I am a person who loves learning. In order to find out what quantitative trading is, I specially checked Baidu and visited Zhihu. I started with this question:
Is programmatic trading a quantitative trading?
Here I summarize several concepts:
Programmatic transaction
Or automated trading, which is a trading mode in which strategies are handed over to computers for execution. In quantitative trading, many transactions are automatically executed by computers, but they cannot be equated.
Hedging transaction
It is more a trading idea than a specific strategy.
Quantitative trading
It is more based on data and historical statistics to formulate some trading strategies. Even if it is not executed by a computer, the transaction triggered by the quantitative change of trading factors can also be called quantitative transaction.
Then, I found a passage in Zhihu, which introduced the research and development method of quantitative trading strategy, which can better answer the relationship between different concepts and advanced quantitative strategy. The author divides quantitative strategy research and development into three levels:
The first category: traditional strategic quantification.
A long time ago, traders began to formulate various styles of strategies, such as trend strategy, reversal strategy, scalper strategy, market-making strategy and so on. , but it was manual operation or semi-automation. With the development of the market and the maturity of technology, quantitative trading automates the research and implementation of these strategies, thus improving the efficiency and level of R&D, reducing transaction costs and largely eliminating the unstable factors of people.
This kind of transaction can be said to have improved the research and implementation of the original strategy by using technology, and the frequency and scale of the transaction have also changed, but it is not a brand-new strategic category in essence. The strategy of making money in the past may earn more, and the strategy of losing money cannot turn it into making money. This is a wrong idea, and quantification can't save you.
At present, most quantitative transactions in China belong to this category.
The second category: technology-driven strategy
Strategies based entirely or mainly on technical differences. This category also has a certain history, but it really became a huge and striking strategic category in the past 10 years with the rapid development of computer technology. It is common that an organization takes the lead in trading because of its higher algorithm efficiency, more powerful computer hardware (supercomputer) and a slight advantage in speed and calculation, and uses automation to trade a large number of products in intraday trading, resulting in stable income and huge trading volume. In this strategy, IT technology and scientific model play a key role. That's technology, that's your idea.
For example:
Tradebot, which started high-frequency trading earlier, is a typical user of this strategy. In 2002, it reached 1 100 million bills per day. At about that time, many traditional market makers were squeezed out of the market by new electronic market makers such as Tradebot and Getco. Later, Tradebot and Getco crushed other electronic market makers with the same technology.
In 2005, Tradebot spun off BATS Global Markets, which is now the third largest stock market in the United States. 1999 when tradebot was first established, the studio was located in a small basement in rural Kansas city, USA. It was dark and humid, and only five traders sat in front of the computer screen to monitor the trading. At that time, every computer was equipped with a set of software called Tradebot. Getco uses strategy more widely and is more ambitious. In 20 12, Knight, also a veteran market maker, sent a large number of wrong instructions to NYSE due to technical failure, resulting in a huge loss of $440 million, and its share price plummeted by 70% in two trading days, which was acquired by Getco for $1800 million.
People are often impressed by the long-term and sustained high returns of Simmons Renaissance Medal Fund. What is actually unknown to the media is that Tradebot keeps daily (instead of monthly or annual) profits all the year round, even without a single-day loss, because many new funds in Fuxing have raised funds from external investors (the medal of making money stopped external financing long ago, but the actual performance of new funds is much worse than the medal), which requires a certain degree of IR, while Tradebot is not open to external investors and makes money in a low profile, which is also a very common feature of HFT. If it weren't for several market turmoil, HFT was found out as a scapegoat, and the media criticized it. Basically, not many people knew about the existence of this low-key category.
In this category, a small number of similar traders have entered China. They deeply studied the trading rules and market structure, formulated corresponding high-frequency strategies, and cooperated with efficient software and hardware to strive for profits from many a mickle makes a muckle.
The third category: new quantitative strategies.
This strategy is a kind of strategy developed slowly thanks to the development of computer technology. It is not entirely based on the technical advantages of execution, but more on the use of technology to formulate new strategies. For example, statistical arbitrage requires more computer computing resources for data mining and pattern recognition, which was difficult to be competent only by manpower in the past. The development of IT technology and the reduction of cost make it possible to develop these strategies. This is a new strategy for technology generation.
This category is still in its infancy in China.
Thanks to Zhihu author Leon.
Expansion: How to design quantitative trading strategy?