Shulou(Shulou.com)06/03 Report--

AI quantitative transaction (1)-- quantitative transaction introduction 1, quantitative transaction introduction 1, quantitative transaction introduction

Quantitative trading is based on mathematical model as trading thinking, based on historical data, mathematical modeling, statistical analysis and programming as tools. Computer technology is used to select a variety of high-probability profit events that can bring excess returns from the huge historical data to formulate trading strategies.

2. the characteristics of quantitative transactions.

(1) discipline. Quantitative investment decisions are made based on the model, which will be simulated and tested thousands of times to achieve a high fault tolerance rate.

(2) systematization. Quantitative transaction data analysis has a set of very comprehensive data evaluation system, which will consider the market from many aspects, such as macro cycle, digital currency valuation, turnover rate, profit quality, market sentiment and so on.

(3) probability. Through the model and combined with mathematical methods, we can calculate under what circumstances the profit rate is the highest, and the appropriate position can be increased.

(4) arbitrage thought. The use of mathematical analysis and combined with computer technology to find valuation depressions, sell high and buy low, earn the middle price difference, and gain profits.

3. The advantages of quantifying transactions

(1) the investment performance is stable and the withdrawal is low. Quantitative trading constantly excavates and uses historical rules that are expected to be repeated in the future from historical data; quantitative trading depends on a group of stocks to win, not one or more stocks to win.

(2) it can overcome the weakness of human nature and realize rational investment. Help investors to remain rational when it is easy to lose rationality, so when the market overreacts and loses rationality, it can seize the opportunity in time.

(3) the ability to process information is strong. Quantitative transactions use computer technology to deal with massive data, and have a stronger ability to process information.

4. The application of quantitative transaction

(1) Statistical arbitrage

The main idea of statistical arbitrage is to first find out several pairs of investment varieties with the best correlation, and then find out the long-term equilibrium relationship (cointegration relationship) of each pair of investment varieties. when the price difference of a pair of varieties (the residual of the cointegration equation) deviates to a certain extent, it starts to build positions, buy relatively undervalued varieties and relatively overvalued varieties, and make a profit after the equivalent difference returns to equilibrium.

(2) algorithmic transaction

The main idea of algorithm trading is to predict the rise and fall in the future according to the quantitative formula, which is a kind of trend trading. The prediction of algorithm strategy is right and wrong, and it belongs to high-risk trading, but it has large profit space and large market capacity.

(3) High frequency trading

High-frequency trading position time is short, through a large number of transactions and rapid withdrawal of orders, the average profit of each transaction is small, but the risk is also small.

Second, quantitative trading mode 1. Brief introduction of quantitative trading mode

According to the concept of mathematical model and the use of computer technology, quantitative trading can be subdivided into automated trading (Automatic Trading), quantitative investment (Quantitative Investment), programmed trading (Program Trading), algorithmic trading (Algorithm Trading) and high frequency trading (High Frequency Trading). The emphasis of different quantitative trading methods is different, which is not only the product of the development of quantitative trading technology to different stages, but also different trading methods of different quantitative trading user groups.

2. Automated transaction

Automatic transaction refers to the transaction mode in which the investment mode of technical analysis is solidified into models and technical indicators that can be understood by the computer, and the computer program automatically generates investment decisions and implements them according to market changes. Automated trading is the automation of investment in technical analysis, which can avoid the psychological changes and emotional fluctuations of investors, and strictly implement the established strategy, which is the basic quantitative trading method.

3. Quantitative investment

Quantitative investment generally refers to the investment determined by higher mathematics tools such as probability theory and calculus to study the structural causes of various asset prices in the financial market. Quantitative investment requires high mathematical ability of investors, so funds and investment companies that specialize in quantitative investment like to recruit PhDs in mathematics, physics and other science subjects.

4. Programmed transaction

Programmed trading is the use of procedures for easy delivery, trading timing, trading positions, stop-loss and profit-making standards can be included in the program, can also be independent of the program, the program itself is only the way of execution.

5. Algorithmic transaction

Algorithmic trading means that trading decisions are made according to one or more algorithms (algorithm), and algorithms are the basis of trading. The execution of algorithmic transactions can be manual or automated. If the transaction program is used to execute, it is a programmed algorithm transaction.

6. High frequency trading

High-frequency trading is that there is only a short interval from opening to closing each trade, usually ranging from more than ten minutes to a few microseconds. The main purpose of high-frequency trading is to profit from temporary price fluctuations in the market. Whether it is trend-following trading or arbitrage trading, as long as the frequency reaches, it can be called high-frequency trading. It is difficult to reach the standard of high-frequency trading manually, so it is generally traded through the program: the algorithm and strategy are set up and executed by the order-issuing software.

7. Strategic transaction

In the field of investment, it is customary to call buy and hold, value investment, growth investment and so on as strategy, while inertia, reversal, trend, support resistance and so on are called strategy. Because the strategy is mainly technical analysis, and in the computerized history of transaction decision analysis, technical analysis goes relatively early, so Strategy Trading habitually refers to strategic trading. In general, a trading strategy is called a policy, and a system transaction is called a strategic transaction.

Third, the mainstream quantitative trading platform 1. Brief introduction of the quantitative trading platform

Quantitative trading platform refers to the platform that can meet different quantitative trading methods, which requires it to be large and comprehensive from three main aspects: market and basic data of the trading system, trading and execution, strategy research and development and operation. but also to be deep and sophisticated.

The current quantitative trading platform can be divided into low-end and high-end quantitative trading platform from the aspects of development language, technical architecture, system architecture, strategic direction, transaction mode and so on.

2. Medium-and low-end quantitative trading platform

The technical architecture generally adopted in the middle and low-end platforms is that investors use the client software provided by platform companies and use Internet access to connect to the market and basic data servers provided by platform merchants or financial brokerage companies. after the strategy that investors run locally is triggered, they trade through the ordinary trading seats of brokerage companies.

Due to the limitations of policy script analysis and execution efficiency and technical architecture, the middle and low-end platforms have certain restrictions on the support of complex system architectures such as multi-variety, multi-cycle, multi-account, multi-trading market, multi-strategy, complex financial toolkits and so on. The general implementation process of the system is as follows: after receiving the market data locally, the investor's strategy carries out simple account position, fund calculation and management according to the trigger conditions of simple strategy calculation, and then issues orders such as buying and selling direction, quantity, price and so on. to trade automatically.

The middle and low-end quantitative trading platform only supports low-complexity script language to implement strategy logic, and generally can only load technical indicators on the chart for automated trading, programmed trading and other quantitative trading methods.

The middle and low-end platform is suitable for investors to carry out trend, anti-trend and other strategies that do not require high market and trading logic, and it is a kind of popular quantitative trading platform which is most widely used by individual investors in the market.

The domestic mid-and low-end quantitative trading platforms mainly include Wenhua Wisdom programmed Trading, Trading Pioneer, Pyramid decision-making Trading system, Da Qian & multicharts, Anyi Financial Terminal and so on.

(1) Wenhua Wisdom programmed Trading platform

Wenhua Yingzhi uses Mai language to develop a technical index model to generate a buy and sell signal to drive the transaction to issue an order. In the aspect of quantitative model research and development, Yingzhi provides historical market data and recent TICK data of all varieties and multi-periods of domestic stocks and futures, at the same time, it provides rich market functions, some functions of accounts and transactions and some statistical functions for strategy development, as well as rich strategy return test report items as the basis for strategy performance evaluation. In terms of quantitative transactions, Yingzhi provides multi-thread independent programming transactions for up to 24 varieties, and uses the order-issuing refinement component to achieve part of the algorithmic transaction function. Due to the use of client-side technical architecture, although Yingzhi has realized the functional module of high-frequency trading, in practical application, high-frequency trading is recommended to be hosted in the Mandarin computer room. At this stage, Wisdom win has a certain advantage in the middle and low-end quantitative trading platform because of its simple procedural realization and high performance-to-price ratio.

(2) Trading trailblazer programmed trading platform

Trading pioneer (TB) uses TBL language to develop a strategy model, which drives trading orders according to account positions and chart buying and selling signals. In the aspect of quantitative model research and development, TB provides multi-cycle historical market data and recent TICK data of domestic futures; provides more comprehensive market data functions, account and trading functions, and statistical functions for strategy development; and provides rich policy return report items as the basis for strategy performance evaluation. In terms of quantitative transactions, a single TB terminal supports 20-30 single-variety charts to receive quotes and trade concurrently, but due to the limitations of the client technical architecture, it does not support high-frequency and more complex strategies. At this stage, TB market promotion has been done well, more futures companies have cooperated, and the market share of the quantitative trading platform at the middle and low end is higher.

(3) Pyramid decision trading system

Pyramid decision trading system (hereinafter referred to as Pyramid) uses VB scripting language to develop strategy model, uses more complex account functions and transaction functions for fund management, and can use chart buying and selling points or non-chart transaction judgment to drive transactions to place orders. In the aspect of quantitative model research and development, the pyramid provides historical market data and TICK data of domestic stocks and futures, as well as outer disk data, provides more comprehensive market data functions, more account and trading functions, statistical functions for strategy development, and supports the expansion of external statistical database and professional statistical analysis software Lib library. It provides a wealth of strategy return test report items as the basis for strategy performance evaluation. In the aspect of quantitative trading, in addition to supporting chart-driven programmed trading, basket trading, algorithmic trading and more complex hedging trading can also be implemented, but it is also limited by the technical architecture of the client. It does not support more complex strategies such as high-frequency trading and market-wide strategy trading. At the present stage, the number of pyramid cooperation futures companies is gradually increasing, and the market share of the middle and low-end quantitative trading platform is higher.

(4) Dachan multicharts automatic transaction

Dachan multicharts Automated Trading system (MC) uses power language to develop strategy model, Dachan provides market and transaction gateway, and multicharts implements strategy development and execution platform. In the quantitative model research and development, the domestic futures historical market and TICK market within a period of time provided by Da Qian. MC inherits the rich function library and strategy library of TradeStation, as well as convenient development characteristics, provides a more perfect back test and performance evaluation system, and provides a perfect evaluation for the research and development of the strategy. In terms of quantitative transactions, MC only supports programmed and automated transactions, but not enough for high-end quantitative trading models. Due to the short entry of MC into China, the market share of the quantitative trading platform in the middle and low end is not high.

(5) programmed transaction of Anyi financial terminal

Anyi Financial Terminal (hereinafter referred to as Anyi) uses the general script language of technical indicators to develop trading models and carries out chart-driven automatic trading. It is an automatic trading tool for domestic stocks and futures independently developed by a securities firm. At present, Anyi provides the historical quotation of domestic stocks and futures, which can be used for relatively simple chart trading and hedging trading of stocks and futures, and programmed trading tools are used free of charge. Although Anyi can only trade through the Anxin securities trading channel, it indicates that the quantitative trading of domestic stocks and futures has been promoted to a stage of all-round development.

3. High-end quantitative trading platform

In addition to supporting complex scripting languages to implement strategy logic, high-end quantitative platforms all support the direct use of development languages such as C++ and JAVA to achieve complex strategy logic. Generally, in order to pursue execution efficiency, they do not use interface to display charts, but adopt multi-process and multi-threaded methods for automated trading, programmed trading, algorithmic trading, and even quantitative trading methods such as high-frequency trading using hardware technology for the pursuit of extreme.

The technical architecture commonly used in the high-end trading platform is the architecture that uses the server to implement the strategy, the market uses the extreme speed and depth quotation with the least forwarding path, and the trading channel uses a dedicated, directly connected trading channel for trading. Market prices and trading delays are required to be as low as possible.

The high-end trading platform is located in asset management, which strictly distinguishes the two stages of strategy research and development and strategy operation and implementation in the system architecture. For the strategy research and development stage, it needs the support of multi-variety, multi-cycle, multi-account, multi-trading market, multi-strategy and complex financial engineering package to realize the complex strategy logic; for the implementation phase of strategy operation, the system architecture should ensure the stable and effective implementation of various risk control, emergency handling, transaction methods and strategies. The implementation process of the system not only meets the requirements of the transaction itself, but also meets the requirements of the organization's own business processes and specifications, as well as regulatory requirements.

High-end trading platform is suitable for institutional investors to carry out trends, arbitrage, hedging, high-frequency and other strategies that require high market and trading requirements and high logical complexity. With the acceleration of innovation in the domestic financial market, the demand and potential demand of institutional investors for high-end trading platform is rising rapidly.

Domestic high-end quantitative trading platforms mainly include Progress Apama, Longsoft DTS, Cathay Pacific quantitative investment platform, Tian soft quantitative platform, Feichuang STP, Yi Sheng programmed trading, Shengli SPT platform and so on.

(1) Progress Apama

Apama uses EPL and JAVA language to develop or customize the strategy model, through the market, information and other driving CEP engine for trading, risk control and other operations. In the research and development of quantitative models, Apama uses third-party market authorization to provide access to various market interfaces and over-the-counter trading interfaces, which can access domestic stock and futures multi-cycle time series historical market data and TICK data; provides rich financial toolkits for complex strategy development; provides convenient studio development tools for rapid development and customization of complex strategies 10,000 times accelerated testing is provided for policy backtesting, and the test report can be easily customized. In terms of quantitative trading, Apama provides 1.5 million transactions per second concurrent processing capacity for high-frequency trading, algorithm trading. The high-end concurrent processing capability of Apama enables the market-wide multi-variety concurrent arbitrage, hedging and other trading strategies and real-time risk control strategies to be implemented at a high speed. At the present stage, Apama occupies a large market share in the self-management, asset management and brokerage business of international investment banks. Since 2012, Apama has gradually expanded its domestic business, and several large securities and futures companies have officially launched to promote Apama and related quantitative trading applications.

(2) Dragon soft DTS

DTS uses LUA scripting language to develop the strategy model, through the statistical analysis of historical and real-time market, basic data and macro data provided by the platform to realize investment research and transaction. In the research and development of quantitative models, DTS can not only use the platform's own data sources, but also access third-party data sources. DTS also provides financial toolkits for complex strategy development, backtesting, and performance evaluation. In the aspect of quantitative trading, the scalable server-side technical architecture provided by DTS ensures the high concurrency and high-speed execution of the strategy. It has practical applications in programmed trading, quantitative trading, algorithmic trading, hedging and arbitrage trading.

(3) quantitative investment platform of Guotai'an

Cathay Pacific quantitative investment platform is divided into research platform (QIA-Lite) and trading platform (QRC). The toolbox form of matlab is seamlessly compatible with the R & D environment of matlab, and strategic trading is realized by the trading platform. In the research and development of quantitative model, Guotai'an investment and research platform uses its own data sources, fundamental data, high-frequency data and quantitative factor database, which is fully compatible with all the functions of matlab, and realizes the research and development and back-testing of the model. In the aspect of quantitative trading, it supports the counter of domestic mainstream securities and futures, and has practical applications in programmed trading and algorithmic trading of stocks and futures.

(4) Tian soft quantitative research and trading platform

The research and trading platform of Tian soft adopts the unique TSL language to develop the strategy model, and realizes the execution of quantitative transactions through the transaction gateway of Tian soft. In the quantitative model research and development, the use of high-performance data warehouse provided by the history and TICK market, basic data, macro data and other data sources, while providing 7000 kinds of open source function libraries for strategy research and development, back testing, performance analysis. In the aspect of quantitative transaction, it basically realizes the quantitative trading methods, such as automatic transaction, programmed transaction, algorithm transaction and so on.

(5) Fei Chuang STP

Fei Chuang quantitative trading platform uses Java language, through customizable template development strategy model, high-frequency trading. STP implements strategic research and development, back-testing, risk control and asset management operation through a unified development and asset management operation platform. Due to the use of high-speed over-the-counter trading interface, it is mainly for users of high-frequency arbitrage, programmed trading and other trading modes.

(6) Yi Sheng programmed trading platform

Yi Sheng programmed trading can not only use the language development strategy model similar to Easy Language to realize programmed trading and arbitrage trading, but also use C++ to develop external applications according to the quotation and trading API provided by Yisheng counter to realize more complex quantitative trading of futures and stocks. In the research and development of quantitative model, the EL development model provided by Yisheng program is similar to the middle and low-end quantitative trading platform, but it meets the requirements of high-end quantitative trading platform in terms of market speed, real-time and fine processing of trading and account functions. In terms of quantitative trading, the market and trading speed of Yisheng counter have certain comparative advantages, and the applications supported by quantitative trading platform are mainly programmed futures trading, automatic trading, hedging and arbitrage trading.

(7) Shengli SPT platform

The SPT platform of Shengli financial software uses C++ language and customized strategy development template for strategy research and development, and uses independent operation and back-test platform for simulation and real transactions. Although the SPT platform is not widely used in China, it attracts attention in the quantitative trading platform because of its concurrent processing capacity of 1 million transactions per second and millisecond delay of transactions. SPT provides some strategy templates, which can easily realize programmed trading, arbitrage and hedging trading, algorithmic trading, high-frequency trading and so on.

4. Mainstream quantitative funds 1. Qiaoshui Fund

Founded by Ray Dalio in 1975, Bridge Water hedge Fund (Bridgewater Associates) is headquartered in Connecticut and currently employs about 1500 people. Qiaoshui Fund is the evergreen tree among hedge funds. It is perennially at the top of the list of hedge funds in the world, managing about 150 billion US dollars. Its clients are mainly composed of institutional clients, including foreign governments, central banks, enterprises and public pensions. University donations and charitable funds.

Qiaoshui Fund has a unique investment concept, mainly based on global macro strategies, and puts forward theories such as all-weather investment strategy and the separation of alpha and beta strategies. Among them, all-weather investment strategy emphasizes different types of portfolio allocation in different macroeconomic periods, so as to achieve a profitable state all the time. The Bridge Fund made positive gains during the 2008 financial crisis and still performed well after the collapse of Lehman Brothers in 2009.

In June 2018, Qiaoshui Fund completed the registration of private equity fund manager in China Securities Investment Fund Industry Association and officially became a domestic private equity manager, indicating that its private equity business in China has been officially launched.

2. AQR Capital Management

AQR is a quantitative hedge fund co-founded by Asness, a former Goldman Sachs portfolio manager, and partners in 1998. Headquartered in Greenwich, Connecticut, it now manages $159.2 billion, employs 693 people and has offices in Boston, Chicago, Los Angeles, London and Sydney.

AQR's clients are mainly institutional investors, such as pension funds, insurance companies, mutual funds, sovereign wealth funds and so on.

AQR uses algorithms and computer models to find and profit from the temporary inefficiency of the market. Its investment strategies are very extensive, including long and short positions, arbitrage, equity, global macro, insurance, absolute returns, momentum, multi-strategies and so on. The primary goal of AQR is value stock and momentum stock; when choosing investment portfolio, AQR emphasizes the combination of fundamentals and quantitative analysis and bottom-up stock selection; the three core principles of investment are systematic approach, diversified investment and alpha technology.

AQR Capital suffered heavy losses in the 2008 financial crisis, with its flagship absolute return fund losing more than 50 per cent, while assets under management fell from a peak of $39.1 billion in September 2007 to $17.2 billion in March 2009.

3. Millennium Management Company

Founded by Englander in 1989 with the help of Canadian tycoon Belzberg family and other investors, Millennium Management (Millennium Management LLC), with initial assets of US $35 million, now manages US $33.6 billion, employs more than 2000 people and has offices in the United States, Europe and Asia.

The investment method of Millennium Management pays great attention to risk and tends to have higher returns under certain risks (such as low Sharp rate). The investment concept of risk aversion has become the rule of the trading team. Therefore, millennium management requires trading teams to have smaller gains on profitable days and smaller losses on lossmaking days, so as to strive for more profitable days.

The investment strategy of Millennium Management focuses on diversification and globalization, including relative value, statistical arbitrage, M & An arbitrage, fixed income and commodities, etc., and is very diversified in asset classes, industries to which commodities belong, and the location of investment targets, including domestic and foreign equity, debt, currency, futures, forwards, options and so on. Millennium Management attaches great importance to the use of high technology, and its subsidiary quantification department has a system that allows amateur traders to submit algorithms for specific trades.

4. Castle Investment Group

Founded by Kenneth Griffin in 1990, Castle Capital Group (Citadel Investment Group) is headquartered in Chicago and has offices in North America, Asia and Europe. Castle Asset Management currently manages more than $24 billion and has more than 1400 employees. Castle's clients include sovereign wealth funds, pensions, university donations and so on.

Castle's investment approach is driven by rigorous fundamental research, high-end quantitative analysis and a proven technology platform. The investment principles are effort, scenario planning and repetition. Investment strategies focus on some of the major asset classes in the world's largest financial markets, including stocks, credit, quantitative strategies, commodities, fixed income and macro.

5. Soros Quantum Fund

Founded by George Soros in 1969, Soros Quantum Fund (Soros Fund Management), once a leader in the hedge fund industry, is headquartered in New York and has been transformed into a family office with more than $20 billion under management.

The investment targets of quantum funds include stocks, worldwide fixed income products and foreign exchange, currencies, commodities, private equity funds and venture capital funds, with a large number of investments in transportation, energy, retail, finance and other industries.

Founder Soros once blocked the pound and brought down the Bank of England, attacking the Thai baht and the Hong Kong dollar, triggering the Asian financial turmoil.

6. Yuansheng Capital

Founded in 1997 by fund manager David Harding, Winton Capital Management currently manages more than US $30 billion and employs 330 people in 25 countries. It is the largest futures investment fund company in the world.

Yuansheng Capital is a systematic investment company that uses scientific means to trade and look for profit opportunities through statistical analysis and mathematical modeling of historical data.

7. German Investment

Founded in 1988 by its founder David E. Shaw, Shaw (D.E.) now manages $50 billion and employs more than 1300 people.

Founder David E. Shaw is a computer teacher at Columbia University, has served as a government science and technology adviser and other positions, proficient in information technology and related technology, the company attaches great importance to the use of quantitative skills in investment, but also developed sophisticated computer technology for trading.

Founder David E. Shaw took a faculty position at Columbia University quickly after graduating from Stanford and then joined Morgan Stanley's quantification department. In 1988, the German fund was founded as a result of its defeat in the company's internal struggle, and it was born on Wall Street using high-frequency trading technology, which was rare at that time, taking advantage of the inefficiency of the market to cut the sheep of the market.

In 2004, David E.Shaw, who achieved financial freedom, invested the wealth he earned in quantitative investment into his own field of computational chemistry, founded D.E.Shaw Research, recruited a number of basic science doctorates, and used three years to develop the first generation of Anton, which is 10000 times faster than the average supercomputer. The team continues to win the opportunity to publish papers in world-famous scientific journals, and the academic reputation continues to rise.

In 2015, David E. Shaw's personal wealth reached $4.1 billion.

In April 2019, Dezhou Investment Management (Shanghai) completed its registration with the China Securities Investment Fund Industry Association and officially entered the Chinese market.

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8. Renaissance

Renaissance Technology (Renaissance Technologies LLC), founded in 1982 by James Simmons (James Simons), currently manages more than $65 billion and includes the Grand Medal Fund (Medallion Fund), which is open only to internal employees, and RIEF (Institutional Equity Fund) and RIDA (Institutional diversification Alpha Fund), which are open to outside investors.

James Simons received his doctorate in mathematics from the University of California, Berkeley at the age of 23, worked as a lecturer in mathematics at Harvard University at 24, and headed the department at Stony Brook University in New York at the age of 30, where he studied pure mathematics for eight years, during which he co-founded the Chern-Simons theory, which has a profound impact on mathematics and physics, with Shiing-Shen Chern, a well-known mathematician of Chinese descent.

In 1976, James Simons won the Veblen Award in the United States, the crown of mathematics, and his personal achievement in mathematics reached its peak.

In finance, James Simons invented a unique gecko investment method, that is, making short-term directional predictions while trading many varieties at the same time, profiting from a large number of transactions completed in a short period of time, that is, transactions should be like geckos, lying motionless on the wall, mosquitoes quickly eat them as soon as they appear, and then restore calm and wait for the next opportunity.

Between 1989 and 2009, the average annual return of the Grand Medal Fund was as high as 35%, more than 20 percentage points higher than the average annual return of the S & P 500 index over the same period, and more than 10 percentage points higher than the trading performance of "financial giant" Soros and "stock god" Buffett. Even in 2007, when the subprime crisis broke out, returns were as high as 85 per cent.

The mathematical model of the Grand Medal Fund mainly finds out the mathematical relationship among financial product prices, macro-economy, market indicators, technical indicators and other indicators through the statistics of historical data, and finds the small profit opportunities that exist in the market at present. and make a quick and large-scale profit through leverage ratio. At present, the investment portfolio of the Grand Medal Fund contains investment targets of thousands of stock markets and other markets around the world. The model continuously monitors the prices of major investment targets such as treasury bonds, futures, currencies, stocks, and so on. And give orders to buy or sell.

9 、 Two Sigma

Founded in 2001 by founders John Overdeck and David Siegel, Two Sigma currently manages $50 billion, with more than 2/3 R & D employees and more than 60% employees with no financial background.

Two Sigma follows the principle of technology and innovation, makes decisions under the guidance of machine learning and distributed computing, and always develops the latest technology to make better decisions. The founders are all leaders in the field of technology investment, with more than 40 years of experience in the development of computer-driven, model-based trading systems. John Overdeck is the godfather of Wall Street Quantification Fund and founder of German Investment D.E. Shaw, and has great attainments in mathematics and statistics. David Siegel is good at computers and artificial intelligence. The company combines huge amounts of data, world-class computer systems and financial experts to complete high-end trading models, while also using the perspective of technology to optimize investment and manage risks.

In September 2019, Two Sigma announced that its subsidiary Tengsheng Investment Management (Shanghai) Co., Ltd. had successfully registered as a private equity fund manager with the China Securities Investment Fund Industry Association (AMAC).

5. Introduction of mainstream PB institutions 1. PB

Prime Brokerage (PB for short), as an institutional business of securities firms, means that securities firms provide professional investors with one-stop comprehensive financial services such as transaction settlement, asset trusteeship, background operation, research support, leveraged financing, fund raising and so on.

2. Goldman Sachs Group

As the largest foreign PB service organization, Goldman Sachs' firm commitment to technology and innovation has led it to develop many practices and technologies that have become industry standards. Goldman Sachs has been a pioneer in electronic trading and connectivity systems, with REDIPlus, its electronic trading platform, a global leader in pre-transaction analysis, value-added execution services, algorithmic trading, portfolio trading solutions and post-transaction analysis. Among them, Goldman Sachs algorithmic Trading (GSAT) is a group of algorithmic programs involving a variety of assets around the world, including stocks, futures, synthetic derivatives and options. Through trading with GSAT, clients can also access a variety of resources of Goldman Sachs, including before and during the transaction analysis, transaction cost analysis and execution strategy.

In addition to trading tools, Goldman Sachs makes great use of technology to promote business innovation and development in all its businesses. In foreign exchange and derivatives trading, Goldman's original and proprietary data modeling technology enables clients to calculate margin on the basis of their portfolios, thereby efficiently managing risk and optimizing the use of capital. and Goldman's internal technology platform simplifies transaction recognition, portfolio reconciliation and management. In terms of escrow settlement, Goldman Sachs has developed a powerful and extensive global settlement and settlement network. Goldman's platform provides a complete set of tools that allow clients to trade across multiple types of assets and currencies in a single consolidated account. In terms of margin trading, Goldman Sachs uses proprietary portfolio risk modeling tools that use cutting-edge technology to evaluate clients' portfolios and strategies. In terms of reporting services, the Goldman Institutional client Network provides clients with online access to Goldman's global online resources, including trading concepts, investment opportunities, market insight, personalized investment research and other resources. At the same time, Goldman Sachs has developed a highly customizable comprehensive reporting platform to provide clients with customized business solutions covering a wide range of products and markets.

3. Yitou Securities

Interactive Brokers,IB is a US online securities firm known for its low transaction costs and technology-driven business, with 50-50 institutional and individual customers. PB service is a rapidly developed field of IB in recent years. IB has two core competencies in PB services: one is the IB SmartRouting SM intelligent trading system developed by IB, and the other is the absolute advantage of IB in cost control. IB can choose to provide hosting services for customers free of charge.

Under the influence of regulatory policies such as Basel III and MiFID II, prime brokers controlled by banks such as Goldman Sachs and Morgan Stanley are subject to strict liquidity management constraints, forcing them to raise customer access standards and service pricing. IB accepts hedge funds that big prime brokers are reluctant to serve, and attracts a large number of rate-sensitive clients. Because of its excellent technical reserves and planning, it is not necessary to be forced to carry out comprehensive technological upgrades and hire new staff in the face of new regulatory regulations such as MiFID II. IB has developed a set of intelligent trading system-IB SmartRouting SM for customers, which uses algorithms to find the best price in the whole market to complete the transaction. SmartRouting replaces manual operation through technical means, and integrates into each business process to transform into an automated workflow, which can greatly reduce the cost. As a result, IB has an absolute advantage in cost control, thus realizing the requirement of not putting forward the minimum management scale or revenue contribution to customers.

In addition, IB has a set of programming interfaces that support C++, Java and Python, mainly serving programmed trading customers. IB has also launched an automated trading program for foreign exchange swaps that allows customers to hold foreign exchange positions at a more reasonable price. To satisfy hedge funds' desire to have access to different assets in global markets through a single platform, IB developed Investors' Marketplace, a search tool for institutions that allocate hedge funds, which currently has 2911 hedge funds.

4. UBS

UBS (UBS Group AG, UBS or UBS) was founded in 1862. Headquartered in Zurich, Switzerland, with 67481 full-time employees, UBS is the largest financial holding group in Europe. It is composed of three branches of UBS Warburg, UBS Institutional Asset Management and UBS Swiss Private Bank. UBS Group's business mainly includes wealth management, investment banking and securities and asset management. UBS UBS is a versatile bank that provides a wide range of banking services to domestic and foreign customers (enterprises, individuals, public institutions, etc.), including working capital loans, construction loans, special financing, international commercial loans, export financing, project financing, securities credit and guarantee, investment advice and custody, securities trading, securities management and indirect loans, issuance and distribution of stocks, bonds and notes, and syndicated loans. Engaged in foreign exchange, bank bills, precious metals, money market business, transfer and payment and so on.

5 、 China International Capital Corporation

China International Capital Corporation (CICC) is the first Sino-foreign joint venture investment bank in China. CICC has been committed to providing high-quality financial value-added services to clients and has established a research-based business structure with all-round development of investment banking, stock business, fixed income, wealth management and investment management.

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