| 000 | 03634nam a22004815i 4500 | ||
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| 001 | 978-1-4614-5239-3 | ||
| 003 | DE-He213 | ||
| 005 | 20200420211748.0 | ||
| 007 | cr nn 008mamaa | ||
| 008 | 130107s2013 xxu| s |||| 0|eng d | ||
| 020 |
_a9781461452393 _9978-1-4614-5239-3 |
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| 024 | 7 |
_a10.1007/978-1-4614-5239-3 _2doi |
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| 050 | 4 | _aHB172.5 | |
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_aKCB _2bicssc |
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| 072 | 7 |
_aBUS045000 _2bisacsh |
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| 082 | 0 | 4 |
_a339 _223 |
| 100 | 1 |
_aGuerard, Jr., John B. _eauthor. |
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| 245 | 1 | 0 |
_aIntroduction to Financial Forecasting in Investment Analysis _h[electronic resource] / _cby John B. Guerard, Jr. |
| 264 | 1 |
_aNew York, NY : _bSpringer New York : _bImprint: Springer, _c2013. |
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| 300 |
_aXI, 236 p. _bonline resource. |
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| 336 |
_atext _btxt _2rdacontent |
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_acomputer _bc _2rdamedia |
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| 338 |
_aonline resource _bcr _2rdacarrier |
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_atext file _bPDF _2rda |
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| 505 | 0 | _aChapter 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. | |
| 520 | _aForecasting-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. | ||
| 650 | 0 | _aFinance. | |
| 650 | 0 | _aEconomics, Mathematical. | |
| 650 | 0 | _aMacroeconomics. | |
| 650 | 1 | 4 | _aEconomics. |
| 650 | 2 | 4 | _aMacroeconomics/Monetary Economics//Financial Economics. |
| 650 | 2 | 4 | _aFinance, general. |
| 650 | 2 | 4 | _aQuantitative Finance. |
| 710 | 2 | _aSpringerLink (Online service) | |
| 773 | 0 | _tSpringer eBooks | |
| 776 | 0 | 8 |
_iPrinted edition: _z9781461452386 |
| 856 | 4 | 0 | _uhttp://dx.doi.org/10.1007/978-1-4614-5239-3 |
| 912 | _aZDB-2-SBE | ||
| 942 | _cEBK | ||
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_c51120 _d51120 |
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