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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.
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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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Econometric tests of rationality and market efficiency
TL;DR: In this article, the authors describe how economic theories can be tested from vector time series models using cointegration and the concept of co-integration in the modeling and testing procedure.
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Full Bayesian Inference for GARCH and EGARCH Models
TL;DR: A full Bayesian analysis of GARCH and EGARCH models is proposed consisting of parameter estimation, model selection, and volatility prediction and implemented via Markov-chain Monte Carlo methodologies.
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Trading volume and transaction costs in futures markets
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A New Class of Multivariate Skew Densities, with Application to GARCH Models
Luc Bauwens,Sébastien Laurent +1 more
TL;DR: In this article, the authors proposed a method to introduce skewness in multivariate symmetric distributions, which leads to a multivariate skew-student density, in which each marginal has a specific asymmetry coefficient.
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Multivariate stochastic volatility models: Estimation and a comparison with VGARCH models
TL;DR: In this article, a multivariate stochastic volatility (MSV) model is presented together with an estimation method, which requires specialized estimation techniques since the volatility is a dynamic latent variable.