Investment-Timing and the Threat of Disruption

<p>An incumbent firm needs to determine how to best manage the risk of the arrival of a disruptive technology. The numerous actions available to the incumbent firm indicates a complex real-options model of investment is required. This thesis investigates the behaviour of an incumbent firm, with assets-in-place, when they have access to an investment opportunity. The incumbent must not only choose when to invest in the opportunity, but also the optimal structure with which to compete against a new entrant who also has this investment opportunity. In order to delay competition in the market the incumbent can elect to permanently abandon the innovative option rather than seek to compete with the new entrant. The assets-in-place contributes significant value to the incumbent and by delaying the competition effect, the incumbent can reduce the cannibalization of assets-in-place. This is despite the fact that the incumbent can attempt to profitably invest in the innovation before the entrant. Clearly the assets-in-place provide a benefit to firm value for the incumbent, but act as a burden for the growth option’s development. Should consumer preferences begin to favour the innovation, then the decision to abandon the growth option loses its value. The incumbent in this instance does not care that they may accelerate the entrant’s investment as they can still profitably preempt the entrant. In a competitive market, when the incumbent efficiently produces the innovation at no extra cost compared to an independent firm, the incumbent will elect to internalise, rather than spin off, the growth option. When the incumbent produces the innovation at a higher cost, than other market participants, they will spin off the growth option instead of internalising. When consumers favour the innovation, the incumbent becomes indifferent between spinning off and internalising the growth option as the objective functions in both cases converge to maximising the value of the growth option.</p>

Investment-Timing and the Threat of Disruption

<p>An incumbent firm needs to determine how to best manage the risk of the arrival of a disruptive technology. The numerous actions available to the incumbent firm indicates a complex real-options model of investment is required. This thesis investigates the behaviour of an incumbent firm, with assets-in-place, when they have access to an investment opportunity. The incumbent must not only choose when to invest in the opportunity, but also the optimal structure with which to compete against a new entrant who also has this investment opportunity. In order to delay competition in the market the incumbent can elect to permanently abandon the innovative option rather than seek to compete with the new entrant. The assets-in-place contributes significant value to the incumbent and by delaying the competition effect, the incumbent can reduce the cannibalization of assets-in-place. This is despite the fact that the incumbent can attempt to profitably invest in the innovation before the entrant. Clearly the assets-in-place provide a benefit to firm value for the incumbent, but act as a burden for the growth option’s development. Should consumer preferences begin to favour the innovation, then the decision to abandon the growth option loses its value. The incumbent in this instance does not care that they may accelerate the entrant’s investment as they can still profitably preempt the entrant. In a competitive market, when the incumbent efficiently produces the innovation at no extra cost compared to an independent firm, the incumbent will elect to internalise, rather than spin off, the growth option. When the incumbent produces the innovation at a higher cost, than other market participants, they will spin off the growth option instead of internalising. When consumers favour the innovation, the incumbent becomes indifferent between spinning off and internalising the growth option as the objective functions in both cases converge to maximising the value of the growth option.</p>

Spectral analysis of the dry bulk shipping market by utilizing the system dynamics approach

PurposeThis research analyzes the cycle of the dry bulk shipping market (DBSM) as a representative of spot and period charter rates in dry bulk shipping to develop strategies for investment timing (i.e. asset play) and fleet trading (chartering strategy).Design/methodology/approachSpectral analysis is a numerical approach to extract significant cyclicality, which may be utilized to develop trading strategies. Instead of working with a single dataset (univariate), a system approach can be utilized to observe a significant shipping market cycle in its multi-variate circumstance. In this paper, a system dynamics design is employed to extract cyclicality in the DBSM in its particular industrial environment. The system dynamic design has competitive forecasting accuracy relative to univariate time series models and artificial neural networks (ANNs) in terms of forecasting outcomes.FindingsThe results show that the system dynamic design has a better forecasting performance according to three evaluation metrics, mean absolute scale error (MASE), root mean square error (RMSE) and mean absolute percentage error (MAPE).Originality/valueCyclical analysis is a significantly useful instrument for shipping asset management, particularly in market entry–exit operations. This paper investigated the cyclical nature of the dry bulk shipping business and estimated significant business cycle periodicity at around 4.5-year frequency (i.e. the Kitchin cycle).

A framework for modelling cash flow lags

Traditional models of irreversible investment problems assume that the investment starts generating cash flows immediately, i.e., at the same time as the investment is undertaken. Real-world investment situations are characterized by time-to-build or investment lags, which means that there is a time difference between when the investment is made and when the investment starts generating cash flows. We combine two existing models of investment lags to obtain a flexible, yet simple, way of modelling and analyzing the effects of investment lags. Both traditional models, and models that incorporate the effects of time-to-build, typically assume that the expected future cash flows generated by an investment are represented by a single cash flow that reflects the size of the market value of an investment. To reflect real-world cases where investments generate cash flows in several time periods, we present a framework in which cash flows are explicitly allowed to be spread out in time. Our model can be used to incorporate cases where an investment is partially sold in different time periods. Using an irreversible optimal investment timing problem case study, we show how our framework makes it possible to easily compare the effect of different cash flow timings. In this case, the value and the timing of the investment depend on a constant that in a natural way can be decomposed into three parts, thereby showing the influence of the value and timing from the respective parts of the framework.

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

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.

Determinants of Investment Timing of Government Venture Capital Guiding Funds in China

With the prosperity of venture capital, all kinds of government venture capital guiding funds have sprung up, and the scale is explosive growth. However, the current investment of government guiding funds in enterprises has not fundamentally solved the financial difficulties in the early development of enterprises. This study examines the determinants of investment timing of government guiding funds. We investigate this question using the data of China’s new three board companies that have been invested by government guiding funds in the year of 2015-2016. We find that government guiding funds enter the enterprises into developed areas earlier. The innovation ability and the market competitiveness of the invested enterprises are positively correlated with the investment timing of government guiding funds. There is no significant relationship between the investment proportion of government guiding funds and the timing of entering the enterprises. The research of this paper can provide theoretical reference for the subsequent optimization of the resource allocation and provide ideas and methods for the policy improvement and management optimization of government venture capital guiding funds in the future.