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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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Some Tests for Homoscedasticity
TL;DR: In this article, two exact tests for testing the hypothesis that the residuals from a least square regression are homoscedastic are presented, one parametric and using the F-statistic, and the other nonparametric and uses the number of peaks in the ordered sequence of unsigned residuals.
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Determining the Order of Differencing in Autoregressive Processes
TL;DR: In this paper, a proper sequence of statistical tests that allows the practitioner to handle cases in which a high order of differencing may be needed is presented, and the proper sequence is not the traditional sequence, which begins with a test for a single unit root.
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Modeling stochastic volatility: a review and comparative study
TL;DR: The authors compared a discrete-time approximation of a popular diffusion model with ARCH models for daily DM/exchange rates from 1978 to 1990, and found that the models make different assumptions about how the magnitude of price responses to information alters volatility and the amount of subsequent information.
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Introduction to Multiple Time Series Analysis
TL;DR: In this article, a wide range of multiple time series models and methods are considered, including vector autoregressive, vector auto-regressive moving average, cointegrated and periodic processes as well as state space and dynamic simultaneous equations models.