Sequential capital investment decision making under extreme cash fl ow situations: evidence using Monte Carlo simulation

    Wenqing Zhang Info
    Prasad Padmanabhan Info
    Chia-Hsing Huang Info
DOI: https://doi.org/10.3846/16111699.2015.1039056

Abstract

Uncertainty influences a decision maker's choices when making sequential capital investment decisions. With the possibility of extremely negative cash inflows, firms may need to curtail operations significantly. Traditional Net Present Value analysis does not allow for efficient management of these problems. In addition, firm managers may behave irrationally by accepting negative Net Present Value projects in the short term. This paper presents a Monte Carlo simulation based model to provide policy insights on how to incorporate extreme cash flows and manager irrationality scenarios into the capital budgeting process. This paper presents evidence that firms with irrational managers and experiencing extremely negative cash flows may, under certain conditions, reap long term rewards associated with the acceptance of negative Net Present Value projects in the short term. These benefits are largest if cost ratios (discount rates) are small, or investment horizons are high. We argue that acceptance of short term negative Net Present Value projects implies the purchase of a long term real option which can generate positive long term cash flows under certain conditions.

Keywords:

sequential capital investment, extreme values, Monte Carlo simulation, real options, uncertainty, net present value

How to Cite

Zhang, W., Padmanabhan, P., & Huang, C.-H. (2015). Sequential capital investment decision making under extreme cash fl ow situations: evidence using Monte Carlo simulation. Journal of Business Economics and Management, 16(5), 877-900. https://doi.org/10.3846/16111699.2015.1039056

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October 26, 2015
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2015-10-26

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How to Cite

Zhang, W., Padmanabhan, P., & Huang, C.-H. (2015). Sequential capital investment decision making under extreme cash fl ow situations: evidence using Monte Carlo simulation. Journal of Business Economics and Management, 16(5), 877-900. https://doi.org/10.3846/16111699.2015.1039056

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