Market Valuation of Innovation, Historical Mispricing and Later Correction, U.S. Markets, 1975 – 2021

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School of Business | Bachelor's thesis

Date

2022

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Degree programme

Rahoitus

Language

en

Pages

18 + 1

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Abstract

I study the R&D return predictability using a large sample of all firms listed on NYSE, Nasdaq & AMEX during the years 1975 to 2021. I construct portfolios yearly based on measured firm R&D intensity by R&D expenditure to market capitalization ratio. I then regress the portfolio monthly returns using the CAPM, Carhart model, and a more recent six-factor model proposed by recent academic research. Using these models, I estimate the historical return predictability of R&D intensity in the U.S. markets. I find evidence that historically firm R&D has gone underpriced with the most R&D-intensive equal-weighted portfolio showing an estimated monthly alpha of 1.26% during the first post formation year. Similar risk-adjusted excess returns are also found in value-weighted portfolios. Additionally, to further illuminate the risk premia vs. mispricing debate, I then regress the abnormal monthly returns of the most intensive portfolio using fixed effects to control for post-publication of previous academic research. I find evidence that the return predictability of firm R&D has decreased as market participants have become aware of the R&D anomaly. This finding further signals that historically the R&D anomaly has been driven to a great extent by mispricing rather than additional risk premia.

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Thesis advisor

Sean, Shin

Keywords

research & development, anomaly discovery, post-publication effect, apha decay

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