DOCSLIB.ORG

Modelling Stock Market Manipulation in Online Forums

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Modelling Stock Market Manipulation in Online Forums Modelling Stock Market Manipulation in Online Forums by David Nam A thesis submitted to the School of Computing in conformity with the requirements for the degree of Master of Science Queen's University Kingston, Ontario, Canada October 2020 Copyright c David Nam, 2020 Abstract Over the past several decades, advances in technology have significantly impacted all aspects of the financial system. While it has led to numerous benefits, it has also increased the methods for manipulating the market. A frequent platform used to perform these market manipulation schemes has been through social media. In particular, online forums have become a tool for manipulators to disseminate false or misleading information so that they can profit from other investors. As a result, my research provides investors with valuable insights and the tools necessary for detecting pump-and-dump schemes. To achieve this, posts and comments within financial forums were first collected. Then, financial data was added to associate the texts with resulting market behaviours. By using statistical methods, the records were then initially labelled depending on whether they exhibited a known market pattern that commonly occurs when investors act upon deceptive content. To further improve upon the labelling method, comments of deceptive posts were then relabelled based on their level of agreement to fraudulent information. With the described agreement model, results showed that predictions among the tested classification techniques (XGBoost, Random Forest, SVM, MLP, CNN, BiLSTM) were improved. Additionally, by comparing the performance of the classifiers, CNNs were found to be the best performing model among those that were tested. i Acknowledgments I would like to express my sincere gratitude to my supervisor, Dr. David Skillicorn. His guidance and patience throughout this journey have been invaluable to my success. Thank you to all the professors whom I had the pleasure of meeting. The knowledge they shared has played an important role in shaping my research. I would also like to thank all my lab-mates. Their company and support have made my days at the lab enjoyable, and my overall experience at Queen's University memorable. Lastly, I would like to thank my family and friends who have been supportive and patient with me. Their encouragement pushed me to become the best version of myself. ii Contents Abstract i Acknowledgments ii Contents iii List of Tables v List of Figures vi Chapter 1: Introduction 1 Chapter 2: Background and Related Work 6 2.1 Data Sources . 6 2.2 Market Data . 8 2.2.1 OHLCV . 9 2.2.2 Market Capitalization . 10 2.2.3 Penny Stocks . 11 2.2.4 Market Manipulation . 11 2.2.5 Pump and Dump . 13 2.2.6 Event Study . 15 2.3 Tools . 16 2.3.1 Stance Detection . 16 2.3.2 Empath . 16 2.3.3 Synthetic Minority Oversampling Technique (SMOTE) . 17 2.3.4 Adaptive Synthetic (ADASYN) Approach . 17 2.3.5 SHAP . 18 2.4 Techniques . 18 2.4.1 Non-negative Matrix Factorization (NMF) . 19 2.4.2 Latent Dirichlet Allocation (LDA) . 19 2.4.3 Singular Value Decomposition (SVD) . 20 2.4.4 Extreme Gradient Boosting (XGBoost) . 20 iii 2.4.5 Random Forest (RF) . 21 2.4.6 Support Vector Machine (SVM) . 22 2.4.7 Artificial Neural Networks . 22 2.5 Related Work . 25 2.6 Summary . 32 Chapter 3: Experiments 33 3.1 Data Collection . 34 3.1.1 Collecting Data from Reddit . 35 3.1.2 Collecting Data from Yahoo! Finance . 36 3.2 Text Preprocessing . 39 3.3 Data Labelling . 45 3.3.1 Anomaly Detection . 46 3.3.2 Price Trend . 48 3.3.3 Agreement Model . 50 3.4 Handling Class Imbalance . 55 3.5 Techniques Used . 56 3.6 Summary . 59 Chapter 4: Results 60 4.1 Data Overview . 61 4.2 Clustering Results . 69 4.3 Classification Results . 75 4.4 Discussion . 86 4.5 Results Summary . 89 Chapter 5: Conclusion 92 5.1 Summary . 92 5.2 Limitations . 94 5.2.1 Accuracy of Market Behaviour . 94 5.2.2 Labelling of Market Data . 95 5.2.3 Biases within Agreement Model . 95 5.2.4 Mistaking as Deceptive Content . 96 Bibliography 97 Appendix A: Computational Resources 111 Appendix B: SHAP Summary Plots 113 iv List of Tables 3.1 Features of Reddit data . 36 3.2 Features of Yahoo! Finance data . 38 3.3 List of stopwords that were removed . 44 3.4 List of generated words by Empath . 52 3.5 List of custom words used in the Agreement Model . 54 4.1 Breakdown of records collected from subreddits . 61 4.2 Dataset class distribution . 68 4.3 Comments pre and post agreement model . 71 4.4 Summary of individual model performance . 76 4.5 Examples of misclassified posts from CNN model . 87 v List of Figures 2.1 Screenshot of a subreddit on Reddit . 7 2.2 Sample chart of a stock on Yahoo! Finance . 8 2.3 Candlestick for Stock Price (OHLC) . 10 2.4 Stages of Pump and Dump . 14 3.1 Experiment workflow . 34 3.2 Time window used to collect market data. 39 3.3 Labelling of stock behaviours . 49 3.4 Distribution of stock price trend slopes . 51 4.1 Data Collection Trend . 62 4.2 Top 20 frequent words . 64 4.3 Histogram of discussed market sectors within subreddits . 65 4.4 Histogram of discussed market sectors within texts labelled as P&Ds 66 4.5 Healthcare posts and comments trend . 68 4.6 Technology posts and comments trend . 69 4.7 Pump and dump posts trend . 70 4.8 NMF plot for posts . 72 4.9 NMF plot for posts and comments . 72 4.10 LDA plot for posts . 73 vi 4.11 LDA plot for posts and comments . 73 4.12 SVD plot for posts . 74 4.13 SVD plot for posts and comments . 74 4.14 MLP SHAP Summary Plot for posts . 80 4.15 MLP SHAP Summary Plot for posts and comments . 81 4.16 CNN SHAP Summary Plot for posts . 82 4.17 CNN SHAP Summary Plot for posts and comments . 83 4.18 BiLSTM SHAP Summary Plot for posts . 84 4.19 BiLSTM SHAP Summary Plot for posts and comments . 85 B.1 XGBoost SHAP Summary Plot for posts . 114 B.2 XGBoost SHAP Summary Plot for posts and comments . 115 B.3 RF SHAP Summary Plot for posts . 116 B.4 RF SHAP Summary Plot for posts and comments . 117 B.5 SVM SHAP Summary Plot for posts . 118 B.6 SVM SHAP Summary Plot for posts and comments . 119 vii 1 Chapter 1 Introduction Ever since the introduction of the global financial system, market manipulation has been an important issue. Broadly defined as the intentional act of deceiving others to alter or misrepresent market prices, its presence poses a threat to the belief held by many investors that the market is fair and free. In order to provide the public with confidence and bring efficiency within the markets, financial regulators (i.e., SEC) employ various monitoring techniques to detect, investigate and prosecute these illicit activities [12, 27]. While the schemes that manipulate the market are well documented and have stayed relatively the same, the means and opportunities for conducting them have continued to evolve through the years. In particular, the introduction of new financial products and technologies has allowed investors to easily enter the market. However, it has also increased the risk of manipulation. With the growth in participants, detecting and investigating fraudulent activities have become much more difficult, resulting in many to go undetected [32]. The advent of social media has given rise to new methods for manipulating the market. With its development and popularity, many fraudsters have viewed it as an 2 easy and inexpensive mean of exchanging financial information to conduct illegal ac- tivities [49]. As a result, investors who acquire information from online forums must always be cautious of the content that they do come across. The alluring potential of obtaining a quick and easy return on investment is what many manipulators seek to exploit. A scheme known as Pump and Dump (P&D) is popular among forums. Fraudsters disseminate false information about a particular stock in an attempt to ar- tificially raise the price such that they can sell their purchased shares at a higher rate. Investors with little knowledge or trading experience may act upon the information believing it to be credible and fall victim to it by buying in. Once the fraudsters sell off their shares, the price of the stock begins to plummet, resulting in many investors losing their money. While it can be difficult for investors to detect these types of deceptive content, it may be different for computers, as they are known to be capable of handling such tasks [34, 73]. Even though technological advancements attribute to increased risk of manipula- tion, it has also provided new methods for collecting and analyzing data to identify their occurrences. With the use of a computer, an earlier approach to detecting ma- nipulation has been to observe known patterns and predefined thresholds. By taking in the market data, such as the price and trading volume of stocks, suspicious activ- ities are monitored using a set of rules and triggers for notification. However, those methods suffer from various weaknesses, such as the inability to detect abnormal be- haviours that deviate from historical patterns, as well as struggling to adapt to the changing market conditions [44]. Machine Learning is an alternative method that can overcome the mentioned challenges, as it can learn and improve through experience.
Load more

Recommended publications
  • The Economics of Commodity Market Manipulation: a Survey
    The Economics of Commodity Market Manipulation: A Survey Craig Pirrong Bauer College of Business University of Houston February 11, 2017 1 Introduction The subject of market manipulation has bedeviled commodity markets since the dawn of futures trading. Allegations of manipulation have been extremely commonplace, but just what constitutes manipulation, and how charges of manipulation can be proven, have been the subject of intense controversy. The remark of a waggish cotton trader in testimony before a Senate Com- mittee in this regard is revealing: “the word manipulation . initsuse isso broad as to include any operation of the cotton market that does not suit the gentleman who is speaking at the moment.” The Seventh Circuit Court of Appeals echoed this sentiment, though less mordantly, in its decision in the case Cargill v. Hardin: “The methods and techniques of manipulation are limited only by the ingenuity of man.” Concerns about manipulation have driven the regulation of commodity markets: starting with the Grain Fu- tures Act of 1922, United States law has proscribed manipulation, including 1 specifically “corners” and “squeezes.” Exchanges have an affirmative duty to police manipulation, and in the United States, the Commodity Futures Trad- ing Commission and the Department of Justice can, and have exercised, the power to prosecute alleged manipulators. Nonetheless, manipulation does occur. In recent years, there have been allegations that manipulations have occurred in, inter alia, soybeans (1989), copper (1995), gold (2004-2014) nat- ural gas (2006), silver (1998, 2007-2014), refined petroleum products (2008), cocoa (2010), and cotton (2011). Manipulation is therefore both a very old problem, and a continuing one.
    [Show full text]
  • Complete Guide for Trading Pump and Dump Stocks
    Complete Guide for Trading Pump and Dump Stocks Pump and dump stocks make me sick and just to be clear I do not trade these setups. When I look at a stock chart I normally see bulls and bears battling to see who will come out on top. However, when I look at a pump and dump stock it just saddens me. For those of you that watched the show Spartacus, it’s like when Gladiators have to fight outside of the arena and in dark alleys. As I see the sharp incline up and subsequent collapse, I think of all the poor souls that have lost IRA accounts, college savings and down payments for their homes. Well in this article, I’m going to cover 2 ways you can profit from these setups and clues a pump and dump scenario is taking place. Before we hit the two strategies, let’s first ground ourselves on the background of pump and dump stocks. What is a Pump and Dump Stock? These are stocks that shoot up like a rocket in a short period of time, only to crash down just as quickly shortly thereafter. The stocks often come out of nowhere and then the buzz on them reaches a feverish pitch. We can break the pump and dump down into three phases. Pump and Dump Phases Phase 1 – The Markup Every phase of the pump and dump scheme are challenging, but phase one is really tricky. The ring of thieves need to come up with an entire plan of attack to drum up excitement for the security but more importantly people pulling out their own cash.
    [Show full text]
  • Signs of a Slowdown Cast a Shadow Over Markets
    Benjamin H Cohen (+41 61) 280 8921 [email protected] I. Overview of developments: Signs of a slowdown cast a shadow over markets During the fourth quarter of 2000, investors’ expectations of a slowing global economy contributed to a downward shift in yield curves, a widening of credit spreads and further declines in already weak equity markets. Market attention focused on the United States, where macroeconomic data reinforced the view that a slowdown was likely in the first half of 2001. Profit warnings and credit downgrades also weighed heavily on the equity and debt markets and signalled problems of excessive leverage in the corporate sector. Even the normally stable commercial paper markets experienced unusually wide and volatile credit spreads. Market movements also revealed the extent to which the US outlook led to a re-evaluation of growth prospects in other regions. An appreciation of the euro suggested that investors viewed the European economy as likely to maintain momentum, although a downward shift in the euro swaps curve also indicated a potential exposure to the impact of a US slowdown. A depreciation of the yen and a decline in the Tokyo stock market reflected perceptions of a return to weaker growth in Japan. Divergent sovereign spreads corresponded to distinctions investors made in their judgments about the outlook for the emerging economies, with some countries seen as facing severe challenges and others as experiencing an uneven but persistent recovery from recent crises. Markets in general turned around in January 2001. A surprise 50 basis point reduction in the Federal Reserve’s target for the federal funds rate on 3 January, followed by a further 50 basis point cut on 31 January, buoyed both the equity and bond markets, at least temporarily.
    [Show full text]
  • Regulatory Framework of Pre and Post Trading Transparency
    Indian Journal of Fundamental and Applied Life Sciences ISSN: 2231– 6345 (Online) An Open Access, Online International Journal Available at www.cibtech.org/sp.ed/jls/2015/02/jls.htm 2015 Vol. 5 (S2), pp. 81-92/Sarvestani et al. Research Article REGULATORY FRAMEWORK OF PRE AND POST TRADING TRANSPARENCY IN THE TEHRAN STOCK EXCHANGE Hosein Hasanzadeh Sarvestani1, Seeyd Abbas Moosavian2 and Hashem Nikoumaram3 1Department of Financial Management, Science and Research Branch, Islamic Azad University, Tehran, Iran 2Islamic Research Institute for Culture and Thought, Qom, Iran 3Science and Research Branch, Islamic Azad University, Tehran, Iran *Author for Correspondence ABSTRACT Information in securities markets plays central role. The issue of market transparency refers to the clarity with which market participants (and the public at large) can perceive the process of securities trading. In addition to helping investors make better decisions, transparency increases confidence in the fairness of the markets. Thus, regulators should aim to ensure that markets are fair, efficient and transparent and investors are given fair access to market information. In this study, we categorize portions of rules and regulations that were relevant to market transparency and after difining the association between the main categories; we present a regulatory framework for pre-post trading transparency. The main categories of regulatory framework are the dissemination of pre and post transactions information, prohibition of inside information abuse, prohibition of market manipulation, recording, maintenance and reporting documents and information by financial institutions, exchanges and self-regulatory organization, trader's information about procedures and regulation of stocks trading and violations and punishments. We explain the effects of these categories on the market transparency and conclude that the regulatory framework can be used by researchers and SEO for future researches and weaknesses amendment.
    [Show full text]
  • Regulatory Notice 21-03
    Regulatory Notice 21-03 Fraud Prevention February 10, 2021 FINRA Urges Firms to Review Their Policies and Notice Type Procedures Relating to Red Flags of Potential Securities 0 Special Alert Fraud Involving Low-Priced Securities Suggested Routing Summary 0 Anti-Money Laundering 0 Compliance Low-priced securities1 tend to be volatile and trade in low volumes. It may be difficult to find accurate information about them. There is a long history of 0 Financial Crimes bad actors exploiting these features to engage in fraudulent manipulations 0 Fraud of low-priced securities. Frequently, these actors take advantage of trends 0 Internal Audit and major events—such as the growth in cannabis-related businesses or the 0 Legal ongoing COVID-19 pandemic—to perpetrate the fraud.2 0 Operations FINRA has observed potential misrepresentations about low-priced securities 0 Risk issuers’ involvement with COVID-19 related products or services, such as 0 Senior Management vaccines, test kits, personal protective equipment and hand sanitizers. These misrepresentations appear to have been part of potential pump-and-dump Key Topics or market manipulation schemes that target unsuspecting investors.3 These 0 COVID-19-related manipulations are the most recent manifestation of this Anti-Money Laundering type of fraud. 0 Fraud 0 Low-Priced Securities This Notice provides information that may help FINRA member firms 0 Trading that engage in low-priced securities business assess and, as appropriate, strengthen their controls to identify and mitigate their risk, and the risk to their customers, including specified adults and seniors,4 of becoming involved Referenced Rules & Notices in activities related to fraud involving low-priced securities.
    [Show full text]
  • Speculation in the United States Government Securities Market
    Authorized for public release by the FOMC Secretariat on 2/25/2020 Se t m e 1, 958 p e b r 1 1 To Members of the Federal Open Market Committee and Presidents of Federal Reserve Banks not presently serving on the Federal Open Market Committee From R. G. Rouse, Manager, System Open Market Account Attached for your information is a copy of a confidential memorandum we have prepared at this Bank on speculation in the United States Government securities market. Authorized for public release by the FOMC Secretariat on 2/25/2020 C O N F I D E N T I AL -- (F.R.) SPECULATION IN THE UNITED STATES GOVERNMENT SECURITIES MARKET 1957 - 1958* MARKET DEVELOPMENTS Starting late in 1957 and carrying through the middle of August 1958, the United States Government securities market was subjected to a vast amount of speculative buying and liquidation. This speculation was damaging to mar- ket confidence,to the Treasury's debt management operations, and to the Federal Reserve System's open market operations. The experience warrants close scrutiny by all interested parties with a view to developing means of preventing recurrences. The following history of market events is presented in some detail to show fully the significance and continuous effects of the situation as it unfolded. With the decline in business activity and the emergence of easier Federal Reserve credit and monetary policy in October and November 1957, most market elements expected lower interest rates and higher prices for United States Government securities. There was a rapid market adjustment to these expectations.
    [Show full text]
  • US Commercial Banks' Securities
    ecommunications hqnittee on Energy and Commerce, House of Representatives - September 1988 INTERNATIONAL FINANCE a United States General Accounting Office Washington, D.C. 20548 Comptroller General of the United States B-229444 September 8, 1988 The Honorable Edward J. Markey Chairman, Subcommittee on Telecommunications and Finance Committee on Energy and Commerce House of Representatives Dear Mr. Chairman: At your request, we reviewed how U.S. commercial banks performed their securities underwriting and trading activities in the London mar- kets’ during 1986 and 1987 to assess how they might handle such activi- ties within the United States if the Glass-Steagall Act of 1933 were revised or repealed. The Glass-Steagall Act’s prohibition against the underwriting and trad- ing of corporate debt and equity securities by commercial banks applies to business conducted within the United States. According to the Federal Reserve’s Regulation K,’ banks may underwrite and trade securities outside the United States, within certain limits. These activities may be undertaken by subsidiaries of the bank holding company or by subsidi- aries of the bank itself, but not by branches, which are permitted to underwrite only local government securities. U.S. commercial banks conduct the greatest concentration of their over- seas underwriting and trading activities in London. Approximately 50 U.S. commercial banks operate in London, and 18 of them engage in at least a minimal amount of underwriting and trading. The range and type of such activities varies among these 18 banks. Most are large banks; 16 are considered money-center or super-regional banks. Bank examination reports from the Federal Reserve, the New York State Banking Department, and the Office of the Comptroller of the Currency indicate that most of the London securities subsidiaries of U.S.
    [Show full text]
  • The Future of Computer Trading in Financial Markets (11/1276)
    City Research Online City, University of London Institutional Repository Citation: Atak, A. (2011). The Future of Computer Trading in Financial Markets (11/1276). Government Office for Science. This is the published version of the paper. This version of the publication may differ from the final published version. Permanent repository link: https://openaccess.city.ac.uk/id/eprint/13825/ Link to published version: 11/1276 Copyright: City Research Online aims to make research outputs of City, University of London available to a wider audience. Copyright and Moral Rights remain with the author(s) and/or copyright holders. URLs from City Research Online may be freely distributed and linked to. Reuse: Copies of full items can be used for personal research or study, educational, or not-for-profit purposes without prior permission or charge. Provided that the authors, title and full bibliographic details are credited, a hyperlink and/or URL is given for the original metadata page and the content is not changed in any way. City Research Online: http://openaccess.city.ac.uk/ [email protected] The Future of Computer Trading in Financial Markets Working paper Foresight, Government Office for Science This working paper has been commissioned as part of the UK Government’s Foresight Project on The Future of Computer Trading in Financial Markets. The views expressed are not those of the UK Government and do not represent its policies. Introduction by Professor Sir John Beddington Computer based trading has transformed how our financial markets operate. The volume of financial products traded through computer automated trading taking place at high speed and with little human involvement has increased dramatically in the past few years.
    [Show full text]
  • Market Abuse Outlook: Overview of Global Regulatory Priorities and Focus Areas
    February 2021 Market Abuse Outlook: Overview of Global Regulatory Priorities and Focus Areas Contents Introduction 2 Governance landscape 3 Lessons from the past 5 Emerging expectations 9 Technology at play 11 Planning ahead 13 Appendix A—Key Regulators and Exchanges 14 Appendix B—Key Market Abuse Behaviors 18 Endnotes 20 Market Abuse Outlook: Overview of Global Regulatory Priorities and Focus Areas Introduction N 2020, THE US regulator Commodity Futures In 2019 alone, regulators levied fines of Trading Commission (CFTC) filed a record approximately US$1.78 billion across as many as Inumber of enforcement actions related to 160 individual incidents in the United States, market abuse incidents that cumulatively United Kingdom (UK), and several countries in the accounted for more than US$1 billion.1 Over the Asia-Pacific (APAC) region2. In 2020, the trend past decade, numerous organizations have been continued; the pandemic provided a further found guilty of market abuse, driven by regulators’ opportunity for wrongdoing and manipulative adoption of advanced technologies for market behaviors, due to the widespread move to remote surveillance. This trend is evolving across a range working, and the dynamic market conditions of financial products, leading to hefty penalties associated with increased trading volumes and and multi-year remediation programs to address volatility. In parallel, over the past few years the regulatory expectations. financial services industry has been actively working toward an enhanced control environment In financial
    [Show full text]
  • Algorithmic Trading Strategies
    CSP050 MAY 2020 Algorithmic Trading Strategies ANZHELIKA ISHKHANYAN AND ASHER TRANGLE Memorandum TO: Special Counsel, CFTC Division of Market Oversight FROM: Director, CFTC Division of Market Oversight RE: Algorithmic Trading and Regulation Automated Trading DATE: January 9, 2020 Welcome to DMO. I’m confident that you’ll find the position a challenging one, and I’ve already got a meaty topic to get you started on. I recently received an email from the Chairman expressing his concerns regarding the negative effects of algorithmic trading on financial markets. The Chairman is convinced that the CFTC should have direct access to trading systems’ source code to prevent potential market abuses with systemic implications. To that end, the Chairman proposes we reconsider Regulation Automated Trading (“Regulation AT”) which would require all traders using algorithms to register with the CFTC and would give CFTC direct and unfettered access to their source code. Please find attached the Chairman’s email which outlines his priorities and main concerns pertaining to algorithmic trading. In addition, I have sketched out my own reactions to reconsidering Regulation AT in an informal memo, attached as Appendix I. In addition, you may find it useful to refer to a legal intern’s memoranda, attached as Appendix II, which offers a brief overview of Regulation AT, its history, and a short discussion of other regulators’ efforts to address algorithmic trading. After considering these materials, please come and brief me on the following questions: ● What, precisely, are the public policy challenges posed by the emergence of algorithmic trading, and does this practice pose any serious problems to U.S.
    [Show full text]
  • Staff Report on Algorithmic Trading in U.S. Capital Markets
    Staff Report on Algorithmic Trading in U.S. Capital Markets As Required by Section 502 of the Economic Growth, Regulatory Relief, and Consumer Protection Act of 2018 This is a report by the Staff of the U.S. Securities and Exchange Commission. The Commission has expressed no view regarding the analysis, findings, or conclusions contained herein. August 5, 2020 1 Table of Contents I. Introduction ................................................................................................................................................... 3 A. Congressional Mandate ......................................................................................................................... 3 B. Overview ..................................................................................................................................................... 4 C. Algorithmic Trading and Markets ..................................................................................................... 5 II. Overview of Equity Market Structure .................................................................................................. 7 A. Trading Centers ........................................................................................................................................ 9 B. Market Data ............................................................................................................................................. 19 III. Overview of Debt Market Structure .................................................................................................
    [Show full text]
  • The Benchmark US Treasury Market: Recent Performance
    Michael J. Fleming The Benchmark U.S. Treasury Market: Recent Performance and Possible Alternatives he U.S. Treasury securities market is a benchmark. As crisis in the fall of 1998 in a so-called “flight to quality.” A Tobligations of the U.S. government, Treasury securities are related “flight to liquidity” also caused yield spreads among considered to be free of default risk. The market is therefore a Treasury securities of varying liquidity to widen sharply. benchmark for risk-free interest rates, which are used to Consequently, some of the attributes that make the Treasury forecast economic developments and to analyze securities in market an attractive benchmark were adversely affected. other markets that contain default risk. The Treasury market is This paper examines the benchmark role of the U.S. also large and liquid, with active repurchase agreement (repo) Treasury market and the features that make it an attractive and futures markets. These features make it a popular benchmark. In it, I examine the market’s recent performance, benchmark for pricing other fixed-income securities and for including yield changes relative to other fixed-income markets, hedging positions taken in other markets. changes in liquidity, repo market developments, and the The Treasury market’s benchmark status, however, is now aforementioned flight to liquidity. I show that several of the being called into question by the nation’s improved fiscal attributes that make the U.S. Treasury market a useful situation. The U.S. government has run a budget surplus over benchmark were negatively affected by the events of fall 1998, the past two years, and surpluses are expected to continue (and and that some of these attributes did not quickly return to their to continue growing) for years.
    [Show full text]