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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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Option Valuation and Hedging Strategies with Jumps in the Volatility of Asset Returns
TL;DR: This article developed a model in which the volatility of risky assets is subject to random and discontinuous shifts over time, and derived prices of claims contingent on such assets and analyzed options-based trading strategies to hedge against the risk of jumps in the return volatility.
Book
Neural Networks in the Capital Markets
TL;DR: The author takes a pragmatic view of neural networks, treating them as computationally equivalent to well-understood, non-parametric inference methods in decision science and makes comparisons with established techniques where appropriate.
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Tail Index Estimates in Small Samples
TL;DR: In this paper, the authors present a simple methodology that accurately estimates the degree of tail fatness, characterized by the tail index, in small samples using a weighted average of Hill estimators for different threshold values.
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Event study methods and evidence on their performance
TL;DR: In this paper, the authors outline widely used methods of estimating abnormal returns and testing their significance, highlights respects in which they differ conceptually, and reviews research comparing results they produce in various empirical contexts.
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Consistent Ranking of Volatility Models
TL;DR: This article showed that the empirical ranking of volatility models can be inconsistent for the true ranking if the evaluation is based on a proxy for the population measure of volatility, which can result in an inferior model being chosen as "best" with a probability that converges to one as the sample size increases.