Financial Constraints, R&D Investment, and Stock Returns

By Dongmei Li. 2011

510 citations recorded by the source corpus.

Subfields: Accounting, Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/10c8755243e989d4619b7e0f9430d72e1259b55a

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Accounting

1. L. Gu
2. Chen Xue
3. Kewei Hou
4. Lu Zhang
5. Brandon Julio
6. Tiecheng Leng
7. Campbell R. Harvey
8. Julian Atanassov

In Economics and Econometrics

1. L. Gu
2. Tiecheng Leng
3. Lu Zhang
4. Campbell R. Harvey
5. Brandon Julio
6. Kewei Hou
7. Chen Xue
8. Julian Atanassov

In Finance

1. L. Gu
2. Chen Xue
3. Kewei Hou
4. Lu Zhang
5. Campbell R. Harvey
6. Brandon Julio
7. Julian Atanassov
8. Tiecheng Leng

Citations in the corpus

• The effect of firm size on the leverage–performance relationship during the financial crisis of 2007–2009 (2015, unknown): “Prior studies, such as Denis and Sibilkov (2010), Li (2011), and Chen and Chen (2012), show that financial constraints affect investment (e.g., capital expenditure and/or R&D investment).”
• Endogenous Technological Progress and the Cross Section of Stock Returns (2012, unknown): “Li (2008) attributes her results to the fact that R&D rms are more likely to be nancially constrained.”
• The Bright Side of Political Uncertainty: The Case of R&D (2015, background): “The primary source for the U.S. gubernatorial election datais the CQ Press Electronic Library.”
• ... and the Cross-Section of Expected Returns (2013, methodology): “In particular, Benjamini and Yekutieli (2001) show that setting c(M) at c(M)= M∑ j=1 1 j (1) allows the procedure to work under arbitrary dependency among the test statistics.”
• Technological Innovations and Aggregate Risk Premiums (2009, unknown): “Li (2007) extends the above model and shows that, when financially constrained hi-tech firms raise R&D input, they become more vulnerable to systematic risk and provide higher risk premiums.”
• Product market competition, R&D investment, and stock returns (2016, methodology): “First, it contributes to the literature on the relation between R&D investment and stock returns (see, e.g., Lev and Sougiannis, 1996; Chan, Lakonishok, and Sougiannis, 2001; Chambers, Jennings, and Thompson, 2002; Eberhart, Maxwell, and Siddique, 2004; Hsu, 2009; Bena and Garlappi, 2011; Li, 2011; ”
• Digesting Anomalies: An Investment Approach (2015, methodology): “Following Soliman (2008), we use DuPont analysis to decompose ROE as RNA+ FLEV× SPREAD, in which ROE is return on equity, RNAis return on net operating assets, FLEV is financial leverage, and SPREAD is the difference between return on net operating assets and borrowing costs.”
• Are Financial Constraints Priced? Evidence from Textual Analysis (2018, unknown): “For the debt training sample, the annualized risk-adjusted value-weighted return is 4.9%, followed by 4.6% and 4.1% for the equity and Factiva samples, respectively. The five-factor model thus cannot correctly price the FC factor. In fact, this finding is stronger than the one reported by Whited and”
• Investment Cycles and Startup Innovation (2013, unknown): “Our findings are also complementary to recent work examining how R&D by publicly traded firms responds to relaxed financing constraints (Brown, Fazzari, and Petersen, 2009, and Li, 2011).”
• A Comparison of New Factor Models (2017, background): “…Quarterly operating leverage (6-month holding period) (12-month holding period) Hn Hiring rate, Belo, Lin, and Bazdresch (2014) Rca R&D capital-to-assets, Li (2011) Bca Brand capital-to-assets, Aop Analysts optimism, Belo, Lin, and Vitorino (2014) Frankel and Lee (1998) Pafe Predicted…”