Reliability of listed companies' value estimates and target prices: evidence from industry-based combined valuation models

Abstract

The low reliability of listed companies' target prices is a major issue globally. As the foundation of the target price, the value estimate is important in the determination of target price reliability. The value estimate is the estimated intrinsic value of a company produced by the company valuation model. However, there is no individual valuation model capable of fully disclosing the intrinsic value, and the use of more than one valuation model simultaneously is a common practice. In addition, it is important for the valuation model to be consistent with the characteristics of the company. However, the existing literature offers little guidance on this valuation issue, especially on how to appropriately construct a combined valuation model based on the characteristics of the company. This study investigates the underlying reasons for the low reliability of listed companies' value estimates and target prices, and attempts to improve their reliability via the enhanced company valuation method. In particular, the study focuses on the industry based combined valuation models and their application to the valuations of listed companies from different industries. The study begins with the estimation of discount rate for each selected firm, and then applies the industry based individual and combined models to generate value estimates for each firm, followed by the target price setting process to determine the most reasonable target price. The improved reliability test techniques will be used to measure the performance of value estimates, target prices and the financial analysts' target prices, so that the best individual and combined valuation models for different industries can be identified. This study has produced several important findings. The results show that the reliability of the target price is determined by the value estimate and the target price setting process. The reliability of the value estimate is influenced by the data and valuation method. The results also show that absolute valuation models have significant advantages in emerging industries such as biotechnology. The relative valuation models exhibit good performance in the traditional industries such as technology hardware. The forward valuation models are suitable for stable industries such as insurance with accurate forecasts. The trailing valuation models have apparent advantages in unstable industries such as securities with great uncertainty. The results also show that the combined valuation models have significant advantages over the individual valuation models. The mixed combined valuation models are preferred in practice.