Instantaneous optimal investment decisions with costly and costless reversibility

EconoQuantum ◽  
2007 ◽  
Vol 3 (2) ◽  
pp. 71-88
Author(s):  
Öner Günçavdi ◽  
◽  
Seyidali S. Akhiev ◽  
Andrew McKay ◽  
◽  
...  
2021 ◽  
pp. 0958305X2199229
Author(s):  
Jingyu Qu ◽  
Wooyoung Jeon

Renewable generation sources still have not achieved economic validity in many countries including Korea, and require subsidies to support the transition to a low-carbon economy. An initial Feed-In Tariff (FIT) was adopted to support the deployment of renewable energy in Korea until 2011 and then was switched to the Renewable Portfolio Standard (RPS) to implement more market-oriented mechanisms. However, high volatilities in electricity prices and subsidies under the RPS scheme have weakened investment incentives. In this study we estimate how the multiple price volatilities under the RPS scheme affect the optimal investment decisions of energy storage projects, whose importance is increasing rapidly because they can mitigate the variability and uncertainty of solar and wind generation in the power system. We applied mathematical analysis based on real-option methods to estimate the optimal trigger price for investment in energy-storage projects with and without multiple price volatilities. We found that the optimal trigger price of subsidy called the Renewable Energy Certificate (REC) under multiple price volatilities is 10.5% higher than that under no price volatilities. If the volatility of the REC price gets doubled, the project requires a 26.6% higher optimal investment price to justify the investment against the increased risk. In the end, we propose an auction scheme that has the advantage of both RPS and FIT in order to minimize the financial burden of the subsidy program by eliminating subsidy volatility and find the minimum willingness-to-accept price for investors.


Author(s):  
Mo Adam Mahmood ◽  
Gary J. Mann ◽  
Mark Dubrow

This instructional case, based on an actual firm’s experience (name changed) is intended to challenge student thinking with regard to the extent to which information technology (IT) can demonstrably contribute to organizational performance and productivity, and to which users of IT can relate their investment decisions to measurable outcomes. Relationships between an organization’s investment in IT and the effect of such investments on the organization’s performance and productivity have long been the subject of discussion and research. Managers, interested in knowing the “payoff” of such investments, are continually seeking answers to this question. A failure to understand the benefits of IT investment, or an over- or under-estimation of the benefits of a planned investment in IT relative to the costs, will likely result in less than optimal investment decisions.


2008 ◽  
Vol 44 (11) ◽  
pp. 1100-1113 ◽  
Author(s):  
Christophette Blanchet-Scalliet ◽  
Nicole El Karoui ◽  
Monique Jeanblanc ◽  
Lionel Martellini

2011 ◽  
Vol 8 (3) ◽  
pp. 341-343 ◽  
Author(s):  
Jukka T. Forsman ◽  
Janne-Tuomas Seppänen ◽  
Inka L. Nykänen

Optimal investment in offspring is important in maximizing lifetime reproductive success. Yet, very little is known how animals gather and integrate information about environmental factors to fine tune investment. Observing the decisions and success of other individuals, particularly when those individuals initiate breeding earlier, may provide a way for animals to quickly arrive at better breeding investment decisions. Here we show, with a field experiment using artificial nests appearing similar to resident tit nests with completed clutches, that a migratory bird can use the observed high and low clutch size of a resident competing bird species to increase and decrease clutch size and egg mass, accordingly. Our results demonstrate that songbirds can discriminate between high and low quantity of heterospecific eggs, and that social information can have long-term physiological consequences affecting reproductive strategies. Such behaviour may help animals to better adapt to changing environments and lead to convergent traits with competitors.


Author(s):  
Johnson T. S. Cheng ◽  
I-Ming Jiang ◽  
Yu-Hong Liu

This paper employs a real options approach to analyze optimal investment decisions. When investment projects have the characteristics of irreversibility, uncertainty and the option to wait or exit, the traditional net present value (NPV) method would underestimate the value of investment, since it neglects the values of timing and operational flexibility. The distinctive feature of this paper is that the effects of product life cycle (PLC) as well as market power are incorporated into the model. In addition, and different to the approach in Liao et al. [Optimal investment decision and product life cycle: A real options approach, Sun Yat-Sen Management Review 11(3) (2003) 1–36], we introduce the concept of technological innovation into the model. It is shown that the optimal waiting time for the investment is longer than both those in the American call options model of McDonald and Siegel [The value of waiting to invest, Quarterly Journal of Economics 101(4) (1986) 707–727], which does not incorporate dividend yield, and Liao et al. [Optimal investment decision and product life cycle: A real options approach, Sun Yat-Sen Management Review 11(3) (2003) 1–36], but is shorter than that in Dixit and Pindyck's [Investment under Uncertainty (Princeton University Press, Princeton, NJ, 1994)] model, which incorporates dividend yield. Finally, a comparative static is used to analyze the determinants of optimal investment decisions. Our results indicate that the investment-ratio threshold will be higher, and thus the optimal entry time for an investment will be delayed, when (1) the PLC is longer, (2) the uncertainty is greater, (3) the discounting rate is higher, (4) market power is larger, (5) jump size intensity is stronger and (6) the payoff out ratio (R&D/revenue) is larger.


Energy ◽  
2015 ◽  
Vol 88 ◽  
pp. 234-243 ◽  
Author(s):  
Qianli Deng ◽  
Xianglin Jiang ◽  
Limao Zhang ◽  
Qingbin Cui

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