Investment Appraisal: Methods and Models, Edition 2

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This book provides an introduction to investment appraisal and presents a range of methods and models, some of which are not widely known, or at least not well covered by other textbooks. Each approach is thoroughly described, evaluated and illustrated using examples, with its assumptions and limitations analyzed in terms of their implications for investment decision-making practice. Investment decisions are of vital importance to all companies. Getting these decisions right is crucial but, due to a complex and dynamic business environment, this remains a challenging management task. Effective appraisal methods are valuable tools in supporting investment decision-making. As organisations continue to seek a competitive edge, it is increasingly important that management accountants and strategic decision-makers have a sound knowledge of these tools.
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Additional Information

Publisher
Springer
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Published on
Mar 18, 2015
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Pages
366
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ISBN
9783662458518
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Language
English
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Genres
Business & Economics / Accounting / General
Business & Economics / Accounting / Managerial
Business & Economics / Finance / General
Business & Economics / General
Business & Economics / Insurance / General
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Content Protection
This content is DRM protected.
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Peter Schuster
This book has developed over the past fifteen years from a modern course on stochastic chemical kinetics for graduate students in physics, chemistry and biology. The first part presents a systematic collection of the mathematical background material needed to understand probability, statistics, and stochastic processes as a prerequisite for the increasingly challenging practical applications in chemistry and the life sciences examined in the second part.

Recent advances in the development of new techniques and in the resolution of conventional experiments at nano-scales have been tremendous: today molecular spectroscopy can provide insights into processes down to scales at which current theories at the interface of physics, chemistry and the life sciences cannot be successful without a firm grasp of randomness and its sources. Routinely measured data is now sufficiently accurate to allow the direct recording of fluctuations. As a result, the sampling of data and the modeling of relevant processes are doomed to produce artifacts in interpretation unless the observer has a solid background in the mathematics of limited reproducibility.

The material covered is presented in a modular approach, allowing more advanced sections to be skipped if the reader is primarily interested in applications. At the same time, most derivations of analytical solutions for the selected examples are provided in full length to guide more advanced readers in their attempts to derive solutions on their own. The book employs uniform notation throughout, and a glossary has been added to define the most important notions discussed.

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