The management of financial risk is one of the most challenging tasks of financial institutions. In the last two decades, diverse quantitative models and approaches have been developed and refined to address the impact of volatile markets on business. Whereas existing approaches have intensively utilized structured data such as historical price series, little attention has been paid to unstructured (textual) data, which could be a large source of information in this context. Previous empirical research has shown that certain news stories, such as corporate disclosures, can cause abnormal price behavior subsequent to their publication. On the basis of a data set comprising such news stories as well as intraday stock prices, this paper explores the risk implications of information being newly available to market participants. After showing that such events can significantly drive stock price volatilities, this research aims at identifying among the textual data provided those disclosures that have resulted in most supranormal risk exposures. To this end, four different learners - Naive Bayes, k-Nearest Neighbour, Neural Network, and Support Vector Machine - have been applied in order to detect patterns in the textual data that could explain increased risk exposure. Two evaluations are presented in order to assess the learning capabilities of the approach in the context of risk management. First, ''classic'' data mining evaluation metrics are applied and, second, a newly developed simulation-based evaluation method is presented. Evaluation results provide strong evidence that unstructured (textual) data represents a valuable source of information also for financial risk management - a domain in which, in the past, little attention has been paid to unstructured data. With regard to classification performance, it is also shown that there exist significant differences between the applied learning techniques.

An intraday market risk management approach based on textual analysis

This conceptual article suggests a reexamination of current governance structures, specifically those of unitary boards after the financial crisis of 2008. We suggest that the existing governance structures are based on an outdated paradigm of business, rooted in economics. We propose an alternative paradigm, a more humanistic paradigm, which allows conceiving alternative, network-oriented governance structures. As hierarchical firms grow larger and more complex, the risk of failure increases from biases, errors, and missing data in communication and control systems. These problems are exacerbated by information overload on senior managers, directors, and their respective regulators. In contrast to traditional corporate governance, network governance introduces a division of power via multiple boards, checks and balances, and active stakeholder engagement. We argue that those features could have prevented the stresses and failures of financial firms in 2008, since they were anticipated by both individuals within firms and external commentators. However, those exposed to risks possessed insufficient influence in either governing and/or regulating firms to take corrective action.

Toward a More Humanistic Governance Model: Network Governance Structures

https://www.pkusz.edu.cn/uploadfile/2014/0515/20140515042522196.pdf

Bayesian Value-at-Risk and expected shortfall forecasting via the asymmetric Laplace distribution

Hedge funds, with assets under management approaching an estimated $1.5 trillion in 2006, have become important players in the U.S. and global capital markets. These largely unregulated funds differ from other market participants in their use of a variety of complex trading strategies and instruments, in their liberal use of leverage, in their opacity to outsiders, and in their convex compensation structure. These differences can exacerbate potential market failures stemming from agency problems, externalities, and moral hazard. Counterparty credit risk management (CCRM) practices, used by financial institutions to assess credit risk and limit counterparty exposure, are the first line of defense against market disruptions with potential systemic consequences. This article examines how the unique nature of hedge funds may generate market failures that make counterparty credit risk for exposures to the funds intrinsically more difficult to manage, both for regulated institutions and for policymakers concerned with systemic risk. The authors acknowledge that various market failures, such as the events surrounding the 1998 collapse of hedge fund Long-Term Capital Management, may make CCRM imperfect. However, CCRM has improved significantly since then, and it remains the appropriate starting point for limiting the potential for hedge funds to generate systemic disruptions.

/pdf/hedge-funds-financial-intermediation-and-systemic-risk-103p7ba1e4.pdf

Hedge Funds, Financial Intermediation, and Systemic Risk

Measuring and managing exchange rate risk exposure is important for reducing a firm’s vulnerabilities from major exchange rate movements, which could adversely affect profit margins and the value of assets. This paper reviews the traditional types of exchange rate risk faced by firms, namely transaction, translation and economic risks, presents the VaR approach as the currently predominant method of measuring a firm’s exchange rate risk exposure, and examines the main adv antages and disadvantages of various exchange rate risk management strategies, including tactical vs. strategical and passive vs. active hedging. In addition, it outlines a set of widely-accepted best practices in managing currency risk and presents some of the main hedging instruments in the OTC and exchange-traded markets. The paper also provides some data on the use of financial derivatives instruments, and hedging practices by US firms.

http://www.asecu.gr/Seeje/issue07/papaioannou.pdf

Exchange rate risk measurement and management: issues and approaches for firms

A top risk management practitioner addresses the essential aspects of modern financial risk management
	
		In the Second Edition of Financial Risk Management + Website, market risk expert Steve Allen offers an insider's view of this discipline and covers the strategies, principles, and measurement techniques necessary to manage and measure financial risk. Fully revised to reflect today's dynamic environment and the lessons to be learned from the 2008 global financial crisis, this reliable resource provides a comprehensive overview of the entire field of risk management.
	
		Allen explores real-world issues such as proper mark-to-market valuation of trading positions and determination of needed reserves against valuation uncertainty, the structuring of limits to control risk taking, and a review of mathematical models and how they can contribute to risk control. Along the way, he shares valuable lessons that will help to develop an intuitive feel for market risk measurement and reporting.
	
		
			Presents key insights on how risks can be isolated, quantified, and managed from a top risk management practitioner
		
			Offers up-to-date examples of managing market and credit risk
		
			Provides an overview and comparison of the various derivative instruments and their use in risk hedging
		
			Companion Website contains supplementary materials that allow you to continue to learn in a hands-on fashion long after closing the book
	
	
		Focusing on the management of those risks that can be successfully quantified, the Second Edition of Financial Risk Management + Websiteis the definitive source for managing market and credit risk.

Steve L. Allen

Papers

Financial Risk Management: A Practitioner's Guide to Managing Market and Credit Risk