A multilateral approach to examining the comovements among major world equity markets

This study investigates the comovement in stock indices among major developed markets, where Morgan Stanley Capital International (MSCI) indices are employed for the purposes of the study. We employ a model that accommodates multilateral international impacts on equity index movements. The empirical results reveal the existence of significant international transmission effects among these major world markets, both in terms of returns and volatility, and mostly in a positive direction. The U.S. market, as expected, is the leading market in the sense that it has the most pervasive and significant impact on all markets across continents. However, the U.S. market exhibits a different relationship with European markets from that with Asia-Pacific markets. The evidence also suggests that strong regional transmission effects exist. A further investigation using the extended model reveals that the linkages between U.S. and European markets are driven by positive global common forces and by negative international competitive effects. On the other hand, the U.S. and Asian markets are linked through positive global common forces and positive international contagion effects. The United States, Canada, and the U.K. are the three markets that still demonstrate contagion influence over countries outside its own region. The Asia-Pacific markets are more susceptible to contagion effects. Finally, it is interesting to find that Japanese market performance became more contagious toward other markets during the Asian financial crisis period.     

WTO financial services commitments: Determinants and impact on financial stability

The paper investigates the factors that have influenced WTO members to take on their chosen level of liberalization commitments in the framework of liberalization of trade in financial services and the impact of such commitments on financial sector stability. The most important factors are economic growth, current account, trends in banking sector development, policy restrictiveness, and peer-group effects. The econometric evidence suggests that more liberal commitments may be associated with greater vulnerability to currency and banking crises—most likely a short-term effect, which should be mitigated with time through increased market efficiency and better resource allocation.     

Social networks in the global banking sector

We show that banks with shared social connections partner more often in the global syndicated loan market and that central banks in the network play dominant roles in various interbank transactions, indicating that social connections facilitate business connections. However, more centralized banks in the network also contribute significantly to the global systemic risk. Moreover, we find the soft information generated by social networks is particularly valuable when potential partners operate under different accounting and regulatory standards. Finally, we show that the recent banking crisis significantly limited the positive soft information effects of social networks in the global banking system.     

Expected exponential utility maximization of insurers with a Linear Gaussian stochastic factor model

In this paper, we consider the problem of optimal investment by an insurer. The wealth of the insurer is described by a Cramér–Lundberg process. The insurer invests in a market consisting of a bank account and m risky assets. The mean returns and volatilities of the risky assets depend linearly on economic factors that are formulated as the solutions of linear stochastic differential equations. Moreover, the insurer preferences are exponential. With this setting, a Hamilton–Jacobi–Bellman equation that is derived via a dynamic programming approach has an explicit solution found by solving the matrix Riccati equation. Hence, the optimal strategy can be constructed explicitly. Finally, we present some numerical results related to the value function and the ruin probability using the optimal strategy.     

金融投机、实需与国际大宗商品价格——信息摩擦视角下的大宗商品价格影响机制研究

本文实证考察了2005-2015年金融投机和实需对国际大宗商品现货价格的影响及其作用机理。首先对具有信息噪音属性的金融投机进行了明确识别。其次,从多个维度出发区分市场信息摩擦状态,定量分析不同信息摩擦环境中金融投机和实需的影响差异。研究发现:大宗商品价格在长期中由实需因素主导,短期中由金融投机主导;短期中,相对于低信息摩擦环境,在市场波动性较高、金融压力上升以及投资者情绪高涨的高信息摩擦环境中,以金融投机为主的信息噪音对大宗商品价格的影响更强。进一步分析证实,相比于低信息摩擦环境,高信息摩擦环境中金融交易者的市场份额反而降低。据此,本文提出稳定大宗商品市场的关键在于提高市场透明度,减少信息摩擦,从市场质量出发降低信息噪音的影响。     

Sociology,risk and the environment: a material-semiotic approach

Abstract

Sociology has made significant contributions to the conceptualisation of risk and critique of technical risk analysis. It has, however, unintentionally reinforced the division of labour between the natural/technical and social sciences in risk analysis. This paper argues that the problem with conceptualisations of risk is not a misplaced emphasis on calculation. Rather, it is that we have not adequately dealt with ontological distinctions implicit in both sociological and technical work on risk between material or objective risks and our socially mediated understandings and interpretations of those risks. While acknowledging that risks are simultaneously social and technical, sociologists have not, in practice, provided the conceptual and methodological tools to apprehend risk in a less dualistic manner. This limits our ability both to analyse actors and processes outside the social domain and to explore the recursive relationships between risk calculus, social action and the material outcomes of risk. In response, this paper develops a material-semiotic conceptualisation of risk and provides an assessment of its relevance to more sociologically informed risk governance. It introduces the ideas of co-constitution, emergent entities and enactment as instruments for reconciling the material and social worlds in a sociological study of risk. It further illustrates the application of a material-semiotic approach using these concepts in the nuclear industry. In deconstructing social–material dualisms in the sociology of risk, this paper argues that a material-semiotic conceptualisation of risk enables both technical and social perspectives on risk not only to coexist but to collaborate, widening the scope for interdisciplinary research.     

Learning minimum variance discrete hedging directly from the market

Option hedging is a critical risk management problem in finance. In the Black–Scholes model, it has been recognized that computing a hedging position from the sensitivity of the calibrated model option value function is inadequate in minimizing variance of the option hedge risk, as it fails to capture the model parameter dependence on the underlying price (see e.g. Coleman et al., J. Risk, 2001, 5(6), 63–89; Hull and White, J. Bank. Finance, 2017, 82, 180–190). In this paper, we demonstrate that this issue can exist generally when determining hedging position from the sensitivity of the option function, either calibrated from a parametric model from current option prices or estimated nonparametricaly from historical option prices. Consequently, the sensitivity of the estimated model option function typically does not minimize variance of the hedge risk, even instantaneously. We propose a data-driven approach to directly learn a hedging function from the market data by minimizing variance of the local hedge risk. Using the S&P 500 index daily option data for more than a decade ending in August 2015, we show that the proposed method outperforms the parametric minimum variance hedging method proposed in Hull and White [J. Bank. Finance, 2017, 82, 180–190], as well as minimum variance hedging corrective techniques based on stochastic volatility or local volatility models. Furthermore, we show that the proposed approach achieves significant gain over the implied BS delta hedging for weekly and monthly hedging.     

Value relevance of proportionate consolidation versus the equity method: Evidence from Hong Kong

Whether proportionate consolidation (PC) or the equity method (EM) provides more informative financial statements is a controversial issue. This study uses data from listed companies in Hong Kong to investigate the value relevance of the EM compared with PC during 2005–2008 when the local word-for-word equivalent HKAS 31 offered the same options. The results of this study provide evidence that PC does not offer higher value relevance than the EM. PC’s horizontal aggregation of a portion of the operations, assets and liabilities of the jointly controlled entities with those of the venturer is less informative to investors than the EM’s vertical aggregation.     

Forecasting U.S. money growth using economic uncertainty measures and regularisation techniques

This paper examines the out-of-sample forecasting properties of six different economic uncertainty variables for the growth of the real M2 and real M4 Divisia money series for the U.S. using monthly data. The core contention is that information on economic uncertainty improves the forecasting accuracy. We estimate vector autoregressive models using the iterated rolling-window forecasting scheme, in combination with modern regularisation techniques from the field of machine learning. Applying the Hansen-Lunde-Nason model confidence set approach under two different loss functions reveals strong evidence that uncertainty variables that are related to financial markets, the state of the macroeconomy or economic policy provide additional informational content when forecasting monetary dynamics. The use of regularisation techniques improves the forecast accuracy substantially.     

地方政府债务、金融营商环境与实体企业融资约束

文章基于“财政金融关联”视角,利用2015至2020年省级层面的面板数据,实证检验了地方政府债务、金融营商环境与实体企业融资约束三者间的作用效果。研究结果表明：地方政府债务与企业融资约束存在正向推高关系,而良好的金融营商环境对实体企业融资约束存在负向抑制关系;异质性检验显示,地方政府债务对民营实体企业、中西部实体企业融资约束的推高作用更强;交互效应结果显示,金融营商环境的优化能有效缓解地方政府债务对实体企业融资约束的推高作用。因此,提出改善地区金融营商环境、对差异化企业性质实施优惠帮扶政策以及严控地方政府隐性债务增量是缓解实体企业融资困境,促进地区经济平稳发展的重要措施。