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Real options valuationthe importance...

Schone, Max.

Real options valuationthe importance of stochastic process choice in commodity price modelling /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Real options valuationby Max Schone.
Reminder of title:	the importance of stochastic process choice in commodity price modelling /
Author:	Schone, Max.
Published:	Wiesbaden :Springer Fachmedien Wiesbaden :2015.
Description:	xiv, 104 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
Subject:	Prices.
Online resource:	http://dx.doi.org/10.1007/978-3-658-07493-7
ISBN:	9783658074937 (electronic bk.)

Real options valuationthe importance of stochastic process choice in commodity price modelling /
Schone, Max.

Real options valuationthe importance of stochastic process choice in commodity price modelling /[electronic resource] :by Max Schone. - Wiesbaden :Springer Fachmedien Wiesbaden :2015. - xiv, 104 p. :ill., digital ;24 cm. - BestMasters. - BestMasters.

Empirical Analysis of Statistical Commodity Price Properties -- Stochastic Volatility, Jump Diffusion, and Levy Processes -- Real Options Valuation Using Monte Carlo Simulation and the Longstaff-Schwartz Method.

The Author shows that modelling the uncertain cash flow dynamics of an investment project deserves careful attention in real options valuation. Focusing on the case of commodity price uncertainty, a broad empirical study reveals that, contrary to common assumptions, prices are often non-stationary and exhibit non-normally distributed returns. Subsequently, more realistic stochastic volatility, jump diffusion, and Levy processes are evaluated in the context of a stylised investment project. The valuation results suggest that stochastic process choice can have substantial implications for valuation results and optimal investment rules. Contents Empirical Analysis of Statistical Commodity Price Properties Stochastic Volatility, Jump Diffusion, and Levy Processes Real Options Valuation Using Monte Carlo Simulation and the Longstaff-Schwartz Method Target Groups Researchers and students in the field of Finance, Operations Research, and Management Professionals in the field of Corporate Finance / Operations Research / Consulting The Author Max Schone is a Ph.D. student at the WHU - Otto Beisheim School of Management with a research focus on real options valuation and decision making under uncertainty.

ISBN: 9783658074937 (electronic bk.)

Standard No.: 10.1007/978-3-658-07493-7doiSubjects--Topical Terms:

182958
Prices.

LC Class. No.: HB221

Dewey Class. No.: 338.52

Real options valuationthe importance of stochastic process choice in commodity price modelling /
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505 0 $a Empirical Analysis of Statistical Commodity Price Properties -- Stochastic Volatility, Jump Diffusion, and Levy Processes -- Real Options Valuation Using Monte Carlo Simulation and the Longstaff-Schwartz Method.
520 $a The Author shows that modelling the uncertain cash flow dynamics of an investment project deserves careful attention in real options valuation. Focusing on the case of commodity price uncertainty, a broad empirical study reveals that, contrary to common assumptions, prices are often non-stationary and exhibit non-normally distributed returns. Subsequently, more realistic stochastic volatility, jump diffusion, and Levy processes are evaluated in the context of a stylised investment project. The valuation results suggest that stochastic process choice can have substantial implications for valuation results and optimal investment rules. Contents Empirical Analysis of Statistical Commodity Price Properties Stochastic Volatility, Jump Diffusion, and Levy Processes Real Options Valuation Using Monte Carlo Simulation and the Longstaff-Schwartz Method Target Groups Researchers and students in the field of Finance, Operations Research, and Management Professionals in the field of Corporate Finance / Operations Research / Consulting The Author Max Schone is a Ph.D. student at the WHU - Otto Beisheim School of Management with a research focus on real options valuation and decision making under uncertainty.
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