Time to build and the real-options channel of residential investment

Oh, Hyun-seung; Yoon, Chamna

doi:10.1016/j.jfineco.2018.10.019

Cited by 18 publications

(8 citation statements)

References 25 publications

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“…When facing uncertainties (e.g., energy price and policy fluctuations), real option theory can be used to conduct project evaluation to address the issue of investment decisions (Yao et al, 2019). Likewise, timeto-build investments could be predicted to be delayed over future revenue (Oh & Yoon, 2020). Simultaneously considering the option to defer and the option to abandon, Yu et al (2019) constructed a real option model for geothermal heating investment decision-making that incorporates carbon trading and resource taxes.…”

Section: Real Option Theorymentioning

confidence: 99%

Value of Investors’ Escalation of Commitment in PPP Projects Using Real Option Thinking

Gao

Liu

2020

International Journal of Strategic Property Management

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Escalation of commitment (EOC) is a common behavior among investors who receive negative feedback (NF) in public-private partnership (PPP) projects, and this behavior typically leads to sizable losses. Recognizing this, investors set a mental threshold and track investments for escalation. Once losses reach the threshold, investors will terminate the escalation behavior, namely, they will transfer projects to governments to obtain compensation or residual asset value. This paper analyzes the maximum amount of NF that investors can sustain based on a belief-adjustment model, followed by the analysis of the greatest loss degree. Then, a threshold model for EOC is constructed using real option thinking. Different from the usual judgment criteria of the traditional option method, the threshold is less than zero in the EOC scenario. The results show that the threshold correlates with the initial generative cognition, the sunk cost level, the degree of the government guarantee and investors’ behavioral preferences as well as with total investment and return on investment. These findings serve as a reference for governments to de-escalate investors’ commitment in PPP projects.

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Section: Real Option Theorymentioning

confidence: 99%

Value of Investors’ Escalation of Commitment in PPP Projects Using Real Option Thinking

Gao

Liu

2020

International Journal of Strategic Property Management

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“…It therefore seems natural to investigate whether an index of credit conditions may contain valuable information for forecasting. 2 Similarly, changes in house price uncertainty impact on housing investment and real estate construction decisions (Cunningham, 2006;Banks et al, 2015;Oh and Yoon, 2019), and thus may lead to future house price movements.…”

Section: Gradual Driftmentioning

confidence: 99%

Adaptive Dynamic Model Averaging with an Application to House Price Forecasting

Yusupova,

Pavlidis,

Pavlidis

2019

Preprint

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Dynamic model averaging (DMA) combines the forecasts of a large number of dynamic linear models (DLMs) to predict the future value of a time series. The performance of DMA critically depends on the appropriate choice of two forgetting factors. The first of these controls the speed of adaptation of the coefficient vector of each DLM, while the second enables time variation in the model averaging stage. In this paper we develop a novel, adaptive dynamic model averaging (ADMA) methodology. The proposed methodology employs a stochastic optimisation algorithm that sequentially updates the forgetting factor of each DLM, and uses a state-of-the-art non-parametric model combination algorithm from the prediction with expert advice literature, which offers finite-time performance guarantees. An empirical application to quarterly UK house price data suggests that ADMA produces more accurate forecasts than the benchmark autoregressive model, as well as competing DMA specifications.

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“…There exist several examples of recent literature that study the effect of investment lags in various industries. Oh and Yoon (2020) study how construction lags affect decisions around residential construction projects. Balliauw (2020) considers time-to-build in port capacity expansion investments.…”

Section: Introductionmentioning

confidence: 99%

A framework for modelling cash flow lags

Armerin

Song

2021

SN Bus Econ

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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.

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Time to build and the real-options channel of residential investment

Cited by 18 publications

References 25 publications

Value of Investors’ Escalation of Commitment in PPP Projects Using Real Option Thinking

Value of Investors’ Escalation of Commitment in PPP Projects Using Real Option Thinking

Adaptive Dynamic Model Averaging with an Application to House Price Forecasting

A framework for modelling cash flow lags

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