With the incomparable advantages of many people, quantitative investment has gradually become a sharp tool to make money in the capital market, but it does not mean that people's subjective initiative can be completely replaced. On the contrary, the excellent quantitative investment team, their investment model is constantly optimized and iterative. In the world of machines, it is people who issue the most core instructions, and also people who observe the results of the execution of the machine and discover the potential risks in the process and solve them.
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Quantitative investment shows the world that it is not a dream to squeeze into the super-rich circle. Hedge funds are the most widely used products for quantitative investment. On the Forbes 2013 global billionaire list, hedge fund managers won about 21 seats, or about 2%, of the top 1000, with four in the top 100.
The Grand Medal of bravery.
James Simmons' grand medal fund, owned by the Renaissance Corporation, made an average annual net return of 38.5% in the 20 years from 1998 to 2008, creating a myth in the investment community. Simmons himself has become the best profitable fund manager in 20 years, the new hedging king, and is still on the Forbes billionaire list.
The Grand Medal Fund is mainly short-term operation, mainly through the statistical information analysis method to judge the short-term price changes of foreign exchange and bonds, especially the overreaction of the market, to carry out arbitrage activities. How short is this short-term? the shortest short-term measure in financial investment is called "one stroke". For example, hundreds of transactions may be made every second.
It can be said that the Grand Medal Fund is almost quantified to the existence of hair, but this does not mean that computers have replaced the role of people and become the masters of people. Simmons himself has said that there is no model that can still make money for a long time, and the model must be constantly updated, which is done entirely through people.
Black swan defeats the perfect model.
When it comes to quantitative investment, American long-term capital, as the most famous investment case, has to be mentioned. John Merriwether founded the American long-term capital company (LTCM) in February 1994. Relying on Blake-Shules-Merton's derivative pricing theory, the company adopts a "market-neutral" trading strategy to buy undervalued securities and sell overvalued securities for arbitrage. LTCM seems to have peeped into the mystery of quantification, with annual returns of 28.5 per cent, 42.8 per cent and 17 per cent respectively between 1994 and 1997, a net increase of 2.84 per cent. Huge profitability made LTCM recognized by the capital markets and Merriwether was honored as the father of arbitrage.
On August 17, 1998, the Black Swan came and LTCM suffered a default on the Russian government's foreign debt. The crisis has caused turmoil in global financial markets, with investors exiting the markets of developing countries and turning to low-risk, high-quality bonds such as the United States and Germany. As a result, LTCM went in the wrong direction, the price of short German bonds rose, while the bond prices of long developing countries fell, while the expected convergent spreads tended to diverge, resulting in its Waterloo in the capital markets. Although the American financial giant later funded the takeover of the company, LTCM was running out of steam and declared liquidation in 2000.
Private equity professionals pointed out that LTCM placed too much trust in its own investment strategy portfolio and ignored low-probability events, coupled with excessive leverage, which led to its eventual demise. As a matter of fact, there is no permanent secret book of getting rich in quantitative investment, and there is no investment model of eternal youth. With the improvement of market efficiency and the upgrading of IT technology, there are misunderstandings and loopholes in any investment strategy and operation method in the short term or long term. At this time, it is necessary for the human brain to keep pace with the times and let the system modify and improve according to the dynamic and uncertain environment. The human brain and the computer should complete each other, not replace each other.
The "black box" of quantitative investment.
Just as coins have both positive and negative sides, they can be called quantitative investments with sharp tools to make money, and they will also face huge investment risks because of the frequent "madness" of computers, such as the wrong trading order of Wall Street giant Goldman Sachs, the three-hour suspension of trading on the NASDAQ Stock Exchange in New York, the second largest stock exchange in the United States, and the domestic 8 / 16 own finger trading incident. The high-frequency trading of quantitative investment has aroused people's concern about the potential risks of computers, but like the blood circulation system, it accelerates the flow of funds in the capital market and is indispensable in the course of financial development. "We can't give up eating for fear of choking, because the BUG, of one system abandons the whole system."
With the increase of the types of financial products and the increase of the amount of information tracking, the demand for quantitative investment will continue to increase. From the perspective of risk management and control, this not only requires the investment company to improve its own risk control system, but also needs the cooperation of the whole industry chain. The so-called quantitative investment refers to the investment according to the pre-set logical strategy or mathematical formula, which is also done by Renaissance Technology Company and American long-term Capital Company. In a broad sense, all investment methods that use mathematical tools and computer programs are included in the category of quantitative investment. Among them, the controversial high-frequency trading is essentially used to eliminate the temporary inefficiency of the market, and it can promote market prices to reflect market information more quickly. The world's largest well-known high-frequency trading companies include Millennium, DE Shaw, Worldquant and Renaissance Technologies.
Although quantitative investment is favored by more and more investors because of its stable investment return, the operation process of quantitative investment is still very vague, so a "black box" is formed. What is the secret in the "black box" of quantitative investment?
According to Wall Street's top quantitative financial expert Rish? Nalan reveals that the basic structure of the "black box" of quantitative investment includes manual data input and research, transaction strategy model, risk control model, transaction cost model and portfolio construction model, four of which constitute the trading system.
How to make quantitative investment "alive"? The answer is manual data input and research, and cooperation with the trading system. It is generally believed that quantitative trading minimizes the role of human factors in the system, and when the system carefully studied and developed by quantitative traders comes online, they seem to be of no use to heroes. In fact, the computer will only faithfully and reliably follow what people tell it to do step by step, and with the continuous evolution of time and market, the defects of the trading model will continue to expand. At this time, the subjective judgment of quantitative traders is particularly important. With the addition of artificial factors, quantitative investment has a normal human mind, seems to be "alive", and can actively and flexibly respond to the rapid changes of the outside world. In other words, once the market triggers a systematic "panic", traders will immediately show up to avoid the risk of investment by modifying the trading list or reducing the size of the portfolio and the corresponding leverage ratio.
MOM allows quantitative investment to take into account both the subjective advantages of people and the objective executive advantages of machines.
Today, the MOM model has become the mainstream asset management model in Europe and the United States, and it is also the best work to quantify the combination of human brain and computer in the investment community.
As an indirect asset management model, MOM (Manager of Managers)) was born in Russell Asset Management in the United States. Its clients can be institutional investors or high net worth individuals. Since it was developed, it has been applied by many foreign institutions. The most successful one is the Yale University Foundation, which has earned nearly 150 times from 200 million US dollars in 1980 to about 30 billion US dollars now.
The so-called MOM model, also known as selected multiple managers, through the method of selecting the best, screening fund managers or asset managers, let these top professionals to manage assets, while themselves through dynamic tracking, supervision, management of them, timely adjustment of asset allocation programs to reap benefits.
The essence of MOM mode is to find the best people to do the most professional things. MOM model has only been around for 30 years, but it has developed rapidly and has attracted the attention of many domestic and foreign investment companies. The related products of MOM model, which is still a new thing, have begun to test the water in China. In 2011, Ping an of China partnered with Russell to set up Ping an Russell and issued the first phase of MOM products. In addition, the MOM model can also be widely used in hedge funds and futures products.
Compared with the trust (TOT), MOM model in the fund (FOF), trust, which is highly respected in recent years, it is more attractive in terms of covering the number and professionalism of asset managers. In essence, FOF and TOT are still limited to selected products, while MOM model is more inclined to select selected managers. It can rely on the company's research ability, relatively independently select professional managers who are more suitable for investment needs, and use the combination of quantitative and qualitative methods to give full play to the dual advantages of optimizing product managers and multi-person risk management.
The MOM model not only uses multiple professionals to break the inherent form of quantitative investment, but also avoids the habitual deviation of traders' agile induction of profit but slow response loss through the rational judgment of the computer system, so that professionals and computer systems can complete and cooperate with each other in the "black box", in order to gain a more stable and higher return on investment, so that it has great space and potential for development.
Manual data input and research, and the mutual completion of the trading system, is the inevitable combination that quantitative investment can give full play to all its advantages.
Data input and research is an important part of the "black box", which needs to be determined according to the specific financial environment. Without them, even shrewd quantitative traders may not be able to complete various forms of testing, verification and simulation. It is impossible to build an effective trading portfolio strategy. The trading strategy model is the core of the trading system. At present, the mainstream is alpha strategy and beta strategy, which are used to track or predict the trend of financial products to be traded.
Relatively speaking, the risk control model, which can only attract disasters but not profit, is easy to be ignored. in fact, it is related to the survival of the whole system and limits the scale of investment risk exposure. Benefits and costs are relative, and the transaction cost model can help to determine whether the constructed portfolio is feasible or not. The portfolio construction model is formed by finding the balance point among risk limitation, profit pursuit and cost constraint and getting the optimal investment portfolio.
