@article{46b9e938bff44dbe91168d57381e7953,
title = "The value premium and investors' appetite for risk",
abstract = "The value premium is always discussed in the literature as a phenomenon driven by rational economic factors such as risks related to leverage, default or liquidity, cash flow or technological shocks. In this study, we use parametric and non-parametric methods with daily, weekly and monthly data for 1965–2019 to show that the value premium correlates with and is predictable by investors{\textquoteright} appetite for risk. The latter is captured using various measures of investor sentiment, including survey-based, stock market-based, press-based, Internet search-based and social media-based proxies. In addition, utilizing the quantile regression procedure, we find that the dependence between the value premium and some of the measures of risk appetite is non-linear and varies with the distribution of the data. Our findings are based on examining 100 portfolios created based on their book-to-market ratios and size. The results hold true for different sample periods and various model specifications.",
keywords = "Investor sentiment, Risk appetite, Value investing, Value premium",
author = "Mahmoud Qadan and Maram Jacob",
note = "Funding Information: As indicated in the method section, the purpose of running this type of regression is to test for the degree of dependence between the value premium (set as the dependent variable) and the measures of investors' risk appetite. Doing so allows us to test for the possibility that both variables do not co-move linearly. The results for the Baker and Wurgler (2006) and their aligned measures indicate an increasing degree of dependence, as evident in the increasing betas from the lower to the higher quantiles. While the lower parts of the distribution indicate negative dependence or dependence equal to zero, the higher quantiles are associated with positive and statistically significant coefficients. For example, while the first two quantiles listed under BW1 contain negative beta coefficients (−0.131 and −0.039), respectively, the last two quantiles in the same column indicate statistically positive coefficients. A relatively similar picture emerges when considering BW2, HJTZ1 and HJTZ2. This increase in dependence is also supported by the results of the coefficient equality tests (ET) reported in the last two lines of the tables. In ET1 and ET2, we list the statistics resulting in the equality test that βτ=0.1=βτ=0.9 and βτ=0.1=βτ=0.2=…=βτ=0.9, respectively. Significant statistics indicate a rejection of a given hypothesis. The quantile regression results for the rest of the measures of investors{\textquoteright} risk appetite display a similar pattern, with low beta coefficients in the lower decile but higher ones in the higher deciles. Publisher Copyright: {\textcopyright} 2022 Elsevier Inc.",
year = "2022",
month = nov,
doi = "https://doi.org/10.1016/j.iref.2022.06.014",
language = "American English",
volume = "82",
pages = "194--219",
journal = "International Review of Economics and Finance",
issn = "1059-0560",
publisher = "Elsevier Inc.",
}