Righteousness and Profitableness: The Moral Choices of Contemporary Confucian Entrepreneurs

This paper explores the relationship of various trait emotions to the ethical choices of 189 college students who completed a managerial decision-making task as part of an in-basket exercise in a laboratory setting. Prior research regarding emotion influences on ethical decision-making and linkages between emotions and cognition informed hypotheses about how different types of emotions impact ethical choices. Findings supported our expectations that positive and negative emotions classified as active would be more strongly related to interpersonally-directed ethical choices than to organizationally-directed ones, and that passive emotions would be less related to ethical choices than active emotions. Implications for ethical decision-making research and organizational practices are discussed.     

Sub-Replication and Replenishing Premium: Efficient Pricing of Multi-State Lookbacks

The direct valuation procedure of performing discounted expectation to obtain the prices of multi-state lookback options may lead to insurmountable complexity and numerical difficulties. The computation may require numerical differentiation of the joint distribution function of the extremum values, then followed by numerical integration over a semi-infinite domain. In this paper, we illustrate the use of an alternative approach that significantly simplifies the calculations of multi-state lookback option prices. The financial intuition behind the new approach involves the choice of a sub-replicating portfolio and the adoption of the corresponding replenishing strategy to achieve the subsequent full replication of the derivative. The replenishing premium is obtained by performing the integration of an appropriate distribution function over the range of asset price within which under replication occurs. The sub-replication and replenishment procedures may be utilized as hedging strategies for the lookback options. The pricing and hedging properties of multi-state lookback options are also discussed. This revised version was published online in June 2006 with corrections to the Cover Date.     

Sustainability Strategy and Eco‐Innovation: A Moderation Model

This study develops a moderation model to examine the role of a proactive environmental strategy on eco‐innovation. Drawing upon the perspectives of contingency theory, this study argues that the impacts of sustainability strategy on eco‐innovation depend on market demand, innovation intensity and government subsidy. The sample used to test the hypotheses is obtained from the Community Innovation Survey in Taiwan. A total of 2955 manufacturing firms are included in the final sample. A logit moderating regression is adopted to analyze the models. The results reveal that market demand and government subsidy positively moderate the relationship between environmental strategy and eco‐innovation. Specifically, firms are more likely to adopt a proactive environmental strategy to improve eco‐innovation under high levels of market demand and government subsidy. Furthermore, the results indicate that innovation intensity affects the effect of environmental strategy on eco‐innovation, but the direction of the influence varies with different categories of eco‐innovation. Copyright © 2016 John Wiley & Sons, Ltd and ERP Environment     

CLOSED FORM PRICING FORMULAS FOR DISCRETELY SAMPLED GENERALIZED VARIANCE SWAPS

Most of the existing pricing models of variance derivative products assume continuous sampling of the realized variance processes, though actual contractual specifications compute the realized variance based on sampling at discrete times. We present a general analytic approach for pricing discretely sampled generalized variance swaps under the stochastic volatility models with simultaneous jumps in the asset price and variance processes. The resulting pricing formula of the gamma swap is in closed form while those of the corridor variance swaps and conditional variance swaps take the form of one‐dimensional Fourier integrals. We also verify through analytic calculations the convergence of the asymptotic limit of the pricing formulas of the discretely sampled generalized variance swaps under vanishing sampling interval to the analytic pricing formulas of the continuously sampled counterparts. The proposed methodology can be applied to any affine model and other higher moments swaps as well. We examine the exposure to convexity (volatility of variance) and skew (correlation between the equity returns and variance process) of these discretely sampled generalized variance swaps. We explore the impact on the fair strike prices of these exotic variance swaps with respect to different sets of parameter values, like varying sampling frequencies, jump intensity, and width of the monitoring corridor.     

Instrumental measurement of the cognitive and emotional background of deception

Quality & Quantity - The aim of this study is to instrumentally explore the cognitive and emotional load behind deception. According to literature, the cognitive and emotional load comprises of...     

Variance swaps valuation under non-affine GARCH models and their diffusion limits

In this article, we investigate the pricing and convergence of general non-affine non-Gaussian GARCH-based discretely sampled variance swaps. Explicit solutions for fair strike prices under two different sampling schemes are derived using the extended Girsanov principle as the pricing kernel candidate. Following standard assumptions on time-varying GARCH parameters, we show that these quantities converge respectively to fair strikes of discretely and continuously sampled variance swaps that are constructed based on the weak diffusion limit of the underlying GARCH model. An empirical study which relies on a joint estimation using both historical returns and VIX data indicates that an asymmetric heavier tailed distribution is more appropriate for modelling the GARCH innovations. Finally, we provide several numerical exercises to support our theoretical convergence results in which we further investigate the effect of the quadratic variation approximation for the realized variance, as well as the impact of discrete versus continuous-time modelling of asset returns.     

Valuation of VIX and target volatility options with affine GARCH models

In this paper we propose semiclosed-form solutions, subject to an inversion of the Fourier transform, for the price of VIX options and target volatility options under affine GARCH models based on Gaussian and Inverse Gaussian distributions. We illustrate the advantage of the proposed analytic expressions by comparing them with those obtained from benchmark Monte–Carlo simulations. The empirical performance of the two affine GARCH models is tested using different calibration exercises based on historical returns and market quotes on VIX and SPX options.     

Information effects of dividends: Evidence from the Hong Kong market

The literature has suggested that earnings and earnings forecasts provide stronger signals than dividends about future performance of a firm. We test the information effects of simultaneous announcement of earnings and dividends in the Hong Kong market, distinguished by three interesting features (concentrated family-shareholdings, low corporate transparency, and no tax on dividends). Our results show significant share price reactions to unexpected earnings and dividend changes, but dividends appear to play a dominant role over earnings in pricing, a result contrary to findings in the literature. The signaling hypothesis works primarily for firms with earning increases, while the maturity hypothesis works mainly for firms with earnings declines.

Multivariate Cox Hidden Markov models with an application to operational risk

ABSTRACT

Modeling multivariate time-series aggregate losses is an important actuarial topic that is very challenging due to the fact that losses can be serially dependent with heterogeneous dependence structures across loss types and business lines. In this paper, we investigate a flexible class of multivariate Cox Hidden Markov Models for the joint arrival process of loss events. Some of the nice properties possessed by this class of models, such as closed-form expressions, thinning properties and model versatility are discussed in details. We provide the expectation-maximization (EM) algorithm for efficient model calibration. Applying the proposed model to an operational risk dataset, we demonstrate that the model offers sufficient flexibility to capture most characteristics of the observed loss frequencies. By modeling the log-transformed loss severities through mixture of Erlang distributions, we can model the aggregate losses. Finally, out-of-sample testing shows that the proposed model is adequate to predict short-term future operational risk losses.     

Justifying top management pay in a transitional economy

We investigate some aspects of top management pay in China's listed firms. We find positive pay and performance sensitivities and elasticities for top executives. In terms of magnitude, these sensitivities are similar to those reported in U.S. firms during the 1970s. However, the pay and performance relation is slightly weaker for firms located in less developed provinces. We also find that the pay disparities between top managers and employees are positively related to a firm's performance. Thus, it appears that any deviation away from a manager-worker compensation norm has to be justified by superior firm performance. In additional analyses, we find that managers' perquisites are not related to performance.