Financial risk

About: Financial risk is a research topic. Over the lifetime, 11899 publications have been published within this topic receiving 231404 citations. The topic is also known as: economic risk.

A technical guide

Abstract: This appraisal guide and its companion resource manual incorporate the latest microfinance knowledge and best practices to form a comprehensive guide that analysts can use to evaluate microfinance institutions (MFIs). This guide is primarily for funders and their qualified consultants who analyze the MFIs. This guide is organized in the form of an outline of a complete appraisal report. A complete report covers seven areas: Overview-summarizes the MFI's vision and mission, organizational strengths and weaknesses, and macroeconomic, political, and other external factors. Institution-describes the MFI's ownership and governance, organizational structure, regulation and supervision, management, external relationships, human resource management, information and communications technology, information availability and quality, internal controls, and external auditing. Products-analyze the MFI's voluntary savings, lending, and financial and non-financial products. Social performance-assesses how well the MFI translates its social goals into practice, looking at systems, outreach, and potential for achieving impact. Loan portfolio quality-reviews how the MFI measures, monitors, and manages its loan portfolio, including delinquency and write-offs. Financial performance and risk management-analyzes the MFI's financial performance, risk management, and financial ratios. Business planning-evaluates the MFI's strategic and business planning processes and financial projections.

The impact of prior firm financial performance on subsequent corporate reputation

Abstract: This study links corporate reputation, as measured byFortune magazine's Most Admired list, with firm financial performance. Seven measures of financial risk and return were collected for a sample of 149 firms from two time periods, 1981 and 1986. The mean score of four attributes from the 1993Fortune Most Admired list for the sample was then analyzed with the financial data through regression analysis. Two financial variables, Standard Deviation of the Market Return of the Firm and Return on Sales, explained between 0.12 and 0.14 of subsequent reputation. The implication for management is that they can affect a firm's subsequent reputation by lowering financial risk and controlling costs.

The Relationship between Liquidity Risk and Credit Risk in Banks

Abstract: This paper investigates the relationship between the two major sources of bank default risk: liquidity risk and credit risk. We use a sample of virtually all U.S. commercial banks during the period 1998 to 2010 to analyze the relationship between these two risk sources on the bank institutional-level and how this relationship influences banks’ probabilities of default (PD). Our results show that both risk categories do not have an economically meaningful reciprocal contemporaneous or time-lagged relationship. However, they do influence banks’ probability of default. This effect is twofold: whereas both risks separately increase the PD, the influence of their interaction depends on the overall level of bank risk and can either aggravate or mitigate default risk. These results provide new insights into the understanding of bank risk, as developed by the body of literature on bank stability risk in general and credit and liquidity risk in particular. They also serve as an underpinning for recent regulatory efforts aimed at strengthening banks (joint) risk management of liquidity and credit risks, such as the Basel III and Dodd-Frank frameworks.

After VaR: The Theory, Estimation, and Insurance Applications of Quantile‐Based Risk Measures

Abstract: We discuss a number of quantile-based risk measures (QBRMs) that have recently been developed in the financial risk and actuarial/insurance literatures. The measures considered include the Value-at-Risk (VaR), coherent risk measures, spectral risk measures, and distortion risk measures. We discuss and compare the properties of these different measures, and point out that the VaR is seriously flawed. We then discuss how QBRMs can be estimated, and discuss some of the many ways they might be applied to insurance risk problems. These applications are typically very complex, and this complexity means that the most appropriate estimation method will often be some form of stochastic simulation.