ABSTRACT This paper investigates the effects of regulatory interventions on contracting relationships within firms by examining the impacts of the Sarbanes–Oxley (SOX) Act on CEO compensation. Using panel data of the S&P 1500 firms, it quantifies welfare gains from a principal–agent model with hidden information and hidden actions. It finds that SOX: (1) reduced the conflict of interest between shareholders and their CEOs, mainly by reducing shareholder loss from CEOs deviating from their goal of expected value maximization; (2) increased the cost of agency, or the risk premium CEOs are paid to align their interests with those of shareholders; (3) increased administrative costs in the primary sector (which includes utilities and energy) but the effect in the other two broadly defined sectors, services and consumer goods, was more nuanced; and (4) had no effect on the attitude of CEOs toward risk.

This study examines the information content of stock option-implied volatility. We measure the arrival intensities and magnitudes of scheduled and unscheduled news as well as fundamental and non-fundamental news. Most of these news measures exhibit strong and positive associations with contemporaneous stock return volatility, and many of them can be predicted by implied volatility. Approximately one third of the predictive power of implied volatility on future realized volatility can be attributed to its ability to predict these news measures, with the majority of the predictive power arising from its capacity to predict the arrival intensities of both scheduled and unscheduled news. The predictive power is higher for fundamental news than for non-fundamental news.

We propose a new class of risk measures which satisfy convexity and monotonicity, two well-accepted axioms a reasonable and realistic risk measure should satisfy. Through a nonlinear weight function, the new measure can flexibly reflect the investor’s degree of risk aversion, and can control the fat-tail phenomenon of the loss distribution. A realistic portfolio selection model with typical market frictions taken into account is established based on the new measure. Real data from the Chinese stock markets and American stock markets are used for empirical comparison of the new risk measure with the expected shortfall risk measure. The in-sample and out-of-sample empirical results show that the new risk measure and the corresponding portfolio selection model can not only reflect the investor’s risk-averse attitude and the impact of different trading constraints, but can find robust optimal portfolios, which are superior to the corresponding optimal portfolios obtained under the expected shortfall risk measure.

Abstract We provide new causal evidence for the impact of equity financing incentive on firms’ voluntary disclosure decisions by exploring the 2008 seasoned equity offering deregulation, which exogenously facilitates small firms’ access to public equity financing and increases their equity issuance incentives without changing their business and information environments. We argue that the heightened equity financing incentive due to the deregulation can motivate a firm to increase disclosures even in the period without actual equity issuance, because such disclosures, by signaling a commitment to disclosure, could reduce the cost of equity in case the firm issues equity in the future. Consistent with this argument, we find that, benchmarking against control firms that are not affected by the deregulation, an average treatment firm that is affected by the deregulation but does not issue equity provides more management earnings forecasts in the post-deregulation period. The effect is mainly driven by repeated forecasters and is more pronounced for firms with greater equity financing needs and firms with higher information asymmetry in the equity market.

ABSTRACT We examine the evolution of accounting regulation by linking disclosure policies and investments in a dynamic voting model. The disclosure policies are the outcome of voting by entrepreneurs, whose preferences are influenced by their investments. The investments are in turn endogenously determined by current and future disclosure policies. Absent external influences, accounting regimes are stable. A disclosure regime of high (low) quality and a strong (weak) economy coexist and reinforce each other. However, regulatory interventions can result in regime changes by changing the entrepreneurs’ expectations, even without direct enforcement. Unexpected shocks could also result in regime changes by impacting economic conditions and hence voter composition. Our analysis provides a framework to study the interaction between accounting regulation and firms’ economic decisions.

ABSTRACT: This study exploits an exogenous change to audit committee policy in Canada and presents new evidence on how high-quality corporate governance mitigates managerial resource diversion and improves firm values. We first examine why some firms listed on the Toronto Venture Exchange (TSX Venture) voluntarily adopted the more stringent governance policy in 2004 that requires all audit committee members to be independent and financially literate. We develop a parsimonious analytical model that shows that both compliance costs and financing needs have an impact on firms' adoption decisions. Confirming the model's predictions, we find that TSX Venture firms with low compliance costs and greater future financing needs are more likely to adopt the new policy voluntarily. The analytical model also shows that high-quality audit committees enhance firm values by reducing the likelihood of managerial resource diversion. Consistent with the predictions of our analytical model, we find that the adoption decision has a positive impact on firm value and a negative impact on firms' cost of equity capital for both Toronto Stock Exchange (TSX) and TSX Venture firms. As corroborating evidence of the economic impact of the more stringent governance policy, we also show that both TSX and TSX Venture firms have improved investment efficiency following the adoption decisions. Data Availability: Data are available from public sources identified in the paper.

Abstract This study examines whether the revised lease standards (ASC 842 and IFRS 16) make U.S. GAAP-based accounting amounts more comparable with IFRS-based accounting amounts. Our study is motivated by the FASB and the IASB’s call for research on the comparability of the revised lease standards. We find that U.S. GAAP and IFRS pairs that are high operating lease users experience a larger increase in accounting comparability after the adoption of revised lease standards than low operating lease U.S. GAAP-IFRS pairs. Additionally, our results suggest that the improvement comes more from the changes to the balance sheet rather than the income statement and is more pronounced for IFRS firms from countries with stronger accounting enforcement. Lastly, we show that analysts who are more GAAP-focused (IFRS-focused) prior to the standard change are more likely to increase their forecasting of book value per share for IFRS (U.S. GAAP) firms.

Abstract We examine a simple measure of operating leverage: the ratio of fixed costs (measured by depreciation and amortization plus selling, general, and administrative expenses) to the market (or book) value of assets. We find that this measure of operating leverage positively predicts returns. This operating leverage measure is not explained by common factors and performs better than the traditional measures of operating leverage. Furthermore, an exploratory two-factor model with the operating leverage factor works at least as well as, but does not subsume, the Fama and French five-factor model. (JEL G11, G12, G30)

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.

Abstract 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.