The quantification system generally consists of several steps, mainly including strategy writing, strategy backtesting, strategy analysis, simulation operation, real trading operation, etc., and the backend needs to be connected to the exchange interface, and the transaction channel can truly send the order to the market .
Quantitative trading works by looking at "market fluctuations", that is, as long as the market fluctuates, there is a chance to earn the difference. It can be said that it can be used whether it is a bull market or a bear market. Rising currency prices can make more difference on the original basis, and falling currency prices can also make a certain difference to subsidize their own losses.
The main advantage of quantitative trading is that it can help investors to invest without market fluctuations. Now it has also been introduced from traditional finance to the digital asset industry, and it is loved by many investors, and many investors have seen the market.
The quantitative trading system can implement richer strategies, and the program functions are more powerful. It provides rich historical data and multi-angle model evaluation algorithms for returns and risks. It supports strategy research, backtesting and automated trading, and has been compared. With mature operation experience, investors can continuously optimize their own strategy models in a systematic simulation trading environment,
To get the fastest progress.
Quantitative investment is also called algorithmic trading:
It is a transaction carried out in accordance with the transaction management decision derived from the algorithm design program process. To put it simply, it means to use the mathematical entity model and the electronic computer method to maintain the efficiency coefficient method of your own project investment ideas.
Quantitative trading system architecture: The quantitative system is divided into front-end and back-end. The front-end is mainly for users and is used for strategy writing, manual order placement, monitoring, report analysis, etc.; the back-end encapsulates transactions and market quotations, as well as order routing, and provides The simplest interface is for front-end use.
Taking into account the access to multiple exchanges in the later period, the market receiver is independent, which can better achieve load balancing, and each market is written into the memory database for other applications; and the market center will collect the received The market information pushed by the device is packaged into a unified format and then released to subscribers.
The internal structure of the trading center and algorithmic workers. The trading center is mainly responsible for receiving the instructions sent by the client, routing the instructions to the algorithmic workers after passing through the risk control layer, and the algorithmic workers processing the order logic, such as: conditional order, chase order, stop loss Profit orders, etc., and finally report the order to the exchange, and return the return to the trading center, and then the trading center will return the return
Back to subscribers.
The trading center is also responsible for routing strategy instructions sent by users, and distributing them to strategy backtesting workers or strategy simulation workers according to the instructions, and executing backtesting instructions or starting strategies accordingly.
Auto-execution is a process in which the strategy is automatically generated and executed, and is a signal sent to the agent without any manual intervention. This is the purest algorithmic trading strategy because it minimizes the problems caused by human intervention.
"Quantitative trading" has two meanings: First, in a narrow sense, it refers to the content of quantitative transactions, which converts trading conditions into procedures and automatically places orders; the other is, in a broad sense, it refers to a systematic trading method, which is an integration. Trading system. That is, based on a series of trading conditions, an intelligent auxiliary decision-making system, combining a wealth of business experience with trading conditions,
Good risk control during the transaction process.