Reseña del editor:
This book is an introduction to financial valuation and financial data analyses using econometric methods. It is intended for advanced finance undergraduates and graduates. Most chapters in the book would contain one or more finance application examples where finance concepts, and sometimes theory, are taught.This book is a modest attempt to bring together several important domains in financial valuation theory, in econometrics modelling, and in the empirical analyses of financial data. These domains are highly intertwined and should be properly understood in order to correctly and effectively harness the power of data and statistical or econometrics methods for investment and financial decision-making.The contribution in this book, and at the same time, its novelty, is in employing materials in basic econometrics, particularly linear regression analyses, and weaving into it threads of foundational finance theory, concepts, ideas, and models. It provides a clear pedagogical approach to allow very effective learning by a finance student who wants to be well equipped in both theory and ability to research the data.This is a handy book for finance professionals doing research to easily access the key techniques in data analyses using regression methods. Students learn all 3 skills at once - finance, econometrics, and data analyses. It provides for very solid and useful learning for advanced undergraduate and graduate students who wish to work in financial analyses, risk analyses, and financial research areas.
Nota de la solapa:
This book brings together domains in financial asset pricing and valuation, financial investment theory, econometrics modeling, and the empirical analyses of financial data by applying appropriate econometric techniques. These domains are highly intertwined and should be properly understood in order to correctly and effectively harness the power of data and methods for investment and financial decision-making. The book is targeted at advanced finance undergraduates and beginner professionals performing financial forecasts or empirical modeling who will find it refreshing to see how forecasting is not simply running a least squares regression line across data points, and that there are many minefields and pitfalls to avoid, such as spurious results and incorrect interpretations.
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