Unique to the world, China adopts a “T+1 trading rule”, which prevents investors from selling stocks bought on the same day. We develop a dynamic price manipulation model to study the effects of the “T+1 trading rule”. Compared to the “T+0 trading rule”, which allows investors to buy and sell the same stocks during the same day, we show that the “T+1 trading rule” reduces the total trading volume and price volatility, and improves the trend chasers’ welfare when trend-chasing is strong. An empirical test using data on China’s B-share stock market supports the model’s theoretical predictions.

This article presents a pure exchange economy that extends Rubinstein (1976) to show how the jump–diffusion option pricing model of Merton (1976) is altered when jumps are correlated with diffusive risks. A non-zero correlation between jumps and diffusive risks is necessary in order to resolve the positively sloped implied volatility term structure inherent in traditional jump diffusion models. Our evidence is consistent with a negative covariance, producing a non-monotonic term structure. For the proposed market structure, we present a closed form asset pricing model that depends on the factors of the traditional jump–diffusion models, and on both the covariance of the diffusive pricing kernel with price jumps and the covariance of the jumps of the pricing kernel with the diffusive price. We present statistical evidence that these covariances are positive. For our model the expected stock return, jump and diffusive risk premiums are non-linear functions of time.

Firms have increasingly started tying their executives’ compensation to CSR-related objectives. In this paper, we attempt to understand why firms offer CSR-contingent compensation and the conditions under which such compensation improves corporate social performance. Using hand-collected data from proxy statements, we find that this emerging compensation practice varies significantly across industries and across different CSR categories. Further, well-governed firms are more likely to offer CSR-contingent compensation, and such compensation does lead to higher corporate social standing. Such firms are more likely to offer formula-based, Objective CSR-contingent compensation. However, our results suggest that non-formulaic, Subjective CSR-contingent compensation also helps improve companies’ social performance when firm outcomes are more volatile and unpredictable, and therefore executives’ effort and performance are harder to evaluate, and when firms have better corporate governance.

Following a direct data-driven approach, we propose a robust encoder-decoder Gated Recurrent Unit (GRU), GRUδ, for optimal discrete option hedging. The proposed GRUδ utilizes the Black-Scholes model as a pre-trained model and incorporates sequential information and feature selection. Using the S&P 500 index European option market data, we demonstrate that the weekly and monthly hedging performance of the proposed GRUδ significantly surpasses that of the data-driven minimum variance (MV) method, the regularized kernel data-driven model, and the SABR-Bartlett method. In addition, the daily hedging performance of the proposed GRUδ also surpasses that of MV methods based on parametric models, the kernel method, and SABR-Bartlett method.

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.

In this paper, we look at how the pre-crisis health of banks is related to the probability of receiving and repaying TARP capital. We find that financial performance characteristics that are related to the probability of receiving TARP funds differ for the healthiest (“over-achiever”) versus the least healthy (“under-achiever”) banks. We find that TARP under-achievers have some, but not consistent, weaknesses in income production. These banks also are experiencing liquidity issues as customers, shut out of public debt markets, get bank loans through drawdowns of loan commitments. Unlike TARP under-achievers, TARP over-achievers’ loans are performing well. Yet, liquidity issues (from low levels of liquid assets and core deposits and drawdowns of loan commitments) hurt the abilities of these banks to continue their lending. Differences between under-achiever and over-achiever banks are also found for repayment and deadbeat TARP banks.

This paper investigates the dynamic correlations among six international stock market indices and their relationship to inflation fluctuation and market volatility. The current research uses a newly developed time series model, the Double Smooth Transition Conditional Correlation with Conditional Auto Regressive Range (DSTCC-CARR) model. Findings reveal that international stock correlations are significantly time-varying and the evolution among them is related to cyclical fluctuations of inflation rates and stock volatility. The higher/lower correlations emerge between countries when both countries experience a contractionary/expansionary phase or higher/lower volatilities.

Local risk minimization and total risk minimization discrete hedging have been extensively studied for European options [e.g., Schweizer, M., 1995. Variance-optimal hedging in discrete time. Mathematics of Operation Research 20, 1–32; Schweizer, M., 2001. A guided tour through quadratic hedging approaches. In: Jouini, E., Cvitanic, J., Musiela, M., Option pricing, interest rates and risk management, Cambridge University Press, pp. 538–574]. In practice, hedging of options with American features is more relevant. For example, equity linked variable annuities provide surrender benefits which are essentially embedded American options. In this paper we generalize both quadratic and piecewise linear local risk minimization hedging frameworks to American options. We illustrate that local risk minimization methods outperform delta hedging when the market is highly incomplete. In addition, compared to European options, distributions of the hedging costs are typically more skewed and heavy-tailed. Moreover, in contrast to quadratic local risk minimization, piecewise linear risk minimization hedging strategies can be significantly different, resulting in larger probabilities of small costs but also larger extreme cost.

Value at risk (VaR) and conditional value at risk (CVaR) are frequently used as risk measures in risk management. Compared to VaR, CVaR is attractive since it is a coherent risk measure. We analyze the problem of computing the optimal VaR and CVaR portfolios. We illustrate that VaR and CVaR minimization problems for derivatives portfolios are typically ill-posed. We propose to include cost as an additional preference criterion for the CVaR optimization problem. We demonstrate that, with the addition of a proportional cost, it is possible to compute an optimal CVaR derivative investment portfolio with significantly fewer instruments and comparable CVaR and VaR. A computational method based on a smoothing technique is proposed to solve a simulation based CVaR optimization problem efficiently. Comparison is made with the linear programming approach for solving the simulation based CVaR optimization problem.

We assess the potential impact for non-high-income countries (NHICs) of linking bank capital asset requirements (CARs) to private sector ratings–as contemplated by the new Basel proposal. Specifically, we show that linking bank CARs to external ratings would have a series of undesirable effects for NHICs. First, since ratings are by far less widespread for banks and corporations in NHICs, bank CARs would be practically insensitive to improvements in the quality of assets, widening the gap between banks of equal financial strength located in higher and lower income countries. Second, bank and corporate ratings in NHICs (as opposed to their homologues in high-income countries) are strongly linked to their sovereign ratings. This would expose bank capital requirements in NHICs to the same “pro-cyclical” swings, which have characterized sovereign rating revision in the recent crisis episodes. We conclude that linking bank CARs to private sector ratings would worsen the availability and cost of credit to NHICs – with potential negative effects on the level of economic activity – and suggest that a reassessment of the Basel proposal may help to avoid such undesired consequences.