Introduction to Financial Forecasting in Investment Analysis

Forecasting—the art and science of predicting future outcomes—has become a crucial skill in business and economic analysis. This volume introduces the reader to the tools, methods, and techniques of forecasting, specifically as they apply to financial and investing decisions.  With an emphasis on “e...

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Bibliographic Details
Main Author: Guerard, Jr., John B.
Format: eBook
Language:English
Published: New York, NY Springer New York 2013, 2013
Edition:1st ed. 2013
Subjects:
Online Access:
Collection: Springer eBooks 2005- - Collection details see MPG.ReNa
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245 0 0 |a Introduction to Financial Forecasting in Investment Analysis  |h Elektronische Ressource  |c by John B. Guerard, Jr 
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300 |a XI, 236 p  |b online resource 
505 0 |a Chapter 1: Why do we forecast? -- Chapter 2: Regression Analysis and Forecasting Models -- Chapter 3: An Introduction to Time Series Modeling and Forecasting -- Chapter 4: Regression Analysis and Multicollinearity: Two Case Studies -- Chapter 5: Multiple Time Series Analysis and Causality Testing -- Chapter 6: A Case Study of Portfolio Construction using the USER Data and the Barra Aegis System -- Chapter 7: More Efficient Portfolios Featuring the USER Data and an Extension to Global Data and Investment Universes -- Chapter 8: Forecasting World Stock Returns and Improved Asset Allocation -- Chapter 9: Summary and Conclusions 
653 |a Finance 
653 |a Quantitative Finance 
653 |a Macroeconomics/Monetary Economics//Financial Economics 
653 |a Economics, Mathematical  
653 |a Macroeconomics 
653 |a Finance, general 
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520 |a Forecasting—the art and science of predicting future outcomes—has become a crucial skill in business and economic analysis. This volume introduces the reader to the tools, methods, and techniques of forecasting, specifically as they apply to financial and investing decisions.  With an emphasis on “earnings per share” (eps), the author presents a data-oriented text on financial forecasting, understanding financial data, assessing firm financial strategies (such as share buybacks and R&D spending), creating efficient portfolios, and hedging stock portfolios with financial futures.  The opening chapters explain how to understand economic fluctuations and how the stock market leads the general economic trend; introduce the concept of portfolio construction and how movements in the economy influence stock price movements; and introduce the reader to the forecasting process, including exponential smoothing and time series model estimations.  Subsequent chapters examine the composite index of leading economic indicators (LEI); review financial statement analysis and mean-variance efficient portfolios; and assess the effectiveness of analysts’ earnings forecasts.  Using data from such firms as Intel, General Electric, and Hitachi, Guerard demonstrates how forecasting tools can be applied to understand the business cycle, evaluate market risk, and demonstrate the impact of global stock selection modeling and portfolio construction