Financial Valuation for Commercial Energy Retrofits under Private Risks

Abstract

Investments in commercial energy retrofits are exposed to unique types of risks that can be placed into two categories of risk: market risks (risks due to volatile market conditions) and private risks (risks due to volatile energy consumptions). By identifying such risks as a major contributor to the financial barrier, most studies to date have focused on market risks, yet these studies lacked consideration of the impact of private risks. In response, this paper aims to present a real options valuation (ROV) which aids in determining the financial impact of private risks on commercial energy retrofit investments. In particular, the study focuses on the valuation of phased investments in a large building portfolio under private risks that contribute to the option to defer (wait-and-see). The ROV adapts the binomial lattice method based on the level of volatility that is estimated using Monte Carlo simulation. The ROV results of the one-phase strategy are compared to those of the two-phase strategy in order to quantify the benefit of the increased managerial flexibility of the phased investments. The valuation presented in this paper is expected to help building owners and investors make better-informed decisions in commercial energy retrofits and, as a result, effectively overcome the financial barrier. 524

Research on Income evaluation of photovoltaic agricultural investment model based on fuzzy real option

“…At the same time, through sensitivity analysis, the impact of market changes and technical changes on the investment value and optimal investment time of photovoltaic power generation is discussed. Lee H W (2014) [15] et al proposed a volatility level estimated by real option valuation (ROV) based on Monte Carlo simulation, and compared ROV results of one-stage strategy with those of two-stage strategy by binomial case method, so as to quantify the benefits of improving management flexibility in this stage. Wang S (2016) [16] proposed a real option investment and evaluation model based on back propagation neural network, and evaluated Chinese renewable energy enterprises.…”