performance of functionally generated portfolios.
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Time-series stochastic process and forecastingChien, Tony Lee-Chuin January 2010 (has links)
Photocopy of typescript. / Digitized by Kansas Correctional Industries
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Escape dynamics in learning models /Williams, Noah. January 2001 (has links)
Thesis (Ph. D.)--University of Chicago, Dept. of Economics, June 2001. / Includes bibliographical references. Also available on the Internet.
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Large deviation principle for functional limit theoremsOprisan, Adina. January 2009 (has links)
Thesis (Ph.D.)--University of Texas at Arlington, 2009.
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Computational nonlinear dynamics monostable stochastic resonance and a bursting neuron model /Breen, Barbara J., January 2003 (has links) (PDF)
Thesis (Ph. D.)--School of Physics, Georgia Institute of Technology, 2004. Directed by Kurt Wiesenfeld. / Includes bibliographical references (leaves 122-128).
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Convergences of stochastic optimization algorithms李國誠, Lee, Kwok-shing. January 1999 (has links)
published_or_final_version / abstract / toc / Computer Science and Information Systems / Master / Master of Philosophy
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On a topic of generalized linear mixed models and stochastic volatility modelYam, Ho-kwan., 任浩君. January 2002 (has links)
published_or_final_version / abstract / toc / Statistics and Actuarial Science / Master / Master of Philosophy
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