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Titlebook: Economic and Financial Modelling with EViews; A Guide for Students Abdulkader Aljandali,Motasam Tatahi Book 2018 Springer International Pub

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書(shū)目名稱(chēng)Economic and Financial Modelling with EViews
副標(biāo)題A Guide for Students
編輯Abdulkader Aljandali,Motasam Tatahi
視頻videohttp://file.papertrans.cn/302/301868/301868.mp4
概述EViews is widely used in top business schools and in industry.Practical guide for both professionals and students.Step-by-step tutorials throughout.More than 100 color graphs and tables.Includes suppl
叢書(shū)名稱(chēng)Statistics and Econometrics for Finance
圖書(shū)封面Titlebook: Economic and Financial Modelling with EViews; A Guide for Students Abdulkader Aljandali,Motasam Tatahi Book 2018 Springer International Pub
描述.This practical guide in Eviews is aimed at practitioners and students in business, economics, econometrics, and finance. It uses a step-by-step approach to equip readers with a toolkit that enables them to make the most of this widely used econometric analysis software. Statistical and econometrics concepts are explained visually with examples, problems, and solutions..Developed by economists, the Eviews statistical software package is used most commonly for time-series oriented econometric analysis. It allows users to quickly develop statistical relations from data and then use those relations to forecast future values of the data. The package provides convenient ways to enter or upload data series, create new series from existing ones, display and print series, carry out statistical analyses of relationships among series, and manipulate results and output. This highly hands-on resource includes more than 200 illustrative graphs and tables and tutorials throughout.?.Abdulkader Aljandali.?is Senior Lecturer at Coventry University in London. He is currently leading the Stochastic Finance Module taught as part of the Global Financial Trading MSc. His previously published work includ
出版日期Book 2018
關(guān)鍵詞one variable analysis; inference statistics; random variables; two-variable analysis correlation; covari
版次1
doihttps://doi.org/10.1007/978-3-319-92985-9
isbn_softcover978-3-030-06562-1
isbn_ebook978-3-319-92985-9Series ISSN 2199-093X Series E-ISSN 2199-0948
issn_series 2199-093X
copyrightSpringer International Publishing AG, part of Springer Nature 2018
The information of publication is updating

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Time Series Modelling,length? Calculating the mean of a sequence of observations might appear to be a trivial problem, as we would just sum all readings and divide by their number. However, if the series is steadily increasing overtime, i.e. exhibits a trend and we make decisions based on this mean, we would certainly no
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Further Properties of Time Series,Greek word . pronounced “stokhos” and which means “a target”. If you throw a dart at the bulls-eye on a target many times, you will probably hit the bulls-eye only a few times. At other times, the dart will miss the target and be spread randomly about that point. Stochastic processes contain such ra
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Vector Autoregression (VAR) Model,istical model), which is explained by the relationships between functions within the model. For example, the equilibrium price of a good in a supply and demand model is endogenous because it is set by a producer in response to consumer demand. If the general movement of one variable can be expected
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Panel Data Analysis,es. This chapter discusses . using the same group of entities like individuals, firms, states, countries, and the like .. Panel data has a lot of advantages over pure cross-sectional data or pure time series data. The advantages are as follows:
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