Interest-Rate Risk Management Section 3010.1
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The Interest Rate Parity (IRP) Is a Theory Regarding the Relationship
What is the Interest Rate Parity (IRP)? The interest rate parity (IRP) is a theory regarding the relationship between the spot exchange rate and the expected spot rate or forward exchange rate of two currencies, based on interest rates. The theory holds that the forward exchange rate should be equal to the spot currency exchange rate times the interest rate of the home country, divided by the interest rate of the foreign country. Uncovered Interest Rate Parity vs Covered Interest Rate Parity The uncovered and covered interest rate parities are very similar. The difference is that the uncovered IRP refers to the state in which no-arbitrage is satisfied without the use of a forward contract. In the uncovered IRP, the expected exchange rate adjusts so that IRP holds. This concept is a part of the expected spot exchange rate determination. The covered interest rate parity refers to the state in which no-arbitrage is satisfied with the use of a forward contract. In the covered IRP, investors would be indifferent as to whether to invest in their home country interest rate or the foreign country interest rate since the forward exchange rate is holding the currencies in equilibrium. This concept is part of the forward exchange rate determination. What is the Interest Rate Parity (IRP) Equation? The covered and uncovered IRP equations are very similar, with the only difference being the substitution of the forward exchange rate for the expected spot exchange rate. The following shows the equation for the uncovered interest rate parity: The following -
An Economic Capital Model Integrating Credit and Interest Rate Risk in the Banking Book 1
WORKING PAPER SERIES NO 1041 / APRIL 2009 AN ECONOMIC CAPITAL MODEL INTEGRATING CR EDIT AND INTEREST RATE RISK IN THE BANKING BOOK by Piergiorgio Alessandri and Mathias Drehmann WORKING PAPER SERIES NO 1041 / APRIL 2009 AN ECONOMIC CAPITAL MODEL INTEGRATING CREDIT AND INTEREST RATE RISK IN THE BANKING BOOK 1 by Piergiorgio Alessandri 2 and Mathias Drehmann 3 In 2009 all ECB publications This paper can be downloaded without charge from feature a motif http://www.ecb.europa.eu or from the Social Science Research Network taken from the €200 banknote. electronic library at http://ssrn.com/abstract_id=1365119. 1 The views and analysis expressed in this paper are those of the author and do not necessarily reflect those of the Bank of England or the Bank for International Settlements. We would like to thank Claus Puhr for coding support. We would also like to thank Matt Pritzker and anonymous referees for very helpful comments. We also benefited from the discussant and participants at the conference on the Interaction of Market and Credit Risk jointly hosted by the Basel Committee, the Bundesbank and the Journal of Banking and Finance. 2 Bank of England, Threadneedle Street, London, EC2R 8AH, UK; e-mail: [email protected] 3 Corresponding author: Bank for International Settlements, Centralbahnplatz 2, CH-4002 Basel, Switzerland; e-mail: [email protected] © European Central Bank, 2009 Address Kaiserstrasse 29 60311 Frankfurt am Main, Germany Postal address Postfach 16 03 19 60066 Frankfurt am Main, Germany Telephone +49 69 1344 0 Website http://www.ecb.europa.eu Fax +49 69 1344 6000 All rights reserved. -
Interest Rate Risk and Market Risk Lr024
INTEREST RATE RISK AND MARKET RISK LR024 Basis of Factors The interest rate risk is the risk of losses due to changes in interest rate levels. The factors chosen represent the surplus necessary to provide for a lack of synchronization of asset and liability cash flows. The impact of interest rate changes will be greatest on those products where the guarantees are most in favor of the policyholder and where the policyholder is most likely to be responsive to changes in interest rates. Therefore, risk categories vary by withdrawal provision. Factors for each risk category were developed based on the assumption of well matched asset and liability durations. A loading of 50 percent was then added on to represent the extra risk of less well-matched portfolios. Companies must submit an unqualified actuarial opinion based on asset adequacy testing to be eligible for a credit of one-third of the RBC otherwise needed. Consideration is needed for products with credited rates tied to an index, as the risk of synchronization of asset and liability cash flows is tied not only to changes in interest rates but also to changes in the underlying index. In particular, equity-indexed products have recently grown in popularity with many new product variations evolving. The same C-3 factors are to be applied for equity-indexed products as for their non-indexed counterparts; i.e., based on guaranteed values ignoring those related to the index. In addition, some companies may choose to or be required to calculate part of the RBC on Certain Annuities under a method using cash flow testing techniques. -
Request for Information and Comment: Financial Institutions' Use of Artificial Intelligence, Including Machine Learning
Request for Information and Comment: Financial Institutions' Use of Artificial Intelligence, including Machine Learning May 21, 2021 Dr. Peter Quell Dr. Joseph L. Breeden Summary An increasing number of business decisions within the financial industry are made in whole or in part by machine learning applications. Since the application of these approaches in business decisions implies various forms of model risks, the Board of Governors of the Federal Reserve System, the Bureau of Consumer Financial Protection, the Federal Deposit Insurance Corporation, the National the Credit Union Administration, and Office of the Comptroller of the Currency issued an request for information and comment on the use of AI in the financial industry. The Model Risk Managers’ International Association MRMIA welcomes the opportunity to comment on the topics stated in the agencies’ document. Our contact is [email protected] . Request for information and comment on AI 2 TABLE OF CONTENTS Summary ..................................................................................................................... 2 1. Introduction to MRMIA ............................................................................................ 4 2. Explainability ........................................................................................................... 4 3. Risks from Broader or More Intensive Data Processing and Usage ................... 7 4. Overfitting ............................................................................................................... -
Hedge Performance: Insurer Market Penetration and Basis Risk
CORE Metadata, citation and similar papers at core.ac.uk Provided by Research Papers in Economics This PDF is a selection from an out-of-print volume from the National Bureau of Economic Research Volume Title: The Financing of Catastrophe Risk Volume Author/Editor: Kenneth A. Froot, editor Volume Publisher: University of Chicago Press Volume ISBN: 0-226-26623-0 Volume URL: http://www.nber.org/books/froo99-1 Publication Date: January 1999 Chapter Title: Index Hedge Performance: Insurer Market Penetration and Basis Risk Chapter Author: John Major Chapter URL: http://www.nber.org/chapters/c7956 Chapter pages in book: (p. 391 - 432) 10 Index Hedge Performance: Insurer Market Penetration and Basis Risk John A. Major Index-based financial instruments bring transparency and efficiency to both sides of risk transfer, to investor and hedger alike. Unfortunately, to the extent that an index is anonymous and commoditized, it cannot correlate perfectly with a specific portfolio. Thus, hedging with index-based financial instruments brings with it basis risk. The result is “significant practical and philosophical barriers” to the financing of propertykasualty catastrophe risks by means of catastrophe derivatives (Foppert 1993). This study explores the basis risk be- tween catastrophe futures and portfolios of insured homeowners’ building risks subject to the hurricane peril.’ A concrete example of the influence of market penetration on basis risk can be seen in figures 10.1-10.3. Figure 10.1 is a map of the Miami, Florida, vicin- John A. Major is senior vice president at Guy Carpenter and Company, Inc. He is an Associate of the Society of Actuaries. -
Risk Parity an Alternative Approach to Asset Allocation
FEATURE Risk Parity An Alternative Approach to Asset Allocation Alexander Pekker, PhD, CFA®, ASA, Meghan P. Elwell, JD, AIFA®, and Robert G. Smith III, CIMC®, AIF® ollowing the financial crisis of tors, traditional RP strategies fall short respectively, but a rather high Sharpe 2008, many members of the of required return targets and leveraged ratio, 0.86. In other words, while the investment management com- RP strategies do not provide enough portfolio is unlikely to meet the expected F munity, including Sage,intensified their potential benefits to outweigh their return target of many institutional inves- scrutiny of mean-variance optimization risks. Instead we advocate a liability- tors (say, 7 percent or higher), its effi- (MVO) and modern portfolio theory based approach that incorporates risk ciency, or “bang for the buck” (i.e., return (MPT) as the bedrock of asset alloca- budgeting, a key theme of RP, as well as per unit of risk, in excess of the risk-free tion (Elwell and Pekker 2010). Among tactical asset allocation. rate), is quite strong. various alternative approaches to asset How does this sample RP portfo- What is Risk Parity? allocation, risk parity (RP) has been in the lio compare with a sample MVO port- news lately (e.g., Nauman 2012; Summers As noted above, an RP portfolio is one folio? A sample MVO portfolio with a 2012), especially as some hedge funds, where risk, defined as standard deviation return target of 7 percent is shown in such as AQR, and large plan sponsors, of returns, is distributed evenly among table 2. Unlike the sample RP portfolio, such as the San Diego County Employees all potential asset classes;1 table 1 shows the MVO portfolio is heavily allocated Retirement Association, have advocated a sample (unleveraged) RP portfolio toward equities, and it has much higher its adoption. -
What Matters Is Meta-Risks
spotlight RISK MANAGEMENT WHAT MATTERS IS META-RISKS JACK GRAY OF GMO RECKONS WE CAN ALL LEARN FROM OTHER PEOPLE’S MISTAKES WHEN IT COMES TO EMPLOYING EFFECTIVE MANAGEMENT TECHNIQUES FOR THOSE RISKS BEYOND THE SCORE OF EXPLICIT FINANCIAL RISKS. eta-risks are the qualitative implicit risks that pass The perceived complexity of quant tools exposes some to the beyond the scope of explicit financial risks. Most are meta-risk of failing to capitalise on their potential. The US Congress born from complex interactions between the behaviour rejected statistical sampling in the 2000 census as it is “less patterns of individuals and organisational structures. accurate”, even though it lowers the risk of miscounting. In the same MThe archetypal meta-risk is moral hazard where the very act of spirit are those who override the discipline of quant. As Nick hedging encourages reckless behaviour. The IMF has been accused of Leeson’s performance reached stellar heights, his supervisors creating moral hazard by providing countries with a safety net that expanded his trading limits. None had the wisdom to narrow them. tempts authorities to accept inappropriate risks. Similarly, Consider an investment committee that makes a global bet on Greenspan’s quick response to the sharp market downturn in 1998 commodities. The manager responsible for North America, who had probably contributed to the US equity bubble. previously been rolled, makes a stand: “Not in my portfolio.” The We are all exposed to the quintessentially human meta-risk of committee reduces the North American bet, but retains its overall hubris. We all risk acting like “masters of the universe”, believing we size by squeezing more into ‘ego-free’ regions. -
Factors That Shape an Organisation‟S Risk Appetite: Insights from the International Hotel Industry
Oxford Brookes University FACTORS THAT SHAPE AN ORGANISATION‟S RISK APPETITE: INSIGHTS FROM THE INTERNATIONAL HOTEL INDUSTRY Xiaolei Zhang Thesis submitted in partial fulfilment of the requirements of the award of Doctor of Philosophy December 2016 ABSTRACT Since the 2008 global financial crisis, a major challenge for the Board of Directors (BoD) and risk managers of large, public corporations has been to clearly define and articulate their company‟s risk appetite. Considered as a business imperative to ensure successful enterprise risk management, risk appetite has been widely discussed among practitioners and, more recently, academics. Whilst much emphasis has been placed upon defining risk appetite and identifying the ways in which an organisation‟s risk appetite statement can be articulated, the literature has largely ignored the critical idea that risk appetite is not a „static picture‟, but changes over time according to a variety of factors residing in the organisation‟s internal and external contexts. Using the international hotel industry as research context, this study explores the underlying factors that shape an organisation‟s risk appetite. Building on the „living organisation‟ thinking and employing the „living composition‟ model as a conceptual lens, this thesis integrated several strands of literature related to risk appetite, organisational risk taking and individual risk taking, and developed a conceptual framework of factors that shape an organisation‟s risk appetite. Given the scarcity of risk appetite research, an exploratory, qualitative approach was adopted and the fieldwork was conducted in two stages: stage one served to gain a generic-business perspective of the main factors that shape an organisation‟s risk appetite. -
Banking on Deposits: Maturity Transformation Without Interest Rate Risk
THE JOURNAL OF FINANCE • VOL. LXXVI, NO. 3 • JUNE 2021 Banking on Deposits: Maturity Transformation without Interest Rate Risk ITAMAR DRECHSLER, ALEXI SAVOV, and PHILIPP SCHNABL ABSTRACT We show that maturity transformation does not expose banks to interest rate risk— it hedges it. The reason is the deposit franchise, which allows banks to pay deposit rates that are low and insensitive to market interest rates. Hedging the deposit fran- chise requires banks to earn income that is also insensitive, that is, to lend long term at fixed rates. As predicted by this theory, we show that banks closely match the interest rate sensitivities of their interest income and expense, and that this insu- lates their equity from interest rate shocks. Our results explain why banks supply long-term credit. A DEFINING FUNCTION OF BANKS is maturity transformation—borrowing short term and lending long term. This function is important because it sup- plies firms with long-term credit and households with short-term liquid de- posits. In textbook models, banks engage in maturity transformation to earn the average difference between long-term and short-term rates, that is, to earn the term premium. However, doing so exposes them to interest rate risk: an unexpected increase in the short rate increases banks’ interest expense Itamar Drechsler is at the Wharton School, University of Pennsylvania. Alexi Savov and Philipp Schnabl are at New York University Stern School of Business. Itamar Drechsler and Alexi Savov are also with NBER. Philipp Schnabl is also with NBER -
Pillar 3 Disclosures 2019
Pillar 3 Disclosures 2019 Metals | Energy | Agriculture | Financial Futures & Options www.marexspectron.com CONTENTS 1 INTRODUCTION 3 2 DISCLOSURE POLICY 3 3 SCOPE AND APPLICATION OF DIRECTIVE REQUIREMENTS 4 4 RISK MANAGEMENT 6 5 GROUP CAPITAL RESOURCES 13 6 GROUP CAPITAL RESOURCES REQUIREMENT 15 7 ASSET ENCUMBRANCE 22 8 LEVERAGE 22 9 REMUNERATION CODE 23 2 1 INTRODUCTION The Capital Requirements Directive (‘the Directive’), the European Union’s implementation of the Basel II Accord, establishes a regulatory framework comprising of three ‘Pillars’: • Pillar 1 sets out the minimum capital required to meet a firm’s credit, market and operational risks; • Pillar 2 requires a firm to undertake an Internal Capital Adequacy Assessment Process (‘ICAAP’) that establishes whether the Pillar 1 capital is adequate to cover all the risks faced and, if not, calculates the additional capital required. The ICAAP is reviewed by the Financial Conduct Authority (‘FCA’) through a Supervisory Review and Evaluation Process (‘SREP’); and • Pillar 3 requires a firm to disclose specific information concerning its risk management policies and procedures as well as the firm’s regulatory capital position. From 1 January 2014, Marex Spectron Group Limited (‘the Group’) was required to comply with Basel III requirements, which are implemented through the Directive and the Capital Requirement Regulation (‘CRR’), collectively referred to as CRD IV. These regulations are also implemented in the UK through the Prudential Sourcebook for Investment firms (IFPRU) and Prudential Sourcebook for Banks, Building Societies and Investment firms (BIPRU). This document contains the disclosures outlined in Part Eight of the CRR and FCA BIPRU 11, fulfilling the disclosure requirements under these regimes and making them accessible to clients and market participants. -
Model Risk Management: Quantitative and Qualitative Aspects
Model Risk Management Quantitative and qualitative aspects Financial Institutions www.managementsolutions.com Design and Layout Marketing and Communication Department Management Solutions - Spain Photographs Photographic archive of Management Solutions Fotolia © Management Solutions 2014 All rights reserved. Cannot be reproduced, distributed, publicly disclosed, converted, totally or partially, freely or with a charge, in any way or procedure, without the express written authorisation of Management Solutions. The information contained in this publication is merely to be used as a guideline. Management Solutions shall not be held responsible for the use which could be made of this information by third parties. Nobody is entitled to use this material except by express authorisation of Management Solutions. Content Introduction 4 Executive summary 8 Model risk definition and regulations 12 Elements of an objective MRM framework 18 Model risk quantification 26 Bibliography 36 Glossary 37 4 Model Risk Management - Quantitative and qualitative aspects MANAGEMENT SOLUTIONS I n t r o d u c t i o n In recent years there has been a trend in financial institutions Also, customer onboarding, engagement and marketing towards greater use of models in decision making, driven in campaign models have become more prevalent. These models part by regulation but manifest in all areas of management. are used to automatically establish customer loyalty and engagement actions both in the first stage of the relationship In this regard, a high proportion of bank decisions are with the institution and at any time in the customer life cycle. automated through decision models (whether statistical Actions include the cross-selling of products and services that algorithms or sets of rules) 1. -
Best's Enterprise Risk Model: a Value-At-Risk Approach
Best's Enterprise Risk Model: A Value-at-Risk Approach By Seabury Insurance Capital April, 2001 Tim Freestone, Seabury Insurance Capital, 540 Madison Ave, 17th Floor, New York, NY 10022 (212) 284-1141 William Lui, Seabury Insurance Capital, 540 Madison Ave, 17th Floor, New York, NY 10022 (212) 284-1142 1 SEABURY CAPITAL Table of Contents 1. A.M. Best’s Enterprise Risk Model 2. A.M. Best’s Enterprise Risk Model Example 3. Applications of Best’s Enterprise Risk Model 4. Shareholder Value Perspectives 5. Appendix 2 SEABURY CAPITAL Best's Enterprise Risk Model Based on Value-at-Risk methodology, A.M. Best and Seabury jointly created A.M. Best’s Enterprise Risk Model (ERM) which should assess insurance companies’ risks more accurately. Our objectives for ERM are: • Consistent with state of art risk management concepts - Value at Risk (VaR). • Simple and transparent methodology. • Risk parameters are based on current market data. • Risk parameters can be easily updated annually. • Minimum burden imposed on insurance companies to produce inputs. • Explicitly models country risk. • Explicitly calculates the covariance between all of a company’s assets and liabilities globally. • Aggregates all of an insurance company’s risks into a composite risk measure for the whole insurance company. 3 SEABURY CAPITAL Best's Enterprise Risk Model will improve the rating process, but it will also generate some additional costs Advantages: ■ Based on historical market data ■ Most data are publicly available ■ Data is easily updated ■ The model can be easily expanded to include more risk factors Disadvantages: ■ Extra information request for the companies ■ Rating analysts need to verify that the companies understand the information specifications ■ Yearly update of the Variance-Covariance matrix 4 SEABURY CAPITAL Definition of Risk ■ Risk is measured in standard deviations.