IDEAS home Printed from https://ideas.repec.org/a/rsr/supplm/v64y2016i8p59-69.html
   My bibliography  Save this article

Sensitivity analysis methods in uncertainty environment

Author

Listed:
  • Alexandru MANOLE

    (Universitatea „ARTIFEX” din Bucuresti)

  • Constantin ANGHELACHE

    (Universitatea „ARTIFEX” din Bucuresti, Academia de Studii Economice, Bucuresti)

  • Madalina Gabriela ANGHEL

    (Universitatea „ARTIFEX” din Bucuresti)

  • Andreea MARINESCU

    (Academia de Studii Economice, Bucuresti)

Abstract

The realization of the sensitivity analysis in the practice of investments is a determinant element in the choice of optimum variance. In practice, the variables and data taken into consideration when determining the investment happen to modify. There must be interpreted the variables considered also from the viewpoint of each one’s sensitivity. For the control of the investment process, it is mandatory to realize feasibility studies, by taking into account the complexity of the business environment, the change of the influences of some factos or even the occurrence of some that have not been initially considered. The model used in the elaboration of the feasibility study must outline the factorial variables of sensitivity, specifical to uncertainty.Among the models used for sensitivity analysis, we have emphasized the Monte Carlo simulation model, because it takes into account all posibilities to combine the influence factors on the Net Value Added (VAN). The steps in using the Monte Carlo simulation model are thoroughly presented and explained by precise case studies. Also, we have presented the decision tree method and others, likewise effective.

Suggested Citation

  • Alexandru MANOLE & Constantin ANGHELACHE & Madalina Gabriela ANGHEL & Andreea MARINESCU, 2016. "Sensitivity analysis methods in uncertainty environment," Romanian Statistical Review Supplement, Romanian Statistical Review, vol. 64(8), pages 59-69, August.
  • Handle: RePEc:rsr:supplm:v:64:y:2016:i:8:p:59-69
    as

    Download full text from publisher

    File URL: http://www.revistadestatistica.ro/supliment/wp-content/uploads/2016/09/RRSS_08_2016_A4_en.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Grenadier, Steven R. & Wang, Neng, 2007. "Investment under uncertainty and time-inconsistent preferences," Journal of Financial Economics, Elsevier, vol. 84(1), pages 2-39, April.
    2. Ravi Bansal & Dana Kiku & Ivan Shaliastovich & Amir Yaron, 2014. "Volatility, the Macroeconomy, and Asset Prices," Journal of Finance, American Finance Association, vol. 69(6), pages 2471-2511, December.
    3. Constantin ANGHELACHE & Alexandru MANOLE & Mădălina Gabriela ANGHEL, 2015. "Analysis of final consumption and gross investment influence on GDP – multiple linear regression model," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania - AGER, vol. 0(3(604), A), pages 137-142, Autumn.
    4. Constantin Anghelache & Alexandru Manole & Madalina Gabriela Anghel, 2015. "Analysis of Final Consumption, Gross Investment, the Changes in Inventories and Net Exports Influence of GDP Evolution, by Multiple Regression," International Journal of Academic Research in Accounting, Finance and Management Sciences, Human Resource Management Academic Research Society, International Journal of Academic Research in Accounting, Finance and Management Sciences, vol. 5(3), pages 66-70, July.
    5. repec:agr:journl:v:3(604):y:2015:i:3(604):p:137-142 is not listed on IDEAS
    6. Reinhold Hafner & Martin Wallmeier, 2008. "Optimal investments in volatility," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 22(2), pages 147-167, June.
    7. Saman, Corina, 2010. "Macroeconomic Uncertainty and Investment – Empirical Analysis for Romania," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 155-164, July.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Constantin ANGHELACHE & Alexandru MANOLE & Mădălina-Gabriela ANGHEL, 2017. "Macroeconomic models used in structural analysis of GDP," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania - AGER, vol. 0(1(610), S), pages 197-206, Spring.
    2. Madalina-Gabriela ANGHEL & Georgiana NITA & Alexandru BADIU, 2017. "Impact of Remittances on Financial Development and Economic Growth," Romanian Statistical Review Supplement, Romanian Statistical Review, vol. 65(1), pages 106-112, January.
    3. Constantin ANGHELACHE & Alexandru MANOLE & Mădălina-Gabriela ANGHEL, 2017. "Macroeconomic models used in structural analysis of GDP," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania - AGER, vol. 0(1(610), S), pages 197-206, Spring.
    4. Constantin ANGHELACHE & Aurelian DIACONU & Emilia STANCIU, 2017. "Precaution Of Savings Under Uncertain Circumstances," Romanian Statistical Review Supplement, Romanian Statistical Review, vol. 65(2), pages 30-37, February.
    5. Constantin Anghelache & Alexandru Manole & Madalina-Gabriela Anghel & Emilia Stanciu & Alexandru Ursache, 2017. "Some Significant Macroeconomic Evolutions at the End of 2016," International Journal of Academic Research in Accounting, Finance and Management Sciences, Human Resource Management Academic Research Society, International Journal of Academic Research in Accounting, Finance and Management Sciences, vol. 7(1), pages 213-224, January.
    6. Constantin ANGHELACHE & Madalina Gabriela ANGHEL, 2017. "Econometric Methods And Models Used In The Analysis Of The Factorial Influence Of The Gross Domestic Product Growth," Network Intelligence Studies, Romanian Foundation for Business Intelligence, Editorial Department, issue 9, pages 67-78, June.
    7. Madalina-Gabriela ANGHEL & Constantin ANGHELACHE & Diana Valentina DUMITRESCU & Daniel DUMITRESCU, 2016. "Analysis of the correlation between the Gross Domestic Product and some factorial variables," Romanian Statistical Review Supplement, Romanian Statistical Review, vol. 64(10), pages 138-145, October.
    8. Yang Liu & Mariano Croce & Ivan Shaliastovich & Ric Colacito, 2016. "Volatility Risk Pass-Through," 2016 Meeting Papers 135, Society for Economic Dynamics.
    9. Ping‐Wen Sun & Yifan Shen & Meifen Qian & Wu Yan, 2021. "Risk of holding stocks with liquidity sensitive to market uncertainty: evidence from China," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 61(S1), pages 1993-2029, April.
    10. Yu-Jui Huang & Adrien Nguyen-Huu, 2018. "Time-consistent stopping under decreasing impatience," Finance and Stochastics, Springer, vol. 22(1), pages 69-95, January.
    11. Sunil S. Poshakwale & Pankaj Chandorkar, 2019. "The Impact of Aggregate and Disaggregate Consumption Shocks on the Equity Risk Premium in the United Kingdom," Annals of Economics and Finance, Society for AEF, vol. 20(2), pages 489-524, November.
    12. Agliardi, Elettra & Andergassen, Rainer, 2009. "Last resort gambles, risky debt and liquidation policy," Review of Financial Economics, Elsevier, vol. 18(3), pages 142-155, August.
    13. Geert Bekaert & Eric C. Engstrom & Nancy R. Xu, 2022. "The Time Variation in Risk Appetite and Uncertainty," Management Science, INFORMS, vol. 68(6), pages 3975-4004, June.
    14. Gao, Lin & Hitzemann, Steffen & Shaliastovich, Ivan & Xu, Lai, 2022. "Oil volatility risk," Journal of Financial Economics, Elsevier, vol. 144(2), pages 456-491.
    15. Kanwal Iqbal Khan & Syed M. Waqar Azeem Naqvi & Muhammad Mudassar Ghafoor & Rana Shahid Imdad Akash, 2020. "Sustainable Portfolio Optimization with Higher-Order Moments of Risk," Sustainability, MDPI, vol. 12(5), pages 1-14, March.
    16. Li, Jiangyuan & Liu, Bo & Yang, Jinqiang & Zou, Zhentao, 2020. "Hedge fund’s dynamic leverage decisions under time-inconsistent preferences," European Journal of Operational Research, Elsevier, vol. 284(2), pages 779-791.
    17. Campbell, John Y. & Giglio, Stefano & Polk, Christopher & Turley, Robert, 2018. "An intertemporal CAPM with stochastic volatility," Journal of Financial Economics, Elsevier, vol. 128(2), pages 207-233.
    18. Liu, Bo & Mu, Congming & Yang, Jinqiang, 2017. "Dynamic agency and investment theory with time-inconsistent preferences," Finance Research Letters, Elsevier, vol. 20(C), pages 88-95.
    19. Andersen, Torben G. & Varneskov, Rasmus T., 2021. "Consistent inference for predictive regressions in persistent economic systems," Journal of Econometrics, Elsevier, vol. 224(1), pages 215-244.
    20. Qinglong Zhou & Gaofeng Zong, 2016. "Time-Inconsistent Stochastic Linear-quadratic Differential Game," Papers 1607.00638, arXiv.org.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:rsr:supplm:v:64:y:2016:i:8:p:59-69. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Adrian Visoiu (email available below). General contact details of provider: https://edirc.repec.org/data/stagvro.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.