BASEL PILLAR 3 DISCLOSURE for the Year Ended 30 June 2017 Contents

Total Page:16

File Type:pdf, Size:1020Kb

BASEL PILLAR 3 DISCLOSURE for the Year Ended 30 June 2017 Contents BASEL PILLAR 3 DISCLOSURE for the year ended 30 June 2017 contents Overview of risk management ..... 01 Introduction ..... 01 FirstRand strategy ..... 03 Risk profile ..... 05 Current and emerging challenges ..... 07 Risk management approach ..... 08 Risk governance ..... 10 Risk measurement approaches ..... 18 Risk mitigation ..... 20 Financial resource management ..... 22 Risk appetite ..... 22 Stress testing and scenario planning ..... 25 Recovery and resolution regime ..... 26 Link between financial statements and regulatory exposures ..... 27 Capital management ..... 34 Common disclosures ..... 43 Funding and liquidity risk ..... 44 Credit risk ..... 57 Counterparty credit risk ..... 118 Securitisations ..... 133 Market risk in the trading book ..... 141 Non-traded market risk ..... 152 Interest rate risk in the banking book ..... 152 Structural foreign exchange risk ..... 156 Equity investment risk ..... 158 Insurance risk ..... 163 Operational risk ..... 164 Other risks ..... 170 Strategic risk ..... 170 Business risk ..... 171 Reputational risk ..... 172 Environmental and social risk ..... 172 Model risk ..... 173 Regulatory risk ..... 176 Conduct risk ..... 181 Remuneration and compensation ..... 183 1966/010753/06 Index of Pillar 3 disclosure templates and Regulation 43 ..... 184 Certain entities within the Definitions ..... 186 FirstRand group are Authorised Financial Services and Credit Abbreviations ..... 187 Providers. This report is available on the group’s website: www.firstrand.co.za Email questions to [email protected] OVERVIEW OF THE FIRSTRAND GROUP FirstRand’s portfolio of franchises comprises FNB, RMB, WesBank and Ashburton Investments and provides a universal set of transactional, lending, investment and insurance products and services. The FCC franchise represents group-wide functions. OVERVIEW OF RISK MANAGEMENT Introduction This risk and capital management report (Pillar 3 disclosure) covers the operations of FirstRand Limited (FirstRand or the group) and complies with: the Basel Committee on Banking Supervision’s (BCBS) revised Pillar 3 disclosure requirements (Pillar 3 standard), BCBS 309 published in January 2015; and Regulation 43 of the Regulations relating to Banks (Regulations), issued in terms of the Banks Act, 1990 (Act No. 94 of 1990), where not superseded by the revised Pillar 3 disclosure requirements. The most significant revisions are templates for quantitative disclosure and definitions; some with a fixed format which aims to enhance comparability of banks’ disclosures. Some differences exist between the practices, approaches, processes and policies of FirstRand Bank Limited (the bank or FRB) and its fellow wholly-owned subsidiaries of FirstRand. These are highlighted by reference to the appropriate entity, where necessary. This report has been internally verified through the group’s governance processes, in line with the group’s external communication and disclosure policy. The external communication and disclosure policy describes the responsibilities and duties of senior management and the board in the preparation and review of the Pillar 3 disclosure and aims to ensure that: minimum disclosure requirements of the Regulations, standards and directives are met; disclosed information is consistent with the manner in which the board assesses the group’s risk portfolio; the disclosure provides a true reflection of the group’s financial condition and risk profile; and the quantitative and qualitative disclosures are appropriately reviewed. 01 BASEL PILLAR 3 DISCLOSURE Overview of risk management continued SIMPLIFIED GROUP AND SHAREHOLDING STRUCTURE Remgro Limited Directors Royal Bafokeng Holdings (Pty) Ltd 3.9% 28.2% 9.9% 15.0% RMB Holdings Limited 34.1% BEE partners 5.2% LISTED HOLDING COMPANY (FIRSTRAND LIMITED, JSE: FSR) 100% 100% 100% 100% 100% FirstRand EMA FirstRand Investment FirstRand Investment FirstRand Bank FirstRand Insurance Holdings (Pty) Ltd Holdings (Pty) Ltd Management Limited Holdings (Pty) Ltd (FREMA) (FRIHL) Holdings Limited Africa and Investment Banking Other activities Insurance emerging markets management First National Bank1 58% FNB Namibia 96% RMB Private 100% Ashburton Fund 100% FirstRand Life Equity Holdings Managers Assurance Rand Merchant Bank1 69% FNB Botswana 93% RMB Private Equity 100% Ashburton Investor 100% FirstRand Insurance WesBank1 100% FNB Swaziland Services Services Company 100% RMB Securities FirstRand Bank India2 90% FNB Mozambique (FRISCOL)† 100% Ashburton 50% RMB Morgan FirstRand Bank London2,* 100% FNB Zambia Management Stanley Company (RF) FirstRand Bank 100% FNB Lesotho 100% FNB Securities Guernsey2,** Ashburton 100% FNB Tanzania 100% 100% RentWorks FirstRand Bank Kenya3 Investments 100% First National Bank International 100% Direct Axis FirstRand Bank Angola3 Ghana Holdings 81% MotoVantage FirstRand Bank Dubai3 100% RMB Nigeria 100% FNB CIS 100% FirstRand FirstRand Bank Shanghai3 100% FirstRand Management International International Company (RF) – Guernsey – Mauritius 100% Atlantic Asset 100% RMB Australia Management 1. Division Holdings 2. Branch 100% Various general 3. Representative office 100% FirstRand Securities partners# * MotoNovo Finance is a business segment of FirstRand Bank Limited 48% NewDisc (London Branch). ** Trading as FNB Channel Islands. # Ashburton Investments has a number of general partners for fund seeding purposes – all of these entities fall under FirstRand Investment Management Holdings Limited. † With effect from 1 July 2017. Structure shows effective consolidated shareholding For segmental analysis purposes, entities included in FRIHL and FREMA, FirstRand Investment Management Holdings Limited and FirstRand Insurance Holdings (Pty) Ltd are reported as part of the results of the managing franchise. The group’s securitisations and conduits are in FRIHL. 02 FirstRand strategy FirstRand’s portfolio of leading financial services franchises provides a universal set of transactional, lending, investment and insurance products and services. The franchises operate in markets and segments where they can deliver competitive and differentiated client-centric value propositions, leveraging the relevant distribution channels, product skills, licences and operating platforms of the wider group. Strategy is executed on the back of disruptive and innovative thinking, underpinned by an owner-manager culture combined with the disciplined allocation of financial resources. FirstRand’s strategy accommodates a broad set of growth opportunities across the entire financial services universe from a product, market, segment and geographic perspective. The group believes this will create long-term franchise value, ensure sustainable and superior returns for shareholders, within acceptable levels of volatility and maintain balance sheet strength. Currently group earnings are tilted to its domestic market where the lending and transactional franchises have delivered sustained growth since 2010 resulting from the acquisition of a deep and loyal customer base. The group recognises the imperative to continue to protect and grow these very valuable banking franchises, but it also believes that through the utilisation of the origination capabilities and distribution networks of those franchises, it can diversify and capture a larger share of profits from savings, insurance and investment products within its existing customer base. The growth opportunity is significant given the annual flows to other providers from FNB’s customer base alone. Through the manufacture and sale of its own insurance, savings and investment products, the group will, over time, offer differentiated value propositions for customers and generate new and potentially meaningful revenue streams for the group. To date, progress looks promising and FirstRand is incrementally increasing its share of the insurance, savings and investment profit pools that exist within its own customer base. The group also continues to protect and grow its large transactional and lending franchises. The group’s strategy outside of its domestic market centres on growing its presence and offerings in nine markets in the rest of Africa where it believes it can organically build competitive advantage and scale over time. In addition, it is focusing on leveraging its current operations in the UK to create new revenue streams. Over the past year, the group has focused on execution on the strategic framework depicted in the schematic below. FirstRand aims to create long-term franchise value, ensure sustainable and superior returns for shareholders within acceptable levels of volatility and maintain balance sheet strength DELIVERED THROUGH CURRENT STRATEGIES: INCREASE DIVERSIFICATION – ACTIVITY AND GEOGRAPHY Protect and grow Build a sustainable banking franchises Broaden financial Portfolio approach developed markets services offering to the rest of Africa business SUCCESS LIES IN EXECUTING ON THE FOLLOWING: Disciplined Create a platform- Drive efficiencies Cross-franchise Build allocation and franchise- and manage cost collaboration organisational of financial neutral business base structures and resources model develop diverse talent pools to enable execution 03 BASEL PILLAR 3 DISCLOSURE Overview of risk management continued The group’s strategy is executed through its portfolio of franchises within the framework set by the group. Retail and commercial Corporate and Instalment finance Asset Group-wide Key banking, and insurance investment and short-term management functions activities
Recommended publications
  • Liquidity Shock: the Hidden Risk in Modern Markets March 2018
    Investment Intelligence Liquidity Shock: The Hidden Risk in Modern Markets March 2018 Introduction Post-crisis changes to regulations and market Key Takeaways structure have combined with innovations in technology and financial products to make global Today’s markets contain hidden risks that markets more robust and efficient. Despite this increase vulnerability to volatility spikes and progress, today’s markets still contain risks that liquidity shortages. increase vulnerability to volatility spikes, episodic The main sources of these risks are financial Steven Malin, PhD disappearances of liquidity and, potentially, another product innovations, automated and algorithmic Director liquidity crisis. The main sources of these risks are trading practices and regulatory adjustments Senior Investment the ongoing stream of financial product innovations, Strategist put in place to strengthen markets after the automated and algorithmic trading practices and, Global Economics 2008 crisis. & Strategy ironically, some of the very regulatory adjustments put in place to strengthen markets after the Also contributing to more “accident prone” 2008 crisis. markets are diminished bank bond inventories, Together, these factors have the potential to turn the growth of high-frequency trading, and the a small market disruption into a rapid collapse of proliferation of ETFs and rules-based trading asset prices—a danger that became all too real strategies. to investors during the sudden and dramatic reappearance of market volatility in February These risks could be exacerbated in coming 2018. Over the coming decade, these risks could years by unprecedented “quantitative be exacerbated by unprecedented “quantitative tightening” by central banks. tightening” by central banks that could cause funding Institutional investors should act now to account liquidity and, ultimately, market liquidity to shrink.
    [Show full text]
  • Liquidity at Risk Joint Stress Testing of Liquidity and Solvency Risk
    Liquidity at Risk Joint Stress Testing of Liquidity and Solvency Risk Rama Cont & Artur Kotlicki University of Oxford Laura Valderrama International Monetary Fund 1 Solvency stress testing 2 Solvency Risk • Solvency risk is driven by the difference in firm’s asset values and its liabilities. • Bank stress testing, which has become a key tool for bank supervisors, has also mainly focused on solvency risk. • Regulation of insurance companies also focused on solvency risk (Solvency II, Swiss Solvency test). • However, solvency risk does not give the full picture – we have spectacular failures of SIFIs due to lack of liquidity: • Bear Stearns held excess capital at the time of its default. • AIG, which failed to fulfill large payment triggered by a downgrade, was not insolvent at the time of failure. • Banco Popular, which failed through a lack of liquidity in 2017, displayed a capital ratio 6:6% in the 2016 EBA adverse scenario. 3 Liquidity Risk and Default • Liquidity risk: failure to meet a short-term payment obligation. • Default of payment is the legal definition of default. • Inherent risk to instability in short-term funding (e.g. debt roll-over risk) and cash-flows (e.g. variation margin). • Supervision and regulation of bank liquidity: • Liquidity Coverage Ratio (LCR): banks to hold liquidity provision for expected outflows over 30-day time horizon. • Net Stable Funding Ratio (NSFR): limits over-reliance on short-term wholesale funding and aims to increase funding stability. • Liquidity stress testing: e.g. ECB’s 2019 sensitivity analysis of liquidity risk (LiST) typically done separately from solvency stress testing. 4 Liquidity Risk Defining liquidity requires the introduction of a horizon T.
    [Show full text]
  • Deloitte ALM Survey of European Banks Practices 2019
    Asset and Liability Management in banks Results of 2019 Deloitte Survey Agenda Introduction and context 3 Executive summary 5 Regulatory background 7 Results of Deloitte Survey 10 Survey participants Risk estimation and measurement • Division of responsibilities concerning planning • Approaches applied in relation to interest rate risk • Approaches applied in relation to liquidity risk • ALM model validation • xVA models and adjustments The role of ALM units in banks Other related Deloitte publications 33 How can we help you? 35 Contact 37 © 2019 Deloitte Polska Asset and Liability Management in banksu 2 Introduction and context © 2019 Deloitte Polska Asset and Liability Management in banks 3 Introduction About the survey There were In 2019 Deloitte asked Central and Eastern European 33 banks to participate in a survey regarding ALM solutions applied. institutions participating in the survey. The survey consisted of open and closed 53 questions aimed survey participants at evaluation of current ALM practices adopted on the A large number of Polish market. The questions focused on the following areas: banks participated due to The survey included banks high involvement of from Central and Eastern Polish Deloitte team. European countries 01 Risk estimation and measurement: Division of responsibilities concerning planning The number of participants totalled 33 leading banks Approaches applied in relation to interest rate risk varying in terms of size and business models Approaches applied in relation to liquidity risk Definition of current
    [Show full text]
  • Liquidity Stress Testing: a Survey of Theory, Empirics and Current Industry and Supervisory Practices
    Basel Committee on Banking Supervision Working Paper No. 24 Liquidity stress testing: a survey of theory, empirics and current industry and supervisory practices October 2013 This publication is available on the BIS website (www.bis.org). © Bank for International Settlements 2013. All rights reserved. Brief excerpts may be reproduced or translated provided the source is stated. ISBN 92-9131-969-4 (print) ISBN 92-9197-969-4 (online) Contents Liquidity stress testing: a survey of theory, empirics and current industry and supervisory practices ........... 1 1. Introduction ...................................................................................................................................................................... 1 2. A set of global case studies ........................................................................................................................................ 5 2.1 Overview .......................................................................................................................................................... 5 2.2 Sources and quantities of liquidity stress ........................................................................................... 7 2.3 Liquidity buffers .......................................................................................................................................... 11 2.4 Other considerations ................................................................................................................................. 14 3. Literature
    [Show full text]
  • Fordham Journal of Corporate & Financial
    Fordham Journal of Corporate & Financial Law Volume 13 Issue 3 Article 4 2008 Hedge Funds, Liquidity and Prime Brokers Nathan Bryce Follow this and additional works at: https://ir.lawnet.fordham.edu/jcfl Part of the Banking and Finance Law Commons, and the Business Organizations Law Commons Recommended Citation Nathan Bryce, Hedge Funds, Liquidity and Prime Brokers, 13 Fordham J. Corp. & Fin. L. 475 (2008). Available at: https://ir.lawnet.fordham.edu/jcfl/vol13/iss3/4 This Note is brought to you for free and open access by FLASH: The Fordham Law Archive of Scholarship and History. It has been accepted for inclusion in Fordham Journal of Corporate & Financial Law by an authorized editor of FLASH: The Fordham Law Archive of Scholarship and History. For more information, please contact [email protected]. HEDGE FUNDS, LIQUIDITY AND PRIME BROKERS By Nathan Bryce* * J.D., expected, Fordham University School of Law, 2009; B.A., cum laude, Cornell University, 2006. I would like to thank Professor Caroline Gentile for her insight, support, and recommendations. I would also like to thank the members of the Fordham Journal of Corporate & Financial Law for their editorial assistance and diligent help throughout the writing process. 475 476 FORDHAM JOURNAL OF Vol. XIII CORPORATE & FINANCIAL LAW INTRODUCTION Over the past decade, the hedge fund industry has enjoyed remarkable growth. The media enthusiastically described the success of the top-performing funds and the lavish riches they bestowed on their employees.1 At the same time, however, there were remarkable stories of failure in the industry.2 Both politicians and economists warned of the potential dangers hedge funds present to the national and global economies.3 These warnings and concerns created a debate regarding the level of regulation needed, if any, over what is currently a largely unregulated industry.4 This Note argues that while increased regulation of the hedge fund industry is necessary, the government’s recent and ongoing attempts to increase regulation are misguided.
    [Show full text]
  • Measuring and Managing Liquidity Risk for Other Titles in the Wiley Finance Series Please See Measuring and Managing Liquidity Risk
    Measuring and Managing Liquidity Risk For other titles in the Wiley Finance Series please see www.wiley.com/finance Measuring and Managing Liquidity Risk Antonio Castagna and Francesco Fede This edition first published 2013 Copyright# 2013 John Wiley & Sons Registered office John Wiley & Sons Ltd, The Atrium, Southern Gate, Chichester, West Sussex, PO19 8SQ, United Kingdom For details of our global editorial offices, for customer services and for information about how to apply for permission to reuse the copyright material in this book please see our website at www.wiley.com All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording or otherwise, except as permitted by the UK Copyright, Designs and Patents Act 1988, without the prior permission of the publisher. Wiley publishes in a variety of print and electronic formats and by print-on-demand. Some material included with standard print versions of this book may not be included in e-books or in print-on-demand. If this book refers to media such as a CD or DVD that is not included in the version you purchased, you may download this material at http://booksupport.wiley.com For more information about Wiley products, visit www.wiley.com Designations used by companies to distinguish their products are often claimed as trademarks. All brand names and product names used in this book and on its cover are trade names, service marks, trademarks or registered trademarks of their respective owners. The publisher and the book are not associated with any product or vendor mentioned in this book.
    [Show full text]
  • The Impact of Asset Price Bubbles on Liquidity Risk Measures from a Financial Institutions Perspective
    Int. J. Bonds and Derivatives, Vol. X, No. Y, xxxx 1 The impact of asset price bubbles on liquidity risk measures from a financial institutions perspective Michael Jacobs Jr. Accenture Consulting, Finance and Risk Services Advisory/Models, Methodologies & Analytics, 1345 Avenue of the Americas, New York, N.Y., 10105, USA Email: [email protected] Abstract: This study presents an analysis of the impact of asset price bubbles on a liquidity risk measure, the liquidity risk option premium (‘LROP’). We present a styled model of asset price bubbles in continuous time, and perform a simulation experiment of a stochastic differential equation (‘SDE’) system for the asset value through a constant elasticity of variance (‘CEV’) process. Comparing bubble to non-bubble economies, it is shown that asset price bubbles may cause an firm’s traditional risk measures, such as value-at-risk (‘VaR’) to decline, due to an increase in the right skewness of the value distribution, which results in the LROP to decline and therefore an underpricing of liquidity risk. Keywords: financial crisis; liquidity risk; model risk; asset price bubbles; value-at-risk; stochastic differential equation; SDE; constant elasticity of variance; CEV. Reference to this paper should be made as follows: Jacobs Jr., M. (xxxx) ‘The impact of asset price bubbles on liquidity risk measures from a financial institutions perspective’, Int. J. Bonds and Derivatives, Vol. X, No. Y, pp.000–000. Biographical notes: Michael Jacobs Jr., PhD, CFA, is a Principal Director in the Risk Analytics practice of Accenture. He specialises in risk model development and validation across a range of risk and product types.
    [Show full text]
  • CRAFIELD UNIVERSITY Naif A
    CRAFIELD UNIVERSITY Naif A. Al Baz MODELLING CREDIT RISK FOR SMES IN SAUDI ARABIA Cranfield School of Management Doctor of Business Administration Academic Year: 2016–2017 Supervisors: Professor Huainan Zhao Dr. Vineet Agarwal July 2017 CRANFIELD UNIVERSITY Doctor of Business Administration Academic Year: 2016–2017 Naif A. Al Baz MODELLING CREDIT RISK FOR SMES IN SAUDI ARABIA Supervisors: Professor Huainan Zhao Dr. Vineet Agarwal July 2017 This thesis is submitted in partial fulfillment of the requirements for the degree of Doctor of Business Administration © Cranfield University 2017. All rights reserved. No part of this publication may be reproduced without the written permission of the copyright owner. ABSTRACT The Saudi Government’s 2030 Vision directs local banks to increase and improve credit for the Small and Medium Enterprises (SMEs) of the economy (Jadwa, 2017). Banks are, however, still finding it difficult to provide credit for small businesses that meet Basel’s capital requirements. Most of the current credit-risk models only apply to large corporations with little constructed for SMEs applications (Altman and Sabato, 2007). This study fills this gap by focusing on the Saudi SMEs perspective. My empirical work constructs a bankruptcy prediction model based on logistic regressions that cover 14,727 firm-year observations for an 11-year period between 2001 and 2011. I use the first eight years data (2001-2008) to build the model and use it to predict the last three years (2009-2011) of the sample, i.e. conducting an out-of-sample test. This approach yields a highly accurate model with great prediction power, though the results are partially influenced by the external economic and geopolitical volatilities that took place during the period of 2009-2010 (the world financial crisis).
    [Show full text]
  • Dynamic Balance Sheet Model with Liquidity Risk
    Working Paper Series Grzegorz Hałaj Dynamic balance sheet model with liquidity risk No 1896 / April 2016 Note: This Working Paper should not be reported as representing the views of the European Central Bank (ECB). The views expressed are those of the author and do not necessarily reflect those of the ECB. Abstract Theoretically optimal responses of banks to various liquidity and solvency shocks are mod- elled. The proposed framework is based on a risk-adjusted return portfolio choice in multiple periods subject to the default risk related either to liquidity or solvency problems. Performance of the model and sensitivity of optimal balance sheet structures to some key parameters of the model are illustrated in a specific calibrated setup. The results of the simulations shed light on the effectiveness of the liquidity and solvency regulation. The flexible implementation of the model and its semi-analytical solvability allows for various easy applications of the framework for the macro-prudential policy analysis. Keywords: asset structure, optimal portfolio, banking JEL Classification: G11, G21, C61 ECB Working Paper 1896, April 2016 1 1 Non-technical summary Banks’ balance sheets change their composition due to market conditions implied by a generic growth of credit and debt in the economy and valuation changes, but also due to bank’s strategic actions. The strategic driver is particularly interesting and challenging from the modeling perspective since it combines the changes in risk and trends in the economy, the impact of the regulatory regime and the asset and liability management (ALM). These strategic responses to the changing market and regulatory parameters have to be well understood in order to gauge the influence and effectiveness that macro-prudential policies can have on banking system.
    [Show full text]
  • Market and Liquidity Risks Using Transaction-By-Transaction Information
    mathematics Article Market and Liquidity Risks Using Transaction-by-Transaction Information Mariano González-Sánchez * , Eva M. Ibáñez Jiménez and Ana I. Segovia San Juan Department of Business and Accounting, UNED (Universidad Nacional de Educación a Distancia), Paseo Senda del Rey, 11 Madrid, Spain; [email protected] (E.M.I.J.); [email protected] (A.I.S.S.J.) * Correspondence: [email protected] Abstract: The usual measures of market risk are based on the axiom of positive homogeneity while neglecting an important element of market information—liquidity. To analyze the effects of this omission, in the present study, we define the behavior of prices and volume via stochastic processes subordinated to the time elapsing between two consecutive transactions in the market. Using simulated data and market data from companies of different sizes and capitalization levels, we compare the results of measuring risk using prices compared to using both prices and volumes. The results indicate that traditional measures of market risk behave inversely to the degree of liquidity of the asset, thereby underestimating the risk of liquid assets and overestimating the risk of less liquid assets. Keywords: liquidity risk; volume; trade; intraday frequency Citation: González-Sánchez, M.; Ibáñez Jiménez, E.M.; Segovia San Juan, A.I. Market and 1. Introduction Liquidity Risks Using Liquidity risk is an important field of research in finance, as evidenced by the large Transaction-by-Transaction number of papers published on this subject ([1–16]). However, the large timespan of these Information. Mathematics 2021, 9, publications indicates that this question does not yet have a single answer.
    [Show full text]
  • Financial Analysis Made Easy
    financial analysis made easy IRIS integrated risk management ag www.iris.ch : leading provider of financial analysis solutions IRIS delivers unified risk and profitability analysis solutions for the banking, insurance and corporate sectors. The integrated IRIS solutions cover a broad scope and depth of financial analysis, ensuring consistency of results, and redu- cing the costs of analysis. In addition, the IRIS solutions provide the user with the power of dynamic simulation. Dynamic simulation allows evaluating poten- tial decisions in a what-if environment, and as a consequence making highly quantified strategic decisions. The success of the IRIS solutions relies on the following strengths: 1. easy to use and highly flexible modular software platforms satisfying the internal and external analysis requirements in the field of financial and ope- rational risk analysis for small to large organizations: • riskpro™, including the OpRisk Suite from RCS AG • riskprolight™, a simplified subset of riskpro™ for Basel II standard credit risk 2. unmatched financial products coverage, from saving accounts, complex loans, insurance instruments to exotic options and structured products 3. experienced and talented implementation and support resources providing quality services and know-how transfer to secure effective solution imple- mentation and use. This covers: • management consulting • project management • functional and technical implementation • technical data integration • modeling support • training and workshops by the IRIS academy 4. worldwide
    [Show full text]
  • Liquidity and Volatility in the US Treasury Market
    Federal Reserve Bank of New York Staff Reports Liquidity and Volatility in the U.S. Treasury Market Giang Nguyen Robert Engle Michael Fleming Eric Ghysels Staff Report No. 590 December 2012 Revised November 2018 This paper presents preliminary findings and is being distributed to economists and other interested readers solely to stimulate discussion and elicit comments. The views expressed in this paper are those of the authors and do not necessarily reflect the position of the Federal Reserve Bank of New York or the Federal Reserve System. Any errors or omissions are the responsibility of the authors. Liquidity and Volatility in the U.S. Treasury Market Giang Nguyen, Robert Engle, Michael Fleming, and Eric Ghysels Federal Reserve Bank of New York Staff Reports, no. 590 December 2012; revised November 2018 JEL classification: C58, G01, G12 Abstract We model the joint dynamics of intraday liquidity, volume, and volatility in the U.S. Treasury market, especially through the 2007-09 financial crisis and around important economic announcements. Using various specifications based on Bauwens and Giot’s (2000) Log- ACD(1,1) model, we find that liquidity, volume, and volatility are highly persistent, with volatility having a lower short-term persistence than the other two. Market liquidity and volume are important to explaining volatility dynamics but not vice versa. In addition, market dynamics change during the financial crisis, with all variables exhibiting increased responsiveness to their most recent realizations. Our models also reveal different market dynamics around announcements. Finally, we introduce new measures of liquidity risk that are useful for continually monitoring liquidity conditions and the risk of liquidity stress in the market.
    [Show full text]