Abstract

This paper examines how the real option value of R&D expenditure in financial market changes as time proceeds. It examines the relations between the R&D capital and the firm value for 4 years from the time a firm increases its R&D expenditure unexpectedly. The results show that the financial market evaluates the unexpected increased R&D with real option logic. We find that the financial market takes account of the market uncertainty and the technology uncertainty of R&D for the valuation of firms. These effects appear significantly right after the R&D capital increases unexpectedly. However, the lasting period of them is shorter than 1 year. The operational performance doesn’t have any relation with the firm value in our analysis.

Highlights

  • The discounted cash flow (DCF) method has been used to evaluate R&D projects

  • The results show that the financial market evaluates the unexpected increased R&D with real option logic

  • This paper examines the relations between the R&D capital and the firm value for four years from the time a firm increases its R&D expenditure unexpectedly

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Summary

Introduction

The discounted cash flow (DCF) method has been used to evaluate R&D projects. We assume that unexpected R&D expenditures generate market and technology uncertainties and are reflected in the valuation of the firm with the real option logic when they are evaluated in financial markets. One of the main contributions of our paper is the empirical evidence that confirms that financial markets evaluate market and technology uncertainties inherent in R&D investment, in particular, by the logic of real option. We argue that it is worthwhile to investigate how the firm value reacted to unexpected R&D expenditure increases during this time period, when the global and Korean financial markets experienced turbulent and unstable changes with the IT bubble and global financial crisis In this way, this paper deals with a focused time period and provides a specific insight to the corporate finance research.

Existing Research
Industry Moderator
Hypotheses
The Hedonic Model
Market Uncertainty
C29 Other machinery and equipment
Technology Uncertainty
Technology Cumulativeness
4.10. Other Variables
4.11. Descriptive Statistics and Correlations
Findings
Conclusion

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