scholarly journals Missed Opportunities: Optimal Investment Timing when Information is Costly

2005 ◽  
Author(s):  
Graeme Guthrie
Keyword(s):  
Optimal Investment ◽  
Missed Opportunities ◽  
Investment Timing

scholarly journals Missed Opportunities: Optimal Investment Timing When Information is Costly

2007 ◽  
Vol 42 (2) ◽  
pp. 467-488 ◽  
Author(s):  
Graeme Guthrie
Keyword(s):  
Real World ◽  
Real Option ◽  
Optimal Investment ◽  
Investment Opportunity ◽  
Missed Opportunities ◽  
Investment Timing ◽  
Real Option Analysis ◽  
Amount Of Information ◽  
Optimal Delay

AbstractReal option analysis typically assumes that projects are continuously evaluated and launched at precisely the time determined to be optimal, but real world projects cannot be managed in this way because of the costs of formally evaluating an investment opportunity. This paper shows that immediate investment is more attractive if evaluation costs are high or the amount of information to be revealed by an evaluation is large. The optimal delay until a reevaluation is long if evaluation costs are high or the amount of information to be revealed by an evaluation is small. The reduction in the value of project rights is especially severe when the value of the completed project is strongly mean reverting because then precision in investment timing is particularly important.

IRREVERSIBLE INVESTMENT, OPERATING FLEXIBILITY, AND TIME LAGS

2010 ◽  
Vol 27 (02) ◽  
pp. 271-286 ◽  
Author(s):  
RYUTA TAKASHIMA ◽  
MAKOTO GOTO ◽  
MOTOH TSUJIMURA
Keyword(s):  
Time Lag ◽  
Peak Load ◽  
Price Volatility ◽  
Optimal Investment ◽  
Capacity Expansion ◽  
Fixed Cost ◽  
Time Lags ◽  
Investment Timing ◽  
Power Company ◽  
Optimal Investment Problem

We consider an optimal investment problem when a firm such as an electric power company has the operational flexibility to expand and contract capacity with fixed cost. This problem is formulated as an impulse control problem combined with optimal stopping. Consequently, we obtain optimal investment timing, optimal capacity expansion and contraction timing, and the investment value. We also show investment, capacity expansion and contraction rule are influenced by the price volatility and the initial capacity is also influenced by the ratio between base-load plant and peak-load plant. In addition, we investigate how time lag between investment and operation influences the investment rule.

scholarly journals Least Squares Monte Carlo Simulation-Based Decision-Making Method for Photovoltaic Investment in Korea

2021 ◽  
Vol 13 (19) ◽  
pp. 10613
Author(s):  
Jungmin An ◽  
Dong-Kwan Kim ◽  
Jinyeong Lee ◽  
Sung-Kwan Joo
Keyword(s):  
Decision Making ◽  
Monte Carlo ◽  
Renewable Energy ◽  
Least Squares ◽  
Sustainable Energy ◽  
Clean Energy ◽  
Optimal Investment ◽  
Investment Timing ◽  
Least Squares Monte Carlo ◽  
The Impact

Solar power for clean energy is an important asset that will drive the future of sustainable energy generation. As interest in sustainable energy increases with Korea’s renewable energy expansion plan, a strategy for photovoltaic investment (PV) is important from an investor’s point of view. Previous research primarily focused on assessing and analyzing the impact of the volatility but paid little attention to the modeling decision-making project to obtain the optimal investment timing. This paper utilizes a Least Squares Monte Carlo-based method for determining the timing of PV plant investment. The proposed PV decision-making method is designed to simulate the total PV generation revenue period with all uncertain PV price factors handled before determining the optimal investment time. The numerical studies with nine different scenarios considering system marginal price (SMP) and renewable energy certificate (REC) spot market price in Korea demonstrated how to determine the optimal investment time for different PV capacities. Therefore, the proposed method can be used as a decision-making tool to provide PV investors with information on the best time to invest in the renewable energy market.

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