lecture15 - Lecture 15: Time Series Modeling Steven Skiena...

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Lecture 15: Time Series Modeling Steven Skiena Department of Computer Science State University of New York Stony Brook, NY 11794–4400 http://www.cs.sunysb.edu/ skiena
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Modeling and Forecasting We seek to construct a model of a function so as to forecast future values of it. Certain models are proposed on theoretical grounds from first principles. If stock prices are defined by an unbiased random walk, the best forecast is the last observation, F n = S n 1 . Other models are constructed by fitting observed time series data.
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Statisticians vs. Computer Scientists There is tension between the way different disciplines view the world of modeling/forecasting. Statisticians are concerned with the limits of what can rigorously be inferred from data. Computer Scientists are concerned with building the best model they can, regardless of whether it can be justified. We will first explore standard statistical time series models before introducing data mining/pattern recognition methods.
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A Model Building Strategy Model selection / specification identifies the right class of models from observation or a priori knowledge of the time series Model fitting finds the best possible estimates for the parameters underlying the model. Model diagnosis / evaluation assesses how well the model fits the original data and whether it can be improved.
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This note was uploaded on 01/02/2012 for the course FINANCE 347 taught by Professor Bayou during the Fall '11 term at NYU.

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lecture15 - Lecture 15: Time Series Modeling Steven Skiena...

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