Before Noah Holdings : (NYSE Noah) Lin Feng, president of the country (Kenny Lam) since 2019 Nian 4 Yue 8 from the date of his new role quantify hedge fund Two Sigma , as head of the Asia-Pacific region, Hong Kong and CEO, succeeding last year left the party political good (Bonnie Fong) . So Two Sigma entered my worldview.
With the decline of active trading and the rise of passive trading, traditional hedge funds are plagued by declining performance and capital outflows. However, a quantitative hedge fund that relies on big data and artificial intelligence has sprung up, ranking among the world's top quantitative funds with a management scale of more than US$ 50 billion. It is Two Sigma .
According to the British "Financial Times", 2017 Nian 10 Yue, Two Sigma funds under management break through 500 billion US dollars mark, more than Germany Shao fund DE Shaw ( 450 billion dollars), and the Renaissance Fund Renaissance (slightly more than 500 million US dollars) Tied to become the world's largest quantitative hedge fund.
In 2008 , Two Sigma 's management scale was only 4.6 billion US dollars. In less than 10 years, the fund's management scale has expanded by more than 10 times.
Even in the case of poor performance this year, investors are still eager for Two Sigma . This year alone , the company's management scale has increased by more than 20 billion US dollars.
Who is this new quantitative hedging king?
" Atypical " Quantitative Fund
Two Sigma Investment was founded in 2001 by David Siegel , John Overdeck and Mark Pickard (retired). Among them, David Siegel and John Overdeck are both former employees of DE Shaw .
The name Two Sigma represents two different meanings of the word Sigma . The lowercase Sigma "σ" represents the volatility and excess return of an investment, while the uppercase Sigma "Σ" means sum.
The difference between this new quantitative king and traditional quantitative funds is reflected in many aspects.
Two Sigma believes that it is not a typical investment institution, but a company that follows both the principles of technological innovation and investment management. Since its inception, Two Sigma has placed great emphasis on the use of machine learning and distributed computing, and the composition of the fund's internal staff also highlights the emphasis on technology.
At Two Sigma , 72% of employees have no financial background. Most of the staff is from the Massachusetts Institute of Technology, Carnegie - computer science, mathematics and engineering graduates Mellon University and the California Institute of Technology and other institutions in the direct hiring. Of the more than 1,200 employees, two-thirds are engaged in research and development.
On the company's official website, Two Sigma defined itself as follows: " More than 1,200 people believe that scientific methods are the best way to invest. Use information to support ideas. Use repeated experiments to optimize. This is Two Sigma .
The secret of rapid rise
The background of Two Sigma's massive expansion is the rise of the wave of computerized investing .
In this wave, scientists and engineers who know little about finance try to use powerful computing power to find clues from news and data, so as to realize the prediction of securities price trends.
The Wall Street Journal pointed out that although this method is also called quantitative investment, it is not the same as the traditional quantitative investment method, especially in practice.
Traditional quantification uses programming to bet on the statistical relationship between security prices and does not care much about real-world information. The purpose of the new quantitative investment that means more intelligent than humans, faster algorithms to filter the global information discovery mode ( pattern ) and make trading decisions, and thus defeat the manual picking.
Specific to Two Sigma , the quantitative strategy works like this:
Take the stock of a large retailer as an example. When deciding how to trade this stock, Two Sigma scientists and mathematicians will design dozens of computer trading models related to this stock.
One of the models will automatically read the analyst's research report and establish the model based on the analyst's opinion of the retailer. This is more like a human trader's approach. The other model will look for clues on Twitter : it may determine a pattern (such as the increase in the number of customers tweeting complaining) and compare that pattern with another pattern (such as the data showing that the number of people visiting the store has fallen) Associated.
Other algorithms will accomplish tasks traditionally performed by human investors, such as monitoring when the stock price breaks through the 200- day moving average, or whether the company's management has bought or sold the company's stock.
Each model will generate a trading recommendation, and then a specific algorithm will give each recommendation a different weight according to the historical performance of each model and other factors. Then, the risk management algorithm will check the trading recommendation again to ensure that the recommendation does not make the fund excessively exposed to the stock or the industry. Eventually, the execution system will automatically trade.
Scientists may spend weeks optimizing a model. Once the model is optimized and handed over to the computer, the actual running time may only be a few seconds or less.
David Siegel , co-founder of Two Sigma , said that most investment managers still work more or less the same way they were decades ago, that is, use their heads to make investment decisions. The Two Sigma system is artificial intelligence, " it represents the future of investment management " .
Behind this quantitative investment model is the support of massive data and huge computing power. Two Sigma has over . 1 million data sources; 95000 th the CPU , memory up 1695TB , per second can be 1014 times calculated.
Scale Snowball vs Performance Waterloo
In recent years, the market's demand for algorithmic trading has exploded, while other hedge funds are struggling with the quagmire of performance decline and capital outflow. According to Morgan Stanley's calculations, in the past six years, the average annual growth rate of various quantitative strategies has been 15% , and a total of about 1.5 trillion US dollars of funds are currently under management .
It is in this context that Two Sigma ushered in a period of rapid development.
In 2008 , Two Sigma 's management scale reached US$ 4.6 billion. Approximately USD 6 billion in 2011 . At the beginning of 2017 , the scale of Two Sigma's management exceeded US$ 30 billion, and in October it exceeded the US$ 50 billion mark.
The continuous influx of funds has brought substantial management costs to Two Sigma .
According to "Forbes", Two Sigma 's main fund can get a 3% management fee and a 30% profit commission, while the industry standards are generally 2% and 20% .
In 10 Yue 17 Ri-baked " Forbes United States 400 people Rich List " in, David Siegel and John Overdeck to 49 billion dollars in net worth tied for the list of 122 names.
In the context of the rapid growth of the capital scale, Two Sigma once magically maintained a stable high rate of return, until this year it hit a wall.
2014 , the company's assets amounted to 60 billion dollars in Compass Fund annual returns of 25.6% , from 05 years to 14 average return period of nearly 15% . Another large fund Absolute Return in 2015 years 8 months, an increase of 6.1% .
However, since the beginning of this year, the unilateral bull market and low-volatility market environment in US stocks have affected quantitative hedging performance. According to statistics from Hedge Fund Research , the results of the first nine months of 2017 showed that equity funds rose by an average of 9.7 %, while quantitative hedge funds only rose by 0.6 %.
Two Sigma also encountered performance Waterloo. In the first seven months of this year, some of its funds performed as follows:
Absolute Return Macro Cayman，-7.19%；
Compass Fund，-4.4%；
Compass Cayman，-3.8%。
Two Sigma 's earnings have one fund: Absolute Cayman the Return Fund in the 7 month to achieve monthly 1.25% of earnings, up to 7 months earnings during the year was 6.31% . But overall this year is still losing more and earning less.
From another point of view, the performance loss has not stopped the continued influx of investors, which in fact proves the market’s recognition of the new trend, that is, computer technology and big data are becoming more and more important in financial transactions. .
With the influx of more and more funds, some transactions may become very " crowded. " At this time, once the market environment changes, it will likely lead to a large-scale collapse.
In order to avoid this situation, Two Sigma has taken restrictive measures on some funds. According to the Financial Times, its securities and macro hedge fund products currently manage a total of approximately US$ 35 billion and have been closed to external investors. The current growth of the company's management scale mainly comes from the other two main businesses - passive trading type "risk premia" funds and more hybrid funds.
The environment is very good, the salary is high, it is difficult to leave
In Two Sigma , a 20 researcher-something-year-old can get 55 million dollars a year. Compared with colleagues on Wall Street, both the work content and the working environment are more relaxed here.
Employees here do not need to wear suits or tie. In addition to the usual gym, kitchen, and reading room, the company even has a bookshelf full of board game props. Judging from the newness of the props, the usage rate should not be low.
(Image source: Business Insider )
Every year, Two Sigma holds an artificial intelligence competition. The theme of last year's competition was air hockey.
According to Forbes, the employee retention rate of Two Sigma is as high as 97% .
But behind the superior working environment and the enviable high salary, it is not completely without cost.
"Forbes" pointed out that even in the field of investment, Two Sigma 's approach to protecting trade secrets is particularly radical. Several employees of the company have been prosecuted, charged, and even imprisoned.
Among them, the most well-known criminal case involved Chinese employee Kang Gao . Kang Gao is a researcher of the company. In early 2014 , Kang Gao planned to leave and found a job in another investment group, but in order to comply with the competition agreement, he did not immediately report to the new company. Two Sigma believed that Kang Gao had stolen his intellectual property rights and reported the situation to the local supervisory agency. In the end, Kang Gao was arrested for illegal use of scientific research materials and illegal copying of computer-related materials. Not only did he lose his work visa and immigration status, he was also detained in prison for 8 months. 2015 Nian 2 Yue, Kang Gao admitted to the crime of illegal copying of computer-related material.
The departure of key employees is a considerable loss for any company, and it is also true that hedge funds pay more attention to trade secrets than other industries. However , it is rare for Two Sigma to face the enemy and even confront former employees repeatedly.
Does this mean that, compared with traditional hedge funds, the new quantitative fund business model is facing the threat of increased strategy replicability while improving performance?
A trading model that relies on algorithms and data may be a double-edged sword for the entire financial industry or a single fund company.
While big data is king, mathematicians and physicists take over the world, the strong rise of Two Sigma may be just a microcosm of this trend.
Source: Futures Information Network