### 金融代写|金融风险管理代写Financial Risk Management代考|FINC411

statistics-lab™ 为您的留学生涯保驾护航 在代写金融风险管理Financial Risk Management方面已经树立了自己的口碑, 保证靠谱, 高质且原创的统计Statistics代写服务。我们的专家在代写金融风险管理Financial Risk Management方面经验极为丰富，各种代写金融风险管理Financial Risk Management相关的作业也就用不着说。

• Statistical Inference 统计推断
• Statistical Computing 统计计算
• Advanced Probability Theory 高等楖率论
• Advanced Mathematical Statistics 高等数理统计学
• (Generalized) Linear Models 广义线性模型
• Statistical Machine Learning 统计机器学习
• Longitudinal Data Analysis 纵向数据分析
• Foundations of Data Science 数据科学基础

## 金融代写|金融风险管理代写Financial Risk Management代考|LITEREATURE REVIEW

The relationship between risk and return is well known in the finance literature. This relationship has been examined by extensive studies and there is still room for future research. The dynamic changes on business risk environment make this relationship quite difficult to predict, even both practitioners and academicians, have putted efforts to decompose this relationship over the past decades.

It was Knight (1921) who made a significant contribution by introducing the distinction between risk and uncertainty. Several empirical studies are done after that and the relationship between risk and firm performance has attracted the interest of scholars among other views of the risk investigation. For example, Wiseman and Bromiley (1996) in their study examine variables such as: (1) performance, (2) slack, (3) aspirations, (4) expectations, (5) risk, and (6) organization size. The authors among other findings reveal that risk reduces performance. Also, Bromiley (1991) by examining risk, performance, performance expectations and aspirations, slack, and industry performance suggests a model wherein low performance and lack of slack drive risk-taking, but the risks taken have poor returns.

Berman, Wicks, Kotha and Jones (1999) in their study provide evidence that supports a strategic stakeholder management model but no support for an intrinsic stakeholder commitment model.

McNamara and Bromiley (1997) in their study examine the risk assessments bankers assigned to commercial borrowers and reveal that organizational and cognitive factors influenced risky decision making.
Further, Adams and Jiang (2016) investigate the relationship between outside board directors and six measures of financial performance such as: (1) profit margin, (2) return on assets, (3) return on equity, (4) solvency position, (5) loss ratio, and (6) combined operating ratio. By examining panel data for 1999-2012 drawn from the UK’s property-casualty insurance industry, the authors among other findings highlight that the implied understanding of risk management is a core comperence.

Gordon, Loeb and Tseng (2009) investigate whether the relation between ERM and firm performance is contingent upon the proper match between ERM and variables such as: environmental uncertainty, industry competition, firm size, firm complexity, and monitoring by the board of directors. By examining 112 US firms, the authors confirm that argument.

Psillaki, Tsolas and Margaritis (2010) examine whether productive inefficiency measured as the distance from the industry’s ‘best practice’ frontier is an important ex-ante predictor of business failure in the case of French textiles, wood and paper products, computers, and R\&D firms. The authors reveal that productive efficiency has significant explanatory power in predicting the likelihood of default over and above the effect of standard financial indicators.

## 金融代写|金融风险管理代写Financial Risk Management代考|RESULTS AND DISCUSSION

The previous literature has documented the importance of asset liquidity in association with firm innovation (Pham, Vo, Le, \& Le, 2018), capital structure (Morellec, 2001; Sibilkov, 2009), the cost of capital (Ortiz-Molina \& Phillips, 2010), portfolio choice (Geromichalos \& Simonovska, 2014); asset prices (Lester. Postlewaite, \& Wright, 2012) and among others (Amihud \& Mendelson, 1988: Amihud. Mendelson, \& Pedersen, 2006; Gavazza, 2010; Geromichalos, Jung, Lee, \& Carlos, 2021; Herrenbrueck \& Geromichalos, 2017; Kruse, 2002; Nejadmalayeri, 2021). Prior studies capture asset liquidity as the liquidity scores for firms’ major asset classes in their balance sheets including (1) cash and cash equivalents, (2) other non-current assets, (3) tangible fixed assets, and other assets (Gopalan, Kadan, \& Pevzner, 2012) and the non-cash assets (Pham et al., 2018).

For several types of liquidity risk, stock market liquidity has been continuously attractive to international scholars in investigating its relation to several themes of corporate finance as well as the real economy. For instance, Vivian W. Fang, Tian, and Tice (2014) find that higher stock liquidity induces a decrease in future firm innovation, the authors explain by the two possible mechanisms including (1) greater subjection to hostile takeovers and (2) increased attendance of institutional investors who might not actively collect information or keep track of information.

Stock liquidity negatively affects firm default risk via the two possible mechanisms: enhancing informational efficiency in stock prices and promoting corporate governance quality by blockholes (Brogaard, Li, \& Xia, 2017); furthermore, the authors document that the channel of information efficiency presents better explanatory ability than the channel of corporate governance in the negative effects of stock liquidity on default risk.

By employing the 2001 Securities and Exchange Commission decimalization regulation event in the US and difference-in-differences approach, the authors provide that the firms with the lowest change in stock liquidity (treatment group) experience a higher decrease in default risk after the decimalization in comparison with the firms with the highest change in stock liquidity (control group) surrounding the event year.

For an international context, Nadarajah, Duong, Ali, Liu, and Huang (2020) also find the same negative relation between stock liquidity and default risk; using the event of the Directive on Markets in Financial Instruments (MiFID), the authors document a decrease in default risk after the $2007 \mathrm{MiFID}$ event as an exogenous shock to stock liquidity.

## 金融代写|金融风险管理代写Financial Risk Management代考|LITEREATURE REVIEW

Knight (1921) 通过引入风险和不确定性之间的区别做出了重大贡献。之后进行了一些实证研究，风险与企业绩效之间的关系在风险调查的其他观点中引起了学者们的兴趣。例如，Wiseman 和 Bromiley (1996) 在他们的研究中检查了以下变量：(1) 绩效，(2) 懈怠，(3) 抱负，(4) 期望，(5) 风险和 (6) 组织规模。作者的其他研究结果表明，风险会降低绩效。此外，Bromiley (1991) 通过检查风险、绩效、绩效预期和期望、松弛和行业绩效提出了一个模型，其中低绩效和缺乏松弛驱动风险承担，但所承担的风险回报不佳。

Berman、Wicks、Kotha 和 Jones (1999) 在他们的研究中提供了支持战略利益相关者管理模型但不支持内在利益相关者承诺模型的证据。

McNamara 和 Bromiley (1997) 在他们的研究中检查了银行家分配给商业借款人的风险评估，并揭示了组织和认知因素影响了风险决策。

Gordon、Loeb 和 Tseng (2009) 调查 ERM 与公司绩效之间的关系是否取决于 ERM 与变量之间的适当匹配，例如：环境不确定性、行业竞争、公司规模、公司复杂性和董事会监督。通过研究 112 家美国公司，作者证实了这一论点。

Psillaki、Tsolas 和 Margaritis（2010 年）研究了以与行业“最佳实践”前沿的距离来衡量的生产效率低下是否是法国纺织品、木材和纸制品、计算机和 R 业务失败的重要事前预测因素。 \&D 公司。作者揭示了生产效率在预测违约可能性方面具有显着的解释力，超出了标准财务指标的影响。

## 广义线性模型代考

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