SYSTEMIC RISK: WHAT RESEARCH TELLS US and WHAT WE NEED to FIND out Systemic Risk Centre
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Did Spillovers from Europe Indeed Contribute to the 2010 U.S. Flash Crash?
No. 622 / January 2019 Did Spillovers From Europe Indeed Contribute to the 2010 U.S. Flash Crash? David-Jan Jansen Did Spillovers From Europe Indeed Contribute to the 2010 U.S. Flash Crash? David-Jan Jansen * * Views expressed are those of the authors and do not necessarily reflect official positions of De Nederlandsche Bank. De Nederlandsche Bank NV Working Paper No. 622 P.O. Box 98 1000 AB AMSTERDAM January 2019 The Netherlands Did Spillovers From Europe Indeed Contribute to the 2010 U.S. Flash Crash?* David-Jan Jansen a a De Nederlandsche Bank, Amsterdam, The Netherlands This version: January 2019 Abstract Using intraday data, we study spillovers from European stock markets to the U.S. in the hours before the flash crash on 6 May 2010. Many commentators have pointed to negative market sentiment and high volatility during the European trading session before the Flash Crash. However, based on a range of vector autoregressive models, we find no robust evidence that spillovers increased at that time. On the contrary, spillovers on 6 May were mostly smaller than in the preceding days, during which there was great uncertainty surrounding the Greek sovereign debt crisis. The absence of evidence for spillovers underscores the difficulties in understanding the nature of flash events in financial markets. Keywords: flash crash, spillovers, financial stability, connectedness. JEL classifications: G15, N22, N24. * This paper benefitted from discussions with Sweder van Wijnbergen as well as from research assistance by Jack Bekooij. Any errors and omissions remain my responsibility. Views expressed in the paper do not necessarily coincide with those of de Nederlandsche Bank or the Eurosystem. -
Cracks in the Pipeline 2
MEDIA CONTACT: Lauren Strayer | [email protected] 212-389-1413 FINANCIAL PIPELINE .o rg Series CRACKS IN THE PIPELINE 2 HIGH FREQUENCY TRADING by: Wallace C. Turbeville his is the second of a series of articles, that increase the inefficiency of Capital Intermediation and entitled “The Financial Pipeline Series”, its cost. The increased volumes in the traded markets are examining the underlying validity of the largely a result of high-speed, computer driven trading assertion that regulation of the financial by large banks and smaller specialized firms. This article markets reduces their efficiency. These illustrates how this type of trading (along with other activ- articles assert that the value of the finan- ities discussed in subsequent articles) extracts value from cial markets is often mis-measured. The the Capital Intermediation process rendering it less efficient. efficiency of the market in intermediat- It also describes how the value extracted is a driver of even ing flows between capital investors and more increased volume creating a dangerous and powerful capital users (like manufacturing and service businesses, feedback loop. individuals and governments) is the proper measure. Unreg- Tying increased trading volume to inefficiencies runs ulated markets are found to be chronically inefficient using counter to a fundamental tenet of industry opponents to Tthis standard. This costs the economy enormous amounts financial reform. They assert that burdens on trading will each year. In addition, the inefficiencies create stresses to the reduce volumes and thereby impair the efficient functioning system that make systemic crises inevitable. Only prudent of the markets. regulation that moderates trading behavior can reduce these The industry’s position that increased volume reduces inefficiencies. -
The Future of Computer Trading in Financial Markets an International Perspective
The Future of Computer Trading in Financial Markets An International Perspective FINAL PROJECT REPORT This Report should be cited as: Foresight: The Future of Computer Trading in Financial Markets (2012) Final Project Report The Government Office for Science, London The Future of Computer Trading in Financial Markets An International Perspective This Report is intended for: Policy makers, legislators, regulators and a wide range of professionals and researchers whose interest relate to computer trading within financial markets. This Report focuses on computer trading from an international perspective, and is not limited to one particular market. Foreword Well functioning financial markets are vital for everyone. They support businesses and growth across the world. They provide important services for investors, from large pension funds to the smallest investors. And they can even affect the long-term security of entire countries. Financial markets are evolving ever faster through interacting forces such as globalisation, changes in geopolitics, competition, evolving regulation and demographic shifts. However, the development of new technology is arguably driving the fastest changes. Technological developments are undoubtedly fuelling many new products and services, and are contributing to the dynamism of financial markets. In particular, high frequency computer-based trading (HFT) has grown in recent years to represent about 30% of equity trading in the UK and possible over 60% in the USA. HFT has many proponents. Its roll-out is contributing to fundamental shifts in market structures being seen across the world and, in turn, these are significantly affecting the fortunes of many market participants. But the relentless rise of HFT and algorithmic trading (AT) has also attracted considerable controversy and opposition. -
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 ............................................................................................................... -
Ai: Understanding and Harnessing the Potential Wireless & Digital Services Ai: Understanding and Harnessing the Potential White Paper
AI: UNDERSTANDING AND HARNESSING THE POTENTIAL WIRELESS & DIGITAL SERVICES AI: UNDERSTANDING AND HARNESSING THE POTENTIAL WHITE PAPER CONTENTS INTRODUCTION ..............................................................................................................................................................................02 1. THE PRODUCTIVITY CONUNDRUM: WILL AI HELP US BREAK INTO A NEW CYCLE? ...........................................................05 1.1 Global productivity growth is faltering ...................................................................................................... 05 1.2 AI has the potential to drive productivity improvements and hence economic growth .................................... 06 2. AI FUTURES ........................................................................................................................................................................11 2.1 Replacing the smartphone with a ubiquitous voice assistant ....................................................................... 11 2.2 Your AI powered personal digital assistant ............................................................................................... 12 2.3 Is AI the missing piece for a truly smart city? ........................................................................................... 14 2.4 City of the future ................................................................................................................................... 16 2.5 Giving medics more time to care ............................................................................................................ -
Circuit Breakers and New Market Structure Realities
Circuit Breakers and New Market Structure Realities China’s dramatic and short-lived But there are questions about whether regulators have been able to keep up with today’s high-speed markets, with one experience with market circuit trader likening them to police on bicycles trying to catch breakers at the start of the New Year Ferraris.1 Regulators themselves have admitted as much. Testifying before the US Senate Committee on Banking after has revived debate about whether the Flash Crash of 2010, former SEC Chairwoman Mary such market interventions do more Schapiro said: “One of the challenges that we face in recreating the events of May 6 is the reality that the technologies used for harm than good, as regulators and market oversight and surveillance have not kept pace with the market participants around the world technology and trading patterns of the rapidly evolving and expanding securities markets.”2 continue to grapple with new market In response, a growing number of equity and equity-related structure realities and the law of markets (e.g., futures and listed options) around the world have introduced circuit breakers in the form of stock-specific and unintended consequences. market-wide trading halts as well as price limit bands in order to stabilize markets when, as the SEC has said, “severe market While many developments in modern equity markets have price declines reach levels that may exhaust market liquidity.”3 benefited investors in the form of greater efficiency and lower The 10 largest (by value traded) equity markets around the costs, they have also led to highly complex and fragmented world have already implemented or are planning to introduce markets. -
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. -
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. -
2018-09 Interest Rate Risk Management
FEDERAL HOUSING FINANCE AGENCY ADVISORY BULLETIN AB 2018-09: INTEREST RATE RISK MANAGEMENT Purpose This advisory bulletin (AB) provides Federal Housing Finance Agency (FHFA) guidance for interest rate risk management at the Federal Home Loan Banks (Banks), Fannie Mae, and Freddie Mac (the Enterprises), collectively known as the regulated entities. This guidance supersedes the Federal Housing Finance Board’s advisory bulletin, Interest Rate Risk Management (AB 2004-05). Interest rate risk management is a key component in the management of market risk. These guidelines describe principles the regulated entities should follow to identify, measure, monitor, and control interest rate risk. The AB is organized as follows: I. Governance A. Responsibilities of the Board B. Responsibilities of Senior Management C. Risk Management Roles and Responsibilities D. Policies and Procedures II. Interest Rate Risk Strategy, Limits, Mitigation, and Internal Controls A. Limits B. Interest Rate Risk Mitigation C. Internal Controls III. Risk Measurement System, Monitoring, and Reporting A. Interest Rate Risk Measurement System B. Scenario Analysis and Stress Testing C. Monitoring and Reporting Background Interest rate risk is the risk that changes in interest rates may adversely affect financial condition and performance. More specifically, interest rate risk is the sensitivity of cash flows, reported AB 2018-09 (September 28, 2018) Page 1 Public earnings, and economic value to changes in interest rates. As interest rates change, expected cash flows to and from a regulated entity change. The regulated entities may be exposed to changes in: the level of interest rates; the slope and curvature of the yield curve; the volatilities of interest rates; and the spread relationships between assets, liabilities, and derivatives. -