美國證券交易監督委員會：2020年美國資本市場算法交易員工報告（英文版）（99頁）.pdf

1、 1 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 an

2、alysis, findings, or conclusions contained herein. August 5, 2020 2 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 M

3、arket Structure . 23 A. Types of Debt Securities or Instruments . 23 B. Data and Communications . 28 IV. Benefits and Risks of Algorithmic Trading in Equities . 30 A. Investors . 30 B. Brokers . 36 C. Principal Trading . 37 D. Operational Risks to Firms and the Market . 42 E. Studies of Effects on M

4、arket Quality and Provision of Liquidity . 44 F. Effects of the COVID-19 Pandemic . 47 V. Benefits and Risks of Algorithmic Trading in Corporate and Municipal Bonds. 51 A. Liquidity Search and Trade Execution . 51 B. ETF Market Making and Arbitrage . 53 C. Studies of Effects on Market Quality and Pr

5、ovision of Liquidity . 53 VI. Regulatory Responses to Market Complexity, Volatility, and Instability . 55 A. Improving Market Transparency. 55 B. Mitigating Price Volatility . 60 C. Facilitating Market Stability and Security . 63 D. Additional Ongoing and Potential Commission and Staff Actions . 67

6、VII. Summary of Studies on Algorithmic Trading . 69 A. Equities . 69 B. Debt Securities . 82 VIII. Conclusion . 83 IX. Bibliography to Summary of Academic Studies . 85 X. Appendix: Market Participants, Roles, and Obligations . 92 3 I. Introduction A. Congressional Mandate The Economic Growth, Regula

7、tory Relief, and Consumer Protection Act of 2018 requires the staff of the U.S. Securities and Exchange Commission (the “SEC” or “Commission”) to submit to Congress a report on the risks and benefits of algorithmic trading in the U.S. capital markets.1 Specifically, 502 provides: (a) In General. Not

8、 later than 18 months after the date of enactment of this Act, the staff of the Securities and Exchange Commission shall submit to the Committee on Banking, Housing, and Urban Affairs of the Senate and the Committee on Financial Services of the House of Representatives a report on the risks and bene

9、fits of algorithmic trading in capital markets in the United States. (b) Matters Required To Be Included. The matters covered by the report required by subsection (a) shall include the following: (1) An assessment of the effect of algorithmic trading in equity and debt markets in the United States o

10、n the provision of liquidity in stressed and normal market conditions. (2) An assessment of the benefits and risks to equity and debt markets in the United States by algorithmic trading. (3) An analysis of whether the activity of algorithmic trading and entities that engage in algorithmic trading ar

11、e subject to appropriate Federal supervision and regulation. (4) A recommendation of whether (A) based on the analysis described in paragraphs (1), (2), and (3), any changes should be made to regulations; and (B) the Securities and Exchange Commission needs additional legal authorities or resources

12、to effect the changes described in subparagraph (A). 1 Economic Growth, Regulatory Relief, and Consumer Protection Act, Pub. L. No. 115-174, 502, 132 Stat. 1296, 1361-62 (2018). 4 B. Overview As required by 502 of the Economic Growth, Regulatory Relief, and Consumer Protection Act of 2018, this staf

13、f report describes the benefits and risks of algorithmic trading in the U.S. equity and debt markets. Broadly speaking, and as more fully discussed below, algorithmic trading in the equities and to a lesser extentin the debt market, has improved many measures of market quality and liquidity provisio

14、n during normal market conditions, though studies have also shown that some types of algorithmic trading may exacerbate periods of unusual market stress or volatility. Advances in technology and communications have enabled many market participants to more efficiently provide liquidity, more efficien

15、tly access market liquidity, implement new trading services, and more effectively manage risk across a range of markets. Furthermore, commenters have observed that the increasing complexity of multiple interconnected markets may have increased the risk that operational or systems failures at trading

16、 firms, platforms, or infrastructure may have broad, potentially unexpected, detrimental effects on the markets and investors. A number of observers have noted that even as some uses of algorithms may contribute to market complexity, algorithms generally help market participants navigate market comp

17、lexity. A common theme echoed by nearly all market professionals, academic researchers, and other students of the securities markets is that that algorithmic trading, in one form or another, is an integral and permanent part of our modern capital markets. Several variations of algorithmic trading st

18、rategies have developed and expanded over the last several decades. These developments have been driven, in pertinent part, by the growth in available market data generated by and consumed by market professionals, major advances in computational power and the speed of data transmission, and the expo

19、nential increase in the speed of securities trading. Enhancements in algorithmic trading strategies have also been driven by investor demands for execution quality, the search for alpha and trading profits, and the application of sophisticated quantitative analytics. The Commission and other regulat

20、ors have responded with a range of tools intended to mitigate risks to investors and to help ensure fair, efficient, and orderly markets. Commission staff will continue to monitor technological change and its influence on investment, trading, and the capital markets, and will continue to assess the

21、need for additional regulation, resources, or legal authority.2 2 The significant and rapid economic impact precipitated by the COVID-19 pandemic was reflected in extraordinary trading in the U.S. secondary markets for equity and debt during the spring of 2020. While this report briefly discusses re

22、cent market events, including certain significant impacts on trading as market participants reacted to the effects of COVID-19, the report is focused on the broader questions raised in 502. In April 2020, 5 C. Algorithmic Trading and Markets The use of algorithms in trading is pervasive in todays ma

23、rkets. Any analysis of the role that algorithmic trading plays in the US equity and debt markets requires an understanding of equity and debt market structure,3 the role played by different participants in those markets, and the extent to which algorithmic trading is used by market professionals. 4

24、In describing the uses of algorithms in trading, it is useful to first define an algorithm. At its most general level, an algorithm is a finite, deterministic, and effective problem-solving the Commission announced the formation of an internal, cross-divisional COVID-19 Market Monitoring Group to as

25、sist with Commission and staff actions and analysis related to the effects of COVID-19 on markets, issuers, and investors, and with responding to requests for information, analysis and assistance from fellow regulators and other public sector partners. See “SEC Forms Cross-Divisional COVID-19 Market

26、 Monitoring Group,” Press Release 2020-95 (Apr. 24, 2020); see also “COVID-19 Market Monitoring Group Update and Current Efforts,” Statement of Chairman Jay Clayton and S.P. Kothari (May 13, 2020), available at: https:/www.sec.gov/news/public-statement/statement-clayton-kothari- covid-19-2020-05-13

27、(describing some of the initial work of the COVID-19 Market Monitoring Group); COVID-19 Market Monitoring Group, “Credit Ratings, Procyclicality and Related Financial Stability Issues: Select Observations” (Jul. 15, 2020), available at: https:/www.sec.gov/news/public-statement/covid-19-monitoring-gr

28、oup-2020-07-15. 3 The section of this staff report on equity market structure echoes aspects of the Commissions 2010 Concept Release on Equity Market Structure. See Concept Release on Equity Market Structure, Exch. Act. Rel. No. 61358, 75 Fed. Reg. 3594 (Jan. 21, 2010) (“Concept Release”). That Conc

29、ept Release described the transition of modern equity trading markets away from a largely centralized, manual structure to the dispersed, automated structure that exists today. The Concept Release provided many useful institutional details; this report updates some of these details, and describes im

30、portant developments that have occurred since 2010. When discussing debt markets, this report focuses on corporate and municipal bonds. While the markets for U.S. Treasury securities are described briefly, they are not a focus of this report. 4 The main body of this staff report presumes familiarity

31、 with core concepts in securities market structure, such as the distinction between acting as a broker and trading as principal, key differences between types of trading venues such as national securities exchanges and alternative trading systems, the difference between providing and demanding liqui

32、dity, and legal obligations such as best execution. Background on these concepts may be found in the appendix to this report, which provides a more general orientation to market participants, roles, and obligations. 6 method suitable for implementation as a computer program.5 In modern equity and de

33、bt markets, many problems are solved and decisions made in this computational, algorithmic manner. Today, algorithms address many of the problems and decisions that have long been central to the business of trading. What instrument(s) should be invested in or traded? What price should be bid or offe

34、red? What order size is optimal? What should be the response to a request for a quotation? What risk will be taken on by facilitating a trade? How does that risk change with the size of the trade? Is the risk of a trade appropriate to a firms available capital? What is the relationship between the p

35、rice of different but related securities or financial products? To what market should an order be sent? Is it more effective to provide liquidity or demand liquidity? Should an order be displayed or non-displayed? To which broker should an order be sent? When should an order be submitted to a tradin

36、g center? In general, algorithms utilize a rich array of market information to very quickly assess the state of the market, to determine when, where, and how to trade, and then to implement the resulting trading decision(s) in the marketplace.6 As described in more detail below, algorithms are broad

37、ly used in contemporary securities markets, and the range of uses differs across asset classes and across the roles and investment objectives of market participants. In light of the wide diversity of algorithms in modern trading, it is not a goal of this report to define a single type of trading or

38、activity as uniquely algorithmic. Rather, this staff report attempts to describe many dimensions of the contemporary secondary markets for equity and debt securities that operate algorithmically. The types of trading described in more detail below each fundamentally depend upon computerized algorithms, and the data and technological infrastructure through which they operate, to address the types of problems and tasks described above. The staffs approach differs from the more narrow approaches taken in much of the literature on algorithmic trading, which generally seek