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Introductory Econometrics for Finance
TLDR
The third edition has been updated with new data, extensive examples and additional introductory material on mathematics, making the book more accessible to students encountering econometrics for the first time as discussed by the authors.Abstract:
This bestselling and thoroughly classroom-tested textbook is a complete resource for finance students. A comprehensive and illustrated discussion of the most common empirical approaches in finance prepares students for using econometrics in practice, while detailed case studies help them understand how the techniques are used in relevant financial contexts. Worked examples from the latest version of the popular statistical software EViews guide students to implement their own models and interpret results. Learning outcomes, key concepts and end-of-chapter review questions (with full solutions online) highlight the main chapter takeaways and allow students to self-assess their understanding. Building on the successful data- and problem-driven approach of previous editions, this third edition has been updated with new data, extensive examples and additional introductory material on mathematics, making the book more accessible to students encountering econometrics for the first time. A companion website, with numerous student and instructor resources, completes the learning package.read more
Citations
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Oil prices and the stock prices of alternative energy companies
Irene Henriques,Perry Sadorsky +1 more
TL;DR: In this article, a four variable vector autoregression model is developed and estimated in order to investigate the empirical relationship between alternative energy stock prices, technology stock prices and oil prices, and interest rates.
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Impact of Reward and Recognition on Job Satisfaction and Motivation: An Empirical Study from Pakistan
Rizwan Qaiser Danish,Ali Usman +1 more
TL;DR: In this article, the authors present an attempt to find out the major factors that motivate employees and it tells what is the relationship among reward, recognition and motivation while working within an organization.
Posted Content
Volatility and correlation forecasting
TL;DR: A recent survey of the most important theoretical developments and empirical insights to emerge from this burgeoning literature, with a distinct focus on forecasting applications is provided in this paper, where a series of different economic situations in which volatility plays a crucial role, ranging from the use of volatility forecasts in portfolio allocation to density forecasting in risk management.
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Bank Specific and Macroeconomic Determinants of Commercial Bank Profitability Empirical Evidence from Turkey
Değer Alper,Adem Anbar +1 more
TL;DR: In this paper, the authors examined the bank-specific and macroeconomic determinants of the banks profitability in Turkey over the time period from 2002 to 2010 and found that asset size and non-interest income have a positive and significant effect on bank profitability.
Journal ArticleDOI
Forecasting the short-term metro passenger flow with empirical mode decomposition and neural networks
Yu Wei,Mu-Chen Chen +1 more
TL;DR: In this article, a hybrid EMD-BPN forecasting approach which combines empirical mode decomposition (EMD) and back-propagation neural networks (BPN) is developed to predict the short-term passenger flow in metro systems.
References
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Spurious regression and residual-based tests for cointegration in panel data
TL;DR: In this paper, the null distribution of residual-based cointegration tests depends on the asymptotics of the least-squares dummy variable (LSDV) estimator and other conventional statistics.
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Modelling the Coherence in Short-run Nominal Exchange Rates: A Multivariate Generalized ARCH Model.
TL;DR: In this article, a multivariate time series model with time varying conditional variances and covariances but with constant conditional correlations is proposed, which is readily interpreted as an extension of the seemingly unrelated regression (SUR) model allowing for heteroskedasticity.
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Testing for serial correlation in least squares regression. II.
James Durbin,G. S. Watson +1 more
TL;DR: The problem of testing the errors for independence forms the subject of this paper and its successor and deals mainly with the theory on which the test is based, while the second paper describes the test procedures in detail and gives tables of bounds to the significance points of the test criterion adopted.
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Unit root tests for panel data
TL;DR: In this paper, the authors developed unit root tests for panel data under more general assumptions than the tests previously proposed, such as the number of groups in the panel data is assumed to be either finite or infinite.