The aim of this study was to retrospectively analyze 18F-FDG positron emission tomography/computed tomography (18F-FDG PET/CT) metabolic variables, programmed death-ligand 1 (PD-L1) and phosphorylated signal transducer and activator of transcription 3 (p-STAT3) tumor expression, and other factors as predictors of disease-free survival (DFS) in patients with lung adenocarcinoma (LUAD) (stage IA-IIIA) who underwent surgical resection. We still lack predictor of immune checkpoint (programmed cell death-1 [PD-1]/PD-L1) inhibitors. Herein, we investigated the correlation between metabolic parameters from 18F-FDG PET/CT and PD-L1 expression in patients with surgically resected LUAD.Seventy-four patients who underwent 18F-FDG PET/CT prior to treatment were consecutively enrolled. The main 18F-FDG PET/CT-derived variables were primary tumor maximum standardized uptake value (SUVmax), metabolic tumor volume (MTV), and total lesion glycolysis (TLG). Surgical tumor specimens were analyzed for PD-L1 and p-STAT3 expression using immunohistochemistry. Correlations between immunohistochemistry results and 18F-FDG PET/CT-derived variables were compared. Associations of PD-L1 and p-STAT3 tumor expression, 18F-FDG PET/CT-derived variables, and other factors with DFS in resected LUAD were evaluated.All tumors were FDG-avid. The cutoff values of low and high SUVmax, MTV, and TLG were 12.60, 14.87, and 90.85, respectively. The results indicated that TNM stage, PD-L1 positivity, and high 18F-FDG PET/CT metabolic volume parameters (TLG ≥90.85 or MTV ≥14.87) were independent predictors of worse DFS in resected LUAD. No 18F-FDG metabolic parameters associated with PD-L1 expression were observed (chi-square test), but we found that patients with positive PD-L1 expression have significantly higher SUVmax (P = .01), MTV (P = .00), and TLG (P = .00) than patients with negative PD-L1 expression.18F-FDG PET/CT metabolic volume parameters (TLG ≥90.85 or MTV ≥14.87) were more helpful in prognostication than the conventional parameter (SUVmax), PD-L1 expression was an independent predictor of DFS in patients with resected LUAD. Metabolic parameters on 18F-FDG PET/CT have a potential role for 18F-FDG PET/CT in selecting candidate LUAD for treatment with checkpoint inhibitors.

This paper proposes “implied stochastic volatility models” designed to fit option-implied volatility data and implements a new estimation method for such models. The method is based on explicitly linking observed shape characteristics of the implied volatility surface to the coefficient functions that define the stochastic volatility model. The method can be applied to estimate a fully flexible nonparametric model, or to estimate by the generalized method of moments any arbitrary parametric stochastic volatility model, affine or not. Empirical evidence based on S&P 500 index options data show that the method is stable and performs well out of sample.

In empirical corporate finance, firm size is commonly used as an important, fundamental firm characteristic. However, no research comprehensively assesses the sensitivity of empirical results in corporate finance to different measures of firm size. This paper fills this hole by providing empirical evidence for a “measurement effect” in the “size effect”. In particular, we examine the influences of employing different proxies (total assets, total sales, and market capitalization) of firm size in 20 prominent areas in empirical corporate finance research. We highlight several empirical implications. First, in most areas of corporate finance the coefficients of firm size measures are robust in sign and statistical significance. Second, the coefficients on regressors other than firm size often change sign and significance when different size measures are used. Unfortunately, this suggests that some previous studies are not robust to different firm size proxies. Third, the goodness of fit measured by R-squared also varies with different size measures, suggesting that some measures are more relevant than others in different situations. Fourth, different proxies capture different aspects of “firm size”, and thus have different implications. Therefore, the choice of size measures needs both theoretical and empirical justification. Finally, our empirical assessment provides guidance to empirical corporate finance researchers who must use firm size measures in their work.

We find that analysts are more likely to downgrade stocks when prices approach the 52-week high. The results are stronger for stocks with higher information asymmetry but moderated by analysts' reputation, work experience, and educational background. We also find a strategy that shorts stocks with recommendation downgrades is less profitable for the downgrades near 52-week high than for other downgrades. Moreover, these downgraded firms with prices near 52-week high subsequently experience relatively less negative earnings forecast revisions. These results suggest that these downgrade decisions are less likely to be information-driven and consistent with our anchoring interpretation.

Employing a sample of 4271 initial-industry acquisitions across 34 countries from 1989 to 2013, we show that the rival firms which are in the same industry as the target firms exhibit positive cumulative abnormal returns (CARs). In addition, those rivals with higher analyst coverage are associated with higher CARs. The results are robust to the natural experiment based on the exogenous decrease in analyst coverage (i.e., brokerage closure and merger). Careful comparisons of the results show dramatic differences between the United States (U.S.) and non-U.S. subsamples. We further show that a more transparent macro information environment can substitute for the role of financial analysts in determining the rival response. Overall, our findings support the Acquisition Probability Hypothesis.

Using a large panel of more than 140,000 state-owned enterprises (SOEs), this study examines SOEs’ investment behavior surrounding 82 national elections in 25 European countries between 2001 and 2015. We find that SOEs increase their corporate investment by about 29% of the sample average during national election years. This effect is more pronounced in fixed timing and closely contested elections. The effect is also stronger in countries with low institutional quality, more centralized political systems, and state-controlled banking systems. In contrast, we find the matched non-SOEs significantly decrease their corporate investment during national election years. (JEL G18, G30, G32, E22) Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.

This paper studies the rise and fall of “Mini” options that are especially catered to retail investors for popular but high-priced securities. Using transaction-level data, we find that transaction costs of Mini options are much higher than those of standard options and the difference cannot be fully explained by cost-related determinants. Furthermore, we find evidence of price discrimination against retail investors from analyses of price elasticities of option traders, an event-study of changes in bid-ask spreads around earnings announcements, and comparisons of trade prices paid by Mini and standard option traders for the same security at approximately the same time.

Mini options are specially catered to retail investors with limited capital for trading options on extremely high-priced securities. The coexistence of both Mini and standard options for the same underlying security provides us a novel setting to investigate whether and how small retail investors use derivatives contracts differently compared to their counterparts. First, we find that the Mini option investors are more subject to constraints of limited attention. Specifically, Mini option investors trade more intensively near market opens, and their trading activities are more heavily influenced by attention-grabbing events and attention-distracting events. Second, we document that Mini option investors’ trading is more likely to be driven by market sentiment than standard option investors. Third, the trading performance of Mini option investors is also worse than that of standard option investors, with less positive intraday returns and more negative overnight returns.