Equity Derivatives And Market Risk Models Download __HOT__
This reading is an introduction to the process of measuring and managing market risk. Market risk is the risk that arises from movements in stock prices, interest rates, exchange rates, and commodity prices. Market risk is distinguished from credit risk, which is the risk of loss from the failure of a counterparty to make a promised payment, and also from a number of other risks that organizations face, such as breakdowns in their operational procedures. In essence, market risk is the risk arising from changes in the markets to which an organization has exposure.
Equity Derivatives And Market Risk Models Download
Value at risk (VaR) is the minimum loss in either currency units or as a percentage of portfolio value that would be expected to be incurred a certain percentage of the time over a certain period of time given assumed market conditions.
Property and casualty insurers use sensitivity and exposure measures to ensure exposures remain within defined asset allocation ranges. They use economic capital and VaR measures to estimate the impairment in the event of a catastrophic loss. They use scenario analysis to stress the market risks and insurance risks simultaneously.
We are exposed to foreign currency, interest rate, fixed-income, equity, and commodity price risks. A portion of these risks is hedged, but fluctuations could impact our results of operations, financial position, and cash flows. We hedge a portion of anticipated revenue and accounts receivable exposure to foreign currency fluctuations, primarily with option contracts. We monitor our foreign currency exposures daily to maximize the overall effectiveness of our foreign currency hedge positions. Principal currencies hedged include the euro, Japanese yen, British pound, and Canadian dollar. Fixed-income securities and interest rate derivatives are subject primarily to interest rate risk. The portfolio is diversified and structured to minimize credit risk. Securities held in our equity and other investments portfolio and equity derivatives are subject to price risk, and are generally not hedged. However, we use put-call collars to hedge our price risk on certain equity securities that are held primarily for strategic purposes. Commodity derivatives held for the purpose of portfolio diversification are subject to commodity price risk.
VaR numbers are shown separately for interest rate, currency rate, equity price, and commodity price risks. These VaR numbers include the underlying portfolio positions and related hedges. We use historical data to estimate VaR. Given the reliance on historical data, VaR is most effective in estimating risk exposures in markets in which there are no fundamental changes or shifts in market conditions. An inherent limitation in VaR is that the distribution of past changes in market risk factors may not produce accurate predictions of future market risk.
As monetary institutions rely greatly on economic and financial models for a wide array of applications, model validation has become progressively inventive within the field of risk. The Journal of Risk Model Validation focuses on the implementation and validation of risk models, and aims to provide a greater understanding of key issues including the empirical evaluation of existing models, pitfalls in model validation and the development of new methods. We also publish papers on back-testing. Our main field of application is in credit risk modelling but we are happy to consider any issues of risk model validation for any financial asset class.
In this paper the authors propose a semi-parametric, parsimonious value-at-risk forecasting model based on quantile regression and readily available market prices of option contracts from the over-the-counter foreign exchange interbank market.
In this study different value-at-risk (VaR) models are analyzed under different estimation approaches (filtered historical simulation, extreme value theory and Monte Carlo simulation) and backtested with different techniques.
He is the Global Head of S&P Global's (now part of S&PGlobal) Financial Risk Analytics business which provides awardwinning products and solutions to financial institutions to measureand manage their counterparty credit risk, market risk, regulatoryrisk capital, derivative valuation adjustments as well as custom ondemand risk services. Using the latest analytics and technologysuch as a fully vectorized pricing library, Machine Learning and aBig Data stack for scalability, the products and solutions are alsoavailable in the cloud and are used by the largest tier-one banksto smaller niche firms.Prior to joining S&P Global, Mark worked as a Partner atTLG, a specialist risk management consultancy in London.Previously, Mark held Chief Operating Officer positions infinancial markets trading and quantitative risk management roles atABN AMRO, UBS and Bank of America Merrill Lynch. He was also theCapital Management Program Director of global markets at HSBC.Mark holds an MBA from CASS Business School, University ofLondon, UK.
As global head of Financial Engineering, Dr. Cowan is responsible for the R&D initiatives for the Financial Risk Analytics team. He oversees the research and development of the quantitative libraries and methodology used in the groups counterparty credit risk and xVA solutions. With over 13 years of experience, he is an expert in the field of derivatives valuations, regulatory risk and xVA management. Dr. Cowan joined Markit, now S&P Global, through the 2011 acquisition of QuIC Financial Technology, where he held the role of senior financial engineer. He took on responsibility for the Financial Engineering team in October 2016. He attained a Ph.D. in physics from the University of British Columbia, Canada.
This paper provides real-world techniques and optimum asset allocation strategies that can be applied to equity trading portfolios in emerging and illiquid financial markets. Key market risk management methods and procedures that financial entities, regulators and policymakers should consider in formulating their daily market risk management objectives are examined and are adapted to the specific needs of emerging countries. The aim of this paper is to fill a gap in the trading risk management literature and particularly from the perspective of emerging and illiquid markets, such as in the context of the Mexican financial markets. In this paper, we demonstrate a comprehensive and proactive approach for the measurement, management and control of equity trading risk exposure, which takes into account proper adjustments for the illiquidity of both long and short trading/investment positions under normal and severe market conditions and within a multi-security setting. Our approach is based on the renowned concept of Value-at-Risk (VAR) along with the innovation of a software tool utilising matrix-algebra and other optimisation techniques. To illustrate the proper use of VAR and stress-testing (scenario analysis) methods, real-world examples and practical reports of market risk management are calculated and presented for a selected portfolio from the Mexican Stock Market (BMV). To this end, several case studies were achieved with the objective of creating a realistic framework of trading risk measurement and control reports in addition to the inception of procedures for the calculation of the maximum authorised VAR limits.
Trading consists of the proprietary positions in financial instruments which are held for resale (available for sale) and/or which are taken on by the financial entity with the intention of benefiting from actual and/or expected differences between purchase and sale prices or from other price variations (such as spread differentials). Market risk (or trading) is defined as the risk that the trading income will decrease due to an adverse price change in the traded financial instruments. To have a choice between a certain loss and a speculation with cash-markets or derivative instruments, one should set his organisation objectives and decisions utilising modern financial risk measurement tools to estimate worst-case scenarios. Thereafter, the level of the measured risk should be compared with the entity risk appetite. This is with the objective to ascertain if the risk falls within its risk limits and also to reveal if there are enough economic capital cushions to withstand unforeseen surprises. After all, what is most needed is a better understanding of the market risk management process. This can be accomplished by striking a number of institutional changes that will help reduce the uncertainties in the trading of securities. Naturally, this has to be accompanied with clearer legal environment, risk management and accounting standards, in addition to greater disclosures of trading transactions. Accordingly, this will make users, dealers and regulators better off and can improve their assessments of all kinds of risks they may encounter.
The lack of adequate market risk measurement, management and control tools are one of the contributing factors that have led to major financial losses among national/multinational corporations in emerging countries. The new Basle accord (so-called Basle II), for the establishment of adequate internal models of risk management, has motivated several emerging countries to be part of the agreement at different implementation levels. Several emerging markets, in the Asian and Latin American continents, would like to be Basel-compliant and hence are already in advanced steps to implement, by the end of the year 2007, modified versions of the Basle agreement with its suggested internal models.
A number of Latin American countries, such as Mexico, are also voluntarily joining the implementation of modified versions of the Basle II accord. In fact, the Mexican financial markets, in general, are in progressive stages vis-à-vis other emerging markets of implementing advanced risk management regulations and techniques. Moreover, in recent years local regulatory authorities have made certain progress in cultivating the culture of risk management among local financial entities and regulatory/supervisory institutions.