Rare disasters and the equity premium in a two-country world.

We extend the Barro (2006) closed-economy model of the equity risk premium in the presence of extreme events ("disasters") to a two-country world. In this more general setting, both the output risk of rare disasters and the associated risk of a default on Government debt, can be diversified. The extent to which agents in one country can diversify away the risk of extreme events depends on the relative size of the two countries, and critically on the probability of a disaster in one country conditional on a disaster in the other. We show that, using Barro�s own calibration in combination with a broad range of plausible values for the additional parameters, the model implies levels of the equity risk premium far lower than those typically observed in the data. We conclude that the model is unlikely to explain the equity risk premium

The credit risk premium in a disaster-prone world

The seminal Barro (2006) closed-economy model of the equity risk premium in the presence of extreme events ("disasters") allowed for leverage in the form of risky corporate debt which defaulted only in states when the Government defaulted on its debt. The probability of default was therefore exogenous and independent of the degree of leverage. In this paper, we take the model a step closer reality by assuming that, on the one hand, the Government never defaults, and on the the other hand, that the "corporate sector" in the form of the Lucas tree owner pays its debts in full if and only if its asset value is sufficient, which is always the case in non-crisis states. Otherwise, in exceptionally severe crises, it defaults and hands over the whole "firm" to its creditors. The probability of default by the tree owner is thus endogenous, dependent both on the volume of debt issued (taken as exogenous) and on the uncertain value of output. We show, using data from both Barro (2006) and Barro and Ursua (2008), that the model can generate values of the riskless rate, equity risk premium and credit risk spread broadly consistent with those typically observed in the data

Does ownership type matter for corporate social responsibility disclosure: Evidence from China

The evidence of the effect of ownership structure on corporate social responsibility (CSR) is relatively sparse especially in the emerging economies. This paper seeks to address this situation to comprehensively examine the link between different types of shareholders and CSR disclosure in the context of China. Our findings reveal that different owners have differential impact on the CSR. The firms controlled by the state are more likely to disclose CSR information and their CSR reports’ quality is better compared with non-SOEs. Interestingly, firms with more shares held by mutual funds, foreign investors or other corporations are significantly better at CSR disclosure. The study also discloses that firm size, profitability, and leverage affect CSR in China. Overall the study contributes to the literature on CSR practices in emerging countries and point to some policy suggestions

Nature and management of financial risk in global stock markets

This thesis addresses three problems associated with the risk in stock markets from a global perspective. First, we investigate the empirical hedging effectiveness using index futures in six world major stock markets. A variety of econometric models including STVECM with bivariate GARCH error structure are employed. The within-sample and out-of-sample results suggest sophisticated models do not produce the best hedging strategies consistently and their usefulness has to be judged on a case-by-case basis. Second, we examine the cross hedging effectiveness of seventeen MS CI indices through a global approach of using a combination of the related index futures. A thorough comparison among strategies corresponding to different combinations of hedging instruments and econometric models is conducted for each MSCI index. The optimal hedge ratio vector is derived for each country on the basis of both within- sample and out-of-sample results. Third, we develop a global asset pricing model on the basis of Barro's rare disaster model to explain the equity risk premium puzzle. Despite the plausible analytical predictions on the expected return of the bill and equity and the equity risk premium, the global model fails to explain the scale of the equity premium observed in the data since the diversification in a global market brings down both the aggregate risk and the reward for holding risk equity. The former results in a rise in the expected return of government bills and the latter leads to a fall in the expected return of equities

Ownership influence and CSR disclosure in China

© 2018, Emerald Publishing Limited. Purpose: This paper aims to examine the relationship between ownership type and the likelihood of publication of a corporate social responsibility (CSR) report. Design/methodology/approach: Drawing on stakeholder salience theory, the probit model is used for a sample of 1,839 Chinese listed firms to study how different types of owners influence firm CSR engagement. Findings: The analysis reveals that the Chinese stock exchanges exert a positive influence on the likelihood of a firm producing a CSR report, an effect which is more significant in state-owned enterprises (SOEs). Foreign investors lead to a greater likelihood of publication of a CSR report, though this effect is weaker in SOEs. In contrast, the holdings of state and domestic institutional investors are broadly neutral. Practical implications: The study helps corporate managers to recognise how particular types of shareholders will value their efforts regarding CSR activities and disclosure and also assists policymakers in improving the level of CSR disclosure through the development of new policy. Social implications: Apposite CSR disclosure enhances trust and facilitates the shared values on which to build a more cohesive society. Originality/value: The novelty of this study is that it addresses the effect of institutional investors on Chinese firm CSR engagement and thus provides an important insight for firms, investors and other stakeholders into the interplay of portfolio investment and CSR

MLA-BIN: Model-level Attention and Batch-instance Style Normalization for Domain Generalization of Federated Learning on Medical Image Segmentation

The privacy protection mechanism of federated learning (FL) offers an effective solution for cross-center medical collaboration and data sharing. In multi-site medical image segmentation, each medical site serves as a client of FL, and its data naturally forms a domain. FL supplies the possibility to improve the performance of seen domains model. However, there is a problem of domain generalization (DG) in the actual de-ployment, that is, the performance of the model trained by FL in unseen domains will decrease. Hence, MLA-BIN is proposed to solve the DG of FL in this study. Specifically, the model-level attention module (MLA) and batch-instance style normalization (BIN) block were designed. The MLA represents the unseen domain as a linear combination of seen domain models. The atten-tion mechanism is introduced for the weighting coefficient to obtain the optimal coefficient ac-cording to the similarity of inter-domain data features. MLA enables the global model to gen-eralize to unseen domain. In the BIN block, batch normalization (BN) and instance normalization (IN) are combined to perform the shallow layers of the segmentation network for style normali-zation, solving the influence of inter-domain image style differences on DG. The extensive experimental results of two medical image seg-mentation tasks demonstrate that the proposed MLA-BIN outperforms state-of-the-art methods.Comment: 9 pages, 8 figures, 2 table